BASIC LOG INTERPRETATION_HLS

BASIC LOG INTERPRETATION

Log Interpretation Seminar/ Workshop (14th – 16th May 2007, New Delhi) Name: _____________________________________

© 2007 by HLS Asia Limited. All rights reserved. No part of the contents of this publication may be reproduced or transmitted in any form or by any means, photocopying, electronic, recording, or otherwise, without written permission from the publisher.

Basic Log Interpretation

INDEX Section – 1

BASIC ANALYSIS CONCEPTS

Section – 2

POROSITY AND MINERALOGY

Section – 3

ENVIRONMENTAL CORRECTIONS

Section – 4

CLEAN FORMATION EVALUATION

Section – 5

ADDITIONAL LOG INTERPRETATION TECHNIQUES

Section – 6

SHALY SAND THEORY

Section – 7

SHALY SAND APPLICATIONS

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Open Hole Log Analysis Notes


Section 1

Basic Analysis Concepts Table of Contents Introduction………………………………………………………………………………………….

3

Objectives…………………………………………………………………………………….……..

3

Formation Evaluation and Log analysis………………………………………………………….

4

The Basis for Log analysis………………………………………………………………………...

5

Water Saturation of Clean formations……………………………………………………………

6

Archie's Equation dissected……………………………………………………………………….

10

Essential Calculations……………………………………………………………………………..

10

Determining Geothermal Gradient………………………………………………………………..

11

Determining Formation Temperature (Tf )………………………………………………………..

11

Determining R m f from R m …………………………………………………………………………..

12

Correcting Resistivity for Temperature…………………………………………………………..

12

Determining Formation Water Resistivity (Rw) by the Inverse Archie Method………………

13

Example Application of Archie's Equation……………………………………………………….

13

Rw Calculation by Inverse-Archie Method………………………………………………………..

15

Sw Calculations……………………………………………………………………………………..

16

Permeability Indicators…………………………………………………………………………….

17

Determining Formation Water Resistivity (Rw) by the SP Method…………………………….

19

Detailed Procedure of SP Method………………………………………………………………..

20

Additional Notes about Formation Water Resistivity……………………………………………

21

Additional R w Calculation Example………………………………………………………………. 21 "Quick-Look" Methods in Log Analysis…………………………………………………………..

25

References………………………………………………………………………………………….

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Introduction This section presents an overview of the basic concepts of open hole log analysis and provides practical examples of the techniques and methods. A working knowledge of each of these concepts is fundamental for performing a basic well-site analysis.

Objectives After completing this section, the participant should be able to §

clearly identify and mark on a log the potential water-bearing zones

§

clearly identify and mark on a log the potential hydrocarbon-bearing zones.

§

recognize potential water-bearing zones that are amenable to formation water resistivity (Rw ) derivation by judging their cleanliness, porosity, and qualitative permeability.

§

estimate lithology of potential water-bearing and hydrocarbon-bearing zones.

§

calculate the cross-plot porosity of a zone of interest.

§

select appropriate values for tortuosity factor (a) and cementation exponent (m) values required for calculating formation water resistivity (Rw ) and water saturation (S w ) in zones of different lithology and/or porosity.

§

calculate geothermal gradient (gG) for a particular well location by equation and by chart.

§

calculate formation temperature (Tf ) for any depth of interest by equation and by chart.

§

determine values for mud filtrate resistivity (Rmf ) and mudcake resistivity (Rmc ) from mud resistivity (Rm) by chart and by equation.

§

convert measured and/or derived resistivity values (Rm, Rmf , Rmc ) to formation temperature (Tf ) for any depth of interest by equation and by chart.

§

calculate value for formation water resistivity (Rw ) in a selected clean waterbearing zone by inverse-Archie method.

§

determine value for formation water resistivity (Rw ) in a selected clean waterbearing zone by SP method.

§

determine a reasonable and optimistic value for formation water resistivity (Rw ) by comparing values derived from inverse-Archie and SP methods.

§

convert derived values of formation water resistivity (Rw ) to formation temperature (Tf ) for any depth of interest by equation and by chart.

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Basic Log Interpretation §

calculate water saturation (S w ) for a clean hydrocarbon-bearing zone by Archie equation.

§

calculate hydrocarbon saturation (S hc ) for a clean hydrocarbon-bearing zone by equation.

§

clearly identify and mark on a log potential perforated intervals based on water saturation (S w ) calculations.

Formation Evaluation and Log Analysis Formation evaluation can be generally defined as the practice of determining both the physical and chemical properties of rocks and the fluids they contain. The objective of formation evaluation is to locate, define, and produce from a given reservoir by drilling as few wells as possible. To this end, oil companies utilize a variety of formation evaluation methods, some of which are outlined in Figure 1.1. Figure 1.1.

Formation Evaluation methods

PHASE

ACTIVITY

EVALUATION METHOD

Exploration

Define Structure

Seismic, gravity mapping, magnetic mapping

Drilling

Drill well

Mud logging, whole coring, MWD

Logging

Log well

Open hole logs

Primary Evaluation

Log analysis and testing

Sidewall cores, vertical seismic profile (VSP), Wireline formation testing, drillstem testing

Analysis

Core analysis

Laboratory studies

Feedback

Refinement of seismic model Log calibration via core analysis results, and log analysis seismic calibration from log analysis results

Exploration

Producing hydrocarbons

Material balance analysis

Secondary recovery

Water or gas injection and production logging

Production log analysis, flood efficiency analysis, micro-rock property analysis

Abandonment

Economic decisions

Wireline logs are one of the many different sources of data used in formation evaluation. However, due to accurate depth determination and near proximity of receiver to formation, wireline logs occupy an important position in formation evaluation. Logging is a very small, but very important, piece of the larger puzzle. The decision to

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Basic Log Interpretation plug or complete a well is often based upon the logs response and hence a proper and accurate acquisition and analysis of these data is a must.

The Basis for Log Analysis Resistivity is, perhaps, the most fundamental of all measurements in logging. All geological materials possess some amount of resistance which is inherent to the flow of an electrical current. Resistivity (R) is the physical measurement of resistance and is defined as the reciprocal of material's electrical conductivity (C).

Rock matrix, oil, and gas are electrical insulators. They will not conduct the flow of an electrical current and therefore their resistivities are said to be infinite.Water, however, will conduct electricity depending upon its salinity. This implies that any current flow through a formation is taking place in the formation water,and not hydrocarbons or the rock matrix. Salt water, with high concentrations of dissolved solids (e.g., NaCl, etc.), will conduct electricity much more readily than will fresh water. Therefore, salt water has a much lower resistivity than fresh water. In most instances, the water present in a formation at depth will be moderately saline. Water-bearing zones, therefore, have higher conductivity--or lower resistivity--than hydrocarbon-bearing zones. Because oil and gas will not conduct electrical current, it is impossible to distinguish them from rock matrix on the basis of resistivity. These fluids do, however, fill the pore space of a formation, leaving less room for conductive formation water. The electrical current that does flow through a hydrocarbon bearing formation is forced to take a more tortuous path, weaving around the hydrocarbon that occupies part of the pore space. The overall effect of the presence of hydrocarbons is an increase in resistivity. The basis for log analysis is to compare the measured resistivity of a formation with the calculated resistivity of that formation assuming its porosity is 100% water-filled. The resistivity of a rock at 100% water saturation is referred to as wet resistivity (Ro). If, for a given porosity, the measured resistivity is significantly higher than the wet resistivity, then the presence of hydrocarbons is indicated. This relationship is the basis for determining the percentage of porosity that is filled with formation water (water saturation) and therefore the percentage of porosity that is filled with hydrocarbon (hydrocarbon saturation). Water saturation (S w ) for a clean formation may be calculated using the Archie equation. Archie Water Saturation

Shc = 1.0 - Sw

Hydrocarbon Saturation

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Water Saturation of Clean Formations Consider a formation with a given amount of porosity and assume that porosity is completely filled with saline formation water of a given resistivity (Figure 1.2). The formation water resistivity (Rw ), because the saline water is capable of conducting electrical current, is quite low. The resistivity of the formation itself (Ro, or wet resistivity, where porosity is 100% filled with water) will depend upon the formation water resistivity and some other factor referred to as the formation resistivity factor (Fr). Figure 1.2. Model formation: 100% water saturated.

By rearranging this equation, formation resistivity factor (F r) can be quantified as the ratio of the formation's wet resistivity to the resistivity of the water (Rw ) present in that formation.

In this example, formation water resistivity (Rw ) is defined as constant and therefore, changes in formation resistivity factor (F r) will occur only with changes in the overall formation resistivity (Ro). The one way in which Ro can change in a formation of constant Rw is by changing the amount of fluid available to conduct an electrical current. This is accomplished through changes in porosity. As porosity decreases, the amount of water available to conduct electrical current is decreased, resulting in an increase in formation resistivity (Ro). Therefore, formation resistivity factor (F r) is inversely proportional to porosity (Φ).

This relationship between formation resistivity and porosity was researched by G.E. Archie of Shell Oil while working on limestones in France. Archie had electric (resistivity) logs from several wells, and core porosity from productive zones within these wells. He noticed that there was some relation between resistivity and porosity, and thus was able to identify zones of interest through the use of electric logs alone. What he wanted to know was the existence of some relationship that makes it possible to determine whether a zone would be productive on the basis of measured resistivity and core porosity. HLS Asia Limited

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Basic Log Interpretation Changes in the porosity of a formation may have effects other than simply increasing or decreasing the amount of fluid available to conduct electrical current. With a change in porosity, there may be concomitant changes in the complexity of the pore network that affect the conductive nature of the fluids present, and formation resistivity factor (F r) can therefore vary with the type of reservoir. These changes are expressed by the tortuosity factor (a) and cementation exponent (m).

For the limestones of Archie's experiments, the tortuosity factors and cementation exponents were always constant (a = 1.0, m = 2.0). However, this may not be the case for all reservoirs. Although both parameters can be determined experimentally for a specific reservoir, log analysts commonly use set values for tortuosity factor (a) and cementation exponent (m) depending upon lithology and porosity. These standard values are presented in Figure 1.3. Figure 1.3. Standard values for tortuosity factor and cementation exponent.

Consider now that the porous formation discussed previously is filled with some combination of conductive formation water of constant resistivity (Rw ) and oil (Figure 1.4). Oil is an insulator and will not conduct electrical current. Furthermore, because the formation is filled with both water and oil, the resistivity of the formation can no longer be referred to as wet resistivity (Ro). The measure of formation resistivity in this instance--taking into account the resistivity of the rock matrix and the fluids contained--is called true resistivity (Rt). Figure 1.4. Model formation containing both water and oil.

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Basic Log Interpretation True resistivity of a formation will only be equal to wet resistivity (Rt = Ro) when the porosity of that formation is completely filled with conductive water. However, because some of the available porosity may be filled with nonconductive oil or gas, the wet resistivity (Ro) of that formation can now be related to the measured true resistivity (Rt) by some additional factor, referred to as F'.

The factor F' can therefore be expressed as a ratio of the theoretical wet resistivity of that formation (Ro) to the actual omeasured resistivity of the formation (Rt)

In this example, because both porosity and formation water resistivity (Rw ) are considered to be constant, the resulting wet resistivity (Ro) will be constant. Therefore, changes in the factor F' will occur with changes in measured true resistivity (Rt). Under the given conditions, the only way in which measured true resistivity (Rt) of the formation can change is through the addition or subtraction of conductive fluid. For example, the addition of oil to the reservoir would result in the increase of that formation's measured resistivity (Rt) because some amount of conductive formation water would be displaced by the oil. Therefore, the factor F' is dependent upon the relative proportion of conductive fluids (water) and non-conductive fluids (hydrocarbons) in the formation. The factor F' in the above equation represents water saturation (usually expressed as Sw) which is the percentage of pore space within a formation that is occupied by conductive formation water. By substitution of equations, water saturation can be related to the physical properties of the formation and the conductive properties of the fluids it contains.

Water saturation is related to these properties by the exponent n (saturation exponent). Saturation exponent may have a range of values dependent upon specific reservoir conditions, but generally is assumed to be equal to 2.0. With knowledge of the production characteristics of the formation in question, it is possible to determine more accurate values for saturation exponent. The equation for water saturation (S w ), an expanded version of that presented as a footnote in Archie's 1942 publication and commonly referred to as "Archie's equation," has become the foundation of the entire industry of well logging. In its simplest form, Archie's equation is often expressed as:

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Basic Log Interpretation where: n

=

saturation exponent

a

=

tortuosity factor

Φ

=

porosity

m

=

cementation exponent

Rw

=

formation water resistivity

Rt

=

true formation resistivity

It is important to realize that while water saturation represents the percentage of water present in the pores of a formation, it does not represent the ratio of water to hydrocarbons that will be produced from a reservoir. Shaly sandstone reservoirs with clay minerals that trap a large amount of formation water may have high water saturations, yet produce only hydrocarbons. Water saturation simply reflects the relative proportions of these fluids contained in the reservoir. Nonetheless, obtaining accurate values for water saturation is the primary goal of open hole log analysis. With knowledge of water saturation, it is possible to determine what percentage of porosity is filled with a fluid other than water (i.e., hydrocarbons) and therefore, hydrocarbon reserves.

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Archie's Equation Dissected

Essential Calculations Log analysis calculations require values of resistivity, in particular mud filtrate resistivity (Rmf ) and formation water resistivity (Rw ). A single measured or calculated value of Rmf and/or Rw may need to be applied over a wide range of depths. Because resistivity varies with temperature, this practice requires that resistivities be corrected for the

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Basic Log Interpretation appropriate temperatures at depth. Bear in mind that Rmf and/or Rw must be corrected to the temperature at a certain depth if those values are to be used in calculations.

Determining Geothermal Gradient The first step involved in determining temperature at a particular depth is to determine the geothermal gradient (gG) of the region. Temperature increases with depth, and the temperature gradient of a particular region depends upon the geologic, or tectonic, activity within that region. The more activity, the higher the geothermal gradient. Geothermal gradients are commonly expressed in degrees Fahrenheit per 100 feet (?F/100'). If the geothermal gradient of an area is not known, then it can be determined by chart or by formula. If using a chart, it is important to use the correct chart, depending upon your location. Instructions and an example for using these charts accompany charts GEN-2a (international locations) and GEN-2b (North America locations). Geothermal gradient may also be determined by taking pertinent information from the header and using the following equation:

Note that both the chart method and the formula method require a value for mean surface temperature (Tms ). This refers to the average annual temperature of a region, and not the temperature at which resistivity measurements were made during the logging job (e.g., mud press resistivities). Mean surface temperatures for international and North America locations are presented on charts GEN-2a and GEN-2b, respectively. If the mean surface temperature for a region is not known, then it is standard practice to assume 75?F as a value for Tms , and realize the potential calculation errors that may result from this assumption.

Determining Formation Temperature (T f) Once the geothermal gradient (gG) has been established, it is possible to determine the temperature for a particular depth. This is often referred to as formation temperature (Tf ). As with geothermal gradient, Tf may be determined through the use of charts GEN2a or GEN-2b. It may also be calculated using the following equation.

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Determining R mf from R m In some cases, a value of mud filtrate resistivity (Rmf ) may not be available from the header, or there may be a question about the validity or accuracy of the measurement. A value of Rmf may be obtained from the mud resistivity (Rm) through the use of chart GEN-3. This chart requires only mud density (or mud weight) as input, and allows the determination of both Rmf and mudcake resistivity (Rmc ) from Rm. It should be remembered that values of Rmf obtained from this chart also require correction to formation temperature before their use.

Correcting Resistivity for Temperature Resistivity decreases with increasing temperature, and therefore any value of Rmf and/or Rw determined at one depth must be corrected for the appropriate formation temperature (Tf ) where those values will be used to calculate water saturation (S w ). It is vital that formation water resistivity (Rw ) be corrected for temperature. Failing to correct Rw to a higher temperature will result in erroneously high values of water saturation (S w). Therefore, it is possible to calculate a hydrocarbon-bearing zone as a wet zone if the temperature correction is not applied. Correction may be applied through the use of a chart (GEN-5) or an equation (Arp's equation). Chart GEN-5 may be used to determine the resistivity of a solution (such as Rm, Rmf , Rw , etc.) at a given temperature when the NaCl concentration of that solution is known, and vice versa. It may also be used to determine the resistivity of a solution at a given temperature when the resistivity of this same solution at another temperature is known. Instructions and examples for these particular uses accompany chart GEN-5. A more straightforward method of correcting resistivity for temperature is through the use of Arp's equation:

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Determining Formation Water Resistivity (Rw) by the Inverse Archie Method Determining a value for formation water resistivity (Rw ) from logs may not always provide reliable results; however, in many cases logs provide the only means of determining Rw . Two of the most common methods of determining Rw from logs are the inverse-Archie method and the SP method. The inverse-Archie method of determining Rw works under the assumption that water saturation (S w ) is 100%. It is necessary, therefore, that the inverse-Archie method be employed in a zone that is obviously wet. Furthermore, it is desirable to calculate Rw from the inverse-Archie method in a clean formation with relatively high porosity.

Once a clean and porous wet zone is located, lithological assumptions must be made about that formation in order to select the appropriate values of cementation exponent (m) and tortuosity factor (a) to use in the equation. This estimate should be accomplished by quick-look means using a combination of the gamma ray, porosity, and Pe curves. Formation water resistivity calculated by the inverse- Archie method (Rw a) depends upon lithology; however, Rwa calculated in one lithology can be used for water saturation (S w ) calculations in a zone of different lithology. For example, Rwa may be determined in a sandstone, and this value may then be used in the Archie equation to calculate water saturation (S w ) in a limestone, provided that the necessary temperature corrections have been made. This is one of the many assumptions that must be made in log analysis applications.

Example Application of Archie's Equation The following examples are worked with respect to the log presented in Figure 1.5. It is assumed that any zones of interest are limestone. By first observing the resistivity log, one can infer that the areas of high resistivity (8515 and 8610) indicate zones containing hydrocarbons. Areas with low resistivity (8535 and 8710) are more likely to contain conductive formation water. These axioms are not always correct because high resistivity in a formation may also be caused by a lack of porosity. Therefore, sections of higher porosity (8515 and 8710) should be of more interest than those with lower porosity (8610). The flat-line areas, falling between the zones of interest, are assumed to be nonproductive shale zones.

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Basic Log Interpretation For optimistic values of Rw to be obtained, a zone most likely to produce 100% water should be chosen for calculations. This zone should have low resistivity and relatively high porosity. There are two obvious zones fitting these criteria (8535 and 8710). The zone at 8710 has higher porosity; however, the zone at 8535 is in close proximity to the hydrocarbon zone just above it at 8515. The Rw value of this wet zone probably closely matches the Rw value of the hydrocarbon zone because they occur at virtually the same depth. On a more pessimistic note, however, this upper wet zone (8535) may contain some hydrocarbons because both the wet zone and hydrocarbon zone occur in the same porous lithologic unit. Because two wet zones are present, values of Rwa should be calculated for both, and the lesser of these two values should be used in order to obtain more optimistic water saturation (S w ) results. Lithology of the zones of interest has been given as limestone. Therefore, for all calculations, the appropriate values of cementation exponent (m) and tortuosity factor (a) must be assumed. In this case, for limestone, a = 1.0 and m = 2.0. Figure 1.5. Example log.

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Rw Calculation by Inverse-Archie Method

There are several possible explanations for the variance in calculated values for Rw a. The lesser of the two values (at 8710) may possibly be the result of a cleaner wet zone. It could also be the result of the water at 8710 having a completely different salinity than the water at 8535. More than likely, the higher value (at 8535) results from the fact that the wet zone probably contains residual hydrocarbons from the overlying zone. The decision of which value of Rwa to use in water saturation calculations should be based on experience, common sense, and logical deductions. All of the conditions discussed above should be considered. In any case where R w may be calculated in different zones or by different methods, the lowest calculated value of R w (within reason) should be used in order to obtain more optimistic (lower) calculated values of water saturation. This is a critical assumption!

