COPPE/UFR J
Completion Course Work Digital Management of Oil Fields
Executive Post Graduate in Oil & Gas March 13, 2007 / February 28, 2008 18ª Class Coordinator: Suzana Kahn Ribeiro
Flávio Ferreira da Fonte
Summary of work submitted to the COPPE / UFRJ as part of the requirements for obtaining the Diploma of Specialization in Executive Post Graduate in Oil and Natural Gas.
DIGITAL MANAGEMENT OF OIL FIELDS
Flávio Ferreira da Fonte February/2008 Advisor: Prof. Gilberto Ellwanger
This study aims to examine the emerging technologies being employed in the Digital Management of Oil Fields, which aim to maximize production, increase the rate of recovery of oil and optimize optim ize the costs of exploration and production.
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Curriculum Summary The author, Flavio Ferreira da Fonte, has been working at Oracle since 2004 as a Senior Sales Consultant and expert in technology solutions from Oracle to customers such as Petrobras, PDVSA and PEMEX. In June 2007 attended the Oil & Gas Oracle Global Industry Business Unit training. He also participed in the development of a Business Intelligence Dashboards for the Upstream area. He worked in Petrobras, at the Information Technology area, from 2000 to 2004 and worked in specific systems for the Downstream area, participated in the implementation and deployment of the Petrobras e-Marketplace, called Petronect and participated in the ISO-9001 certification process at Petrobras IT. Graduated in Technologist in Data Processing, the author also completed the courses of specialization of Systems Analysis and Post-Graduate at IAG Master, both from Catholic University from Rio R io de Janeiro (PUC-RIO). The autor is doing an MBA at IBMEC Business School at Rio de Janeiro.
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Acknowledgements I thank to my family and co-workers from Oracle, Andres Prieto, David Shimbo, Miguel Cruz, Eduardo Lopez, Elizabeth Faria, João Fernandez and Samy Szpigiel for the support received.
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Index
1. Introduction ..........................................................................................................................6 2. Analysis of k ey technologies used in Digital Oilfields projects .....................................8 2.1.Gathering information in real time ...............................................................................8 2.2.Information Management ...........................................................................................15 2.3. High Performance Computing ..................................................................................17 2.4. Centers of command c ommand and remote monitoring ........................................................18 2.5 Sistems for analysis and simulations of hydrocarbon reservoirs .........................20 2.6. Systems for analysis and decision support ............................................................22 3. Conclusions ........................................................................................................................28 References .............................................................................................................................31
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1. Introduction The world`s geopolitical, the mass dependence of fossil fuels, the question on the duration of world reserves of hydrocarbons, among other factors, have caused an escalation of the price of a barrel of oil. With the price of oil above US$ 60 a barrel, companies began to invest more in research and development of new technologies. As na example we can cite Chevron, which in the past 5 years spent more than $ 5 billion of its budget on technology, geared not only to area of industrial automation, but also to the area of information technology. Despite this development, the oil industry still lives a shortage of infrastructure resources, such as drilling rigs and production platforms, which entails a great demand for resources available on the market, which will now be leased or constructed by values larger than usual, thereby increasing the costs c osts associated with the operations of exploration and production (E & P). With this background established, where it is necessary to find a balance between revenue and costs, the major oil companies began increasingly to innovate and implement projects with intensive use of automation and information technologies in the area of E & P, aiming to mitigate risk, accelerate the production, increasing the rates of recovery of reserves and optimize costs. These projects received the name of "Digital Oilfields" [1]. Ex amples are: Shell, with Smart Fields [2], BP [3] with the t he Fields of Future (which envisages achieving the goal of 1 billion barrels by incremental use of new technologies) and Chevron [4], with the iField. In Brazil, Petrobras is running a programme of E & P similar, called GeDIg [5]. This program provides the integrated management of production processes of E & P, through the use of objective information, automation, modeling and simulation technologies to add value to the assets of E & P.
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In this project are being evaluated technologies in 6 pilots, seeking to establish standards and "benchmarks" which are most suitable and profitable for each field of oil, whether onshore or offshore. The main topics discussed by GeDIg are: the testing of software provided by the companies' service (Halliburton / Landmark, Schlumberger, etc.); map and recommend new procedures and workflows; implement remote centres of operations; assess intelligent completions; automation rate of artificial elevation and databases in real time. The figure below shows the vision of technology of Chevron and Shell for these projects [6], which includes obtaining information in real time, inf ormation management, management, high performance computing, systems for viewing, analysis and simulation of reservoirs, centres of command and remote monitoring, analysis and systems to support the decision. FIGURE 1
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The projects of "Digital Oilfields" are among the major initiatives of oil companies for the coming years and the technologies used are innovative and must be analyzed and studied before being used. In the next topic, this work details the main technologies used in these projects, so that it can be an initial guide for those who wish to study this issue or work on projects related.
