8. Surveliance Best Practices

SURVEILLANCE

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BEST PRACTICES

September 17, 1999

BY

M. (Mike) C. ARNONDIN C. (Chlris) V. CHOW A. (Tony) S. NWANKWO R. (Ray) R. OTT N. D. (Dave) BALLARD

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TABLE OF CONTENCE

• Introduction

II.

Management Commitment

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III.

General Discussion

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IV.

Well and Reservoir Surveillance

V.

Surveillance Process Structure

A. B. C. D. E. F.

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .3

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............... ................................. 1 2 ............... .................................13 .......---..... .................................14 ..... .......... ................................ 15 ............... ................................ 16 ............. ... ................................ 16

Process Data Analysis Recommendations Implementation Continuous Improvement

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VI.

Conclusions

VII.

Appendices Best Practices Summary .............................................................. .....18 A. B. Successes 1. SHO-VEL-TUM AREA production vs. surveillance effort ............. .....19 .................................................... ......20 2. Field A: Oil Production .............................. .....21 AERA Energy Six Top Surveillance measures C. D. Process 1. New Orleans (MEPUS) "Field Surveillance Line of Sight" diagrams .., ,...23 ............................................................ ..... 30 2. SIPOCC ...................... .....38 3. Meeting Formats (McElmo Creek, MEPUS) 4. Well Testing Practices (MEPTEC) ........................................... ....39 ........................................................... ....41 5. KPI 6. What Is A Process ............................................................. .....44 ............. .....47 7. Pattern Analysis Process Flow - High Level Summary E. DATA ................................ .....52 1. Steamflood Guidelines (AERA Energy) .......................................... ....60 2. Subsurface Data Requirements F. TOOLS 1. GRACE Tool (Midland, MEPUS) .......................................... ....62 ....................... ....65 2. Chevron Decline Analysis (Midland, MEPUS)

G.

3. WELL NOTES (Midland, MEPUS) .......................................... ....76 Other Reading . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . . . . . . . .. . . . . . . . . . . .... . ..... .. . .88

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^ Although surveillance is often recognized as important, it is subject to several interpretations as to its definition, potential value, usefulness, execution, and impact on maximization of profit. Consequently, its application is often underutilized. The goal of this report is to clarify the surveillance process and document surveillance "best practices" as identified by the team. The report examines Well and Reservoir Surveillance. It also gives insight into the process of surveillance and how to practice high quality surveillance. Also included in the appendices are examples of how various tools and techniques have been used by some affiliates and subsidiaries in their surveillance programs. This report does not cover detailed surveillance analysis practices as this is beyond the initial scope. That would be the next logical step if there were sufficient further interest. The report comes from brainstorming sessions with a wide crosssection of affiliate engineers, visits to several affiliate offices to observe local best practices, competitor analysis and literature reviews. Management must be committed to support structured surveillance processes and to hold itself and staff responsible for success. The surveillance process is best described within the context of the reservoir management process. Figure I shows a high level description of this process from exploration through abandonment, with particular focus on the depletion planning cycle. In this model of the integrated reservoir management framework (IRMF), surveillance is a continual (looped) process for gathering and analyzing data to monitor and optimize system (i.e., reservoir to sales line and beyond) perforrnance subject to constraints established in the depletion plan. The foundation of the surveillance process is captured in the bottom-most loop, where data is acquired, validated, stored, and analyzed, and recommendations on changes are made. Since the analysis occurs at several levels (e.g., individual well, pattern of wells, reservoir, and system) the surveillance process can impact the entire IRMF'throu,gh changes in the reservoir description, infrastructure design, and depletion • plan modifications and implementation. As an asset moves through its lifecycle time line from discovery through abandonment, some data types, types of analyses, and surveillance support infrastructure will change. However when done properly using the appropriate tools and practices and integrated to the reservoir management process, surveillance will always increase corporate profits. The different tasks and analyses over an asset's lifetime have resulted in some confusion in defining surveillance and its focus (e.g., well, reservoir, flood, and pattern surveillance.) Another source of confusion results from the way jobs have been aligned according to traditional, functional tasks (e.g., reservoir, drilling, completion, operations, and facility engineers.) According to the IRMF model, reservoir, well construction, operations, facilities engineers, and geoscientists are all associated with surveillance tasks. However, surveillance is usually associated with the operations engineer, primarily because of their proximity to data collection. Some affiliates have adopted the job title of surveillance engineer, perhaps to create greater emphasis on the entire process, yet it is clear that no single person can accomplish all of the tasks described in the process above. Hence, a "best in class" surveillance program cannot be done without people and requires management commitments to staffing and teamwork. For the remainder of this report, surveillance will be grouped into two focus areas. One being "Well Surveillance" the other being "Reservoir Surveillance". Using "best practices" for a combination of Well and Reservoir surveillance will provide a complete surveillance package from reservoir to wellhead. We recognize that surveillance does not stop here, but has a very important facilities component that goes beyond the scope of this document.