For the purposes of this example, the lowest value of formation water resistivity from 8710 (Rw = 0.038 ? -m) will be used. This value, because it is the lesser of the two, will produce more optimistic values of water saturation. Once a reasonable value for Rw is established for a zone or groups of zones, it should be temperature corrected for depth, depending upon the differences in depth between its origin and its implementation. This is accomplished by using either GEN-5 or Arp's equation. In this particular example, the temperature variation between the top and bottom of the log is only 2?F, therefore no temperature correction is necessary.

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Sw Calculations Potential hydrocarbon-bearing zones may now be evaluated using the value for Rw that was previously established. High resistivity and high porosity typically characterize hydrocarbon-bearing formations, again because of the nonconductive behavior of oil and gas. There are two zones illustrated in Figure 1.5 that fit these criteria--8515 and 8610. The zone at 8610 has very low porosity; its high resistivity results from the fact that there is little pore water available to conduct current. The zone at 8515 has good porosity (~28%), and warrants further investigation. When taking measurement values from a log for use in the Archie equation, it is desirable to select a single depth rather than averaging values across a zone. Through the course of actual interpretation there may be many appealing formations. In any single formation, an analyst may choose several depths at which to calculate water saturation (S w ). Because the zones in the example log are so well defined, only two calculations are required--one in each zone.

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Permeability Indicators Scanning a log in search of zones with high porosity and high resistivity may yield a number of appealing formations. However, the presence of high porosity and high resistivity does not necessarily mean that a formation that contains hydrocarbons will actually produce those hydrocarbons (especially without stimulation or hydraulic fracturing). Without data from a Formation Tester or Magnetic Resonance Imaging log, quantitative estimates of permeability are lacking. Permeability refers to the ability of a formation to transmit the fluids it contains through the existing pore network, and is a fundamental requirement of a productive reservoir. Some standard open hole logging services provide several means of getting a qualitative estimate of a formation's permeability. The most commonly used permeability indicators are the Micro Electric (or Microlog) and the Spontaneous Potential (SP) tools. The Microlog indicates permeability when there is separation between the Micronormal (or Normal) and Microinverse (or Lateral) curves. The Micronormal curve will read a higher resistivity than the Microinverse curve because of the effects of mudcake (Rmc ) on the resistivity measurements. Mudcake can only be present opposite a permeable formation, therefore the presence of this separation is used as a qualitative indicator of permeability. The Spontaneous Potential, apart from providing a qualitative estimate of permeability, may also be used to determine a value of formation water resistivity (Rw ). A permeability indicator (in this case the SP response) for the log presented in Figure 1.5 might appear as the curve presented in Track 1 of Figure 1.6. The SP will often respond in such a way that it reflects the same trend as the porosity device; however, this is not always the case. Negative deflections of the SP curve are used as qualitative indicators of permeability. Permeable zones in this example log (Figure 1.6) are indicated at 8500 to 8535, 8595 to 8610, and 8680 to 8720. The zone responsible for the most SP deflection (8700) is not necessarily the zone with the most permeability. Likewise, because the zone at 8500 exhibits less SP deflection than the zone at 8700, this does not mean that it has less permeability than the deeper of the two formations. Whereas the presence of negative SP deflection may be an indicator of permeability in a particular zone, the absence of any deflection does not indicate an absence of permeability. If permeability is not evident on a log, evaluation of the porosity and resistivity curves can still result in low water saturation calculations. Depending upon the geology and the type of tool used to indicate permeability, hydraulic fracturing or other formation treatment methods may be necessary to produce hydrocarbons. Locating permeable zones using SP response is an important first step in any "quick-look" analysis program.

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Basic Log Interpretation Figure 1.6. Example log illustrating permeability indicator (SP curve) in Track 1.

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Determining Formation Water Resistivity (Rw) by the SP Method Once zones of interest are located by observing trends in their resistivity, porosity, and permeability indicator responses, determination of formation water resistivity (Rw ) is in order. As discussed previously, Rw can be calculated by rearranging the Archie equation and assuming a water saturation (S w ) of 100%. An additional method of assessing Rw is through the use of an SP versus Rmf chart (SP-4), and is referred to as the SP method. As with the inverse-Archie method, the SP method gives best results in clean and relative porous formations. However, because virtually anything and everything affects the SP measurement it sometimes does not yield reliable results. The SP method may be advantageous in certain circumstances where porosity data are not available. Several steps are involved in determining Rw from the SP response. These procedures are outlined in Figure 1.7. Figure 1.7. Steps involved in determining Rw by the SP method.

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Detailed Procedure of SP Method Determine Formation Temperature (T f) From chart GEN-2b, locate the mean surface temperature (Tms = 60oF) for the Midontinent. Using this value, determine the geothermal gradient (gG = 1.14oF/100') and formation temperature (Tf = 159oF) from the chart or by the appropriate equation. Determine R m f Plot Rm = 0.88 Ω-m versus Rm reference temperature (70oF) on GEN-5. This results in a salinity value of 7,000ppm NaCl. Following this salinity curve to the formation temperature of the zone of interest (Tf = 159oF) results in a mud resistivity (Rm) value of 0.40 Ω-m at 159oF. With the value of the mud resistivity (Rm = 0.40 Ω-m) at the proper formation temperature (Tf = 159oF), use GEN-3 to determine Rmf = 0.22 Ω-m and Rmc = 0.75 Ω-m at 8710. Plot R mf and Determine SSP Plot Rmf = 0.22 Ω-m on the X-axis of SP-4. Project a vertical line upward to an interpolated imaginary line representing Tf = 159oF (slightly less than half-way between 150oF and 175oF). From this point, extend a horizontal line to the Yaxis to find SSP = 132mV. Determine SP Deflection Assuming the SP base line to be the second division from the right of Track 1, the deflection at 8710 is -70mV. Differentiate Between SSP and SP

Re-enter SP-4 on the Y-axis at 62mV. Project a horizontal line to intersect the interpolated imaginary line representing Tf = 159oF. Determine R w From the intersection determined in the previous step, project a vertical line downward to the X-axis. This plot should fall on a value of Rw = 0.037 Ω-m. There is a 0.001 Ω-m difference between the Rw values determined by the inverse-Archie method and the SP method at 8710 (Rwa = 0.038 Ω-m and RwSP = 0.037 Ω-m). This minor difference is in support of the fact that both measurements likely represent accurate values of formation water resistivity (Rw ). Water saturation (S w ) calculations using these two values would result in differences of less than 1%. HLS Asia Limited

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Additional Notes on Formation Water Resistivity Determining an accurate value of formation water resistivity (Rw ) from logs is often quite difficult, and usually not as straightforward as presented in these examples. A zone that is assumed to be 100% water saturated may, in actuality, not be. The presence of hydrocarbons may suppress any SP deflections, resulting in erroneous calculations. Furthermore, in a slightly shaly formation, clay minerals may result in abnormally low resistivities. Perhaps the most dangerous situation is assuming that a particular zone is wet when it actually contains hydrocarbons. This misinterpretation will result in compounded errors in the process of log analysis. When possible, it is best to calculate formation water resistivity (Rw ) using a variety of methods at several different depths. The results can then be ranked and compared to reveal a "best pick" for the reservoir. In an effort to be optimistic in water saturation (S w) calculations, it is usually beneficial to pick the lowest value (within reason) of formation water resistivity (R w). The worldwide average for formation water resistivity without correcting for temperature is 0.05 Ω-m. Additional methods of evaluating formation water resistivity will be discussed in later sections of this text.

Additional Rw Calculation Example The log for this example calculation is illustrated in Figure 1.8. The objective is to determine an appropriate value for Rw from the log. It may be assumed that any zones of interest are sandstone. Given Location: T.D.: B.H.T.: Mud weight:

Santa Cruz, Bolivia 3,600 meters 60 deg. C 13 lbs/gal

Drilling Fluid Constituents: Sodium 3,000 ppm Chloride 4,000 ppm Magnesium 2,900 ppm Calcium 2,500 ppm Define Zones of Interest The only worthwhile SP deflection occurs from 2775m to 2830m. Within these limits there are two definite zones of interest. The upper zone (2790m) has low resistivity and high porosity, and is an ideal choice for Rw calculations assuming 100% water saturation. The lower zone (2815m) has high resistivity and high porosity, making it a likely candidate for a hydrocarbon-bearing zone. The zone at 2900m exhibits no indication of permeability, and has both lower resistivity and lower porosity than the zone at 2815m. Because the SP response may be suppressed by the ratio Rmf /Rw , a zone of this nature may still be of interest to the client, and should be evaluated.

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Basic Log Interpretation Determine Formation Temperature (T f) From chart GEN-2a, determine the mean surface temperature (Tms = 15oC) of Santa Cruz. After establishing a base line, project a vertical line upward from BHT = 60oC on the X-axis, and project a horizontal line from the right of the TD (3600m) on the Y-axis. The intersection of these two lines should fall on a line representing the geothermal gradient (gG = .25oC/100m). Following the geothermal gradient line upward to the depth of the zone of interest and descending from that intersection to the X-axis yields a formation temperature (Tf ) of 50oC at 2790m (wet zone). Figure 1.8. Example log from Santa Cruz, Bolivia, region.

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Basic Log Interpretation Determine Equivalent NaCl Concentration The equivalent NaCl concentration can lead to an estimated value of mud resistivity (Rm) at the zone of interest. To determine this concentration, chart GEN-4 must be used.

Add the concentrations of the four ionic constituents to obtain a total ion concentration. Enter GEN-4 on the X-axis at a value equal to this total concentration. Project a vertical line upward to intersect with the lines corresponding to each of the particular constituents (Ca, Cl, Mg, Na). From the projected intersections, extend horizontal lines to intersect the Y-axis. The Y-axis values represent corrective multipliers for each constituent. Determine R m at Zone of Interest With the estimated total solution of NaCl = 12,596ppm, use chart GEN-5 to obtain a mud resistivity (Rm = 0.29 Ω-m) at 2790m. Determine R m f Using GEN-3, determine Rmf = 0.13 Ω-m at 2790m. Plot R mf and Determine SSP Using SP-4, plot Rmf = 0.13 Ω-m on the X-axis and extend a vertical line upward to the proper formation temperature line (Tf = 122oF). To convert between oF and oC, use the top and bottom scales of GEN-5. Project a horizontal line from this intersection to the Y-axis and obtain an SSP value of 98mV. Determine SP Deflection From the log, the SP deflection at 2790m is roughly -62mV from the baseline. Differentiate between SSP and SP

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Basic Log Interpretation Plot ∆SP Re-enter chart SP-4 on the Y-axis with a value of 36mV. Project a horizontal line to the interpolated 122oF line representing formation temperature (Tf ). Determine R w From the intersection established in the previous step, extend a vertical line downward to the X-axis. This plot should fall on a value of Rw = 0.035 Ω-m. Determine R w from the Inverse-Archie Method Because the lithology of formations of interest is given to be sandstone and the porosity of the zone at 2790m is greater than 16%, the Humble values of tortuosity factor (a) and cementation exponent (m) may be assumed.

Comparison of R w Results The values of Rw calculated by different methods for the zone at 2790m differ by 0.091 Ω-m. This is a major difference, and will have detrimental effects on calculated values of water saturation (S w ). The decision as to which value to use should be based on experience as well as information taken from the log. The SP method has yielded a more reasonable and optimistic value of formation water resistivity (Rw = 0.034 Ω-m), and should be used in future calculations to obtain more optimistic values of water saturation (S w ).

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"Quick-Look" Methods in Log Analysis Before water saturation is calculated for any zone, it is necessary to scan a log and locate favorable zones that warrant further investigation. This is true not only for potential hydrocarbon-bearing zones, but water-bearing zones as well. This is often referred to as ”scanilizing" a log. There are certain responses that should be looked for, and these responses may indicate whether a zone is water-bearing or hydrocarbonbearing. "Quick-look" log analysis employs scanilizing to locate potential zones of interest, and also employs the basic concepts and procedures thus far considered in this text. The objective in performing a "quick-look" analysis is to quickly produce values of water saturation for zones that appear interesting on a log. It is important to remember that in "quick-look" analysis environmental corrections are not applied. Therefore, the water saturation values obtained during "quicklook" analysis may not be as accurate as those determined through in-depth and detailed log analysis and interpretation. When performing a "quick-look" analysis--which should be the first step of any detailed investigation--six questions must be asked when considering whether a zone is potentially productive. What value will be used for R w ? What are the lithologies of the zones of interest? Are the hydrocarbon-bearing zones "clean" (shale-free)? Is there sufficient porosity in the zones? Is there satisfactory resistivity in the zones? Are the zones permeable? The particular methodology by which an individual approaches the "quick-look" analysis may vary, yet should address all of the questions posed above. There should be some order and consistency to the method. A suggested "quick-look" approach is outlined in the following paragraphs.

Identify Permeability Indicators Scan the appropriate permeability indicators presented with the log. These may include the SP, Microlog, Caliper, and even resistivity invasion profiles. Mark on the log all zones that exhibit potential permeability, regardless of whether they appear waterbearing or hydrocarbon-bearing. This should always be the first step of a "quick-look" analysis, particularly with High Resolution Induction (HRI) logging suites.

Determine Formation Water Resistivity (R w ) If the customer provides this data, then the source is defined. If not, then it may be necessary to calculate Rw from the logs. Locate a relatively clean waterbearing zone of sufficient porosity and determine Rw using the inverse-Archie and/or SP methods. If

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Basic Log Interpretation more than one water-bearing zone is located, then Rw should be calculated for all zones. Tabulate the results and select the lowest value of Rw for future calculations, remembering that lower values of Rw (within reason) produce more optimistic values of water saturation (S w ).

Determine Porosity and Resistivity of Zones Once a permeable zone is located, porosity and resistivity curves should be checked to see if the relationship between them indicates the possible presence of hydrocarbons. These curves should be considered together, and not without respect to one another. Recall that it is entirely possible for a zone to exhibit an increase in resistivity because of a decrease in porosity. Therefore, without considering all the data, it is possible to misidentify a tight zone as being potentially productive. Most porosity logs will present two porosity curves--density porosity (Φ D) and neutron porosity (Φ N). Both of these curves reflect formation porosity, but the differences in their values depend upon the different ways in which the respective measurements are made. The Archie equation provides for only one value of porosity, therefore it is necessary to calculate cross-plot porosity before calculating water saturation. Cross-plot porosity is a weighted average of the two values, and is calculated by the equation below. Additional discussion of cross-plot porosity is included in later sections of this text.

A quick determination of cross-plot porosity may be made by estimating "two thirds" porosity. This is done by visually estimating two-thirds the distance between the minimum-porosity curve and the maximum-porosity curve. For "quick-look" purposes, the use of visually estimated "two-thirds" porosity is sufficient for making water saturation calculations.

Determine Formation Lithology Lithology identification can be accomplished in several different ways, the most basic of which is to examine the responses of various curves. For "quick-look purposes, the curves most useful for lithology determination are gamma ray, Pe, resistivity, and a combination of neutron porosity and density porosity. Once lithology of the zone is determined, the necessary parameters (a & m) may be selected for water saturation calculations.

Determine Formation "Cleanliness" An additional concern is the "cleanliness" of the formation which refers to the amount of shale present. All types of formations--sandstone, limestone, and dolomite--may contain clay minerals ("shale"). The presence of these clay minerals effects the responses of certain tools--namely, resistivity and porosity tools--and may result in a productive formation being overlooked as waterbearing The degree of shaliness of a formation can be judged from the gamma ray response. In general, the lower the

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Basic Log Interpretation gamma ray response of a porous zone, the lesser the amount of shale ("clean formation"). This judgement requires some amount of experience and knowledge in the area, and a later section of this text addresses more detailed methods of shaly sand analysis.

Calculate Water Saturation Water saturation may now be calculated for those zones that appear to be hydrocarbon-bearing. Remember that this value is not a reflection of the ratio of water to hydrocarbons that will be produced from the reservoir. It is simply the relative proportion of water to hydrocarbons in the porosity of that formation. There are no safe guidelines for determining what constitutes "good" and "bad" values for water saturation. This judgement calls upon experience and local knowledge.

References Archie, G. E., 1942, The electrical resistivity log as an aid in determining some reservoir characteristics: SPE-AIME Transactions, v. 146, p. 64-62. Asquith, G. B., 1982, Basic well log analysis for geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p. Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston MA, 647 p. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishing, Tulsa, OK, 361 p. Halliburton Energy Services, 1994, Log Interpretation Charts.

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Section 2

Porosity and Mineralogy Table of Contents Introduction………………………………………………………………………………………….

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Objectives…………………………………………………………………………………………...

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Cross-Plot Porosity and Lithology (CP Plots)…………………………………………………...

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Two-Thirds Porosity………………………………………………………………………………..

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Cross-Plot Porosity…………………………………………………………………………………

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Cross-Plot Porosity and Lithology from Chart…………………………………………………..

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Limitations of Cross-Plot Porosity (CP) Charts………………………………………………….

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Cross-Plot Gas Effect……………………………………………………………………………...

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Cross-Plot Shale Effect……………………………………………………………………………

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Sonic Tool Cross-Plot Charts……………………………………………………………………..

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Complex Reservoir Mineralogy…………………………………………………………………...

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Clastic Sedimentary Rocks………………………………………………………………………..

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Carbonate Sedimentary Rocks…………………………………………………………………...

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Complex Lithologies………………………………………………………………………………..

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Mineral Identification Plots (MIP Plots)…………………………………………………………..

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References………………………………………………………………………………………….

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Introduction Determining accurate values of porosity (Φ) and describe lithology of a formation based on log responses is one of the vital step in any log analysis. Assumed values of tortuosity factor (a) and cementation exponent (m) necessary to calculate water saturation (S w ) are dependant on these determinations. This section presents an overview of the different methods available for determining porosity and lithology as well as methods for determining complex lithology composition. To effectively use this section, the participant should have a copy of the Halliburton Log Interpretation Charts manual. Examples illustrated in this section will make frequent references to this Log Interpretation Charts manual.


visually estimate "two-thirds" porosity from neutron-density data.

§

calculate cross-plot porosity of a formation by equation.

§

determine cross-plot porosity of a formation by Cross-Plot (CP) chart using a combination of neutron, density, and/or sonic data.

§

determine two end-member lithology of a formation by Cross-Plot (CP) chart using a combination of neutron, density, and/or sonic data.

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recognize the effects of gas and shale on Cross-Plot (CP) data plots.

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apply the appropriate correction on a Cross-Plot (CP) chart to compensate for the effects of the presence of gas.

§

determine three end-member lithology of a formation by Mineral Identification Plot (MIP) using a combination of neutron, density, and/or sonic data.

§

recognize the effects of shale on Mineral Identification Plots (MIPs).

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Cross-Plot Porosity and Lithology (CP Plots) Two of the most important uses of log data are to provide porosity and lithology Information to the geo-scientific community and use it for calculating water saturation (S w ). Porosity is a vital input to Archie equation. A knowledge of lithology is also helpful because it empowers the analyst make a reasonable determination to choose appropriate value of tortuosity factor (a) and cementation exponent (m). Porosity measurements taken from an individual logs are rarely adequate for use in calculating water saturation. This is because of Natures heterogeneity. Once density and neutron porosity values are corrected for environmental effects, the analyst has two values of porosity--neutron porosity and density porosity. Archie water saturation calculations require only one input value for porosity. Which one to be considered for rational saturation evaluation? This is a big dilemma and requires a step to move forward.

Two-Thirds Porosity One method of visually estimating a value of porosity for use in the Archie equation is referred to as "two-thirds" porosity. This method simply involves estimating two-thirds the distance between the lowest porosity reading and the highest porosity reading, and taking that value as input into the Archie equation. This method may be used regardless of which matrix (e.g., limestone, sandstone, dolomite) was used to calculate porosity. Regardless of matrix choice, two -thirds porosity may be assumed to reflect the approximate porosity of a formation of any lithology. The reason for taking twothirds the distance between porosity readings rather than a simple average is to more closely approximate the value that would be calculated by the cross-plot porosity equation (discussed below). Some analysts prefer to take a simple average of the two measurements. An important limitation in the estimation of two-thirds porosity is the presence of gas. Because gas affects neutron porosity more than it does density porosity, any averaging routine may contain error. Fortunately, in the presence of gas, density and neutron porosity partially compensate one another. This limitation should be kept in mind when applying the method. Furthermore, this approximation should be made with caution where anhydrite is present. Because of the high bulk density of anhydrite (ρb = 2.98g/cc), density porosity will often read too low (in some cases, negative). Averaging methods, therefore, will result in a value of formation porosity that is too low.

