IPTC 11958 Diagnosis of Excessive Water Production in Horizontal Wells Using WOR Plots Majid A. Al Hasani, Petroleum Development Oman, SPE, Saif R. Al Khayari, SPE, and Rashid S. Al Maamari, Majid A. Al Wadhahi, Sultan Qaboos University, SPE
Copyright 2008, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Kuala Lumpur, Malaysia, 3–5 December 2008. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax +1-972-952-9435.
Abstract Many oil fields in Oman are developed with horizontal wells to maximize productivity and develop wider drainage areas for more cost effective recovery. Premature water breakthrough either from water injectors or from water aquifer reduces the wells profitability because of both reduction in net oil rate and additional cost for water handling. To determine the best solution to shut-off, source and nature of the water entries must be well identified. The flow dynamics and fluid entry mechanisms in horizontal wells are complex and identification of water inflow zones is challenging even when using the best production logging technology available today. Traditionally, when the water cut increase becomes abnormally high, production logging tool (PLT) is run to identify water inflow zones. However interpretation of PLT logs in horizontal wells is not an easy task for log analysts because of the complex flow dynamics and logging tool’s limitations in measuring downhole fluid velocities and fluid holdups coverage across the borehole. This paper discusses the limitations of PLT and focuses on diagnosing excessive water production problems using wateroil-ratio (WOR) plots, which is commonly used for screening and selecting water shut-off candidates. A 3-D simulation model was used to investigate the effect of water arial coning and channeling through fractures on WOR and WOR derivative trends in vertical and horizontal wells. Simulation results are in good agreement with field data, which are also presented in this this paper.
Introduction Excessive water production is one of the major factor contribute in reduction of wells productivity. Increasing water
cut in general impacts both the inflow and outflow curves negatively. Higher water production increases the cost of fluids lifting to surface, water treatment, and disposal. Water production is also related to scale problems at various production system components. Excessive water production can be resulted from either a problem of the well (mechanical failure) or other reasons related to the reservoir like Water channelling from water table to the well through natural fractures or faults, water breakthrough in high permeability permeability zones, or water coning. coning. In general, water production problems related to wells integrity easier to solve and it gets more complicated to control water production if it is related to the reservoir characteristics. Various water control techniques were developed to shut-off or reduce excessive water production. However, the rate of success of water shut-off jobs is still considered to be low. In some publications, that was reasoned as the mechanisms that contribute to excessive water (1) . Water coning, production are not well understood multilayer channeling and near wellbore problems are the main three contributors to excessive water production (2). Obviously, the understanding of excessive water production mechanism and identifying the water entry in the well are the two major factors make the shut-off job successful. The common practice for many operators is using production logging tools (PLT) to define water entries and then select the shut-off technique and design the job. It is very important to notice that the high technology PLT available in the market still have some limitations in horizontal wells due to complex fluid entry mechanisms and flow dynamics of multi-phase flow in the wellbore. To aid understanding excessive water mechanism, several methods and techniques have been developed. Majority of the techniques are specialized plots (3) (4) such as linear water cut vs. time ;, linear WOR plots , semi-log WOR (5), X-plot (6), Wilhite's WOR (7), Novotny's method (8), log-log plots of the WOR (2), Egbe and Dulu method (9), Yortsos et al. method (10) .
Use and limitation of Production Logging Tool (PLT) PLT is one of the most common practices to identify the source of excessive water production. The most advanced PLTs have very complex tools that measure instantaneous fluid hold up, fluid density, flow velocity and temperature in highly deviated and horizontal wells (11 - 13).
2
IPTC 11958
There are some factors influence the conclusiveness of PLT results such as: 1.
2.
3.
4.
5.