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Figure 1. Integrated Reservoi r Management Framework

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MANAGEMENT COMMITTMENT

Mana g ement always influences the surveillance effort of a company. Maximum positive impact occurs when management has a full understanding of the profit value of surveillance and actively holds itself and the staff accountable for maximizing profit through surveillance. Maximum negative impact from surveillance occurs when management has other priorities. Experience tells us that all surveillance efforts fall somewhere between these two extremes. Surveillance can survive, but not flourish, if individuals are interested and committed to it. Surveillance will most likely die as soon as these individuals relocate if it is not recognized as having merit, being the best way to maximize profit, supported by management and by management holding themselves and the organization accountable for the care and feeding of the surveillance effort. If we do not have a consistent message, followed by rewards and enforcement, the message is lost and the effort is abandoned to do things where the message is consistent and the effort rewarded. This means that if surveillance is deemed to be how business is done, then staff and policy need to be directed to do it. Only then will surveillance flourish. Initially the surveillance process improves production, which increases revenue, and reduces expenses ($/BO). Improvement is usually seen quickly and results are significant. As the process matures, returns diminish and there is the temptation to think that the surveillance effort is no longer beneficial or needed. What is taking place in this situation is that surveillance is maintaining the base just as a good preventative maintenance program maintains runtime and reliability. All too often surveillance becomes a target of expense reduction. History is littered with examples where surveillance is reduced or suspended. In every case after some short period of time production falls precipitously, actual expenses increase and on a $/BO basis expenses skyrocket.

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GENERAL DISUCSSION

• Surveillance when practiced properly reduces expenses and increases production; both of these increase the profit margin. Implementation of surveillance in the Beryl field in the early 1990s increased production by 15%. At SHO-VEL-TUM the field decline was arrested as can be seen in Appendix " B" on page 20. Other operators have also experienced arrested field declines through surveillance as can also be seen in Appendix "B" on page. 21. The following definition of "field surveillance" was developed based on input from across MEPUS by field surveillance personnel. Field surveillance is the frequent and regular monitoring and analyzing of existing reservoirs and wells including all related subsurface and surface production and injection systems, to generate recommendations and implement actions that obtain hydrocarbon production in the most cost effective and efficient manner possible. Hydrocarbon target volumes can be realized and reservoir recovery maximized by rigorously employing field surveillance techniques and striving to daily improve the procedures, processes and performance indicators. Field surveillance, therefore, directly supports the overall reservoir management plan by ensuring all production and injection rate targets are being met. When targets are not met, that deviation, as identified by performing surveillance, triggers a response to either remedy the deviation or better understand the reservoir and related mechanical circumstances responsible for the targets not being met. The end result is that well-managed total reservoir and production systems are continually monitored and analyzed to ensure performance is as planned. The ultimate goal of surveillance is to improve the profit ^ realized by the corporation. Underlying any surveillance effort is data. Data accuracy, collection, storage, quality control, ease of accessibility, and methods of presentation is a complex and difficult task. Involved are end devices (e. g. transducers, meters, etc.), databases, hardware, software, personal and ideological considerations. One size definitely does not fit all, however the concepts are universal. Data must be accurate to have value. It must be collected to have value. It also must be easily retrieved to maximize value. Above all data must be analyzed on a frequent and consistent basis and recommendations implemented to have any chance to maximize value to the corporation. Aera Energy has determined that data should reside in one central database that is accessible to all users. They have selected software that facilitates one time data entry and allows analysis by all, with electronic capture of recommendations and transmission directly to those responsible for implementation. Midland is implementing software to do much the same as Aera Energy. There is a core of "Industry Best Practices" (IBP) for surveillance in any oilfield application. Other complementary "Local Best Practices" (LBP) will be added for applications such as: 1. Primary Oil 2. Enhanced Oil 3. Primary Gas 4. Enhanced Gas Surveillance efforts should be measured to insure that the data is sufficient and of high quality. Metrics should also be used to determine if the analysis is being done and how many recommendations are being generated per time period. Results of recommendations should be measured and fed back to the originators and management to demonstrate the quality of the recommendation and how accurate the targets of the • recommendations were. Appendix "C" page 22 lists Aera Energy's six top surveillance measures. These have been determined to be their most important issues and are used throughout the organization. 6