Cross-Plot Porosity Another method of obtaining a single value for porosity from density porosity and neutron porosity data is through the use of the cross-plot porosity equation.

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Basic Log Interpretation The value obtained from this equation likewise may be assumed to represent the actual formation porosity, regardless of which matrix value was used during logging. This weighted average results in values similar to those obtained by visually estimating the two-thirds porosity of a formation. Again, an important limitation in the use of this method is the presence of gas and anhydrite. These circumstances will create a situation in which the value of crossplot porosity is not an accurate approximation of formation porosity. In cases where density porosity reads negative values (common in anhydritic dolomite reservoirs), some analysts prefer to use a simple average of density and neutron values as illustrated below.

Cross-Plot Porosity and Lithology from Chart The cross-plot porosity equation is assumed to be correct for any particular matrix (e.g., limestone, sandstone, dolomite) that may have been used to calculate density and neutron porosity. However, this assumption is in error because the porosity values do, in fact, depend upon what matrix was used in calculating porosity. For instance, a formation consisting of 70% limestone and 30% dolomite might have two possible porosities; one if run on a limestone matrix, and another if run on a dolomite matrix. This condition may necessitate that crossplot porosity be determined from chart. An added benefit of this method is that a basic lithology of the formation in question is also obtained. The proper Cross-Plot Porosity (CP) chart is determined first by tool type, and second by the density of the drilling fluid. The chartbook differentiates between five types of neutron tools: Dual Spaced Neutron (DSN); Compensated Neutron (CNT-K); Hostile Dual Spaced Neutron (HDSN); Dual Spaced Epithermal Neutron (DSEN); and, Sidewall Neutron (SNL). Each of these chart sections contains Cross-Plot Porosity charts for oil-based muds (ρfl = 0.85g/cc), freshwater-based muds (ρfl = 1.0g/cc), and saltwater-based muds (ρfl = 1.15g/cc). On these charts, neutron porosity is cross-plotted with bulk density (ρb). Neutron porosity may also be cross-plotted with interval transit time (∆t), or bulk density and sonic measurements may be cross-plotted together without implementing a neutron measurement at all. To illustrate the use of the neutron-density Cross-Plot Porosity (CP) chart, refer to the example worked in blue on the CPDSN-II-1a chart. This chart fits the conditions where a Dual Spaced Neutron (DSN) tool was logged in an oil-based mud (ρfl = 0.85g/cc). Example Data for Chart CPDSN-II-1a Φ N = 17% on limestone matrix (environmentally corrected) Φ D = 20% on limestone matrix (ρb = 2.34g/cc)

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Basic Log Interpretation To correctly use this chart, it is important to ensure that environmental corrections have already been applied to the recorded porosity measurements. Furthermore, notice that both density and neutron porosity values are in units of limestone porosity. If these conditions are not met, then the use of the chart will not yield accurate results. Neutron porosity may be converted from one lithology to another through the use of chart POR12. Using the example data above, enter the chart with the environmentally corrected value of neutron limestone porosity (17%) on the X-axis. Extend a vertical line upward to intersect a horizontal line that represents either the bulk density (? b = 2.34g/cc) or density limestone porosity (? D = 20%). The resulting plot falls between the sandstone and limestone matrix division lines. Assuming that the formation consists of a mixture of sandstone and limestone, to interpolate cross-plot porosity extend a straight line (solid blue line) between equal values of porosity on both the quartz and calcite matrix division lines (the black lines at the top of the red shaded regions). In this example, the point plots along a line representing a cross-plot porosity of 19% if that formation is, indeed, a mixture of sandstone and limestone. Relative proportions of the two end-member lithologies (sandstone and limestone) may be estimated by normalizing a scale along the solid blue line between the two matrix division line with each division line representing 100% of that particular lithology. The point in question plots at approximately 65% calcite and 35% quartz (sandy limestone). However, this is not the only possible solution for the plotted data. Notice that the plotted point also falls between the matrix division lines of sandstone and dolomite. Without previous knowledge of the reservoir, it is impossible to determine from the log which lithology mixture is correct. It is therefore necessary to obtain a second value for cross-plot porosity assuming that the formation consists of a mixture of sandstone and dolomite. This is accomplished in the same manner as above by extending a straight line (dashed blue line) between equal values of porosity on both the quartz and dolomite matrix division lines. For the assumed sandstone-dolomite mixture, cross-plot porosity is 20%. Again, relative proportions of the two end-members (sandstone and dolomite) may be estimated by normalizing a scale along the dashed blue line between the two matrix division lines. The plotted point represents a mixture of approximately 70% quartz and 30% dolomite (dolomitic sandstone). In this particular example, cross-plot porosity differed only slightly between the two possible lithology combinations. In other instances, the difference may be more significant. Cross-plot porosity is relatively insensitive to the mineralogy mixture provided that the lithology is composed of two of the three common minerals: quartz, calcite, and dolomite. The presence of other minerals, however, will require a different approach. When different porosity values and different lithologies are obtained from Cross-Plot charts, it is advisable to calculate formation water resistivity (R w ) and water saturation (S w ) for both situations, and present the results of each. HLS Asia Limited

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Basic Log Interpretation Do not base an interpretation on a single chart or a single method. An errorfree evaluation can seldom be made from one curve, or from a single chart or evaluation technique.

Limitations of Cross-Plot Porosity (CP) Charts The choice of basic lithology is obviously quite important. Apart from the difference in resulting cross-plot porosities, the values for tortuosity factor (a), cementation exponent (m) and even saturation exponent (n) may need to be altered. In the previous example, the cross-plot lithology determination was based upon only two measurements (neutron porosity and bulk density). At best, the Cross-Plot method can differentiate between only two minerals. The previous example data presented two possible solutions: sandy limestone or dolomitic sandstone. There are, however, certain effects that tend to mask the apparent lithology of a formation, thereby making their evaluation more difficult.

Cross-Plot Gas Effect The presence of gas in a formation has a profound effect on the neutron porosity measurement. Because the tool measures hydrogen index, the low hydrogen density of gas (compared to hydrogen density of liquids) causes the neutron tool to underestimate porosity. Gas also affects the density measurement, causing density porosity to be overestimated. If gas is present, then the base lithology of the formation of interest must fall somewhere to the lower right of its plotted point. Although not a precise method by any means, the presence of gas may be corrected for by drafting a line parallel to and in the same direction as the "Approximate Gas Correct" arrow. This line should extend from the plotted point of interest to the nearest lower-right matrix division line. The base lithology, of course, should be logically determined from cuttings, core samples, tool response in non-gassy zones, etc.. The presence of gas may cause tremendous problems in resolving lithology from a Cross-Plot chart. Because gas tends to pull points up and to the left, it is entirely possible for a 100% dolomite gassy formation to plot along the matrix division line representing 100% sandstone. For that matter, the point may also fall somewhere between the quartz and calcite matrix division lines, giving the impression that dolomite is not present at all.

Cross-Plot Shale Effect The presence of shale will also adversely influence the interpretation of the plotted point. In reality, the properties of shale (to be discussed in more detail later) affect all logging responses to some degree. The primary concern on a neutron-density CrossPlot chart is the characteristic high porosity reading of the neutron tool. The high porosity response of the neutron tool together with the relatively high bulk densities typical of shales will push the plotted point of a shaly formation to the bottom right of where it would fall if it were clean. For example, a shaly sandstone could

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Basic Log Interpretation feasibly have a point which plots along the matrix division line representing 100% dolomite. A 100% pure shale will typically plot within an area defined by the following limits: 30% < Φ N < 40% 2.35g/cc < ρb < 2.50g/cc Because the presence of shale tends to pull plotted points down and to the right, correction for shale would therefore be up and to the left. How far to the left and at what angle the correction is to be taken would be determined by the characteristics of that particular shale. For now, it is sufficient to realize that the presence of shale can cause dramatic misinterpretations about the lithology of a formation when using Cross-Plot porosity charts.

Sonic Tool Cross-Plot Charts The "Sonic versus Bulk Density" and "Sonic versus Neutron Porosity" charts may be interpolated or extrapolated in the same manner as the "Bulk Density versus Neutron Porosity" charts previously discussed. These charts may be used as an alternative to the neutron-density cross-plots, or as an additional method for providing solutions to the constraints that exist on lithology front. The use of "Sonic versus Neutron Porosity" Cross-Plot charts can help refine the estimate of lithology obtained from the neutrondensity Cross-Plot charts. When two different methods converge to a particular solution it gives adequate weight to derived conclusions. The "Time Average" lines represent the response of the Wyllie-Time Average sonic porosity equation. This response is based on the premise that the travel time through a porous formation will remain unchanged irrespective of pressure variations, this happens when the formations have reached the terminal velocity. Porosity is commonly calculated with the Wyllie-Time Average equation illustrated below.

The "empirical," or curved, lines represent the response from a combination of data gathered by Raymer-Hunt and Halliburton. This is a purely emperical calculation based upon comparisons of transit times with core porosities and porosity as derived from other types of logs. The Raymer-Hunt equation for sonic porosity is illustrated below.

The choice of equation for computing sonic porosity should be left to the customer. Because the customer is aware of other wells in the same region and reservoir, and how sonic porosities were calculated from those logs.

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Complex Reservoir Mineralogy Most oil- and gas-bearing formations are composed of sedimentary rock, as opposed to igneous and metamorphic rock. Sedimentary rock, as its name implies, is composed of different types of sediments that have been deposited at some type of accumulation point, possibly an ancient ocean basin or river channel. After some period of geologic time, many such layers of sediment may accumulate. The tectonic forces imposed upon these layers results in compaction and cementation of the loosely consolidated sediments into a sedimentary rock. By volume, sedimentary rocks are estimated to constitute only 5% of the known lithosphere (the 10 mile-thick outer shell of the earth), whereas igneous and metamorphic rocks account for 95%. However, sedimentary rocks cover 75% of the total land area on continents, with igneous and metamorphic rocks covering the remainder. It is evident, therefore, that sedimentary rocks must form only a thin, superficial veneer on the surface of the earth. For the purposes of this discussion, sedimentary rocks can be subdivided into two primary categories: clastic and carbonate. These categories comprise the three most common producing reservoir rock types: sandstones, limestones, and dolomites. The composition, place of origin, and granular size of the individual sediments of a rock are among the factors that determine the rock's identity.

Clastic Sedimentary Rocks Clastic sediments are those produced by the weathering and breakdown of preexisting rocks. These particles, having been derived somewhere other than the accumulation point, are transported, sorted, and modified by moving fluid such as water or air. Their deposition is normally in successive horizontal layers. Clastic sedimentary formations are typically sandstones and shales. Apart from differing in composition, these two rock types also differ dramatically in constituent grain size. This combination of similarities (origin) and differences (grain size) produces formations containing combinations of both sandstone and shale. Because shaliness affects both formation characteristics and log responses, it will be discussed in detail later in the text. Sandstone is composed primarily of quartz, feldspar, and mica. In many forms of sandstone, quartz constitutes over 90% of the detrital fraction of the rock. For this reason, many charts refer to sandstone formations simply as "quartz."

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Carbonate Sedimentary Rocks Carbonate formations are usually marine in origin and composed primarily of skeletal grains and/or seawater precipitates. These constituents are produced within the region of accumulation, and are not derived form weathering or breakdown of pre-existing rocks. Productive carbonate formations typically include limestones and dolomites. The primary difference between these two types of rocks is the chemical composition. The term "limestone" is used for rocks containing predominantly calcite: CaCO3. The term "dolomite" implies substitution of Ca with Mg. Dolomite composition is:(CaMg(CO3)2).

Complex Lithologies Subsurface formations may be heterogeneous e.g. a clastic may have lime marter making it calcarious sandstone and similarly carbonate rocks.may contain high percentage of marl commonly termed as shaly limestone. In addition, the presence of accessory minerals may cause further confusion when determining lithology from a Cross-Plot chart. At best, the Cross-Plot methods discussed previously can identify only two end minerals. The methods are fairly accurate provided that the rock matrix is composed of two of the three common minerals: quartz, calcite, and dolomite. To address the problem of the possible presence of other minerals (e.g., clays, coals, anhydrite, halite etc) a more rigorous method of mineralogy identification (Mineral Identification Plots) may be used.

Mineral Identification Plots (MIP Plots) When complex lithologies are suspected and accuracy is of the utmost importance inverse technique (ULTRA) is the only solution. However, there are techniques through which mineral identification can be tried. In the previous examples of Cross-Plot chart data from two logging measurements (e.g., ρb and Φ N, ρb and ∆t, or Φ N and ∆t) may be used to identify lithologies limited to only two end-members. By using a chart that handles a third measurement (e.g., Pe), a more accurate evaluation can be ascertained. In this discussion, two techniques of "trimineral plots will be considered: Umaa versus ρmaa, and ρmaa versus ∆tmaa. Accurate lithology determination may be necessary for a variety of reasons: §

Porosities may be near cut-off values (~5%); therefore, the most accurate values obtainable from logs are desired. Dolomite and shale, for example, cause similar separation between limestone-based neutron and density porosity curves, but effective porosity is computed differently for each case.

§

Tight (low porosity) formations often require acidizing or acid fracturing to stimulate production. Optimization of this operation requires knowledge of the formation lithology.

§

Lithology distribution across a field may reveal preferential directions for the locations of future offset wells. For example, dolomitization is often accompanied by increased permeability, therefore the direction of increasing dolomite content may be a favorable direction for further exploration.

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Basic Log Interpretation Spectral logging tools (Spectral Density and Spectral Gamma Ray) can be used individually to determine simple lithologies in "pure" formations. Combinations of two more basic tools (e.g., DSN versus CDL, CDL versus BCS) can also be utilized for determining simple lithologies. However, when used in complex lithology situations, such "two tool cross-plots" can be very misleading. For example, a point plotting directly on the limestone matrix division line of a neutron-density Cross-Plot chart could possibly be the response of a dolomitic sandstone. The use of three different types of log responses is the next logical step in the goal of increasing accuracy and reliability of lithology identification. Because the manipulation of a three-dimensional chart (X-axis, Y-axis, and Z-axis) would be rather cumbersome within the confines of a two-dimensional chartbook, the three tool responses must first be incorporated into simple X-Y coordinates. These calculated X and Y coordinates then are introduced into the respective Mineral Identification Plot (MIP), and the complex mineralogy resolved. Mineral Identification Plots (MIPs) have an advantage over Cross-Plot (CP) charts in that they resolve three end-member lithologies.

Umaa Versus ρmaa MIP Method The Umaa versus ρmaa MIP method of lithology determination requires a Spectral Density (SDL, with Pe curve) and neutron for implementation. The Mineral Identification Plot charts are labeled MIP XXX-8, according to the particular type of neutron tool being used. Notice that the X-axis and Y-axis coordinates of these charts are not values that can be taken directly from logs. The "Apparent Matrix Density (ρmaa)" and "Apparent Volumetric Photoelectric Factor (U maa)" must first be determined using separate charts (MIP XXX-4 and MIP XXX-6, respectively). Utilization of this method requires three steps: 1. ρmaa determination (chart MIP XXX-4) 2. Umaa determination (chart MIP XXX-6) 3. ρmaa versus Umaa MIP plot (chart MIP XXX-8) ? maa Determination Without having actual core samples of the formation of interest, it is impossible to know an exact value of matrix density (ρma). However, by being able to determine Cross-Plot lithology of a formation from charts using neutron and density data, it possible to estimate the apparent matrix density (ρmaa) from these data (Step 1). For the purposes of illustration, the chart MIP DSN-II-4 will be referenced here. Notice that this chart is developed for a fluid density (ρfl) of 1.0g/cc (freshwaterbased drilling fluid). There are no charts available for use in those conditions where ρfl _ 1.0g/cc, therefore this same chart will also apply for oil-based mud and saltwater-based mud conditions. Furthermore, notice that neutron porosity must be in limestone porosity units. Again, the conversion of another neutron lithology to limestone, if necessary, may be made using chart POR-12. HLS Asia Limited

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Use of the MIP DSN-II-4 chart is identical to the use of the neutron-density Cross- Plot charts discussed previously. In fact, the red lines representing quartz, calcite, and limestone are identical to the matrix division lines of the Cross-Plot charts. In this case, however, the objective is to determine the apparent matrix density (ρmaa) of the plotted point with respect to the known matrix densities of those three minerals (2.65g/cc, 2.71g/cc, and 2.87g/cc, respectively). To illustrate the use of this chart, the same example data used previously in the CrossPlot charts will be used here as well. Example Data for Chart MIP DSN-II-4 Φ N = 17% on limestone matrix (environmentally corrected) Φ D = 20% on limestone matrix (ρb = 2.34g/cc) Pe = 2.41 Φ XPLOT ≅19% (as determined from CPDSN-II-1a) Using the example data above, enter the chart with the environmentally corrected value of neutron limestone porosity (17%) on the X-axis, and enter the Y-axis with a bulk density (ρb) of 2.34g/cc. The result plot of the example data yields an apparent matrix density (ρmaa) of approximately 2.675g/cc. Again, notice that chart MIP DSN-II-4 is simply a standard neutron-density Cross-Plot chart with matrix density values interpolated between the three primary matrix division lines (e.g., quartz, calcite, and dolomite). The resulting value of apparent matrix density (ρmaa) may be thought of as the matrix density of the formation that is "seen" by a combination of the neutron and density tools. Umaa Determination The photoelectric (P e) response is not linear with changes in formation composition. For example, given that the Pe of sandstone is 1.81 and the Pe of limestone is 5.08, a formation consisting of 50% sandstone and 50% limestone does not necessarily have a Pe value of 3.44. The non-linear response of the Pe requires that a volumetric conversion be considered (Step 2) if Pe values are to be used in lithology determination. This step, considering the use of the DSN-II in our example data, requires the use of chart MIP DSN-II-6. The volumetric cross section (U) is a product of the electron density (ρe) and photoelectric factor (or cross section). By substituting bulk density (ρb) for electron density, a value of Apparent Volumetric Photoelectric Factor (Umaa) can be calculated by the equation illustrated below. This equation is the foundation for all MIP XXX-6 charts, regardless of the type of neutron tool used.

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Basic Log Interpretation Using chart MIP DSN-II-6, enter the lowermost scale on the X-axis with a bulk density (ρb) of 2.34g/cc. From this point, extend a line through the value for Pe taken from the log (2.41) on the Modified Photoelectric Factor scale to a point that plots on the bottom Xaxis of the graph. The value plotted on the bottom Xaxis of the graph represents the Volumetric Modified Photoelectric Factor (Um), and should be approximately 5.7. From this point on the bottom X-axis of the graph, extend a vertical line upward to intersect a horizontal line representing a value of Apparent Total Porosity (Φ ta). A value for Apparent Total Porosity (Φ ta) is obtained by either estimating two -thirds porosity, calculating cross-plot porosity by equation, or by the Cross-Plot charts. From the CrossPlot charts worked previously, this value was determined to be approximately 19%. Cross-plotting a Volumetric Modified Photoelectric Factor (Um) value of 5.7 with an Apparent Total Porosity (Φ ta) value of 19% results in a plot that falls on the line representing an Apparent Volumetric Photoelectric Factor (Umaa) of 7.0. Mineralogy Determination (ρmaa versus U maa MIP Plot) For the DSN-II tool, the next chart to use in determining mineralogy (Step 3) is MIP DSNII-8. Enter this chart with the previously derived matrix information (ρmaa = 2.675g/cc and Umaa = 5.7). Cross-plotting these data yields a point that plots in the vicinity of the triangle apex labeled Quartz, implying that the predominant constituent of the formation is, in fact, quartz. This would appear to correspond with one of the possible combinations obtained from the Cross-Plot method illustrated earlier: 70% quartz and 30% dolomite (dolomitic sand). Using the same method as that with the neutron-density Cross-Plot chart, normalized scales may be constructed along lines connected the apices of the triangle. These apices represent 100% of a particular mineralogy (quartz, calcite, dolomite). The relative position of the plotted point with respect to these normalized scales yields a more detailed assessment of the mineralogy of the formation of interest. Mineralogy of Example Data Quartz = 72% Calcite = 21% Dolomite = 7% Compare these results with those determined for the quartz-dolomite possibility from the Cross-Plot chart (70% quartz and 30% dolomite). The results of the MIP method are strikingly comparable, and have been able to distinguish the difference between the two carbonate end-members (calcite and dolomite) present in the formation. By comparing these results with those of the Cross-Plot method discussed previously, it is now possible to state with greater confidence that the formation of interest is a dolomitic sandstone. (N.B. While proclaiming the conclusions, caution must be applied considering geological constraints, e.g. Carbonate and clastic deposition cannot take place at the same time and same place. Therefore proclaiming the formation of interest “dolomitic sandstone” as have been concluded above, doesn’t make sense to

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Basic Log Interpretation geologist, and so log analyst become the subject of ridicule All interpretation therefore must take into consideration geological inputs.)