Well completi completion on and integrit integrity y problem problems: s: In slight slightly ly inclined wells, fluid segregations are dependent on well deviation angle. For pipe deviations between 80 and 90 degrees from the vertical, the hold-up can vary up to more than 60% and the slip velocity between oil and water can reverse reverse its sign (14). Well accessibi accessibility lity and PLT PLT convey conveyance ance (coil (coil tubing tubing vs. wireline): The presence of the PLT tool with coiled tubing in the well bore can influence the flow rate and pressure measurements. In low-conductivity horizontal wells, the PLT may not indicate the low permeability permeability zones along the the well (15). Fluid Fluid segregat segregation ion and and flow flow dynam dynamics ics in in horizont horizontal al wells: In the case of having gas in addition to oil and water, (Figure 1), fluid segregation and turbulent flow can make interpretation of the PLT data very difficult. For horizontal wells, when the deviation is below 90 degree, the gas usually flows as slugs. When the deviation is above 90 degree, the flow is stratified. For vertical and deviated wells, the flow can be bubbly, plug or slug (16). The gas bubbles or plugs are confined to the high side of the wellbore (annular flow) for relatively small gas entries. The same is true for gas wells, with a small liquid entry (17) . The PLT tools are centred in the wellbore and can easily miss such flow since the tips of probes (where measurements are taken) cannot make physical contacts with such film flow. Also, Horizonta Horizontall well well with with high-con high-conduct ductivit ivity y features: features: The interest in the wellbore flow-rate profile disappears if it is known that the horizontal well displays highconductivity features. In such case, the only visible use of the PLT is to determine the low-productivity zones along the well, which in some cases is affected by the tool presence in the wellbore (18). Data interpret interpretatio ation n related related issues: issues: The compli complicity city of of the interpretation of the PLT data will possibly lead to wrong conclusions.
Still there are many other factors that can affect the accuracy of the PLT, including borehole environment, severe corrosion, scale, mechanical obstructions, formation rock types and presence of shale and washouts in in case of open hole hole (19).
Study Objectives The water-oil ratio plots (WOR and WOR') are popular in diagnosis of excessive water production mechanism. These (2) plots were proposed by Chan in 1995 based on a single vertical well simulation model. In this study we have investigated the applicability of these plots for horizontal wells. A 3-D simulation model was developed to study different excessive water production scenarios and establish WOR and WOR’ diagnostic plots. These plots were applied to diagnose water conformance problems in well from an Omani field. The model properties are attached as appendix (I)
Methodology The numerical model is a two-phase (oil and water) singlewell model and has a producer located at the centre of the model. The water-aquifer is represented by one large cell at the bottom of the oil grid cells. To simulate coning in vertical wells, two scenarios are modelled. One model has a single well that is completed across all reservoir layers and has a strong water support from an active bottom aquifer. The second scenario is similar to the first one except that there is no bottom aquifer support. This model represents the ideal case for channeling/fractures behaviours. In both models, immobile immobile initial water saturation was used. In the numerical models, a channel is represented by a streak of thin reservoir layer (layer two (Z =2)) that has a very high permeable (80000 mD mD in X direction). The The permeabilities permeabilities in Y and Z directions are 800 mD and 400 mD, respectively. The channel layer is 300m × 300m × 1m in the X-Y plane. The aquifer flux through this channel was set constant at 30 SM3/day, entering from one side towards the vertical producer well. To simulate coning in horizontal wells, a two dimensional model with smaller cell size was used. Weak bottom aquifer support is used in the model. Similar well control and internal diameter to vertical well model are used. The fracture in the horizontal well is modelled from edge at layer three (Z =3), X = 30 and between Y = 1 and Y= 60, with permeability permeability in X and Y directions equals to 80000 mD and in the Z direction equals to 40000 mD. The fracture zone is 5m × 300m × 1m in the X-Y plane. The water flux is only in the fracture zone in Y direction towards the centre of the wellbore and has a constant rate of 5 SM3/day. The well is completed in layer three (Z = 3).
Results and discussion Vertical well coning with strong bottom aquifer support The WOR (shown in upper side of Figure 2) increases with time as a result of continuous high pressure support from the bottom aquifer. All the water produced by the well is replaced immediately by the recharge from the aquifer. As a result, the WOR trend does not reach a plateau and the WOR derivative (WOR’) decreases linearly. This behavior is expected as a result of the high bottom aquifer support. Vertical well coning with no bottom aquifer support The WOR, shown in upper side of Figure 2, increases at the beginning as the case with high pressure bottom aquifer support scenario. After some time; here at t 60 days; the WOR trend reaches a plateau. This time depends on the drive energy provided by oil expansion and the drawdown of the well. For high oil expansion and low low well drawdown, drawdown, this time increases. The WOR derivative decreases until it curves down when the system starts to loss its drive energy. This behavior is expected expected as a result of no bottom aquifer support.