2. Analysis of k ey technologies used in Digital Oilfields projects
2.1.Gathering information information in real time tim e Various events generated in the real world, such as to monitor the operation of a turbine, must be caught and mapped in a technology platform that enables the monitoring, analysis and decision-making as soon as possible. Several emerging technologies such as radio frequency identification (RFID), sensors, Wi-Max, satellites are being used to assist in obtaining real time information. For the acquisition of data from oil wells in real time, companies are upgrading their facilities and infrastructure, upgrading valves and installing sensors and fibre optic across platforms and risers. During the drilling of wells, the sensors are used to obtain information about drilling in real time. Through them can be read the pressure near the drill, the density of movement, torque, vibration and so on. Figure 2 shows an equipment capable of obtaining information (logs) while performing drilling (LWD - Log W hile Drilling)
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FIGURE 2
With this information the engineers can carry out drilling more efficiently and less damage to the rock formations. In this case, the challenges for use of sensors, are the high temperatures, pressures encountered, the materials and corrosive fluids that put at risk the reliability and durability of sensors. In the production phase, typically, these sensors monitor the production of oil, gas and water versus cumulative time and volume; difference in pressure on the surface versus the head of the well; efficiency of the flow of artificial rise; etc. The figure below shows two of pressure and temperature sensors specifically designed for the monitoring of the bottom of oil well. This sensor is a version of the PDG conventional optical fiber f iber (Permanent Downhole Gauge).
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FIGURE 3
The technology of the fiber optic sensors has been developing rapidly in recent years. The main reasons for implementation of these sensors in the systems of measurement are inherent characteristics of the optical fibres such as low weight, flexibility, long-distance transmission, low reactivity of the material, electrical insulation and electromagnetic immunity. Besides these, in many cases there is the possibility of multiplexar the signals from several sensors, including various magnitudes along the same fiber sensor. These technological advantages that contribute to the fibre-optic sensors will replace the conventional sensors in various v arious applications. [7] As an example of the use of these sensors in the petroleum industry, we have the Norwegian company StatoilHydro [8] that maintains in its headquarters in Norway, a system called Catamaran TurboWatch, supplied by the company Shipcom Wireless [9], which tracks more than 200 equipment in eight oil platforms in the North Sea. This system makes the collection of information from various machines and feeds other business systems and maintenance of the company. c ompany. Figure 4 shows screens monitoring equipment from Catamaran TurboWatch system. FIGURE 4
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Figure 5 identifies the eight platforms of Statoil using the system Catamaran TurboWatch.
FIGURE 5
The sensors can be installed on the head of the well, on the column of production and in other places and the data collected by them are transferred to supervisory systems specialist called SCADA (Supervisory Control and Data Aquisition). In the SCADA system each sensor is seen as a single "tag", or a unique identifier, under which are allocated and entered the data gathered. In addition to the SCADA system, some companies use other layers of software to maintain a history of these measures obtained. Usually the first interface with the SCADA system is made by a historian. One of the historians systems currently used is called OSI / IP, from OSIsoft company [10].
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However, beyond this historian layer, companies also use a relational database manager system (RDBMS), which store all the information related to fields and wells into relational tables. Currently, Oracle RDBMS (Relational Database Manager System) [11] is the most widely used to store this information critical and fundamental to the oil companies. Figure 6 shows the flow of information between the SCADA systems, OSI / IP and RDBMS.
FIGURE 6
Figure 6 also shows that it is necessary to have a layer of applications that make the interface with the user. In this case, the use of a personalized portal on the Intranet of the company is strongly recommended to meet the need of bringing together all systems and applications that the user need to use at a single point of interaction with an interface to access standard. s tandard.
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This kind of information portal can be developed by the company itself, aiming to meet their specific requirements or can be provided by specialized companies and technologies with itself (Landmark [12], Schlumberger [13], etc.). Figure 7 shows a centre of offshore process control, provided by the company ABB.