ρmaa Versus ∆tmaa MIP Method The ρmaa versus ∆tmaa MIP method of lithology determination requires a Compensated Density (CDL, with no Pe curve), neutron, and sonic tool for implementation. The Mineral Identification Plot charts are labeled MIP XXX-7, according to the particular type of neutron tool being used. Notice that the X-axis and Y-axis coordinates of these charts also are not values that can be taken directly from logs. The "Apparent Matrix Density (ρmaa)" and "Apparent Matrix Transit Time (∆tma)" must be determined using separate Cross-Plot charts (MIP XXX-4 and MIP XXX-5, respectively). The same techniques are used to manipulate these charts as with the previous Umaa versus ρmaa MIP charts. The important point of using this additional sonic method is that different results may be obtained from different methods. The correct choice should be based on clients input.

Further MIP Considerations As was the case with the neutron-density Cross-Plot charts, gas and shale likewise affect the results of the Mineral Identification Plots. Apparent Matrix Density (ρmaa) and Apparent Matrix Volumetric Photoelectric Factor (Umaa) will both decrease in the presence of gas. Therefore, points plotted on the MIP charts will move up and slightly to the left in a gas bearing formation. Unlike the neutron-density Cross-Plot charts, there is no correction technique for gas effect. However, the presence of gas typically causes variance of the plotted data within the confines of the triangle. The presence of shale will shift the points in the plot anywhere within or outside the triangle, falling in between the triangle and the "Muscovite" point. With increasing percentage of shale, these points plot farther and farther away from the triangle. In shaly sandstone situations, it may be extremely helpful to plot several points on the MIP chart representing "typical shales" within the logged interval. A new triangle may then be drawn connecting the Quartz, Calcite, and "Shale" points. This new triangle may be segmented accordingly, and relative proportions of these three new end-member lithologies may be determined. A thorough evaluation of the zone of interest requires the plotting of multiple points. The measurement at any one particular depth may or may not be representative of the entire zone. Analyzing a thick formation using the MIP charts with data points every foot would be rather time consuming, and not practical for wellsite lithology determination. Therefore, picking tool responses at a particular depth and assuming those responses to be representative of the entire formation is acceptable. Computer-generated MIP plots are products offered by Halliburton Reservoir Decision Centers as total analysis packages such as ULTRA.

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References Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston, MA, 647 p. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishers, Tulsa, OK, 361 p. Halliburton Energy Services, 1994, Log Interpretation Charts. Pettijohn, F. J., 1975, Sedimentary Rocks: Harper & Row.

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Section 3

Environmental Corrections Table of Contents Introduction…………………………………………………………………………………………. 43 Objectives…………………………………………………………………………………………... 43 Importance of Environmental Corrections………………………………………………………. 44 SP Bed Thickness Correction (SP-1a, SP-1b)…………………………………………………. 45 Gamma Ray Borehole Corrections (GR-1)……………………………………………………... 46 Density Environmental Corrections (POR-1)…………………………………………………… 46 Neutron Environmental Corrections……………………………………………………………... 48 Resistivity Environmental Corrections…………………………………………………………... 52 Additional Notes on Environmental Corrections………………………………………………..

58

References…………………………………………………………………………………………. 58

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Introduction Very rarely do open hole logs directly provide answers to the questions posed. Log data must be subjected to a number of assumptions and rigorous calculations before they are useful. For instance, neutron porosity and resistivity alone provide no useful information about the productive capabilities of a reservoir. However, by using these data to calculate porosity and water saturation, some of the important questions are answered. Furthermore, before these data are used for basic calculations, the effects of environmental conditions on the measurements must be accounted for. This section stresses the importance of environmental corrections and demonstrates their use and application. To effectively use this section, the participant should have a copy of Halliburton Log Interpretation Charts manual. Examples illustrated in the section will make references to this Log Interpretation Charts manual.


recognize the need and importance of performing environmental corrections on open hole logs before their use in calculations.

§

perform bed thickness corrections on SP measurements.

§

perform borehole corrections on gamma ray measurements.

§

perform open hole environmental corrections on neutron porosity measurements, including mudcake thickness, borehole salinity, mud weight, borehole temperature, and borehole pressure corrections.

§

perform open hole environmental corrections on High Resolution Induction/DFL and Dual Laterolog/MSFL measurements, including MSFL mudcake correction, DFL borehole correction, induction and laterolog borehole correction, induction and laterolog bed thickness corrections, and invasion corrections.

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Importance of Environmental Corrections In actual logging conditions, porosity (Φ) and the "true" resistivity of the uninvaded zone (Rt) cannot be measured precisely for a variety of reasons. Factors affecting these responses may include hole size, mud weight, bed thickness, depth of invasion, and other properties of the logging environment and formation. Many of these effects have strong impacts on analysis and evaluation and must be corrected for prior to evaluating the formation. Several types of corrections and the tools for which these corrections are necessary are illustrated in Figure 3.1.

The corrections listed in Figure 3.1 reference charts for a particular tool type. It should be recognized that corrections may differ between tool types. For example, the charts used to make environmental corrections on High Resolution Induction measurements are not the same charts used to correct Dual Laterolog measurements. Depending on the tool type and other borehole or formation conditions, appropriate charts are selected to workout solution. The proper matching of tool type and environmental conditions to the appropriate correction chart is critical. Furthermore, although the charts provided by different service companies may appear similar, the amounts of their respective corrections may be quite different. The use of environmental correction charts will not always be necessary. In some situations, the effects of certain conditions will be so small that they do not warrant correction. As familiarity with the charts is gained, their usefulness and limitations will become apparent. For instance, applying environmental corrections for a DSN-II neutron in an 8-inch borehole drilled with 9 lb/gal fresh water drilling mud at a depth of 2000 feet would be an exercise in futility. In this case, correction to neutron porosity

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Basic Log Interpretation would be negligible. However, until a working knowledge of the charts and the applicability is gained, corrections should always be applied.

SP Bed Thickness Correction (SP-1a, SP-1b) In relatively thin beds (1 foot to 22 feet), the deflection of the SP curve is suppressed because of the influence of underlying and overlying formations. This is particularly true in sand/shale sequences where sandstones are overlain and underlain by shales. In cases such as this, the SP response in the thin formation of interest may not attain its full deflection because of the adjacent shales. The SP deflection of the formation of interest should actually be greater than is exhibited on the log. The intent of charts SP1a and SP-1b is to correct the SP response in these situations. The determination of which chart to use is made through an estimation of the diameter of invasion.

Example Data Observed SP deflection: Thickness of formation of interest (h): Invaded zone resistivity (Ri): Mud resistivity (Rm) at Tf : Borehole diameter:

- 70 mV 11 feet 90 Ω-m 1.5 Ω-m 7.875 inches

Estimating Diameter of Invasion Diameter of invasion (di) is one of the unknowns determined during invasion correction of resistivity responses; however, it can be estimated by the separation between Medium and Deep resistivity curves. The following rule of thumb applies: the greater the separation, the deeper the invasion. In formations where the Medium and Deep curves stack (e.g., shale), it is assumed that there is no invasion. The diameter of invasion (di) is estimated by taking a ratio of Medium to Deep resistivity. If this ratio is less than 1.1, then invasion is considered to be less than twice the borehole diameter (use SP-1a). If this ratio is greater than 1.1, then it is safe to assume that invasion is greater than twice the borehole diameter (use SP- 1b). In this example, it is assumed that the ratio of Medium to Deep resistivity was greater than 1.1, and therefore SP-1b (moderate to deep invasion) will be used to illustrate the process of SP correction. Realize that this is an estimate of the diameter of invasion, and that differences in borehole size and fluid type may change the results.

Performing SP Bed Thickness Correction (SP-1b) The first step of the correction procedure requires borehole size. This information is best obtained from the caliper measurement. Where no caliper is logged, then bit size from the header may be used as a rough estimate. In this example, borehole diameter is 7.875 inches; therefore, the 7-7/8 inch hole diameter X-axis scale can be used as a starting point.

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Using the 7-7/8 inch X-axis scale of SP-1b, move horizontally to a bed thickness of 11 feet. Bed thickness is best determined by choosing the break points (or deflections) of the tool having the smallest vertical resolution. In many cases, this is the shallowest reading resistivity device (e.g., DFL, MSFL). Each curve in the chart represents a ratio of invaded zone resistivity (Ri) to mud resistivity (Rm). Resistivity of the invaded zone is generally approximated by the measurement of the intermediate resistivity curve. In this example, Ri = 90 Ω-m and Rm = 1.5 Ω-m at formation temperature. It is vital that the value of mud resistivity (Rm) be corrected to the formation temperature of the depth at which the correction is being applied. The resulting ratio Ri/Rm is 60. From the 11 feet bed thickness mark on the X-axis, extend a line vertically to intersect an imaginary interpolated line representing the resistivity ratio of 60. From this intersection, extend a horizontal line to the Y-axis to determine the appropriate SP correction factor of approximately 1.52. The resulting SP correction factor is applied to the amount of SP deflection in the formation of interest with respect to the "shale baseline." Recognizing the baseline on a log can be rather tricky, and the entire log should be considered. In this example, the SP deflection within the zone of interest is given as -70 mV. To correct the SP deflection for the effects of thin beds, the SP correction factor is multiplied by the SP deflection exhibited in the formation of interest. SPcorrected = SP Deflection X Correction Factor SPcorrected = - 70 X 1.52 = - 106.4mV Notice that through this correction the amount of SP deflection has been increased from -70 mV to -106 mV. The corrected value of -106 mV more closely approximates what the actual SP deflection of the formation of interest would be if it were substantially thicker than 11 feet.

Gamma Ray Borehole Corrections (GR-1) The environmental correction charts provided in the Gamma Ray section of the chartbook correct for two separate effects: 1) the distance between the tool and the borehole wall; and, 2) the density of the mud filling the borehole. Both of these conditions affect the amount of natural radiation that is measured at the gamma ray detector. Tool diameter and tool position are both important factors to consider when using GR-1. In a hole of given diameter, the amount of gamma radiation received by a large diameter tool will be greater than that received by a smaller diameter tool because the amount of mud surrounding the larger tool is less. Standard DITS gamma tools have an

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Basic Log Interpretation outer diameter of 3-5/8 inches. Furthermore, if the tool is eccentered, then some gamma rays will be attenuated by the thicker shield of mud on one side of the tool (Figure 3.2). With a centered tool there is still attenuation of the received gamma rays, but it is much more regular in nature. These effects are accounted for through the use of separate tool position reference lines on chart GR-1.

Performing Gamma Ray Borehole Correction (GR-1) Before determining which section of GR-1 is applicable, tool type (i.e., diameter) and tool position should be confirmed from the header information. In this case, a gamma ray tool with an outer diameter of 4 inches was pulled, therefore the upper left section of GR-1 applies. Furthermore, the tool was centralized, so the solid black lines representing mud weight will be used. To correct the gamma ray response, enter the 4 inch diameter section of GR-1 on the X-axis with a borehole diameter of 10 inches. Extend a vertical line upward to intersect an imaginary interpolated line representing a mud weight of 12 lb/gal (from header) for a centered tool (solid black lines). Draw a horizontal line to the Y-axis to obtain a correction factor for the gamma ray response. This correction factor (approximately 1.5; note logarithmic scale) is then multiplied by the observed log response to correct for the effects of borehole size and mud weight. GRcorrected = GR X Correction Factor GRcorrected = 90 X 1.5 = 135API Notice that after correction the gamma ray measurement increased. This is to compensate for the attenuating effects of the heavy mud in the borehole. In smaller hole sizes, it is possible for the resulting correction factor to be negative; however,

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Basic Log Interpretation negative gamma ray corrections are seldom applied. It is unlikely that the presence of mud will cause an observed gamma ray response to read too high. An identical gamma ray correction can be applied with the logging software (result mnemonic, GRCO). Realize that this real-time correction is rarely requested, and then usually only in cases where gamma ray will be used as an estimate of the volume of shale (V sh). For quantitative estimates of Vsh, gamma ray borehole corrections are required.

Density Environmental Corrections (POR-1) The inclusion of the SDL Borehole Curvature Correction chart (POR-1) in the chartbook is often confusing to engineers and customers alike. The pad section of the SDL is 3.25 inches in diameter and is not designed to fit flush against any particular diameter borehole. The SDL is calibrated to read the correct bulk density (ρb) in an 8-inch borehole filled with fresh water. The zero correction point, therefore, is an 8-inch borehole filled with fresh water. As borehole size and fluid density vary, environmental corrections (POR-1) become more critical as the amount of drilling fluid between the pad and formation varies. Borehole curvature corrections do not need to be applied to SDL responses under normal circumstances. These corrections are performed real-time by the logging software, and correct values already appear on the logs. Notice that input into POR-1 is not in units of density porosity, but rather bulk density (ρb). This is the case with many correction charts. In order to use these charts, bulk density may either be taken from the log (if presented) or by calculating ρb from density porosity (Φ D). The following equation may be used to derive bulk density from density porosity, provided that fluid density (ρfl) and matrix density (ρma) are known.

Neutron Environmental Corrections Some of the most important and most complex environmental corrections include those required for neutron porosity measurements. Neutron porosity is affected by a number of factors, most importantly temperature. If these effects are left uncorrected, then neutron porosity will be in error and the Archie equation will not yield accurate results. Also, with neutron corrections, it is vital that the appropriate chart be used for the particular type of tool run. The neutron tools most commonly seen on modern Halliburton logs are Dual Spaced Neutron (DSN-II) tools. Older logs may have been run with the Compensated Neutron (CNT-K). The open hole environmental correction chart for the DSN-II is POR-4a, while the CNT-K is corrected with chart POR-6a. Following both of these main charts is a collection of other charts used to correct for a variety of borehole and formation conditions. It is important to note that when correcting porosity values from a CNT-K,

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Basic Log Interpretation the borehole temperature correction should not be performed because it has already been applied by the logging software.

Performing Open Hole Borehole Diameter Correction (POR-4a) In most situations a caliper tool is pulled in combination with the neutron tool. Under these circumstances, the borehole diameter correction (or caliper correction), is applied real-time by the logging software and it is not necessary to use this section of POR-4a. In this example, the caliper correction was not applied real-time. If the caliper correction was not applied during logging for some reason (as is the case in this example), then this section of the chart is used by entering the top X-axis with the measured value of neutron limestone porosity (32%) and extending a vertical line downward to intersect a horizontal line representing borehole size (10.5 inches). From this intersection, another line is plotted downward—following a curvature relative to that of the nearest curved spine--to the red baseline. From the baseline, another vertical line is extended downward to the bottom X-axis to read the caliper-corrected value of neutron porosity. In this example, the caliper corrected value is 29%. The resulting value of caliper-corrected neutron limestone porosity (29%) is then carried to the next correction step. Again, this correction is not required if a working caliper was used to correct the neutron porosity measurement real-time.

Performing Mudcake Thickness Correction (POR-4a) The mudcake thickness correction requires input of caliper-corrected neutron limestone porosity (29%). Starting on the upper X-axis with a caliper-corrected neutron porosity of 29%, extend a vertical line downward to intersect a horizontal line representing mudcake thickness (0.5 inches). From this intersection, another line is plotted downward--following a curvature relative to that of the nearest curved spine--to the red baseline. The difference between the original value (29%) and the resulting value (28.5%) indicates the magnitude and direction of mudcake thickness correction required (-0.5%). It is important to note that in most cases, mudcake thickness correction will result in a change of no more than 2% porosity. Mudcake thickness can be estimated by the following equation:

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Performing Borehole Salinity Correction (POR-4a) Borehole salinity may be determined from the value of the drilling mud resistivity (Rm) and use of chart GEN-5. In this example, salinity is given as 100,000 ppm NaCl. To use this section of POR-4a, enter the top X-axis of the borehole salinity correction section with the value of caliper-corrected neutron porosity (29%). It is important to note that correction factors from each step of the process are not carried into the next correction section. Beginning with a value of 29% on the top X-axis, extend a vertical line downward to intersect a horizontal line representing 100,000 ppm salinity. From this intersection, another line is plotted downward-- following a curvature relative to that of the nearest curved spine--to the red baseline to read the amount of correction necessary. In this example, the amount of correction is approximately +0.8%.

Performing Mud Weight Correction (POR-4a) The mud weight correction section of POR-4a has two scales: one for bariteloaded mud, and the other for non-barite, or "natural," drilling mud. Header information would dictate which of these two scales to use. The correction proceeds just as the borehole salinity correction. Enter the top X-axis of the mud weight correction section with the value of calipercorrected neutron porosity (29%). Extend a vertical line downward to intersect a horizontal line representing mud weight (10 lb/gal, natural). From this intersection, another line is plotted downward--following a curvature relative to that of the nearest curved spine--to the red baseline. From the baseline, another vertical line is extended downward to the bottom X-axis to read the amount of correction necessary. In this example, the amount of correction is approximately +0.6%.

Performing Borehole Temperature Correction (POR-4a) The borehole temperature correction is the most significant correction applied to the neutron porosity measurement. Notice that the amount of correction increases dramatically (particularly at high borehole temperatures) for higher values of neutron porosity. In cases where other neutron corrections (e.g., mudcake thickness, salinity, mud weight, etc.) are considered negligible, the temperature correction should always be applied so that water saturation calculations are not adversely effected. Enter the top X-axis of the temperature correction section with the value of calipercorrected neutron porosity (29%). Extend a vertical line downward to intersect a horizontal line representing borehole temperature (125oF). From this intersection, another line is plotted downward--following a curvature relative to that of the nearest curved spine--to the red baseline. From the baseline, another vertical line is extended downward to the bottom X-axis to read the amount of correction necessary. In this example, the amount of correction is approximately +1.5%.

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Performing Borehole Pressure Correction (POR-4a) Borehole pressure corrections are generally negligible for porosities of less than 10%, but the slopes of the correction spines suggest that the amount of correction increases with increased porosity. Borehole pressure at a given depth can be derived from the following equation:

Enter the top X-axis of the pressure correction section with the value of calipercorrected neutron porosity (29%). Extend a vertical line downward to intersect a horizontal line representing borehole pressure (2500 psi). From this intersection, another line is plotted downward--following a curvature relative to that of the nearest curved spine--to the red baseline to read the amount of correction necessary. In this example, the amount of correction is approximately -0.3%.

Summation of Open Hole Environmental Corrections Once each of the individual influences has been corrected for, the resulting correction factors must be summed in order to obtain the total effect. This is accomplished by adding the sum of the individual correction factors to the caliper-corrected value of neutron limestone porosity.

Σ CF = CF + CF ?+ CF + CF + CF Σ CF = (-0.5%) + (0.8%) + (0.6%) +(1.5%) + (-??0.3%?)= 2.1% mudcake

salinity

mud weight

temperature

pressure

If the caliper-correction was applied by chart (as in this example), then the environmentally corrected value of neutron porosity in limestone units is obtained by the following equation: Φ nls-corrected = Φ caliper – corrected + ∑CF Φ nls-corrected = 29% + 2.1% + 31.1% If the caliper-correction was applied real-time, then the environmentally corrected value of neutron porosity in limestone units is obtained simply by adding the sum of the correction factors to the observed log response (if in limestone units). Φ nls-corrected = Φ nls from log + ∑CF It is important to note that neutron porosity must be in limestone units for this correction. The chart POR-12 can be used to convert between the different lithologies assumed in the calculation of neutron porosity.