3
IPTC 11958
WOR and WOR' results obtained earlier, are verified against published work (2) for coning in vertical well. As can be seen in bottom of Figure 2, there is a good match between our results with no aquifer support and published work (2). Although, in previous work (2), the model properties were not sated, it was possible to get the same trends using our simple model. It is correct to say that the aquifer support that was used in previous work is very weak. The difference in the magnitude of the WOR and WOR’ between our model results and previous model is due to the difference in the properties between the two two models. Vertical well channeling/fracture Upper part of Figure 3 is for the period of water breakthrough and after. Both WOR and WOR' increase gradually. This is caused by the first layer breakthrough. At about 381 days (about 100 days in upper part of Figure 3), a second trend is observed. This is caused by the second layer breakthrough. As more layers breakthrough, WOR' becomes steeper. At some time later, the WOR' starts to decline as sign of coning. That is expected as most layers are depleted and they act as an edge aquifer.
As shown in Figure 3, the channel behaviour in our model (2) is similar to previous published work , bottom part of Figure 3. It appears that the previous model has movable water at initial conditions (constant WOR 0.1). When the first channel breakthrough occurs, the WOR increases gradually and also the derivative. Another trend is observed at t = 100 days when the second channel breakthrough. This time the WOR is less steep. The same behaviour is observed in our model. Initially, the model has no movable water. The water breakthrough started later at about t = 286 days and as the second layer breaks through, another trend is observed. In our model, only one permeable layer is simulated, all other layers have the same rock properties. Whereas in previous work (2), layers of different permeabilities permeabilities were modelled. Our model is closer to fracture behaviour than multi channeling as the case with previous model. Nevertheless, our model showed that one permeable layer can cause the adjacent layers to behave as if they have higher permeability than the other layers. To verify the findings with examples from the field, three vertical wells were studied. It was found from the field static model that these wells crossed faults or fractures that contributed to the excessive water production or completed across layers of high permeability contrast. All these wells are mechanically lifted with beam pump. The beam pump parameters were checked to make sure that the pump is operating in all times and its speed does not vary in a way that affects the production data collected at surface. Also, production data were cleaned from anomalies. anomalies. These wells wells did not have work-over history like change of completion, re perforation, wire wrap screen back-flush, or any job that can alter the production behaviour. The WOR and WOR' of these wells compared to our model are shown in Figure 4. Horizontal well coning When water has just reached the well’s perforations, the WOR' is decreased as more water is produced. Water breaks
into the adjacent perforations and WOR' shows small peak. However, the general trend continues decreasing in the WOR'. At some other time, the cone stretches and the WOR' shows smooth transition period until a peak is reached at which WOR' decreases slowly where the next perforation watered out. Finally, when water has reached all the perforations, the cone will stretch horizontally. The cone is now acting as a water channel until WOR' reached a maximum at about t = 550 days (313 days in upper left side of Figure 5). However, since the reservoir pressure decreases, the WOR' decreases afterward. Overall trends show a general decrease in the WOR'. The same approach as in vertical wells verification was followed to check our results. The horizontal wells in the field of our interest were carefully chosen based on available history data. All horizontal wells presented here are having no major work-over activities. All bad data due to wrong production test or deferred oil activities are cleaned. The field model was checked to know if there are fractures crossing these wells. Any other data like time-lapse logs are also used to derive the right conclusion. In addition, the pump parameters were checked to make sure that the well is on 24 hour timer and the pump speed does not vary. Three horizontal wells are verified for their trends against our model findings for coning in horizontal wells. These wells are chosen carefully where there is no fracture or fault crossing them. They are completed in the same formation unit and did not experience any possible channeling. Figure 5 shows the WOR and WOR' for the three wells compared to results from our model for horizontal coning scenario. All three wells WOR and WOR' show good match compared to our model results. Horizontal well channeling/fracture From the model results, we can see that the water breakthrough in the horizontal well occurs faster than in the vertical well. As more water get produced, the WOR and WOR' continue to rise (upper part of Figure 6). At about 233 days, the WOR' decreases due to depleted zones acting like water cone from the edge.