Appendix "D" can be used as a "how" to aid in setting up a surveillance process. It includes a line of sight diagram used in New Orleans this can be found on page 24. It also includes potential best practices for the • Gulf of Mexico on page 25. Well review process flow diagrams (PFD) are found on pages 26 through 28. Facilities review PFDs can be found on pages 29 and 30. The remainder of Appendix "D" contains customer supplier relationship charts, Key Perforinance Indicators (KPIs) and other helpful guides for setting up a surveillance program or enhancing a current program. Appendix "G" is a listing of industry papers that address surveillance and can be found on page 89.

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WELL AND RESERVOIR SURVEILLANCE . WELL SURVEILLANCE Well surveillance efforts will normally include such activities as decline curve analysis, well failure frequency studies, artificial lift optimization, pressure build up surveys, gradient surveys, production logging, etc. When properly analyzed, the implementation of the results of these activities plays a very fundamental role in realizing increased profit for the organization. Well surveillance needs data to function as designed. In fact the quality of a well surveillance process is a direct function of the data integrity. Apart from data, dedicated personnel and up-to-date tools are a must for successful implementation of well surveillance practices DATA, TOOLS AND PERSONNEL In any well surveillance process, data collection is always a very difficult but critical first stage. Every effort should be made to ensure that data quality is high. Recommendations based on erroneous data ("garbage") will never yield the desired results. Data collection is followed by data analysis, the outcome of which is used to generate appropriate recommendations, which are then presented to Management for implementation. Post mortem review of recommendations and implementation are routinely carried out for continuous improvement. Dedicated personnel are needed for high quality data collection. But data collection is certainly half the story. It is not only important to collect and analyze accurate data: but also important to store and secure the data for centralized online use. This obviously requires the use of a standardized database for fast and optimum data access. There is usually a QA/QC function charged with the certification of data integrity before it enters the central database. The central figure in this QA/QC function is the Operations Engineer who, depending on the data needs, co-ordinates data input from such personnel as reliability Specialists (operator), Electrical Technicians, Production Technicians, Foremen, Engineering Technicians, Drilling & Reservoir Engineers and Production Geologists. Operations Engineer therefore needs to setup an open and frequent communication channel with these personnel in order to establish trust and team spirit which is a must in the well surveillance business.

FOCUS AREAS Well surveillance has to be designed to focus on the maintenance of a well or cluster of wells to maximize deliverabilitti at optimum cost. To this end, the following focus areas are normally expected of an effective surveillance setup: 1.

2.

3. •

Well mechanical equipment-accurate knowledge of casing, perforations, tubing, packers etc., wellhead equipment, and artificial lift equipment are critical for proper understanding of well performance. Completion/reservoir information or data-gravel pack data, skin, PI, PVT, flowing bottom hole pressure (FBHP), etc. both current and historic are required in understanding of current production and potential remedial actions and estimating results (based on economic assumptions). Well performance monitoring-the central part of well surveillance is the day to day analysis of the critical parameters that have been determined to be monitored to meet the production and reservoir management plans. These may include oil and gas rates, water rate, GOR, GLR, flowing pressure gradients, etc.