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Performing Standoff Correction (POR-4b) Neutron "standoff" occurs when the face of the tool is physically held some distance from the borehole wall. This may be the result of other tools in the toolstring, or misaligned tools. This type of situation will cause the neutron tool to measure the drilling fluid between the tool and the formation, thus producing a neutron porosity that is consistently high. Such standoff is usually avoided during logging by using a bowspring decentralizer. However, if a situation arises where the tool cannot be properly decentralized, standoff correction can be applied realtime by the logging software. If necessary, the correction procedure takes the open hole environmentally correct value of neutron limestone porosity from POR- 4a and proceeds in the same manner, but using POR-4b for the DSN-II tool.

Performing Formation Salinity Correction (POR-4b) The environmentally corrected and standoff-corrected value of neutron limestone porosity can now be corrected for salinity of the formation in which the measurement was made. Formation salinity may be obtained by considering the formation water resistivity (Rw ) of the zone of interest, and using this value in that section of POR-4b which coincides with the primary lithology of the zone of interest. The resulting salinity correction is added to the environmentally corrected and standoff-corrected value of neutron limestone porosity. Because this formation salinity correction is based upon formation water resistivity (which is often not a measured value), salinity corrections must be made with caution. Most analysts tend to forego this correction when Rw is not measured, is uncertain, or has been derived from logs by either the inverse-Archie method or SP method.

Resistivity Environmental Corrections Resistivity tool responses generally must be corrected for a variety of conditions; namely, borehole effects, thin beds, and invasion. Microresistivity measurements must be corrected for the presence of mudcake. Just as neutron corrections were particular to tool type, resistivity corrections also are particular to tool type. The chartbook contains correction sections for each of the following resistivity combinations. 1.

Microresistivity (MSFL and Microguard)

2.

Dual Induction/Short Guard (Welex)

3.

Dual Induction/Laterolog 3 (Gearhart)

4.

High Resolution Induction/DFL

5.

Hostile Dual Induction

6.

Dual Laterolog A (Welex)

7.

Dual Laterolog F (Gearhart)

Furthermore, resistivity corrections must be performed in a particular order because one corrected value is used to make the next required correction. Each resistivity

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Basic Log Interpretation section of the chartbook is arranged in such a way that the charts appear in sequence. For any resistivity tool, environmental corrections should be undertaken in the following order: 1.

Borehole correction of the shallow device on induction tool, or mudcake correction for pad-mounted electrode tool (MSFL).

2.

Borehole correction for deep and medium devices.

3.

Bed thickness correction for deep and medium devices.

4.

Invasion correction.

The ultimate goal in performing environmental corrections is to achieve values for resistivity of the uninvaded zone (Rt), resistivity of the flushed zone (Rxo), and diameter of invasion (di). These three unknowns are determined in the final step of the process (i.e., invasion correction). Invasion corrections assume conditions of infinitely thick homogeneous beds and an 8-inch borehole; therefore, both borehole and bed thickness corrections must be applied to input measurements before this final step is attempted.

Performing Mudcake Correction for the MSFL (R xo-1) The resistivity measurement of the MSFL is often considered to be an accurate measure of flushed zone resistivity (Rxo). However, any measure of flushed zone resistivity by a pad-mounted device will be influenced by the presence of mudcake. Mudcake correction charts are provided in the Microresistivity section of the chartbook. Example Data Observed MSFL response (RMSFL): Mudcake resistivity (Rmc ) at Tf : Mudcake thickness (hmc ):

14.0 Ω-m 1.0 Ω-m 0.175 inches

Using the Rxo-1 chart, enter the X-axis with a value of the RMSFL/Rmc ratio (14 in this example). It is important to note that Rmc must be corrected for formation temperature at the depth at which the correction is being applied. Extend a vertical line upward to intersect a horizontal line representing mudcake thickness (0.175 inches). From this intersection, extend a horizontal line to the Y-axis to read a value of the correction factor (RMSFLcorr/RMSFL = 0.88). This correction factor is then multiplied by the observed MSFL response to obtain a mudcake-corrected value of MSFL resistivity.

It is important to note that the corrected value (12.32 Ω-m) does not represent flushed zone resistivity (R xo). This value merely represents MSFL resistivity that has been corrected for mudcake. The value of mudcake-corrected MSFL resistivity should be retained for later use in the invasion correction.

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Performing Borehole Corrections for the DFL (HRI-1) The DFL borehole correction (HRI-1) compensates the DFL response for the effects of hole size and mud resistivity (Rm). The chart is divided into three sections, each depending upon tool position. Tool position can be determined from resistivity equipment data in the header. Example Data Tool position: Observed DFL response (RDFL): Mud resistivity (Rm) at Tf : Borehole diameter:

slick (no standoff) 31.0 Ω-m 0.91 Ω-m 11.0 inches

Using the 0.0-inch standoff section of HRI-1, enter the X-axis with a value of the RDFL/Rm ratio (34.07 in this example). It is important to note that Rm must be corrected for formation temperature at the depth at which the correction is being applied. Extend a vertical line upward to intersect a horizontal line representing borehole diameter (11 inches). Borehole diameter should be taken from a caliper measurement; however, it may be estimated using bit size if no caliper is available. From this intersection, extend a horizontal line to the Y-axis to read a value of the correction factor (RDFLcorr/RDFL = 1.11). This correction factor is then multiplied by the observed DFL response to obtain a borehole-corrected value of DFL resistivity.

Notice that the correction was slightly positive. This is to account for the fact that the mud contributed excess conductivity to the observed response. This excess conductivity has been removed through the correction, and therefore the boreholecorrected value of resistivity is slightly higher. Again, it is important to note that the corrected value (34.41 Ω-m) does not represent flushed zone resistivity (R xo). This value merely represents DFL resistivity that has been corrected for borehole effects. The value of borehole-corrected DFL resistivity should be retained for later use in the invasion correction.

Performing HRI Deep and Medium Borehole Corrections (HRI-2) Deep and Medium resistivity measurements must also be corrected for the effects of borehole diameter and mud resistivity (Rm). For the HRI, this is accomplished through the use of HRI-2. Again, it is important to remember that the value used for mud resistivity (Rmc ) must be corrected for formation temperature. Example Data Tool position: Observed Deep resistivity (RHRD):

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1.5" standoff (preferred) 13.0 Ω-m 54


Basic Log Interpretation 0.25 Ω-m 14.0 inches

Mud resistivity (Rm) at Tf : Borehole diameter:

To correct the Deep resistivity measurement (RHRD), enter the X-axis of the chart at the appropriate value of borehole diameter (14.0 inches) and extend a vertical reference line upward to intersect the Deep 1.5" standoff correction line (note tool position labels on lines). From this intersection, a horizontal line is plotted to the right edge of the gridded graph area. From this point at the right edge of the graph, a line is projected through the appropriate value of Rm at formation temperature (0.25 Ω-m). The value at which this line crosses the right-side Yaxis reflects the contribution of the borehole, in terms of conductivity, to the Deep measurement (approximately 0.75 mmhos/m). Because the signal contributed by the borehole is represented in units of mmho/m, it is necessary to convert the measured value of Deep resistivity (RHRD = 13.0 Ω-m) to units of conductivity before the correction is applied. This is accomplished through the following reciprocal equation.

Once the observed Deep resistivity is converted to units of conductivity, the correction amount read from the right Y-axis of the graph (0.75 mmhos/m) must be subtracted from the conductivity measurement. This effectively removes that portion of the conductivity signal that is contributed by the borehole. Corrected CHRD = 76.92 - 0.75 = 76.17 mmhos/m The resulting corrected conductivity value (76.17 mmhos/m) must then be converted back into units of resistivity for use in the next step of the correction procedure. This conversion is accomplished by simply rearranging the conductivity equation above, and solving for the borehole-corrected value of Deep resistivity. Corrected RHRD = 13.13 Ω-m In this particular example, there was a minor positive correction applied to the Deep resistivity measurement which is consistent with the borehole contribution being removed from the total signal (i.e., removal of excess conductivity = addition of more resistivity). Correction of the Medium resistivity measurement is analogous to the procedure described for the Deep measurement. In the case of smaller borehole sizes and/or higher values of Rm, it is possible for the borehole contribution in mmhos/m to have a negative sign. In these cases, realize that the borehole contribution is being added to the measured conductivity value (C meas - (-bh) = C meas + bh). Values of borehole-corrected Deep and Medium resistivity should be retained for later use in the following bed thickness correction.

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Performing HRI Deep and Medium Bed Thickness Correction (HRI-3a, HRI-3b) The borehole-correct Deep and Medium resistivity measurements must now be corrected for the effects of the resistivities of overlying and underlying formations, or shoulder beds. This type of correction is also referred to as a thin bed correction or bed thickness correction, and is accomplished through the use of HRI-3a or HRI-3b. Example Data 13.0 Ω-m 1.2 Ω-m 13 feet

Borehole-corrected Deep resistivity: Shoulder bed resistivity (Rs ): Bed thickness (h):

Resistivity of the shoulder bed (Rs ) determines which of the two charts applies. In this example, shoulder bed resistivity (Rs = 1.2 Ω-m) suggests that chart HRI- 3a is the most applicable. Corrections for both the Deep and Medium resistivity measurements are made on the same chart. The two chart sections on the lefthand side of HRI-3a are for shoulder bed resistivities of 1 Ω-m and 2 Ω-m. The upper-left section is for the Deep correction, while the lower-left section is for the Medium correction. To correct the Deep measurement for thin bed effects, enter the upper-left section on the X-axis with a bed thickness of 13 feet. Bed thickness is best determined from the points of deflection on the curve with the smallest vertical resolution (e.g., DFL). A vertical line is projected upward to intersect a line representing borehole-corrected Deep resistivity (13.0 Ω-m). From this intersection, a horizontal line is projected to the left-side Y-axis to read the bed thicknesscorrected value of Deep resistivity (approximately 11.5 Ω-m). Correction of the Medium resistivity measurement is analogous to the procedure described for the Deep measurement, but uses the lowerleft section of HRI-3a. Values of bed thickness-corrected Deep and Medium resistivity should be retained for use in invasion correction.

Performing HRI Invasion Correction (HRI-4a, HRI-4b) Invasion corrections are the final step in High Resolution Induction/DFL environmental corrections, and produce values of flushed zone resistivity (Rxo), uninvaded zone resistivity (Rt), and diameter of invasion (di). To this point, it has been assumed that resistivity of the flushed zone is reflected by the shallowest resistivity measurement, and resistivity of the uninvaded zone is reflected by the deepest resistivity measurement. The depth to which mud filtrate invades the formation determines the validity of these assumptions. The charts used for invasion correction on induction measurements are known as "butterfly charts," while those used for invasion correction on laterolog measurements are referred to as "tornado charts." High Resolution Induction invasion corrections are accomplished through the use of charts HRI-4a and HRI- 4b.

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Basic Log Interpretation The use of a particular invasion correction chart is determined by the relationship between resistivity of the drilling mud (Rm) at formation temperature and the resistivity of the flushed zone (Rxo). Because a value of Rxo is a result of this invasion correction process, it is necessary to use the previously boreholecorrected value of shallow resistivity to approximate Rxo, and thereby determine which chart is applicable. Example Data Corrected Deep resistivity (RHRD): 15.0 Ω-m Corrected Medium resistivity (RHRM): 22.0 Ω-m Corrected DFL resistivity (RDFL): 105.0 Ω-m DFL value is borehole-corrected Deep and Medium values are borehole- and bed thickness-corrected For this example it is assumed that the ratio Rxo/Rm is approximately 100; therefore, HRI-4b is applicable. The first step in the invasion correction process is to determine the Rt/RHRD ratio. Enter the X-axis of the chart with a value for the ratio RHRM/RHRD (1.467 in this example) and plot a vertical line upward to intersect a horizontal line that represents the ratio RDFL/RHRD (7.0). Using the plotted point, estimate the ratio Rt/RHRD using the point's relative position to the solid red lines. In this case, the estimated Rt/RHRD ratio is approximately 0.93. This ratio is multiplied by the borehole-corrected and bed thickness-corrected value of Deep resistivity (RHRD = 15.0 Ω-m) to determine a value for "true" resistivity of the uninvaded zone (Rt).

The second step of the invasion correction process is to determine the Rxo/Rt ratio. Again, using the plotted point, estimate this ratio using the point's relative position to the solid black lines. In this case, the estimated Rxo/Rt ratio is approximately 9.9. This ratio is then multiplied by the previously determined value of uninvaded zone resistivity (Rt = 13.95 Ω-m) to determine a value for flushed zone resistivity (Rxo).

The third step of the invasion correction process is to determine the diameter of invasion (di). Using the plotted point, estimate the diameter of invasion from the point's relative position to the dashed black lines. In this example, the diameter of invasion is approximately 63 inches. Following completion of the invasion correction, environmentally corrected values of uninvaded zone resistivity (Rt) and flushed zone resistivity (Rxo) can be entered into the Archie equation for more accurate values of water saturation (S w ). The diameter of invasion (di) determined from this correction can be used to explain the effects of mud filtrate on other logging measurements (e.g., porosity, etc.).

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In the example demonstrated, the data point plotted fall within the "butterfly," but this will not always be the case. Sometimes, points will fall outside of the "butterfly." This may be the result of a poor fit between the measured Rxo/Rm value and the Rxo/Rm value used to generate the chart. Even though a point may fall outside of the "tornado," it can still be used to determine Rxo and Rt. For points that fall to the left of the Rt/RHRD = 1.0 line, it is valid to assumed that Rt = RHRD (i.e., shallow invasion). If the point falls to the right of the "tornado," it can be referenced back to the nearest Rt/RHRD line, although determined values of Rxo and d i will be less accurate. CAUTION! Do not assume the value of R xo in Butterfly / tornado chart The initial R xo value is simply a borehole corrected shallow resistivity measurement, and not R xo. The R xo/R t correction lines are used to determine R xo from R t.value. Resistivity environmental corrections for Dual Laterolog measurements are analogous to those described for the High Resolution Induction corrections, but use other sections of the chartbook specific to the type of Dual Laterolog tool that was run.

Additional Notes on Environmental Corrections By now it should be apparent that there is an incredible amount of interpretation and assumption required for the use of these correction charts. Very seldom will two people produce the same results from the same correction charts. In many instances, the corrections are so small that they have no effect on the original measurement. Most importantly, any error in using these charts begins with how values are read from the logs. Any error may then be compounded through the use of the charts, and may even be influenced by the thickness of a pencil lead! When using these charts, also bear in mind that they were constructed for a given set of environmental conditions. Those conditions are often listed somewhere on the chart. More robust environmental corrections for conditions other than those that were used to construct the printed charts can be performed in Reservoir Decision Centers. Fortunately, "quick-look" log analysis problems at the well-site often do not call for the use of environmental correction charts. However, a working knowledge of these charts is important from the standpoint that they provide a graphical means of explaining how environmental conditions affect logging measurements.

References Halliburton Energy Services, 1994, Log Interpretation Charts.

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Section 4

Clean Formation Evaluation

Table of Contents Introduction…………………………………………………………………………………………. 60 Objectives…………………………………………………………………………………………... 60 Clean Formation Evaluation…………………………………………………………………….... 60 Typical Approach…………………………………………………………………….……………. 60 Selecting the Appropriate Logs…………………………………………………………………... 61 Exploratory Wells…………………………………………………………………….……………. 61 Development Wells…………………………………………………………………….………….. 62 Infill Wells…………………………………………………………………….…………………….. 63 Log Quality Assessment………………………………………………………………………….. 63 Potential Water-Bearing Zones and Calculations……………………………………………… 65 Potential Hydrocarbon-Bearing Zones and Calculations………………………………………

65

Decisions on Productive Capability……………………………………………………………… 66 References…………………………………………………………………………………………. 67

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Introduction The idea of compiling all of the information necessary for a complete analysis may seem a bit overwhelming at first glance. This is especially true when one realizes that calculations are typically performed at intervals of one to one-half foot throughout the zone or zones of interest. This complex task can result in literally hundreds of data points, all needing environmental corrections, invasion corrections, cross-plot determinations, and lithology identification. If evaluated one depth at a time, then this process could result in maddening hours of tedious calculations or shoddy interpretations based on misread data points and flailing approximations. The purpose of this section is to provide the participant with a basic outline of the steps and procedures of clean formation evaluation, and the order in which these steps should be accomplished.


recognize the importance of an orderly analysis.

§

formulate a reasonable and efficient approach to evaluating a clean formation.

§

recognize the importance of having array of data when making a decision to set pipe and perforate versus abandon a well.

Clean Formation Evaluation A complete evaluation of a clean (i.e., shale-free) formation involvs many different and complex calculations and adopt right techniques suitable to the conditions. Additionally, there are a variety of assumptions that must be made during this analysis. The number of steps involved and the order in which the steps should be performed makes it difficult to remember at times. This section provides guidelines in a frame of an orderly sequence, which an analysts should accomplish when analyzing a clean formation.

Typical Approach 1.

Select the appropriate logs.

2.

Perform detailed log quality assessment.

3.

Locate potential water-bearing zones and determine their lithology.

4.

Select depth(s) at which formation water resistivity (Rw ) is to be determined, and perform environmental corrections on these data.

5.

Determine formation water resistivity (Rw ) by available means.

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Basic Log Interpretation 6.

Locate potential hydrocarbon-bearing zones and determine their lithology.

7.

Select depth(s) at which water saturation (S w ) is to be calculated, and perform environmental corrections on these data.

8.

Correct formation water resistivity (Rw ) to formation temperature of zone(s) of interest.

9.

Calculate water saturation (Sw ) of the potential hydrocarbon-bearing zone(s).

10. Make a decision on the productive capability of the potential hydrocarbon bearing zone(s) based on all of the available information. When making a decision on the productive capability of a potential hydrocarbon bearing zone, all of the available information should be considered. Values of water saturation (S w ) should not be the sole determining factor. Remember that water saturation is not a reflection of the ratio of water to hydrocarbons that will be produced from the reservoirs. It is simply the relative proportion of water to hydrocarbons that exists in the pore space of that reservoir. There are no safe guidelines for determining what constitutes "good" and "bad" values for water saturation. Consider the log responses and any other information that might be available to conclude about production ability of the formation.

Selecting the Appropriate Logs The choice of logging combinations will depend upon a variety of factors, including: mud system, formation type, previous knowledge of the reservoir, hole size and deviation, rig time and cost, equipment availability, and the type of information desired. The types of log run also strongly depend upon the well type. Exploratory wells typically require a comprehensive logging program, whereas infill and development wells may only require basic services. Additional logs may be required in cases where geologists, reservoir engineers, completion engineers, and geophysicists desire additional information for further exploration, evaluation, completion of the well and input to other facilities. The use of computers in formation evaluation and the availability of logging data in a variety of formats (i.e., LIS, LAS, ACSII) has vastly increased the utilization of data recorded with comprehensive logging programs. Exploratory Wells In exploratory (or "wildcat") wells, very little information, is known about the reservoir. These situations typically demand a comprehensive logging program to gain information about subsurface e.g. reservoir porosity, and fluid saturations. In many cases a sonic log may be necessary for correlation to seismic sections. Formation tester and sidewall cores may also be necessary to gain better insight into the formation. All of this information is used to streamline further exploration plan and order for drilling, completion and production facilities down the line.