Figure 6 shows a good match obtained between the model results of WOR and WOR’ and the actual field data.
Conclusions Using simple simulation model of defined static and dynamic properties, it it was possible possible to get similar similar trends of WOR WOR and (2) WOR' to those of published work on single vertical well. Three different scenarios were tested. Two scenarios were for coning and one for channeling/fracture. channeling/fracture. The conning model that has no support from a bottom water aquifer matches very well the published WOR and WOR' (2). The third scenario is about channeling/fracture in single vertical well which also matches well the previous work for single vertical well. Three vertical wells from an Omani oil field were selected after screening to verify their trends against our findings for
4
channeling/fracture in vertical wells. All three wells showed good agreement with our model. Hence, the model was further developed to study coning and channeling/fracture in single horizontal well for the first time. The same approach was used to verify the trends of WOR and WOR' for the different scenarios. Four horizontal wells were chosen after proper screening for verification. The WOR and WOR’ trends for all four wells matched our findings for the single horizontal well simulation model. The good match between the model trends and the actual trends from well history production suggests that these plots can be used to diagnose the excessive water production problems in vertical and horizontal horizontal wells. wells. The WOR and WOR' trends observed are not affected if the well is produced by electric submersible pump (ESP) or beam pump (BP). This is valid when the BP parameters (running time and speed) are almost constant during the life of the well and the ESP has relatively constant intake pressure through the well’s life.
Nomenclature BHP: Bottom Hole Hole Pressure Bo: Oil formation volume factor BP: Beam Pump Bw: Water formation volume factor C r r : Rock compressibility C w: Water compressibility ESP: Electrical Submersible Submersible pump pump K h: Horizontal Pe Permeability K ro Oil re relative pe permeability ro: K rw Water re relative pe permeability rw: K v: Vertical Permeability P c: Capillary pressure PLT: Production Logging Logging Tools PVT: Pressure Volume Temperature WOR: Water Oil Ratio WOR': Derivative of Water Oil Ratio References (1) James Pappas, SPE, Fina Oil & Chemical Co., Prentice Creel, SPE, and Ron Crook, SPE, Halliburton Energy Services, “Problem Identification and Solution Method for Water Flow Problems”, Society of Petroleum Engineers Inc., 1996, SPE 35249 (2) K. S. Chan: "Water Control Diagnostic Plots", presented at the SPE Annual Technical Conferences & Exhibition, Dallas, USA, 22-25 October, 1995, SPE 30775 (3) R-N., Hwan: "Numerical Simulation Study of Water Shutoff Treatment Using Polymers" paper SPE 25854, presented at the 1993 SPE Rocky Mountain Regional/Low-Permeability Reservoirs Symposium, Denver, CO, April 12-14. (4) R. V., Higgins and R. V., Leighton,: "Matching Calculated With Actual Waterflood Performance With Estimation of Some Reservoir Properties", paper SPE 4412, presented at the 1973 SPE Rocky Mountain Regional Meeting, Casper, WY, May 1516. (5) N., Mungan: "A Theoretical and Experimental Coning Study", SPEJ (June 1975) 247-254. (6) I., Ershaghi and D, Abdassah.: "A Prediction Technique for Immiscible Process Using Field Performance Data", JPT (April 1984) 664-670.