FIGURE 7
Each type of well (mature, light oil, heavy oil, deep water, etc.) may have a different automation, which vai from simple monitoring of up to the surface, subsurface control with intelligent completion [14]. Under the project GeDIg of Petrobras, one of the locations that has been chosen to be a pilot was the Carapeba field (which is a mature field composed of 3 wells with dry completion
[14] ), located in the northeastern northeastern part of the Campos Campos Basin, which
received automated and subsurface use of sensors in the wells.
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Figure 8 details the configuration of the Carapeba field.
FIGURE 8
In Carapeba, it was being tracked the rates of productivity, pressure on the basis of the well, total flow versus time, pressure and temperature versus depth, alerts for production below the optimal point, and so on. The wells that make use of these technologies for monitoring, tracking and control are called Smart wells or as the English language "Intelligent Wells." In the Smart wells the use of technology allows: the reduction of assistance and time to repair, the increase in detection pro-active in abnormal conditions, the discovery of root causes of problems, the reduction or elimination of failures, the prioritization and optimization of activities, optimization of the use of resources as crews and equipment, the acceleration of production by the access of more areas at the same time and mitigating risks.
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. 2.2.Information Management Depending on the technology used in wells, the quantity of sensors in operation and the ranges of measurements, can be generated more than 10 GB (gigabyte) of data per day in a single field of offshore oil, which becomes a large concern for CIOs (Chief Information Officer) of oil companies. In this context, the management of the life cycle of information is beginning to have great importance for oil companies. It is necessary to understand which data are active, historical or which shall be filed f iled in the most economical device. There are several s everal types of storage devices, which employ different technologies and thus come to access different speeds. The figure below shows 2 types t ypes of storage equipment, called Storage, the company EMC [15]. FIGURE 9
The means of storage with less time for access to the data have the highest cost, than those who offer a longer time to access the data. With the proper employment of these techniques, you can save space on the means of storage and also save large sums with the use of cheaper storage.
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Another major concern is the availability of such data to users, given the agreed levels of service and levels of security, necessary. To ensure the performance in access to these data, should be carried out regularly, studies of capacity and upgrade technology (hardware and software) of the environment in which they are hosted. Every user to access the data, should pass by a security information flow, in which its digital credential will be verified and authenticated (user identification, password, biometrics, etc.), also occurring at this time the check of what level of access is allowed to information. The figure below illustrates a system of authentication and authorization of Oracle. FIGURE 10
Confidential information should have be limited in terms of access and, if possible, should be kept in encrypted form. Possible access to confidential data or confidential, via the Internet, must be conducted using the VPN (Virtual Private Network) or other secure protocols (i.e. HTTPS).
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Systems auditing and traceability of the use of information must be kept so that in case of attempt to use or undue changes, alerts are rapidly fired to administrators of security of information. On the issue of standardization of data, some initiatives are being developed by manufacturers and organizations, to create models of common data for the industry, such as WITSML (which is a standard aimed at data from drilling), the PRODML (which is a standard for data production), MIMOSA (which is dedicated to monitoring) and a new standard called PPDM. It is also necessary that companies have solutions for disaster recovery, ensuring the least possible time of interruption in case of a disaster in the main site. Today, Oracle provides provides solutions for data management, management, information security and disaster recovery for various oil & gas companies.
2.3. High Performance Computing
The amount of data generated on the Digital Oilfields projects, plus the need of various teams of geophysicists and engineers, to access this huge amount of information in real time, have forced oil companies to use high-performance servers for data processing, with the capacity and scalability capable of monitoring the growth of the applications of E&P. The systems needed to meet this demand, were called to systems of high performance computing. The term High Performance Computing refers to the use in parallel, clusters of computers linked to multiple processors on a single s ingle grid. A high level of technical knowledge is required to assemble and use these s ystems, but they can be created from f rom existing components in the market.
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Because of its flexibility, high processing capacity, and relatively low cost, the HPC systems are increasingly dominating the world of supercomputing s upercomputing.. The use of high performance computing has proven very efficient for the applications of E & P, mainly to the areas of visualization and simulation of reservoirs and also applications aimed at geology and geophysics. Landmark, SGI [16], Oracle and Sun [17] have adopted and the widespread use of high performance computing. c omputing.