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Basic Log Interpretation Typical Logging Suites for Medium-to-Soft Rock, Fresh Mud Exploratory Wells §

High Resolution Array Induction/Short Guard

Induction,

High

§

Spectral Density/Dual Ray/Microlog

Spaced

Neutron/Compensated

§

Full Wave Sonic

§

Magnetic Resonance Imaging

§

Six Electrode Dipmeter, Electrical Micro Imaging, or Circumferential Acoustic Scanning Tool-Visualization

§

Formation Tester

§

Sidewall Coring

Resolution

Induction/DFL, Spectral

or

Dual

Gamma

Typical Logging Suites for Hard Rock or Salt Mud Exploratory Wells §

Dual Laterolog/Micro-Spherically Focused Log (or equivalent induction survey if mud salinity marginal)

§

Spectral Density/Dual Spaced Neutron/Compensated Spectral Gamma Ray

§

Full Wave Sonic

§

Magnetic Resonance Imaging (for optimal borehole conditions)

§

Six Electrode Dipmeter, Electrical Micro Imaging, or Circumferential Acoustic Scanning Tool-Visualization

§

Formation Tester

§

Sidewall Coring

Development Wells Development wells are those that immediately follow exploratory wells; their purpose being to "develop" a field that has recently been discovered, and to identify the limits of the field. Most wells drilled can be classified as development. Although acquisition of data pertaining to the characteristics of the formation is still a priority, logging suites for development wells typically are more limited than those for exploratory wells. The information that is gained may be "correlated" back to the data acquired on the associated exploratory wells for a better picture of the overall field. Typical Logging Suites for Medium-to-Soft Rock Fresh Mud Development Wells §


§

Spectral Density/Dual Spaced Neutron

§

Magnetic Resonance Imaging (with increasing development of a discovered field, MRIL may become the log of choice for gaining information about porosity and fluid types within a reservoir)

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Induction,

High

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Resolution

Induction/DFL,

or

Dual


Basic Log Interpretation §

Sonic Porosity, Formation Tester, Six Electrode Dipmeter, and Sidewall Coring as required

Typical Logging Suite for Hard Rock or Salt Mud Development Wells §

Dual Laterolog/Micro-Spherically Focused Log

§

Spectral Density/Dual Spaced Neutron/Compensated Spectral Gamma Ray

§


§

Sonic Porosity, Formation Tester, Six Electrode Dipmeter, and Sidewall Coring as required

Infill Wells In situations where a reservoir has been very well defined, perhaps by the drilling of numerous wells, the typical logging suite becomes even smaller. Infill wells, or those drilled to "fill in" the areas between previously drilled development wells, are typically logged with only very basic services. Magnetic Resonance Imaging has a tremendous application here because of its ability to gain insight on fluid types, porosity and permeability with a single tool; something that required multiple tools and possibly multiple runs in the past. It should be realized that the limited amounts of data typically gathered during logging of infill wells is generally insufficient for any type of postprocessing analysis applications. Typical Logging Suite for Medium-to-Soft Rock Fresh Mud Infill Wells §


§

Magnetic Resonance Imaging

Induction,

High

Resolution

Induction/DFL,

or

Dual

Typical Logging Suite for Hard Rock Salt Mud Infill Wells §

Dual Laterolog/Micro-Spherically Focused Log

§


§

Sonic Porosity

As is the case with any logging program, the types of logs run must be tailored to the conditions that exist and the types of information sought. The decision about which logs to run is typically made well before the field engineer becomes involved; however, situations may arise during a job in which additional services should be offered to the customer for their consideration.

Log Quality Assessment Quality of the recorded data should be of the utmost concern to both the field engineer and the customer. Very expensive decisions about the future of a well are based on log data, and accurate data are vital to the decision making process and future success/failure of a well. The first step in any analysis problem should be to scan the HLS Asia Limited

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Basic Log Interpretation logs, searching for any anomalous or otherwise strange looking log responses. All service companies and many customers have very detailed log quality assurance programs in place. There are four main areas of concern that should be addressed with any log quality assurance program. Depth Control Depth control is only one of the many vital components of quality data. However, it also is one of the most difficult to assess. In exploratory situations, some assurance can be maintained from comparisons of log depth to driller's depth and casing depth, and to general knowledge of the region's geology. Keep in mind, however, that these are by no means accurate references. In development and infill situations there is typically sufficient well control to assess the correctness of depth data for a particular well. Every effort should be made to insure that proper depth control is practiced on every well. Overall Technical Quality Many conditions beyond human control may adversely affect the quality of logging data. The most obvious of these is equipment malfunction. Preventative maintenance programs are the best way to minimize equipment malfunctions and the possibility of poor quality logs. Other possible causes of poor data may include: rugose boreholes, sticking tools, tool rotation, excessive logging speed, deviated wells, poor centralization or eccentralization, and engineer error. Each of these possibilities should be kept in mind when assessing the quality of log data. In some instances, it may be necessary to make another run, perhaps with a different tool string. Repeatability Many of the previously mentioned factors affecting quality of a log might also apply to repeatability. In addition, a repeat may be affected by time-based phenomena such as changing degree of invasion. Comparing repeated log sections is an important step in assessing the quality of log data; however, it should not be the only method of quality control. Absolute Log Values ("Markers") Comparison of log readings with known absolute values is seldom possible; however, this positive check should be performed where it is possible. Known formations consisting of pure, non-porous lithologies such as halite, anhydrite, or limestone can be used to verify the accuracy of log readings. Casing may also be used to check the accuracy of caliper and sonic measurements. Furthermore, logs of offset wells may provide a ballpark figure of expected values, but these values can vary dramatically between wells. Log quality control is the responsibility of the service company performing the logging job. However, log acceptance should always be determined from the point of view of the customer. Will he or she be able to obtain accurate and reliable information from the log? If an affirmative answer to this question is ever in doubt, then making another run with a different toolstring or pursuing some other alternative should be considered.

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Potential Water-Bearing Zones and Calculations Locating a potential water-bearing zone should be approached by qualitatively assessing intervals in terms of their porosity and resistivity, and considering any permeability indicators presented with the logs. This "visual sifting" of data is usually accomplished by first considering porosity. If a zone is porous, then there are fluids present within that zone. Next, resistivity of the zone must be considered. Because hydrocarbons are electrical insulators, porous zones containing them will have relatively high resistivities. Porous water-bearing zones, on the other hand, will have relatively low resistivities. This process is also aided by recognition of the various resistivity invasion profiles associated with different types of resistivity logs. Do not hesitate to mark logs or highlight intervals to make them more noticeable. A practical method of doing this is to use a yellow highlighter pen to color from the middle of Track 1 left to the Gamma Ray curve. This provides a good visual image of potentially porous formations; those possibly containing water or hydrocarbons. Where a Spontaneous Potential curve is present, the process of locating potentially permeable formations (again, regardless of fluid types contained) is much faster. Those impermeable zones that lack any SP deflection will be of less interest than those with deflection. Keep in mind, however, that the SP response is only a qualitative indicator of formation permeability. Once a potential water-bearing zone is located, several necessary calculations are in order. The formation temperature (Tf ) of the interval should be determined. Furthermore, resistivity measures such as Rm and Rmf should be corrected to formation temperature for the purpose of determining formation water resistivity (Rw ). Before determining formation water resistivity (Rw ), the lithology of the formation of interest should be determined. This may be done by quick-look, or by use of one of the lithology charts. Determination of lithology will assist the analyst in determining the appropriate values of tortuosity factor (a) and cementation exponent (m) for inverseArchie Rw calculations. In a quick-look analysis, environmental corrections are typically not performed on any log measurement. However, to be more precise in an analysis, the various influences of borehole and invasion should be corrected before using any log measurement to determine formation water resistivity (Rw ). Every reasonable effort should be made to obtain an accurate and valid value of formation water resistivity (Rw ) from the logs. If the required data is available, then both the SP method and inverse-Archie method of determining Rw should be pursued. Keep in mind that determining Rw from log data does not always yield accurate results. When analyzing any log, the potential for error created by using an impractical value of Rw should always be considered. Always use the lowest value of determined Rw , within reason, for obtaining more optimistic values of water saturation (S w ).

Potential Hydrocarbon-Bearing Zones and Calculations Locating a potential hydrocarbon-bearing zone should also be approached by qualitatively assessing the porosity and resistivity of zones, and considering HLS Asia Limited

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Basic Log Interpretation permeability indicators. Again, if a zone is porous, then there are fluids present within that zone. Porous zones containing hydrocarbons will have relatively high resistivities because of the poor electrical conductivity of those hydrocarbons. As was the case with water-bearing zones, permeability indicators should also be considered to determine the priority with which a certain zone will be evaluated. The most important thing to consider is that the value for formation water resistivity (Rw ) determined in a water-bearing zone must be corrected to the formation temperature (T f) of the zone in which it is to be used to calculate water saturation (S w). Failing to correct Rw for temperature at greater depths will result in water saturation values being too pessimistic (too high). It is therefore possible, and in many cases a potential hydrocarbon-bearing zone may be overlooked as being wet if Rw is not corrected to formation temperature. This will, of course, require that formation temperature (Tf ) be determined for each potential hydrocarbon-bearing zone. Before calculating water saturation (S w ), the lithology of the formation of interest should be determined. Again, this may be done by quick-look, or by use of one of the lithology charts. Knowledge of lithology will determine the appropriate values of tortuosity factor (a) and cementation exponent (m) for inverse-Archie Rw calculations. Again, in a quick-look analysis, environmental corrections are typically not performed. To be more precise, environmental corrections should be applied to any log measurement before calculating water saturation (S w ). For clean formations, it is assumed that the Archie equation is applicable. Bear in mind, however, that there are certain instances (such as when clay minerals are present in a shaly sand) that alternative methods of calculating water saturation will be more appropriate. Some of these methods will be discussed in the Shaly Sand Analysis sections of this text.

Decisions on Productive Capability The most difficult process in the basic evaluation of a clean formation has now been reached; the decision of whether to set pipe and perforate or consider abandonment still hangs. Calculated values of water saturation (S w ) only provide the analyst with information about what fluids are present in the formation of interest. In many cases, water saturation is not a reflection of the relative proportions of fluids that may be produced. Therefore, when making the decision to set pipe or abandon, all available information should be taken into account. Water saturation (S w ) should be the basis for this important decision, but other factors also enter into the decision making process. These factors include: volume of shale (V sh) of the reservoir, irreducible water saturation (S wirr ) and bulk volume water (BVW), moveable hydrocarbons, etc.. In many instances, much of the decision revolves around a "gut feeling"; however, in all cases, there is no substitute for experience in a particular region when making the choice. Some additional methods that may be used during the decision making process will be addressed in the Additional Log Interpretation Techniques section of this text.

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References Asquith, G. B., 1982, Basic well log analysis for geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p. Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston, MA, 647 p. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishing, Tulsa, OK, 361 p.

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Section 5

Additional Log Interpretation Techniques Table of Contents Introduction…………………………………………………………………….…………………... 69 Objectives…………………………………………………………………….…………………….. 69 Moveable Hydrocarbon Index (MHI) …………………………………………………………….

70

Ratio Water Saturation (Swr) ……………………………………………………………………... 71 Ratio Formation Water Resistivity (Rwr) ………………………………………………………… 72 Bulk Volume Water (BVW) …………………………………………………………………….… 73 Log-Derived Permeability (KL) …………………………………………………………………… 74 Wyllie and Rose (1950) Method…………………………………………………………………. 75 Coates and Dumanoir (1973) Method…………………………………………………………… 75 Calculation of Reserves…………………………………………………………………….…….. 76 Barrels of Oil in Place…………………………………………………………………….……….. 76 Recoverable Oil (Stock Tank Barrels) ………………………………………………………….. 76 Cubic Feet of Gas in Place…………………………………………………………………….…. 77 Recoverable Gas (Cubic Feet) ………………………………………………………………….. 77 References…………………………………………………………………….…………………… 78

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Introduction Calculating water saturation, whether by the Archie equation or one of the many shaly sand equations, is the primary goal of open hole log analysis. This provides an estimate of the relative proportion of water and hydrocarbons contained in a particular reservoir. However, interpretation of log data does not necessarily end with a result for water saturation. There are numerous other basic calculations that may be extremely helpful in evaluating the productive capability of a reservoir. Analysts would also like to know whether hydrocarbons within a reservoir are moveable and capable of being produced, whether water saturation is low enough for water-free production, whether a particular zone is permeable, and if so, whether there are economical recoverable reserves. This section introduces some of these additional evaluation methods and illustrates how they may be used in combination with a basic analysis.


calculate flushed zone water saturation (S xo) of a hydrocarbon-bearing formation.

§

calculate moveable hydrocarbon index (MHI) of a hydrocarbon-bearing formation and estimate whether hydrocarbons were moved during invasion.

§

calculate ratio water saturation (S w r) of a hydrocarbon-bearing formation.

§

calculate ratio formation water resistivity (Rw r) of a water-bearing formation.

§

calculate bulk volume water (BVW) of a hydrocarbon-bearing formation.

§

estimate grain size of a clastic reservoir from bulk volume water (BVW).

§

estimate pore type of a carbonate reservoir from bulk volume water (BVW).

§

calculate log-derived permeability (K L).

§

calculate in place and recoverable reserves for oil- and gas-bearing reservoirs.

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Moveable Hydrocarbon Index (MHI) One way to investigate the moveability of hydrocarbons is to determine water saturation of the flushed zone (S xo). This is accomplished by substituting into the Archie equation those parameters pertaining to the flushed zone.

The only tool that measures an accurate value for resistivity of the flushed zone (Rxo) is the Micro-Spherically Focused Log (MSFL), and even then its measurement should only be taken to reflect Rxo after all environmental corrections have been applied. By environmentally correcting the measurements of shallow resistivity devices such as the DFL or Short Guard, an estimate of Rxo may be obtained. Once flushed zone water saturation (S xo) is calculated, it may be compared with the value for water saturation of the uninvaded zone (S w ) at the same depth to determine whether or not hydrocarbons were moved from the flushed zone during invasion. If the value for Sxo is much greater than the value for Sw , then hydrocarbons were likely moved during invasion, and the reservoir will produce. An easy way of quantifying this relationship is through the moveable hydrocarbon index (MHI).

When the moveable hydrocarbon index (MHI) is equal to 1.0 or greater, then this is an indication that hydrocarbons were not moved from the flushed zone during invasion of mud filtrate. Empirical studies have resulted in some guidelines that should be used with caution. §

sandstones moveable hydrocarbons indicated if MHI < 0.7

§

carbonates moveable hydrocarbons indicated if MHI < 0.6

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Ratio Water Saturation (Swr) Another use of the moveable hydrocarbon index (MHI) equation is to determine water saturation of the uninvaded zone (S w ) when no porosity logs are available. This is known as the ratio method, or Rocky Mountain method after the geographic region in which its use was popularized. The moveable hydrocarbon index (MHI) equation may be rewritten as follows:

In using the ratio method, we are interested in obtaining a value for water saturation of the uninvaded zone (S w ). Therefore, we must assume some relationship between Sw and Sxo so that the Sxo term in the above equation can be eliminated. In most cases where formations are moderately invaded, the following relationship holds:

By substituting this relationship into the MHI equation above, the following results:

Ratio water saturation (S w r) represents water saturation of the uninvaded zone calculated independent of porosity. Once ratio water saturation (S w r) has been calculated, it may be compared with the value of Archie water saturation (S w ) at the same depth to gain even more information on the formation of interest. The following observations--which also should be used with caution--have been made between ratio water saturation (S w r) and Archie water saturation (S w ) of the uninvaded zone. Sw (Archie) ~ Swr (Ratio) All values (S w , Rt, Rxo, and di) are indicated to be correct, and the assumption of a step invasion profile is correct. Sw (Archie) > S w (Ratio) Rxo may be too low because of very shallow invasion, or Rt may be too high because of very deep invasion. Furthermore, a transition invasion profile is

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Basic Log Interpretation indicated. Archie water saturation (S w ) should be considered the more accurate value. Sw (Archie) < S w (Ratio) Rxo may be too high because of the effects of high resistivity adjacent beds, or Rt may be too low. An annulus invasion profile may be indicated in this situation.

Ratio Formation Water Resistivity (Rwr) An alternate method of determining a value for formation water resistivity (Rw ) from logs is the ratio method. This technique is rather easy to use because it eliminates the need to know porosity and lithology of the wet zone, and the necessity of a Spontaneous Potential curve. The premise behind this method is the assumption that in a 100% water saturated zone (S w = 100%), the invaded portion of the well is also 100% water saturated (S xo = 100%, where Sxo represents flushed zone water saturation). If deep and shallow resistivities have been invasion corrected to Rt and Rxo, respectively, and if reliable and accurate Rmf data is available from a full mud press, then a value of formation water resistivity (Rw ) can be determined.

Values for true formation resistivity (Rt) and flushed zone resistivity (Rxo) must be determined from the appropriate tornado or butterfly charts for resistivity devices. In some instances, analysts will take approximate values directly from the logs, realizing that shallow reading Rxo devices may be dramatically effected by the invasion of mud filtrate. The only true Rxo device is the Micro-Spherically Focused Log (MSFL). All other "shallow" resistivity devices will require invasion correction to obtain a reliable value of Rxo. If reliable values for Rt and Rxo are available and a valid mud test reading of Rmf is available, then a value for formation water resistivity (Rw ) can be determined. This resulting value should be compared to other results in an effort to determine which is reasonable and optimistic.

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Bulk Volume Water (BVW) Water saturation simply represents the fraction of porosity in a reservoir that is occupied by water. In some instances, it may be beneficial to know the fraction of rock volume that is occupied by water. This is expressed as bulk volume water (BVW).

Bulk volume water has several important applications. Within a particular reservoir, BVW may be calculated at several depths. Where values for BVW remain constant or very close to constant throughout a reservoir, this may be taken as an indication that the reservoir is at or near irreducible water saturation (S w irr). Irreducible water saturation is the value of water saturation at which all water within the reservoir is either adsorbed onto grain surfaces or bound within the pore network by capillary pressure. If a reservoir is at irreducible water saturation, then the water present within that formation will be immovable and production will--theoretically--be water-free hydrocarbons. Reservoirs that exhibit variation in values for BVW are typically not at irreducible water saturation and, therefore, at least some water production can be expected. Irreducible water saturation is related to the grain size of a reservoir. As grain size decreases, the diameters of pore throats within the reservoir will decrease, resulting in higher capillary pressures. This condition implies a reservoir in which a substantial amount of water may be trapped and unable to move. Therefore, when a reservoir is determined to be at irreducible water saturation, values for bulk volume water (BVW) may be used to estimate the average grain size of that reservoir (Figure 5.1). Realizing the potential for error, this approximation may also be used in reservoirs that are not at irreducible water saturation.

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Bulk volume water (BVW) should not be confused with "bulk volume irreducible" (MBVI) which is a reservoir parameter determined by Magnetic Resonance Imaging Logging (MRIL). BVW represents the percentage of rock volume that is water. MBVI, on the other hand, represents the relative proportion of fluid within the reservoir that is bound by capillary pressure. The presence of clay minerals in a reservoir also has an impact on values of irreducible water saturation (S w irr ) and bulk volume water (BVW). As the volume of clay minerals in a reservoir (V sh) increases, both Sw irr and BVW will increase because of the inclination of clay to trap interstitial formation water.

Log-Derived Permeability (KL) Thus far, permeability has been discussed only in qualitative terms. Microlog and Spontaneous Potential responses may be used as qualitative indicators of permeability; however, it is virtually impossible to derive a reliable and accurate value for reservoir permeability from standard open-hole logging data. Formation tester data may help to further evaluate permeability, and Magnetic Resonance Imaging Logs (MRIL) make another step in getting closer to an accurate value of permeability. If a reservoir is deemed to be at irreducible water saturation (S w irr ), then a logderived estimate of permeability can be made. Constant to near-constant values of bulk volume water (BVW) within a reservoir indicate that reservoir is at (or at least near) irreducible water saturation. Once this determination is made, logderived permeability may be calculated. Two of the possible methods are discussed as follows.

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The constants used in the Wyllie and Rose method (250 and 79) are used to account for the effects that hydrocarbon density (whether it be medium gravity oil or dry gas) has on permeability. The use of these constants is one reason why this calculated value of permeability should be used only as an estimate.

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Calculation of Reserves The decision of whether to set pipe and perforate versus abandon a well can be made easier if there is some estimate of the possible recoverable reserves.Economics are therefore brought into play in the analysis. A basic part of any evaluation should be to at least estimate the volume of hydrocarbon that may be produced from a particular well. Calculation of reserves requires information about the petrophysical characteristics of the reservoir (e.g., water saturation, porosity), dimensions of the reservoir (e.g., drainage acreage, thickness), and production characteristics (e.g., recovery factor, "shrinkage factor").

Barrels of Oil in Place

Most of the information required for this calculation is readily available from the logs or from simple calculations. The volumetric constant 7758 refers to the number of barrels in a 1 acre by 1-foot thick volume. It is very easy to obtain information about reservoir thickness from logs. However, logs do not give any indication about the drainage area of a particular reservoir. Unless information regarding the areal extent of a reservoir is available, then the variable A can be assumed as the allowed well spacing within the field.