4. ^ 5.

Nodal analysis models-powerful tools for better understanding of well performance and of optimizing production rates for both flowing and artificial lift operations. If developed correctly and with the understanding of its limits, these tools can be used to optimize not only well production but also the production system from the reservoir to the separator. Measurement Tools-dynamometers, amp charts, pressure/chart recorders, iron counts, corrosion coupons, etc. are examples of field measurement tools. The Operations Engineer should ensure that the measuring devices are calibrated on a regular basis. Accuracy is important in data acquisition or poor decisions will be derived from the analysis. For instance if the sum of the well tests does not equal or come close to the volumes sold or disposed of there is a measurement problem that must be addressed. Data must be collected and measured with enough frequency to yield valid trends. For example, flowing gradient surveys used in conjunction with nodal analysis tools will give warning of tubing flow problems, while static build up surveys can be used to detect onset of reservoir plugging (skin).

DISCUSSION Well surveillance in summary is a detailed day to day analysis of well performance as measured against specific profit and asset management plans. The well surveillance process requires management support, teamwork, performance measures, good data and accountability. The results of a well planned well surveillance program will yield quick response to well performance deviating from plan, lower operating expenses and reduced cycle time from data collection to implementation of recommendations If there is a conflict in data, nodal analysis tools can be used to help trouble shoot the data, resolve the conflict, or provide direction as to what additional or revised data may he required. When initially implementing a surveillance process, more frequent data acquisition will err on the safe side. As the process moves forward data trends will aid in determining just how frequent data needs to be gathered in ^ order to catch problems at the earliest time. The goal in tool selection should be to select the tool(s) and technique(s) that gather appropriate, accurate and reliable data in a safe and cost effective way that will lead to the most profitable solution(s). Risk is an important consideration in this process. What is the risk of personal injury, damaging the well and getting correct data? Often service companies are relied upon to select the tools or services they think will be appropriate. There is risk in allowing a service company to do our job. More often than not our company will pay more to use an inappropriate tool that will collect bad or inappropriate data, which does little or nothing to give insights into how to solve the problem. Another risk is to "shoot from the hip" in selecting data gathering tools or doing some work. Just as justification should be expected for recommendations made by an Operations Engineer the engineer must demand justification for any work that may be proposed by others that does not make sense. Well symptoms must be studied, analyzed and discussed with Operations, Reservoir and others prior to picking up a tool and running it into the well or connecting it to the wellhead. If two tools essentially collect the same data the Operations Engineer should ask which tool works better in that field; in that type of well; with that type of fluid; which is more reliable; what is the cost; what is the availability; are there mobilization costs; etc. It must be remembered that a service company's goal is to make money for their company, not necessarily make the most money for the operator. Best Practices: 1. All flowing, gas lifted and ESP wells have nodal inflow models. 2. Final tool selection should be done by company personnel not a service company. RESERVOIR SURVEILLANCE • Before we begin to talk about reservoir surveillance, an explanation of how it is different from reservoir management seems to be in order. There are many viewpoints as to what reservoir management is within our industry. Within Mobil, reservoir management is defined as, "the marshalling of all appropriate 9