2.4. Centers of command and remote monitoring
The oil industry has undergone great changes in recent years. Today is also growing worldwide, but still lacks human resources to meet the needs of these companies. Companies usually have their oil production areas in inhospitable regions, such as the seas, in deserts, or in places of difficult access where not many qualified people want work. There are a lot of situations where knowledge of specialists are needed. In that case when there is the necessity to move the specialized s pecialized resource to the location of the problem, sometimes this lag would affect the employment and efficiency of certain solutions. The oil companies are investing heavily in command centres and remote monitoring, so that the specialists, engineers, geoscientists and several other teams, do not need to travel to the area of production. The various teams with different expertise, interact in a command centre for remote, causing a much greater exchange of experience with solving problems in a time shorter. As an example of successful use of such technology we can cite Statoil. At Kristin platform, located at 240 km from the coast of Norway, Statoil saved in the first year of
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use of such technology USD $ 36.5 million in costs of operations, minimizing the number of employees on the platform, number of shifts, maximizing the security, obtaining solutions faster and increasing the quality of life of its employees. [18] Figure 11 shows the Center for operations managers of the Kristin platform, which is connected, continuously, with the command c ommand center of onshore.
FIGURE 11
In Brazil, Petrobras already makes use of this technology in its project of Digital Oilfields, called GeDIg, which has already implemented two Command Centers. In these centres, multidisciplinary teams working on a collaborative way are monitoring the production, detecting problems and propose solutions and acting in decision making processes that were previously drawn. The teams of these centres interact with the teams that are on platforms in real time.
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Figure 12 shows one of the centers of remote control of Petrobras. P etrobras.
FIGURE 12
The oil companies began to adopt the name of Integrated Operations for this new concept, where different departments offshore and onshore work in an integrated manner, increasing productivity and efficiency. 2.5 Sistems for analysis and simulations of hydrocarbon reservoirs One area of industry of E & P, which is the most advanced is the modeling and simulation of reservoirs. Great improvements have been incorporated into existing software, so that the structural models of reservoirs can be constructed, ensuring the highest possible accuracy.
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The structural model of a reservoir is very important because they are made of reserve estimates, predictions of production and development plans of fields. Until very recently ago, in the North Sea region, due to low accuracy of existing models, service companies were required to perform more holes than necessary and constantly revise their forecasts, causing delays and extra costs for putting into production of oil fields. The structural model, which is built initially from the seismic data is refined to build a geological model, which are inserted faults and existing structures, representing the reservoir in a 3D vision. Because of its extreme importance, these models should always be updated with data from the field, allowing the use of simulations to understand the behaviour of the reservoir under the influence of various factors. Most projects of Digital Oilfields makes intensive use of software for visualization and simulation of reservoirs, obtaining data from wells and fields, in the shortest period of time possible, so that these systems can be seen as management systems in reservoirs real time. Available data are loaded continuously in simulators, allowing achieve a better computer model of tanks and conducting forecasts closer to reality. From the existing models, different scenarios can be assembled to assess measures and their possible results. Moreover, from historical data, can be found and analyzed the patterns hold predictions such as entry into the pit of sand. The figure 13 exemplifies a screen of a simulator for tanks of the company Roxar [19].
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FIGURE 13
2.6. Systems for analysis and decision support The industry exploration and production of oil is creating a series of new concepts. One of the concepts in use today is about the existence of a "Fast-Loop" and a "SlowLoop" of information processing, depending on the needs of the business and operations. Exemplificando this concept, we can classify the information operations of oil wells (flow, pressure, temperature, etc.) as belonging to "Fast Loop". These types of information must be displayed and analyzed as soon as possible. We have information from "Slow Loop" may be available in a longer term, for example, details of monthly costs of projects made of E & P. The availability and use of real time information on the behaviour of oil wells, interventions, detailing losses in each well, costs of materials and labour-by suppliers for each intervention, have become essential to the operations of E & P and are the basis for decisions.