Recoverable Oil (Stock Tank Barrels) The amount of oil calculated to be in place does not reflect the amount of oil that can be produced from the reservoir. The percentage of oil that can feasibly be recovered from the reservoir (i.e., recovery factor) and the shrinkage experienced by oil as it comes to the surface (i.e., formation volume factor) must also be considered. Recoverable oil, in stock tank barrels, may be estimated by the following equation:

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The recovery factor (RF) deals with the fact that not all of the oil present in a formation is capable of being produced. Oil that is "dead", trapped by capillary pressure, or otherwise immovable contributes to the volume of oil present in a reservoir, but will not be produced. This recovery factor depends upon reservoir type, the initial hydrocarbon saturation of that reservoir, and the production mechanism. For a typical case where a reservoir is produced by flowing or by pump (primary recovery), it is safe to assume a recovery factor of 20% to 30% (RF = 0.2 to 0.3). In cases where a reservoir is under water flood or other secondary recovery methods, a recovery factor of 40% may be more applicable. Rarely will recovery factors exceed 50%, even in the case of advanced recovery techniques such as steam or CO2 flood. As oil moves toward the surface during production, gas will be evolved from solution. This results in a volumetric difference between the amount of oil in place and the amount of oil existing in stock tanks at the surface. The variable B ("shrinkage factor" or formation volume factor) takes this volumetric difference into account. For oil, it is safe to assume a shrinkage factor of approximately 1.2.

Cubic Feet of Gas in Place The amount of gas in place in a reservoir (in cubic feet) may be estimated in a similar manner as with oil, and by the following equation:

The volumetric constant 43560 refers to the number of cubic feet in a 1 acre by 1- foot thick volume. This equation yields the amount of gas existing in place at formation temperature (Tf ) and formation pressure (P f ).

Recoverable Gas (Cubic Feet) As was the case with oil, the amount of gas calculated to be in place does not reflect the amount of gas that can be produced. The deviation factor (Z) and recovery factor (RF) account for this volumetric difference, and are employed in the following equation to estimate recoverable gas: HLS Asia Limited

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When using the above equation to estimate cubic feet of recoverable gas, it is not necessary to multiple the results by the conversion factor (CF) to yield cubic feet at standard temperature and pressure. The conversion factor is an integral part of this equation. Thus, the result of the equation will be cubic feet of gas at average surficial conditions (60ºF and 14.7 psi).

References Asquith, G. B., 1982, Basic Well Log Analysis for Geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p. Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston, MA, 647 p. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishing, Tulsa, OK, 361 p.

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Section 6

Shaly Sand Theory

Table of Contents Introduction…………………………………………………………………….…………………… 80 Objectives…………………………………………………………………….…………………….. 80 Shaly Sand Analysis…………………………………………………………………….………… 81 The Nature of Clay Minerals and Shale…………………………………………………………. 81 Modes of Occurrence of Clay Minerals…………………………………………………………. 82 Assumptions Involved in Shaly Sand Analysis…………………………………………………. 84 Bound Water in Shaly Sands…………………………………………………………………….. 84 Log Responses in Presence of Clay Minerals………………………………………………….. 86 Porosity Response…………………………………………………………………….…………... 87 Sonic Response…………………………………………………………………….……………... 88 Density Response…………………………………………………………………….…………… 88 Neutron Porosity…………………………………………………………………….…………….. 88 Resistivity Response…………………………………………………………………….………... 89 Combined Effect of Porosity and Resistivity Responses……………………………………… 90 References…………………………………………………………………….…………………… 91

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Introduction To this point the discussion of log analysis has focused on clean formations in which the Archie equation may be used to evaluate water saturation (S w ) of the uninvaded zone. What happens to the analysis if the formation of interest is not clean? Suppose, instead, that the formation contains some amount of "shale," or clay minerals. These clay minerals will have an effect on particular log responses and, therefore, the analysis will be in error unless the presence of these clays in accounted for. This is the field of shaly sand analysis, perhaps one of the most confusing aspects of open hole log analysis. This section introduces the theory and need for shaly sand analysis. The application of specific shaly sand techniques are addressed in the following Shaly Sand Applications section of this manual.


define the term "clay mineral" and how it relates to "shale."

§

list the different modes of occurrence of clay minerals and discuss how each may affect reservoir properties such as porosity and permeability.

§

define the different types of bound water associated with clay minerals/shales.

§

discuss the effects of clay minerals on sonic, density, and neutron porosity.

§

discuss the effects of clay minerals on resistivity measurements.

§

discuss the effects of clay minerals on calculated values of water saturation(S w ) and how shaly sand analysis "modifies" these results.

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Shaly Sand Analysis The presence of clay minerals (i.e., "shale") in a reservoir may either be good or bad in terms of reservoir quality. Small amounts of clay minerals within the pore space of a reservoir may, because of the increased surface adhesion and capillary pressures associated with such small particle sizes, trap interstitial water. The result can be virtually water-free hydrocarbon production from reservoirs of relatively high calculated water saturation (S w ). On the other hand, the presence of a large amount of clay may result in the porosity and permeability of the reservoir being reduced to the point where the reservoir becomes non-productive. A question, then,emerges how much clay is present, and what effects does it have on the reservoir (and the logs)? All lithologies--including limestones and dolomites--may potentially contain some amount of clay minerals. More commonly, however, clay minerals are found associated with sandstone reservoirs. Because of this, log analysts typically make reference to the "shaly sand problem." The presence of clay minerals in a reservoir may seriously affect some log responses, particularly resistivity and porosity. The end result is an erroneously high value of water saturation, and in some cases a productive reservoir may appear to be wet. Field engineers and log analysts should be able to recognize the effects of clay minerals and be able to correct for their presence to yield more accurate values of water saturation. This emphasizes the need for "shaly sand analysis."

The Nature of Clay Minerals and Shale "Shale," in the most basic of definitions, is a sedimentary rock consisting of both siltsized and clay-sized particles that were deposited in a low energy environment. Shale itself is of little interest in log analysis because it typically is not a reservoir rock. However, the clay-sized fraction of shale is extremely important because it is these very fine grained particles that may be found within the pore spaces of a potentially productive reservoir. Clay minerals are very fine grained (< 4?m) hydrous aluminum silicates with minor amounts of potassium (K), magnesium (Mg), iron (Fe), and other elements. Clay minerals may be classified on the basis of their crystalline structures, and each type of clay mineral has particular properties that may influence wireline logs in different ways and to different degrees (Figure 6.1).

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Clay minerals may either be detrital or authigenic in origin. Detrital clay minerals are those that were deposited in low energy environments as a component of shale. During the deposition of other sand sediments nearby, these shales may be ripped up and deposited as laminations, clasts, or even individual grains along with the sand grains. Authigenic clay minerals, on the other hand, are deposited within the pore space of an existing reservoir as the result of some chemical reaction. Both detrital and authigenic clays may influence the productive capability of a reservoir as well as the log responses within that reservoir. However, authigenic clays tend to cause the most problems because of their ability to partially restrict or completely block pore throats. Furthermore, authigenic clays have the ability to trap interstitial formation water, a trait that may be either good or bad. In log analysis, the terms "shale" and "clay" are often used interchangeably. This practice is confusing and should be avoided when possible. Proper reference should be given to each; however, be aware that "shale"--although it is a rock in its own right--is often used to refer to minor amounts of clay minerals within a formation.

Modes of Occurrence of Clay Minerals For the purpose of log analysis, it is necessary to consider clay minerals in terms of their morphology, or mode of occurrence. Typically, log analysts use the terms laminated shale, structural clays, and dispersed clays to refer to the distribution of clay minerals within a reservoir. Laminated shale (Figure 6.2) refers to thin layers of clay minerals--from a fraction of an inch to several inches in thickness--that are interbedded with thin intervals of sandstone. These clays are detrital in origin, and were deposited at the same time as the sand grains of the reservoir. The presence of laminated shale tends to reduce the porosity and permeability of a reservoir, and can be thought of simply as a ductile material that has been squashed between the framework grains (e.g., sand grains) of a reservoir. Shale laminations are typically so thin that they are far below the resolution limits of wireline tools. They do, however, influence log responses because their petrophysical properties are averaged in with the rest of the formation. For example, even if an induction tool cannot resolve an individual shale lamination that is 1 inch thick, the overall resistivity of that zone will be reduced because of the presence of that shale.

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Structural clay (Figure 6.2) refers to detrital clay minerals that exist as individual grains, clasts, or particles along with the framework grains of a reservoir. This type of clay typically has little impact upon reservoir quality because it does not restrict or block pore throats. Furthermore, structural clay is usually present in such small quantities that it is considered to be of little importance. When present, however, structural clays will have an influence on log responses in a similar manner as that of other clays because their petrophysical properties are averaged in with the petrophysical properties of the framework grains. Dispersed clay (Figure 6.2) refers to very fine grained particles that exist within the pore space of a reservoir and actually replace fluid volume. These types of clays, because of their disseminated fibrous and plate-like morphologies, may be very damaging to reservoir quality. In small amounts, dispersed clays may block pore throats and reduce effective porosity and permeability. Furthermore, these types of clays can actually migrate through the pore network of a reservoir causing disastrous completion and production problems. Dispersed clays are much different than laminated shales and structural clays in that they are authigenic in origin. These types of clays precipitated in situ as the result of some chemical reaction. Because of the fact that dispersed clays

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Basic Log Interpretation are capable of trapping large quantities of formation water due to their large surface-tovolume ratios, their effects on log responses may be quite significant.

Assumptions Involved in Shaly Sand Analysis One problem with shaly sand analysis is that it is based upon two rather dubious assumptions. Rarely, if ever, is the type and amount of clays in a reservoir known before that reservoir is logged. Nothing is known about the clays' chemical compositions, modes of occurrence, or effects on log responses unless core data is available. Regardless of what clay types are present, it is necessary to assume that all clays are equal in the eyes of a log. Laminated shales, structural clays, and dispersed clays influence log responses to different degrees; however, because of their size, they are far below the resolution limits of logging tools. Therefore, it is necessary to assume that the petrophysical properties of a clay measured by a log are simply averaged in with the rest of the formation. In addition, because clay minerals are so small and cannot be measured individually by a log, it is necessary to assume that their petrophysical properties are identical to those of adjacent shales. For example, the overall resistivity of a formation may be lowered by the presence of clay. It is impossible to measure the resistivity of that clay mineral with any logging tool, so it must be assumed that its resistivity is the same as that of a shale (Rsh) either above or below the formation of interest. This assumption is usually valid provided there are detrital clays within a reservoir.Laminated shales and structural clays were likely derived from the shale below the formation or interest, or had a similar source. However, authigenic clays were derived by some chemical reaction that was entirely independent of any adjacent shale. Therefore, when dealing with dispersed clays, the assumption that their properties are identical to adjacent shales is invalid, but often necessary for lack of core data to prove otherwise.

Bound Water in Shaly Sands Much of the confusion in shaly sand analysis revolves around misconceptions about what constitutes "bound water" within the reservoir. For a complete understanding of the problems that logging tools encounter in these formations, it is necessary to recognize that there are different types of "bound water," and that each type may have a different degree of influence on log responses. Clay minerals are hydrated sheet silicates and are very similar in crystalline structure to mica minerals (i.e., muscovite and biotite). The basic building block of a clay mineral is the silicon tetrahedron, and these tetrahedra are linked together in layers ("sheets") several Angstroms thick which are separated by other cations such as K, Mg, Ca, and Fe. Figure 6.3 illustrates the crystalline atomic structure of the clay mineral smectite. Bound within the crystalline structure of smectite are hydroxyl ions (OH-), and within the large "interlayers" separating tetrahedra sheets there may be H2O molecules along with other

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Basic Log Interpretation cations (Ca, Mg, etc.). These hydroxyl groups and water molecules are part of the crystalline structure of the clay mineral, and are referred to as structurally bound water. This is not what is typically thought of in terms of "bound water," but adding hydrated clay minerals to a reservoir does increase the hydrogen index of the formation because of these hydroxyl ions and water molecules. This increase in hydrogen abundance will produce misleading neutron porosity responses.

The typical conception of "bound water" within a shaly sand involves what may be referred to as capillary bound water and clay bound water. Capillary bound water exists because of increased capillary pressures in very small diameter pore throats, and may be a characteristic of both very fine grained clean sandstones as well as shaly sandstones. Clay bound water, on the other hand, is that water which is bound to the surface of clay minerals by electrostatic and chemical forces. Because of ionic substitutions within the crystalline structure of clay minerals (mainly Mg2+ for Al3+), clay minerals are often left with a net negative charge (Figure 6.3). Adding to this negative charge are broken chemical bonds along broken crystal edges of clay platelets. In the dry state, this negative charge is balanced by the attraction of positively charged Na + counterions to the clay's surface. These Na + counterions temporarily occupy what are referred to as "exchange sites" on the surface of the clay minerals, and are capable of exchanging themselves for one another as well as with other ions on a charge-percharge basis. When clay minerals exist within a solution such as water, however, these counterions are allowed to migrate a short distance from the clay's surface because the dielectric permitivity of that water will weaken the Coulomb forces binding them to the clay. The counterions will not migrate far from the clay surface because they will still feel the attractive force of the negatively charged clay crystal. In their migration the water in the mineral because Na+ counterions

away from the clay surface, a tremendous surface area is exposed to formation. A thin film of water will adhere to the surface of the clay of high surface tension ("adsorbed water"). Additionally, because the are now existing within a solution, they will be hydrated by several

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Basic Log Interpretation water molecules. The attractive force of the negatively charged clay mineral that acts to restrain the free migration of the Na + counterions will therefore bind this additional later of "water of hydration" to the clay surface. These phenomena of electrostatically and chemically bound clay bound water are illustrated in Figure 6.4. It is the combination of these three types of "bound water"--structural, capillary, and clay bound--that causes problems when analyzing a shaly sand using the conventional Archie approach. The Archie equation treats all water the same, and does not distinguish between what is bound and what is free to move. Another method of calculating water saturation is needed in shaly sands. Archie water saturation (S w a) does not distinguish between bound water and free water, and treats all water as the same.

Log Responses in Presence of Clay Minerals Even more confusion in shaly sand analysis revolves around the fact that the effects of clay minerals in a reservoir are typically not accurately represented on the logs. For instance, even though authigenic dispersed clays actually reduce the porosity of a reservoir, sonic and neutron logs exhibit an increase in porosity. Log responses may reflect a condition entirely different from that actually occurring in the reservoir.

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Porosity Response In order to understand how clay minerals influence log responses, it is best to begin with a model formation consisting of a clean sandstone of given porosity at 100% water saturation. In such a formation, if porosities are calculated for sandstone, then all porosities (sonic, density, and neutron) will be equal. Furthermore, all of these porosities will be equal to the effective porosity of the reservoir. Effective porosity refers to the pore space that is interconnected, or which is available to free fluid (in this case, 100% water). In this situation, the Archie equation generally holds true and may be used to calculate a reasonably accurate water saturation of the reservoir. A possible limitation to using the Archie equation in even a clean sandstone is if the grain size is so small that a high percentage of the water within the formation is bound by capillary pressure. Again, the Archie approach does not distinguish between bound water and free water, and therefore producible water saturation would be overestimated. Now consider that same model sandstone formation at 100% water saturation, but in this case some amount of clay minerals has been added. In this situation, the clay minerals will occupy a volume that was formerly occupied by fluid (100% water). Therefore, through the addition of clay minerals the porosity of the reservoir has decreased. Some fluid in the reservoir (in this case, 100% water) will be "bound" by the clay minerals and will be immovable. The amount of porosity available to free fluids (Φ effective) together with the porosity associated with "bound" fluids represents the total porosity of the reservoir. By adding clay minerals to the model formation, its total porosity has been reduced. However, porosity logs may not reflect this decrease in porosity. They may actually exhibit an increase in porosity (Figure 6.5). Furthermore, each porosity measurement will be influenced to different degrees by the presence of clay minerals, and some clays may not have as profound an effect as others. It is vital to understand how each measurement (sonic, density, and neutron) is influenced, and this requires an understanding of the physical and chemical properties of clay minerals.

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Sonic Response When clay minerals are present in a reservoir, there may be a significant effect on ∆t measurements. For an individual grain of quartz sand in a clean formation, ∆t of that grain will be equal to 55.5 µs/ft. When clays are added in a shaly sand situation, ∆t changes dramatically. The sonic tool "sees" each grain in the reservoir as a grain of sand (55.5 µs/ft) together with the clay minerals (70 – 140 µs/ft). The overall result is that the sonic tool "sees" a much higher "averaged" ∆t when clay minerals are present. Through the Wyllie Time-Average equation, this increase in ∆t translates as an increase in sonic porosity. Density Response Adding clay minerals to a clean sandstone will be correctly reflected on the density log as a decrease in porosity; however, the absolute value of density porosity is often misleading. Depending upon the density of the clay mineral present (ρclay ), density porosity may be underestimated or overestimated when calculated for a sandstone. The reason for this error lies in the assumption of matrix density (ρma). In a shaly sand, the actual ρma of the formation will be some volumetric combination of the density of the clay (ρclay ) and the density of the sand grains (ideally, 2.65 g/cc). When ρclay > ρsand, then the actual ρma of the formation will be higher than that which we assume to calculate porosity (i.e., 2.65 g/cc). The resulting porosity will be underestimated. On the other hand, where ρclay < ρsand, density porosity will be overestimated because the actual formation ρma will be less than that which was assumed to calculate porosity. In those instances where ρclay = ρma, there will be no appreciable effect upon density porosity. Neutron Porosity The response of the neutron tool is not as straightforward as that of the sonic and density tools. By adding clay minerals to the clean formation, the porosity of the formation is reduced. This translates as a reduction in the amount of pore water. It follows then that as the amount of water in the formation (i.e., porosity) decreases, the hydrogen index of the formation will decrease and, as a result, neutron porosity (Φ n) will also decrease. However, this is not the case. Neutron porosity actually increases when clay minerals are added to the reservoir. This results from the fact that clay minerals are hydrated and contain structurally bound hydroxyl ions (OH-) within their crystalline structure. The neutron tool reflects this additional hydrogen as an increase in porosity even though the structurally bound water is not a part of the pore space of the reservoir.

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Resistivity Response The presence of clay minerals in a formation also has a strong effect on the measured resistivity of that formation. Because of the fact that porosity decreases when clay minerals are added to a clean formation, resistivity might be expected to increase. After all, when the amount of pore water available to conduct an electrical current decreases (in this case by the addition of clay minerals), the resistivity of that formation will increase. However, this is not the case in shaly sands. The measured resistivity of a shaly sand will, depending on the amount of clay minerals present, be less than that of a clean formation. This change does not result from a change in formation water resistivity (Rw ). For a clean sand and shaly sand containing the same formation water (constant Rw ), the clean sand will still exhibit higher resistivity. The change results from a specific property of the clay minerals. The graph in Figure 6.6 illustrates that for two formations of identical porosity and identical water salinity, one clean and one clay-bearing, the clay-bearing formation will exhibit a higher conductivity (i.e., lower resistivity). The interesting part of this graph is the non-linear relationship between shaly sand and clean sand conductivities (C o) at lower values of formation water conductivity (C w ).