business, technical, and operating resources to exploit a reservoir optimally from discovery to abandonment". Reservoir management can be viewed as the master plan for the asset with reservoir ^ surveillance being the people, process, and tools necessary to implement the plan. The goal of this section is to clearly identify what reservoir surveillance includes and what are the "best practices" that can be used to build a "best in class" reservoir surveillance process. Reservoir surveillance is a team effort and includes at least the following as core members, reservoir engineer, production geologist, operation engineer, production technician and field reliability specialist(operator). There are additional resources that will be called on from time to time and they include drilling, petrophysicists, geophysicists and facilitity engineers. Surveillance can be thought of as the key to optimal reservoir management. The main areas of focus for a reservoir surveillance team will include the following: 1. Reservoir description-accurate knowledge of the reservoir is critical for understanding historical and future performance and for implementation of the reservoir management plan. 2. Hydrocarbon in place-it is essential to know and constantly update the size of the reservoir and the hydrocarbons it contains. 3. Reserve calculations-it is essential to know the recoverable portion of the hydrocarbons in place as determined by historical performance and future predictions(based on economic assumptions). 4. Performance monitoring-the critical part of surveillance is the day to day analysis of the critical parameters that the team has determined has to be monitored to meet the reservoir management plan. 5. Performance prediction-is a powerful tool for developing and managing reservoirs. If developed correctly and with an understanding of its limits, this tool can be used to help surveillance by setting production and injection targets and predicting future performance. •

There are many tools available to the reservoir surveillance team. The use of uniform tools across an affiliate has been identified as a best practice. Some of the tools available to the reservoir surveillance team are listed below: • Reservoir visualization-Landmark, Earthvision, 3-D seismic, 3-D reservoir model(stratamodel), x-sections • Original hydrocarbons in place-volumetrics, MBAL, simulation • Reserve calculations-production curves, MBAL, simulation • Performance monitoring-well reviews, pattern reviews, field reviews, PA, DSS, OFM, Well Notes, Injection Management Tool, Chevron diagnostics spreadsheet • Reservoir simulation-various models available, must choose best to fit a given set of reservoir and fluid conditions

The "best practices" as identified for reservoir surveillance will have some common "best practices" with artificial lift and well performance. These "best practices", along with a brief explanation are listed below. 1.

Common Data Base-essential to maintain accuracy, ease of data retrieval, consistency, economics of data handling

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Uniform Tools Across Affiliate-consistency of data analysis, ease of technology transfer, improved communications, ease of staffing re-assignments, cost control

3. Team Environment with Management Support-the team environment is essential to establish "best in ^ class" surveillance practices, will not survive without fidl management support 4.

Careful Selection and Clear Definition of KPI's-identify a few critical KP! :r and clearly define the measure, too many KPI' s can confuse the line of sight of the team, the key to remember is-you get what you measure

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Individual Well or Pattern Analysis Process Flow Diagrams-clearly identify the process to be used, data requirements, tools, team members, responsibilities, deliverables ^ 6. Customer Supplier Relationship-clearly define the expectations of the teams that will be either suppliers to the surveillance process or recipients qf recommendations.from the team, this will include data requirements, process measures and results measures 7. Accountability and Results-it is critical to have a process in place that captures recommendations, assigns them to an accountable party, sets delivery dates, and captures results. The results should be evaluated as to technical success and economic competitiveness with other opportunities 5.

Examples of the above best practices using the "best in class tools" can be found in Appendices "D", "E", and "F". Reservoir surveillance, in summary, is the detailed day-to-day analysis of reservoir performance as measured against a detailed reservoir management plan. The reservoir surveillance process requires management support, teamwork, clear measures and accountability, and good data. The results of a well planned reservoir surveillance program will yield more accurate production forecasts, depletion plans for every well (part of reservoir management plan also), quick response when the reservoir or well performance deviates from plan and a better understanding of the economic value of capital/expense invested in surveillance projects.