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The volume of this information is increasing and we can say that belong to the rapid cycle. The task of analyzing these data, without specialized software can tak e a very large and valuable time for engineers in the field. To provide the right information to the right people in time, the oil companies are investing heavily in projects to use the software for Business Intelligence, either for the information of the Fast Loop or f or the information about Slow Loop. According to Wikipedia [20], Business Intelligence is a business term, which refers to applications and technologies that are used to obtain, provide access and analyse data and information in accordance with the operations of c ompanies. The Business Intelligence can help companies to have a better understanding of the factors affecting its business and assist in decision-making, and is currently one of the main needs of companies of E & P. A solution of Business Intelligence is composed of a data warehouse ("Datawarehouse", "DataMarts") and tools to analyse and show their results to users through analytical reports. There are several tools on the market for construction of these reports, which vary according to the needs of users. These reports can be displayed on web portals, into which are also placed important indicators (production of oil and gas, alarms of production below the optimal point, etc.). The data for the assembly of these reports may have various origins, such as specialized systems of Landmark or Schlumberger, databases of oil companies, ERP (Oracle E-Business Suite, JD Edwards, etc.). The companies British Petroleum and OXY, have already started projects in Business Intelligence, called for the rapid cycle of information.
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BP, for the operations in the Gulf of Mexico, is reviewing the use of a solution of the intelligence business that integrates information from its various systems and publish web various reports that help in increasing productivity and reducing costs in a way general. This type of system can be configured so that different people can have different visions of operational and corporate data, according to the need of work. Each employee using the system is part of a group or profile available with the transactions needed to their daily work. The figure 14 shows a web panel, customized to the user, used to monitor the production of oil, gas and water. The user interacts with the plot and may have deeper insight, according to their need. In this example the production is declining, and if the user wishes can have a more detailed (Figure 15), just click on the line l ine graph. The dashboard from figures 14 and 15 was built using the software Oracle Business Intelligence Enterprise Edition.
FIGURE 14
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FIGURE 15
The tools of Business Intelligence can also provide a series of graphs (Figure 16), which combined to textual information and links, help in understanding the information.
FIGURE 16
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Another important feature of such tools is the integration with the Microsoft Office package. The reports and graphics built in Business Intelligence tool can be opened and used in Excel and Powerpoint P owerpoint (Figure 17).
FIGURE 17
With these new tools of Business Intelligence, the engineers can analyze the performance of active, identify which wells are not producing according to plan, analyze costs and access real-time key indicators for business These key indicators include revenue and profit per barrel, lifting costs, etc. etc . From a visual way but in a more timely than through numerical analysis of various reports, these maps of performance can help to increase understanding of a particular operational situation. These panels allow operators to make decisions better and faster, encouraging further operations safer. Information originating from different geographical locations and departments of the company, which previously took weeks to be grouped, are now rapidly analyzed from a single control panel. The applications of Business Intelligence continues to evolve and are integrating the systems GIS (Geographical Information Systems) of companies, making the connection between data and its specific location on a map. 26
With this type of integration, can be built applications for tracking of hurricanes, safety of personnel, monitoring of production and so on. (s ee Figure 18)
FIGURE 18
Regarding the information belonging to the long cycle, highlighted those related to budget and tracking spending, revenue versus expenditure, financial reports for government agencies and SEC, and so on. For these types of information, there are specialized software for Business Intelligence, which facilitate the tasks performed by users, increase productivity and derive detailed information management to improve decision-making. Usually these systems are integrated with the previously used in the rapid cycle of information. Another area in need of exploration and production is the completion of detailed analysis on existing data to f ind patterns and predict situations. With this purpose companies are applying the technique known as Data Mining, or the English language "Data Mining”.
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This technique has been used to identify areas to be drilled, optimize results of hydraulic fractures in wells, select candidates for hydraulic fracture versus chemical treatment anticipate anomalies and so on. There are basically 2 types of "Data Mining", the Descriptive and Predictive. In summary there was a process of exploratory data looking discover patterns and relationships that are repeated in the various characteristics of the data. At Predictive, looking up from a model, anticipate possible facts and characteristics [21]. The tools of "Data Mining" make intensive use of statistical algorithms. Among the existing include the allocation of importance, Classification and Prediction, Regression, Clusters, Rules of Association, extraction of features, Text Mining, BLAST, Trees of Decision Models and SVM.
3. Conclusions The oil industry is going through a phase of unprecedented technological developments with their rapid implementation in the field. The current advances are allowing oil companies to increase the rates of recovery of reserves and accelerate production. The exploitation of oil reserves, taken as a whole, have grown thanks to new technologies and better definition of existing fields. One of the companies that have achieved great success in this field is Saudi Aramco, which has had significant incremental increases in its production. The Saudi Aramco increased its production of 10 million barrels per day in 2004 to 11 million barrels per day in 2008. All new wells of the company are equipped with permanent monitoring, submersible pumps, intelligent completions and connected to a central remote command, in which multidisciplinary teams making decisions.