IPTC 11958
(7) G. P, Wilhite: Waterflooding, Text Book Series, SPE., Richardson, TX (1986) 3, Chapter 5. (8) R. J., Novotny: “Matrix flow evaluation technique for water control application”, SPE paper 030094 presented at the European Formation Damage Conference held in the Hague, the Netherlands, May, 15-16, 1995. (9) ThankGod Egbe and Dulu Appah; Petroleum and Gas Engineering Department, University of Port Harcourt, "Water Coning Diagnosis using Spectral Analysis", Society of Petroleum Engineers Inc, 2005, SPE 98816 (10) Y. C.,Yortsos, C.,Youngman, Y., Zhengming and P.C, Shah: “Analysis and Interpretation of Water Oil Ratio in Water Floods”, SPE Journal Vol. 4, No. 4, Dec 1999. pp 413 -425 (11) H. Dandarawy, A. AlMutairi, G. Abdouche, and O. Khedr, Zadco, and A. Elkadi, Schlumberger, "A New Production Logging Tool Allows a Superior Mapping of the Fluid Velocities and Holdups Inside the Wellbore", Society of Petroleum Engineers, Inc., 2005, SPE 93556 (12) H. Farran, Schlumberger, J. Harris and S. Al Jabri, Petroleum Development Oman, and R. R. Jackson, S. Al Khayari, and T. Thomas, SPE, Schlumberger, "An Integrated Approach for Evaluating and Characterizing Horizontal Well Inflow and Productivity in Heterogeneous Carbonate Reservoirs", International Petroleum Technology Conference, 2005, IPTC 10492 (13) A. AL-Amer, B. A. AL-Dossary, Y. A. AL-Furaidan, and M. K. Hashem, SPE, Saudi Aramco, "Tractoring – A New Era in Horizontal Logging for Ghawar Field, Saudi Arabia", Society of Petroleum Engineers Inc, 2005, SPE 93260 (14) Krimo Laieb/Sonatrach-PED, and Djebbar Tiab/U. of Oklahoma, “Design and Performance of Miscible Flood Displacement”, Society of Petroleum Engineers, 2001, SPE 70021 (15) R. M. McKinley: "Production Logging", Exxon Production Research Co, 1982, SPE (10035) (16) Justin Rounce, Chris Lenn, Schlumberger Technical Services, Gerard Catala, Schlumberger Riboud Product Center: "Pinpointing Fluid Entries in Producing wells" presented at the 1999 SPE Middle East Oil Show held in Bahrain, 20–23 February 1999, SPE 53249 (17) J,R, Fanchi and R.L. Christiansen, Marathon Oil Co, “Applicability of Fractals to the Description of Viscous Fingering”, Society of Engineers, 1989, SPE 19782 (18) B. E. Theron and T. Unwin, Schlumberger Cambridge Research: "Stratified Flow Model and Interpretation in Horizontal wells", SPE 36560, presented at the 1996 SPE Annual Technical Conference and Exhibition held in Derver, Colorado, U SA, 8-9 October 1996 (19) E. Ozkan, Colorado School of Mines, C. Sarica, SPE, The Pennsylvania State University, M. Haci, Drilling Measurements, Inc. :"Interpretation of Horizontal-Well Production Logs: Influence of Logging Tool", presented at the 1998 SPE International Conference on Horizontal Well Technology held in Calgary, Alberta, Canada, 1-4 November 1998, SPE 50395
5
IPTC 11958
Appendix (I) General Model Properties Tables Well type
Grid
Vertical
X,Y 30, 30
Completion interval Z1, Z2 1, 20
Control method BHP (2.7 barsa)
Appendix (II) Figures
Well diameter 0.1143 m (4 1/2")
Table 1: Well properties for strong bottom aquifer support in vertical well-coning Grid X, Y, Z 60, 60, 41
Area
Length
Porosity
Permeability
20000 m2
2000 m
27 %
200 mD
Table 2: Aquifer properties for strong bottom aquifer support in vertical well-coning