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SURVEILLANCE STRUCTURE

• PROCESS The ultimate goal of surveillance is to improve the profit realized by the corporation. The structure of the surveillance process should be designed to understand and maintain system performance, to identify, and correct performance deviations, and to continually address opportunities and risk. An important factor in any endeavor is the process by which business is conducted. This is perhaps more important for a successful surveillance effort than is generally realized. The more structured the process the more likely that the proper surveillance will be conducted and the practices carried forward when personnel changes take place. Structure also leads to consistency. Consistency leads to a better understanding by all individuals, and a realization of the goals. Appendix "D" has several examples of structures and tools used to bring focus to a surveillance process. New Orleans utilized a process outlined in the Appendix on pages 24 through 30. The line of sight found on page 24 illustrates process inputs for well reviews and facilities reviews, what levers are measured, what key performance (KPIs) are generated, and the goals of the process. The goals used in the example are volumes, cash flow and expense reduction. An example of a KPI is "Actual Production" vs. "Capacity". The "GOM Surveillance Potential Best Practice" list can be found on page 25. This outlines what software should be used and how it should be used. Process flow diagrams (PFD) can also be found for the well review process on page 26, identification process on page 27, analysis and documentation on page 28. A facilities PFDs can be found on pages 29 and 30. Structure and consistency can be attained in many ways. One method that works well, albeit painful to initiate, is to develop customer-supplier relationship diagrams also known as SIPOCCs. The SIPOCC is a • methodology whereby a process is studied to identify the supplier(s), customer(s), process measures, and results measures. These can not be worked in a vacuum. For example if a well surveillance team is developing a SIPOCC it is imperative that operations, reservoir and contractors inputs are included. Where differences are identified in deliverables or measures, negotiated solutions must be developed. It is a fact that you can not get anywhere if you don't know where you are going. Development of a customer-supplier relationship diagram identifies what goals, directions, and measurements are required for a successful effort. Processes to conduct surveillance and fulfill the obligations of the customer-supplier relationship will be developed or refined as soon as goals and measurements are quantified. Examples of SIPOCCs can be found in Appendix "D" on pages 28 through 38. Results measures are developed for both supplier and customers. Products and services are identified entering the process from the supplier(s) and being delivered by the process to the customer(s). As stated earlier these items must be agreed upon by the process team and the customers and suppliers. Although there are key individuals in a surveillance effort, surveillance is a team effort. Teams could be formed around crude lifting and measurement, reservoir surveillance, pattern review, flood review, etc. Team membership depends on the structure of the affiliate or asset. But in each case the owners of the tasks should be members of the team. For instance, operators performing well tests should be on the crude lifting and measurement team. Another example would be Production Technicians, Operations Engineers, Engineering Technicians, Operators, Electricians and Foremen should be members of the well review team. These teams should meet regularly. Agendas should be used and action items recorded and reviewed. Standard operating practices (SOPs) should be developed for data gathering, quality control, process measurement, etc. I Team members should be confident enough about the value of their knowledge and ideas to be able to engage in frank and open discussions. All ideas should be heard. Feedback should be positive and respectful of the individual's value. Good teams display a "family spirit". 12

Surveillance to be highly effective should be recognized as a separate and important process. Individuals is working on surveillance teams should not be indiscriminately pulled off other tasks. For example a separate group should do development wherever possible. The imposition of drilling duties on a surveillance team effectively shuts down surveillance efforts in favor of drilling. Best Practices: 1. Develop customer supplier relationship diagrams for all teams involved in surveillance. 2. Regular team meetings. (e.g. Weekly well reviews.) 3. Electronic agenda for use at meetings. 4. Electronic capture of action items and review of open action items at meetings. 5. Separate surveillance from development.

DATA The purpose of this aspect of surveillance is to provide the most up to date, accurate, and applicable data in the most useful format. These data should reside in a common database for the use of those conducting the surveillance effort. You must have a clear understanding of the objective of why you are collecting data. All surveillance is dependent upon data. Data must be first captured, then collected, next quality checked, and set in a location where it may be retrieved and used by all who may need to work with it. If any one of these steps is minimized or not complete then the quality of recommendations from analysis is reduced. The types of data required for surveillance should be thought out thoroughly. As mentioned earlier Appendix "E" has examples of types of data to be gathered and the frequency that the data should be • gathered. Too much data creates the need for more management and quality control. Too little data will not allow proper analysis to be preformed. The challenge is to identify the right data and as a best practice to have all data go into one central database. This database should have QA/QC facilities that do not necessarily involve engineers. In many affiliates databases or applications perform the same or similar functions. In some cases the same data must be entered into several separate databases. This is wasteful and redundant. One example of this is welibore casing and tubing data. Another is wellbore deviation data. These data should be keyed in only once and then be available for all applications. In the context of this report the term "tools" has referred to software tools. However, the tools that gather the data are an important component in the surveillance process and deserve some discussion. Accurate well tests are a must in every operation. A starting point for well tests is that the rates from test to test should be somewhat consistent and the sum of the tests should be no more than +/- 10% that of the volumes shipped. A conunon problem with well tests is the gas rate. Orifice meters must be installed properly if accurate gas rates are to be had. Liquid slugging through an orifice plate can deform the plate inducing a source of great error. If wells can not be tested frequently for production rates and pressures no valid analysis can be done. When expansions are planned it is necessary to include provisions to test all wells frequently. The use of common test lines for more than one well should be avoided when one well has to be shut in to test another well. Some guidelines for data collection frequency can be found in Appendix "E" on page 54 figure 9-75 and page 62 Subsurface data requirements. • If a nodal analysis model has been built (i.e. PROSPER) and matched, multi rate tests may be used to calculate reservoir pressure. Nodal analysis tools can be used to compute the optimum GLR required for 13