Within the range of low conductivity formation waters, the conductivity of the shaly sand increases more dramatically than would be predicted by the increase in formation water conductivity (Ro = Fr ? ? Rw ; hence, Co = (1/F r) X Cw ). At some point a water salinity is reached such that there exists a linear relationship between formation conductivity (C o) and water conductivity (C w ) in both the shaly and clean sands with shaly sand

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Basic Log Interpretation conductivity remaining consistently higher than clean sand conductivity. Because the only difference between these two formations is the presence of clay minerals, then those clay minerals must be the source of the excess conductivity (i.e., lower resistivity). The dramatic increase in formation conductivity with increasing water conductivity can be attributed to the mobility of the charge-balancing Na + counterions. As discussed previously, the dielectric permitivity of the water will allow these exchange counterions to migrate. Migration of these counterions may take place between exchange sites on one clay crystal, between exchange sits on separate clay crystals, or through the formation water. The migration of these counterions produces a potential that contributes to the conductivity of the formation. The greater the clay content, the greater the excess conductivity. As the salinity of the formation water increases, the migrating counterions are provided with a more energetically feasible path of least resistance. As a result, the conductance produced by these counterions will increase even more, and the formation conductivity will continue to increase at a faster rate than does water conductivity. Ultimately, an equilibrating salinity of formation water will be reached such that a further increase in salinity will have little effect on the mobility of the counterions. Beyond this value of salinity, conductivity of the shaly sand will increase linearly with increase in formation water conductivity. Nevertheless, there remains the condition that for all values of moderately saline formation waters (as expected in most reservoirs), shaly formations will exhibit higher conductivities (i.e., lower resistivities) than their clean counterparts containing waters of identical chemistry. This added conductance produced by the clay minerals may be quantified in terms of the cation exchange capacity (CEC) of a particular clay. Clay minerals with high CEC values (see Figure 6.1) result in lower formation resistivities than those clay minerals with lower CEC values. Because the ionic concentration of the bound water is proportional to the volume of clay bound water, CEC may also be used to quantify the volume of clays within a reservoir. CEC must be determined from core data, however. Where core data is absent, values of volume of shale (V sh) calculated from log responses are commonly used as a substitute.

Combined Effect of Porosity and Resistivity Responses The combined effect of the decreased resistivity and typically increased porosity exhibited on logs in the presence of clay results in erroneously high values of water saturation (S w ) calculated by the Archie equation. The purpose of shaly sand analysis is to correct for these effects and thereby reduce water saturation to what it would be if clays were absent. Without prior knowledge of the existence of clays in a reservoir, it must be assumed that clays are present. Thus, any analysis of a reservoir should be approached from the standpoint that clays are present. If clays are subsequently determined to be absent, then the analysis may be undertaken by conventional means (i.e., Archie equation). If, however, clays are present, then modified equations must be used to evaluate water saturation.

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Basic Log Interpretation The danger in assuming that a reservoir contains clay minerals is that the resulting value of Archie water saturation (S w ) is expected to be too high. By performing shaly sand analysis, this value of water saturation is reduced. If a reservoir is falsely assumed to contain clay, then it is entirely possible to lower the water saturation of a zone to the point that a water-bearing zone appears to contain hydrocarbons. By the same token, if the presence of clays is not corrected for, then the resulting water saturation value will be too high and a potentially productive zone may be bypassed. For these reasons, shaly sand analysis should be used with caution, and not as a substitute for knowing everything possible about the formation of interest. Shaly sand analysis may potentially lower the water saturation of a reservoir to the point that a wet zone appears to be productive.

References Asquith, G. B., 1982, Basic well log analysis for geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p. Asquith, G. B., 1985, Log evaluation of shaly sandstones: a practical guide: American Association of Petroleum Geologists Continuing Education Course Note Series No. 31, Tulsa, OK, 59 p. Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston, MA, 647 p. Clavier, C., G. Coates, and J. Dumanoir, 1977, Theoretical and experimental bases for the Dual-Water Model for interpretation of shaly sands: Society of Petroleum Engineers Journal, v. 24, no. 2, p. 153-168, SPE-6859. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishing, Tulsa, OK, 361 p. Waxman, M. H., and L. J. M. Smits, 1968, Electrical conductivities in oil-bearing shaly sands: Society of Petroleum Engineers Journal, v. 8, no. 2, p. 107-122, SPE-1863-A.

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Section 7

Shaly Sand Applications Table of Contents Introduction…………………………………………………………………….…………………

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Objectives…………………………………………………………………….…………………..

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Procedures of Shaly Sand Analysis…………………………………………………………… 94 Determining Volume of Shale (Vsh) ……………………………………………………………

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Vsh from Gamma Ray…………………………………………………………………….………

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Vsh from Spontaneous Potential………………………………………………………………...

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Vsh from Neutron-Density Logs………………………………………………………………….

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Comparison of Vsh Results……………………………………………………………………....

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Determining Effective Porosity (Φ e) ……………………………………………………………

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Effective Porosity from Sonic Logs……………………………………………………………. 97 Effective Porosity from Density Logs…………………………………………………………..

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Effective Porosity from Neutron-Density Combinations……………………………………...

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Determining Effective Water Saturation (Swe) ………………………………………………..

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Simandoux Method…………………………………………………………………….………...

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Fertl Method…………………………………………………………………….………………...

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Dispersed Clay Method…………………………………………………………………….……

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Dual Water Method…………………………………………………………………….………...

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Selecting the Appropriate Method……………………………………………………………...

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Simandoux Method…………………………………………………………………….………...

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Fertl Method…………………………………………………………………….………………...

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Dispersed Clay Method…………………………………………………………………….……

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Dual Water Method…………………………………………………………………….………...

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References…………………………………………………………………….………………….

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Introduction The Archie equation often produces a value of water saturation (S w) that is too high in formations that contain clay minerals. Where clays are known to be present, the Archie equation must be modified to yield more favorable results. Therefore, the effective porosity (Φ effective) and effective water saturation (S we ) of the reservoir must be known. This section presents several methods whereby these values can be determined from conventional open hole logging data.


list the three basic steps of shaly sand analysis.

§

calculate volume of shale (V sh) from a standard suite of open hole logs.

§

calculate effective porosity (Φ e) from a standard suite of open hole logs.

§

calculate effective water saturation (S we ) from a standard suite of open hole logs using the Simandoux, Fertl, Dispersed Clay, and Dual Water methods.

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Procedures of Shaly Sand Analysis The process of shaly sand analysis consists of three main steps, each of which should be accomplished in a specific order. These three steps include: 1.

Determining volume of shale (V sh) in the zone of interest.

2.

Correcting porosity for the presence of clays (determining effective porosity of the zone of interest).

3.

Determining effective water saturation (S we ) of the zone of interest (water saturation of the effective pore network).

Each of these three processes will be examined in more detail in the paragraphs that follow. Realize that the overall goal of shaly sand analysis is to essentially lower the value of water saturation (S w) to what it would be if clay minerals did not exist in the reservoir.

Determining Volume of Shale (Vsh) The first step in shaly sand analysis is to determine the amount of clay minerals present in the formation. There are many methods that are used to determine this, and several are discussed below. It should be remembered that these determinations are simply estimates of the volume, or percentage, of clay minerals within a reservoir, and do not consider the type of clay present or its distribution. When the volume of shale (V sh) is determined to be less than 15% of the bulk rock volume, then it is safe to assume that clay minerals are not having a significant effect on log responses, and analysis may be pursued by conventional means (i.e., Archie equation). Where Vsh exceeds 15% bulk rock volume, shaly sand analysis should be performed to obtain more accurate values of water saturation. Many types of logs, used either alone or in combination with others, are used to indicate shale content, although none of them is consistently reliable. Each method discussed below is designed to give either a good estimation of Vsh in conditions favorable to the particular tool, or to give an upper limit of V sh.

Vsh from Gamma Ray In a formation containing clay minerals or shale of a constant radioactivity level and no other radioactive minerals, the volume of shale (V sh) is expressed as a linear function of the borehole-corrected gamma ray response. GR = A + N + V sh This condition is usually not the case, and an alternative method of determining Vsh must be used. This alternative method requires that the Gamma Ray Index (IGR) be calculated. By using the Gamma Ray Index as an indicator of clay content, we are simply normalizing the gamma ray response to estimate the percentage of shale present in a reservoir.

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Using Gamma Ray Index (IGR) as a linear expression of Vsh is most suitable for laminated shales. In this case, the resulting ratio reflects the percentage of clay minerals contained in the reservoir. Again, when this ratio exceeds 15%, then it should be assumed that the formation is indeed a shaly sand and that the Archie equation should be abandoned for a technique that will yield better results of water saturation in the presence of clay minerals. Some analysts prefer to use Gamma Ray Index (IGR) as a shale indicator in all types of shales; however, the relationship between IGR and Vsh becomes non-linear for both structural clays and dispersed clays. There is a wide variety of non-linear relationships between GI R and Vsh, but none of these is universally accepted. A summary of these non-linear relationships is illustrated below.

The choice of which equation to use depends mainly upon local knowledge. Generally speaking, if the bulk density (? b) of the clean formation did not change as clay minerals were added, then the linear equation will work. If the addition of clay minerals resulted in an increase in bulk density, then the Clavier equation should be considered. For great increases in bulk density, the Steiber equation should be used. Notice from the previous paragraph that choosing between the Clavier and Steiber equations requires that bulk density of the clay-bearing formation be referenced back to the bulk density of that formation if it is considered to be clay-free. This is the same type of approach used in determining Gamma Ray Index (IGR) itself, but can be a very difficult and confusing task. Therefore, it is more common for analysts to calculate Vsh using the Western Atlas equations illustrated below. Typically, Tertiary sands such as those encountered along the Gulf Coast are unconsolidated. Formations of other ages may be considered consolidated.

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Vsh from Spontaneous Potential In water-bearing sandstones of low to medium resistivity, Vsh may be calculated from the SP response by using the equation below. Though this equation works best for laminated shales, it is commonly employed where reservoirs contain structural or dispersed clays as well. Pseudo-SP (PSP) represents the amount of SP deflection in the zone of interest, whereas Static-SP (SSP) represents the maximum SP deflection in a clean formation.

When using the SP response to determine Vsh, the limitations of the SP measurement should be kept in mind. Shaly sands may exhibit extremely suppressed SP responses where there is very little difference between the SP response in the shaly sand and the shale baseline. In this situation, the volume of shale (V sh) determined from the SP method may very easily be overestimated.

Vsh from Neutron-Density Logs Another common method of estimating Vsh in a potentially clay-bearing formation is to use a combination of porosity measurements from neutron and density logs as follows:

Recall that neutron and density responses are both influenced by the presence of clays. When used in estimating Vsh, neutron and density responses tend toexaggerate the influence of kaolinite and chlorite. Kaolinite and chlorite have high neutron porosities in comparison to montmorillonite and illite (Figure 6.1). When gas is present in a formation, Vsh should not be determined from the neutrondensity method. Gas will not equally affect the neutron and density responses. HLS Asia Limited

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Comparison of V sh Results Just like formation water resistivity (Rw), volume of shale (V sh) should be determined from as many methods as possible, and the lowest resulting value should be used in subsequent equations for determining effective porosity. Realize that in using these equations each may yield significantly different values of Vsh depending upon how the particular tool response is affected by the presence of clay minerals. In majority of cases, it has been found that the gamma ray method of determine Vsh provides useable results.

Determining Effective Porosity (Φe) The second step of shaly sand analysis is to determine the effective porosity of the formation. This is analogous to correcting porosity measurements for the presence of clay minerals, or determining porosity of the formation if it did not contain clay minerals. Because clay minerals within a formation represent a volumetric fraction of that reservoir, the calculated estimation of Vsh will be used to "correct" the measured porosity. The three most common methods of correcting porosity measurements for the presence of clay are outlined as follows:

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Notice that each of the above equations (sonic, density, and neutron-density) simply subtracts the amount of clay porosity from the amount of total porosity measured by the log to result in a value of effective porosity (Φ e). Effective porosity is that porosity available to free fluids in the reservoir. Also, note that each equation relies heavily upon the assumption that the clay minerals in the formation of interest are identical in character to the clay minerals in adjacent shales.

Determining Effective Water Saturation (Swe) There are many different equations by which effective water saturation (S we ) of a claybearing formation may be calculated. Effective water saturation simply refers to the percentage of effective porosity occupied by water, whereas total water saturation (S wt) refers to the percentage of total porosity occupied by water. Again, these methods of determining effective water saturation (S we ) in a shaly sand should only be used if it has been determined that Vsh is greater than 15%. To apply these techniques in a clean formation is to risk lowering the calculated water saturation of a zone to the point that a water-bearing zone may appear to be productive. The choice of which method of shaly sand analysis to apply will rely upon the following: §

local knowledge

§

the availability of certain logging suites

§

whether or not the distribution of clays (i.e., laminated, structural, dispersed) is known

The equations involved with each of the different methods of shaly sand analysis were developed around the logging tools that were available at a particular time. Early methods of shaly sand analysis used only input from gamma ray, SP, and resistivity logs. Just as there has been a transition toward more sophisticated logging tools, so too has there been a transition toward more complex equations. In some cases, the amount of calculations required necessitates computers in order to speed the process.

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Basic Log Interpretation With the growing popularity of Nuclear Magnetic Resonance (NMR) logging, there has been a renewed interest in shaly sand analysis. Now there is a new and accurate method of determining the effective porosity (Φ e) of a reservoir. Therefore, in many instances, the process of determining effective porosity by considering Vsh has been replaced by an actual log measurement. Because of the growing popularity of these tools, shaly sand analysis will continue to be an area of interest for years to come. Figure 7.1 illustrates some shaly sand methods developed for certain logging suites, and the decades during which these methods were popular. Each method has its advantages and disadvantages, and most of them are still in use today. Only the most commonly used methods will be considered for discussion here.

Simandoux Method One of the most commonly used shaly sand water saturation techniques during the 1970s was the Simandoux Method, and it remains popular even today with service companies. The Simandoux equation uses input from a typical open hole logging suite: resistivity, and neutron-density porosity.

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Effective porosity (Φ e) used in the Simandoux equation is calculated using the Combination Neutron-Density porosity correction equations. The most apparent limitation in using the Simandoux equation lies in the fact that it depends upon the resistivity of an adjacent shale (Rsh). This implies that the petrophysical properties of the clay minerals within the formation of interest are identical to those of adjacent shales. While this may be true in case of laminated shales and structural clays, but is not the case with authigenic dispersed clays.

Fertl Method The Fertl Method of calculating effective water saturation in shaly sands also relies only upon resistivity and neutron-density porosity data.

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The Fertl Method has two advantages over the Simandoux Method when calculating effective water saturation (S we ). First of all, the Fertl equation is simpler and easier to calculate than the Simandoux equation. Furthermore, the Fertl equation does not require a value for resistivity of an adjacent shale (Rsh). In most instances, the resistivity of an adjacent shale (Rsh) is usually higher than the resistivity of a shaly sandstone (Rt). Although the reliance upon adjacent shales has been reduced in using the Fertl equation, it is still not eliminated because porosity correction algorithms require measurements taken from adjacent shales.

Dispersed Clay Method The Dispersed Clay Method of calculating effective water saturation (S we ) was developed during the 1960s with the advent of density logs, but it remains today a commonly used technique. Sonic logs "see" dispersed clays within pore fluids as a slurry, and present porosity as a sum of the volumetric fraction (total porosity, ∆t). Density logs, on the other hand, "see" only water-filled porosity. The fraction, therefore, of the clean-sand intergranular pore space that is occupied by clay is defined as the shaliness factor “q”.

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Basic Log Interpretation Notice that the Dispersed Clay Method does not require a value for resistivity of an adjacent shale (Rsh) or volume of shale (V sh) within the formation of interest. This is because the shaliness factor (q) is determined within the shaly sand itself (based on the different responses of the sonic and density tools), thereby reducing the reliance of the equation upon adjacent shales. The reduced dependency on the petrophysical parameters of adjacent shales makes this method convenient for determining effective water saturation (S we ) in reservoirs that contain dispersed clays.

Dual Water Method During the 1980s a transformation occurred in the field of shaly sand analysis in which analysts attempted to use cation exchange capacity (CEC) rather than volume of shale (V sh) in determining effect water saturation (S we ). CEC is a much better measure of clay minerals' compared to Vsh; however, CEC necessitates availability of core data and laboratory facilities for its measurement.. The commonly used Waxman-Smits model was developed so that CEC could be implemented in Swe calculations rather than Vsh, but was difficult to use without laboratory data. As an answer to Waxman-Smit, the Dual Water Method was introduced as an effective water saturation (S we ) calculation method based on CEC. The Dual Water Method assumes that pore water is partitioned into both bound water and free water. Both volumetric fractions of pore water will have their own discrete values of water saturation (S b, water saturation of bound water; and, Swf, water saturation of free water). Both of these volumetric fractions of pore water will contribute to the measured resistivity (or conductivity) of the shaly sand; and therefore, both components are said to have their own discrete formation water resistivities (Rb and Rw, respectively). A graphical representation of this partitioning of water components is illustrated in Figure 7.2. The bound water of resistivity Rb and saturation Sb is closely associated with the clay minerals that, in this case, lie in pore cavities. This water is considered to be immovable because of the high surface tensions and capillary pressures associated with the very fine grained clay minerals. The remainder of the water filling the formation is free to move. This free water of resistivity Rw occupies effective porosity (Φ e) of the reservoir and therefore has its own characteristic water saturation (S wt). One advantage of using this method in conjunction with the MRIL is that now there is a method of determining effective porosity (Φ e) rather than obtaining this value by correcting conventional neutron-density and sonic measurements.

Figure 7.2 Partitioning of fluids in Dual Water Method (after Asquith, 1982).

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The Dual Water Method is a very time consuming technique of calculating effective water saturation (S we ), but it may be desirable in certain situations. Notice that many of the steps involved are not necessary if MRIL data are available. Therefore, the Dual Water Method is a desirable choice where MRIL logs are run. In these instances, the Dual Water Method might also be applied to clean sand where water is bound by capillary pressure rather than the presence of clay minerals.

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Selecting the Appropriate Method The choice of which method or equation to use for calculating effective water saturation (S we ) in a shaly sand can be quite confusing. In some cases, more than one method may be recommended. In other situations, there may not be a single method that applies to the particular circumstances. More often than not, the choice of method will be determined by historically accepted method in the region. In ambiguous situations a judicial choice must be exercised that resembles testing data. Because so many assumptions are involved in shaly sand analysis, there is no substitute for experience. The following are some guidelines to follow when deciding which method to utilize. Realize that it may be favorable to use more than one method, and then compare the results with actual testing data. Simandoux Method §

When clays are laminated.

§

When clays are dispersed, and resistivity of this dispersed clay is known to be approximately equal to the resistivity of an adjacent shale (Rsh).

§

When resistivity of the dispersed clay in the reservoir is known by

§

laboratory measurement, or it is assumed that the resistivity of the dispersed clay is equal to 0.4 times the resistivity of an adjacent shale (Rclay = 0.4 X Rsh).

Fertl Method § §

When clays are dispersed or their mode of occurrence is unknown. When Rw > 0.1 Ω-m. In this case, the method must be used with caution. The equation assumes that Rsh >> Rw, but this may not be the case in shaly sands with high Rw values.

Dispersed Clay Method §

When clays are dispersed or their mode of occurrence is unknown.

Dual Water Method §

When clays are laminated.

§

When clays are dispersed, and resistivity of this dispersed clay is known to be approximately equal to the resistivity of an adjacent shale (Rsh).

§

When resistivity of the dispersed clay in the reservoir is known by laboratory measurement, or it is assumed that the resistivity of the dispersed clay is equal to 0.4 times the resistivity of an adjacent shale (Rclay = 0.4 X Rsh).

§

When laboratory data on cation exchange capacity of the clays are available.

When dispersed clays are suspected in a reservoir or the distribution of the clays is unknown, then it is desirable to use either the Dispersed Clay Method or Fertl Method for calculating effective water saturation (S we ). HLS Asia Limited

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References Asquith, G. B., 1982, Basic well log analysis for geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p. Asquith, G. B., 1985, Log evaluation of shaly sandstones: a practical guide: American Association of Petroleum Geologists Continuing Education Course Note Series No. 31, Tulsa, OK, 59 p. Bateman, R. M., 1985, Open-hole log analysis and formation evaluation: IHRDC Publishers, Boston, MA, 647 p. Clavier, C., G. Coates, and J. Dumanoir, 1977, Theoretical and experimental bases for the Dual-Water Model for interpretation of shaly sands: Society of Petroleum Engineers Journal, v. 24, no. 2, p. 153-168, SPE-6859. Dewan, J. T., 1983, Essentials of modern open-hole log interpretation: PennWell Publishing, Tulsa, OK, 361 p. Waxman, M. H., and L. J. M. Smits, 1968, Electrical conductivities in oil-bearing shaly sands: Society of Petroleum Engineers Journal, v. 8, no. 2, p. 107-122, SPE-1863-A.

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BASIC LOG INTERPRETATION_HLS

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