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Alternative sources with higher costs, such as heavy oil from the Orinoco basin, Canadian Sands Tar, now have economic viability in this time when the price of oil has been breaking records every week. Companies such as Petrobras and Chevron, through the use of technologies cited in this work, already reached the border of ultra-deep waters, below the layer of salt (pre-salt). The big oil companies are focused on programs to reduce costs and increase productivity, in order to achieve its operational and financial objectives. The net profit of Exxon Mobil was USD 40 bi in 2007, the Chevron benefited USD 18 bi and bi ConocoPhilips USD 11 in 2007. [22] Use of the technology by itself does not take any company to better results. It is also necessary investment in human capital intensive. Only with a workforce well trained and motivated can we continue with these exceptional rates. Currently one of the biggest challenges for the oil and gas industry is to attract and to train talents. The oil companies are investing heavily in training programmes, in partnerships with educational institutions and in joint ventures with companies desenvolvedoras of technologies. The exchange of experiences and collaboration on a global scale is causing an increasing number of electronic communities geared to the oil and gas industry, the use of blogs and wikis for dissemination of experience and the use of virtual environments, such as "Second Life", for promotion of companies and new technologies. Within this context the SPE (Society of Petroleum Engineers) [23], the IBP (Brazilian Institute of Oil Gas and Biofuels) [24] and COPPE / UFRJ (Luiz Alberto Coimbra Institute of P ost-Graduate Engineering Engineering and Research) have provided valuable contribution. The oil companies must work skills of its employees, as far as the must merge knowledge of engineering, exploration and production and information technology. 29
According to the Vice President of Chevron, Donald L. Paul, we should have soon a new generation of applications for viewing and seismic modeling of reservoirs, major advances in underwater robotics and as a final frontier for the industry, the exploration and production of offshore oil in the Arc tic [25]. With all these technological advances found in the projects of Digital Oilfield, the amount of information being processed, will have a very high growth, leading to a cycle of improvement of software used in industry, will need access a much larger volume of data, maintaining the performance desired by end users. Data that are critical or very used may be held in memory of servers, thus allowing faster access. Software from the market as the "Oracle Timesten (In-Memory Database)" [26], which carry information from the database to the memory of the s erver will become widely used in industry. In the field of technological research some companies are investing in nanotechnology and biotechnology. In the field of nanotechnology one of the major applications is the creation of nano robots capable of being inserted into a reservoir of oil and collect the necessary information. In the field of biotechnology one of the lines of research is related to the development of bacteria capable of turning the heavy oil into lighter oil still in the reservoir. Another line of research is more advanced that foresees the use of enzymes to increase the potential for recovery of oil. Another important direcionador for the development of new technologies is the environmental issue, which is increasingly in this industry requires that companies make their operations safer, which cause the least possible impact to the environment. I think the industry will continue to meet the growing global needs for energy and need to increasingly seek out new technologies to increase the indices for recovery of existing reserves, explore new alternative sources, optimize the costs of E & P and work in a more secure sec ure manner, seeking annul possible environmental impacts. The Digital Management of Oil Field should be employed on a large scale by most of E & P companies and the technologies used in these projects will be increasingly employed in this industry. 30
References Jacobs – “Digital Oil Field of the Future Lessons from Other Industries” Cambridge Energy Research Inc (CERA) Lima e outros - SPE PAPER 112191 – GEDIG Carapeba – A journey from Integrated Intelligent Field Operation to Asset Value Chain Optmization www.shell.com www.bp.com www.chevron.com www.energyinsight.com www.gaveasensors.com http://www.statoilhydro.com www.shipcomwireless.com www.osisoft.com www.oracle.com www.halliburton/landmark www.schlumberger.com José Eduardo Thomas – Book Fundamentos de Engenharia do Petróleo www.emc.com www.sgi.com www.sun.com Digital Energy Journal (Nov & Dec 2007 issue) Digital Energy Journal (Jun 2006 issue) Wikipedia – www.wikipedia.com – www.wikipedia.com Shahab D Mohaghegh – SPE PAPER 84441 – Essential Components for a Data Mining Tool for the Oil & Gas Industry. O Globo Newspaper – 04 March 2008 www.spe.org www.ibp.org.br
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Jornal of Petroleum Technology - October 2007 – Special Comemorative Issue Oracle TimesTen - http://www.oracle.com/technology/products/timesten/index.html
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