gas lift operations. They can be used to review well test data to determine if the tests make sense. Gas lift designs as well as ESP designs and optimization can be preformed. However, none of the analysis can be • done without good test volumes and pressures. Both Operations Engineers and Reservoir Engineers should review pressure build up surveys. The focus of the Operations Engineer should be completion efficiency (PI) and changes in skin. Production Logging Tools (PLT) may yield great insights into the well's operation. The challenge is to determine which tool will give the most cost effective data and what the risk of not getting definitive data is. Temperature tools are generally inexpensive and good at identifying leaking gas lift valves. They may also be used to determine cross flow in commingled completions, however, they may not be definitive. Spinner or tracer tools can be used to determine flow rates, but the engineer must be careful to choose the appropriate one for the job. A small spinner tool in a high angle large bore completion may give output that does not represent what is happening in the well. A tracer tool may be an option, however, using a water soluble tracer at low cuts in high angle holes the readout could experience the same problems that a spinner would have.

Downhole video cameras are expensive and require a clear fluid in the hole. They are generally the most definitive in determining oil and gas entry into the hole. They are also the best method to determine the type and extent of any damage that may be in the. hole. They are a real time read out and are infinitely better than an impression (confusion) block. Problems with getting good data from the cameras are keeping the fluid clear and temperature. Flowing gradient surveys should be run in conjunction with a well test. The well test equipment should be in such a state of operation that consistent and valid measurements will be obtained for oil, water and gas production rates. A recently calibrated dial pressure gauge, dead weight tester or a downhole gauge should be used to record flowing tubinghead pressures (FTHP). Without valid fluid rates and surface pressure . measurements nodal analysis modeling can not be done with any sense of accuracy. The downhole gauges do not have to be state of the art quartz or surface readout equipment. A pair of properly calibrated Amerada pressure bombs can be effective if they are left in the hole long enough to allow the static pressure to be obtained or extrapolated. Best Practice:

1. 2. 3. 4.

Single input for each item of'datum. Single database for data storage. Identify and collect only the correct data. Fewer software applications for data manipulation reduce maintenance and upkeep.

ANALYSIS The overall goal of the analysis phase is to improve the process quality and efficiency so that system performance and optimization is well understood and the team consistently addresses opportunities and risks. Those doing the analysis take the data and generate recommendations for implementation. Four levels of analysis should be considered. I. Well 2. Facilities 3. Reservoir 4. System • Likewise, five primary analysis criteria should be considered. 1. Cost 14

2. 3. 4. . 5.

Production Reserves Time Profitability (Life Cycle Economics)