Initial Pressure Horizontal Permeability (Kh) Vertical Permeability (Kv) Porosity Porosity Hydrocarbone Saturation (Sh) Oil density Water density Relative water volume (Bw) Water compressibility (Cw) Water viscosity The rock compressibility (Cr)
102.9 bars (at datum of 730m) 800 mD 400 mD 27 % 64 % 929 kg/m3 1006 kg/m3 1.02 rm3/sm3 4.35e-05 1/bars 0.54 cP 5.8e-05 1/bars
Figure
1: Principle gas-liquid flow regimes (16)
100
10
Table 3: Rock and fluid properties
WOR (Aquifer Support) WOR' (Aquifer Support) WOR (No Aquifer Support) 1 WOR' (No Aquifer Support)
' R R O O W W
Pressure (barsa) 6.40 17.24 34.47 51.70 69.00 86.19 103.90 137.90
Bo (rm3/sm3) 1.012 1.010 1.008 1.006 1.004 1.002 1.000 0.996
Viscosity (cP) 188 213 254 294 335 375 417 496
Table 4: Model PVT data for dead oil
Sw 0.080 0.081 0.083 0.086 0.090 0.100 0.140 0.180 0.220 0.260 (Swc) 0.300 0.340 0.380 0.420 0.460 0.500 0.540 0.580 0.620 0.700
Krw 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.003 0.005 0.010 0.016 0.026 0.039 0.058 0.084 0.117
K ro ro 1.000 0.996 0.989 0.978 0.963 0.928 0.793 0.670 0.559 0.459 0.371 0.293 0.226 0.169 0.121 0.083 0.052 0.030 0.014 0.000
Pc (bars) 0.303 0.289 0.274 0.260 0.245 0.231 0.217 0.202 0.188 0.173 0.159 0.144 0.130 0.116 0.101 0.087 0.072 0.058 0.044 0.000
Table 5: Model relative permeability and capillary data for dead oil
0.1
0.01
0.001 1
10
100
1000
Time (Days)
Coning: Strong bottom aquifer support No pressure support
Coning: Chan’s paper (2) Figure 2: Vertical well: WOR and WOR' coning trends compared to published results
6
IPTC 11958
1
0.1
' R R O O 0.01 W W
0.001
0.0001 1
10
100
1000
Time (Days) W OR
WOR'
WOR and WOR' trend for channeling/fracture channeling/fracture scenario in vertical well
2
Channeling: Chan trend of WOR and WOR' ( ) Figure
3: Vertical well: WOR and WOR' channeling/fracture trends compared to published results
7
IPTC 11958
1
1000
100
10 0.1
1
' R R O O W W
0.1
' R R O O W W
0.01
0.01
0.001
0.001 0.0001
0.00001
0.0001
0.000001 1
10
100
1000
1
10
100
Time (Days)
Time (Days)
WOR
WOR
W O R'
WOR and WOR' trends for channeling/fracture channeling/fracture scenario in vertical well
1000
10000
1000
10000
W O R'
WOR and WOR' for X- 2
1000
100
100
10
10 1
1 0.1
' R R O O W W
' R R O O W W
0.1
0.01 0.01
0.001 0.001
0.0001
0.0001
0.00001
0.00001 1
10
100
1000
10000
1
10
100
Time (Days)
Time (Days)
WOR
WOR
W O R'
WOR and WOR' for X- 1 Figure 4: WOR and WOR' for three vertical wells compared to model’s trends
W O R'
WOR and WOR' for X- 3
8
IPTC 11958
100
100
10
10
1
1
' R R O O W W
' R R O O W W 0.1
0.1
0.01
0.01
0.001
0.001 1
10
100
1000
1
100
Time (Days)
WOR
WOR
W O R'
WOR and WOR' trends for horizontal well coning scenario, the time step is shifted - 237 days days
' R R O O W W
10
Time (Days)
100
10
10
1
1
' R R O O W W
1000
10000
W O R'
0.1
0.01
0.01
0.001
0.001
0.0001
10000
WOR and WOR' for X- 5
100
0.1
1000
0.0001 1
10
100
1000
10000
1
10
100
Time (Days)
Time (Days)
WOR
WOR
W O R'
WOR and WOR' for X- 4 Figure 5: WOR and WOR' for three horizontal wells compared to model’s trends
W O R'
WOR and WOR' for X- 6
9
IPTC 11958
10
1
Fracture 0.1
' R R O O W W 0.01
0.001
Coning 0.0001 1
10
100
1000
Time (Days) W OR OR
W OR OR '
WOR and WOR' trends for horizontal well channeling/fracture channeling/fracture scenario 1000.00
100.00
10.00
1.00
0.10
0.01
0.00 1
10
100 W OR OR
100 0 W OR OR '
WOR and WOR' for X- 3 H 2 Figure 6: WOR and WOR' for X- 3H2 compared to model’s trend
100 00