The purpose of the analysis phase is to quantify historic performance and to predict future performance. This is done using tools that evaluate past decisions and strategies and can be used to build an optimized future process. Basic tools would be decline curves, well models (nodal analysis), material balance models, root cause analysis, risk assessment, etc. Analysis should be performed on a routine basis. Any recommendations or action items should be captured electronically. The number of recommendations, results of the recommendations, cycle time from recommendation to implementation, and effectiveness of the process are the basic measures required to insure that analysis is done and that the process is continually improved. Tools used for analysis should be capable of downloading data stored in the common database and transforming these data into useful quantifiable predictions. There are several off the shelf tools that may be used. It is imperative that each affiliate standardizes on one application for each process. Examples of tools to be used are OFM, DSS, PA, Well Notes, Injection Management Tool, PROSPER, Mbal, GAP, WEM, Landmark, Earthvision, WORKS, and WELLMASTER. Appendix "F" gives examples "GRACE" tool used by Midland to generate optimal correlations from a data set on page 63 and the Chevron Decline Analysis also used by Midland for C02 WAG pattern analysis on page 67-73. DSS data may be populated from OFM files or PA structure files. Best Practice: 1. 2.

Uniform tools across an affiliate, such as PROSPER, WELLMASTER and DSS. Nodal analYsis on wells where applicable.

. 3. Software tools are fed data directly, fi•om common database. 4. Key measures are formulated and utilized routinely to monitor the process and measure improvement. 5. Measures include but are not limited to expenses in $/BOE, estimated results vs. actual, number of wells reviewed per time period, and failure frequency. 6.

Well Notes and WORKS are excellent for capturing recommendations, cycle time and post work reviews.

Recommendations and action items that are developed through the analysis of surveillance data can be generated in several settings. These can include well reviews, pattern reviews, reservoir management team meetings, morning meetings, etc. What route these recommendations take getting to the responsible party for implementation and how quickly they are acted upon are critical for the successful outcome of any depletion or surveillance strategy. The form and clarity of recommendations are important for the proper implementation, so that no misunderstandings or improper expenditures take place. Recommendations should be detailed enough to explain the need, procedure and history, without being redundant or extraneous. Recommendations should also quantify the expected results (e.g. BOPD, $/BOE, etc.) Electronic capture and routing of recommendations and procedures reduce the risk of them being lost and not acted upon. A recommendation is the result of an investment of time to gather data, analyze them and formulate a plan. Money has been spent to do this; not to act upon it reduces the value of the affiliate by wasting resources.

15

Software like Well Notes and WORKS have been successfully used to capture recommendations, route them to the responsible party, calculate cycle time to implementation, and to evaluate the success of the recommendation. ^ Best Practices: 1. Well Notes and WORKS type products for linking analysis to recommendations and implementation. 2. Routine follow up on process cycle time. 3. Metrics to measure the process. These could include number of recommendations per review, Number of various types of recornmendations, time from recommendation to implementation, estimated result vs. actual result, $/BOE (expense vs. incremental production), etc. 4. Expected results should be part of all recommendations so the individual responsible for implementation may prioritize them.

IMPLEMENTATION The motivation of all surveillance is to increase profit. Surveillance is a wasted effort without implementation. Implementation is the enactment of action items and recommendations developed during well reviews, pattern analysis, reservoir management team (RMT) meetings and flood reviews. Implementation encompasses communication, action and follow up. This predicates the need for developing a process that facilitates the collation, ranking, action and follow up on all recommendations. Included in the process is identifying who is involved in implementation, what system(s) are to be used, what hardware and software are to be used, how they are to be used and how often they will be used. ^ During the implementation stage recommendations should be ranked by expected results. A quality check on recommendations should be made at this point in the process. The tools used should facilitate the review of expected results vs. results from similar past recommendations. If the expected results vary significantly from the past results a flag should be raised and the person responsible for implementation should review the recommendation with the person (team) who made the recommendations. Several measures should be considered at this point. Cycle time from receipt of the recommendation to implementation of the work. Estimated results vs. past vs. actual results are other measures. Number of times recommendations need to be reviewed for variations of expected vs. past or actual results is another type of measurement. Measuring these and having mandatory periodic review are a necessary part of keeping surveillance focused and on track. All measurements should be preformed electronically and be reviewed at team meetings and routinely by supervision. Best Practices: 1. Quality check recommendation expectations vs. past results of similar jobs. 2. Work (opportunities) should be ranked on expected results. 3. Review results at team meetings. CONTINUOUS IMPROVEMENT A good surveillance process includes a continuous improvement loop. The plan-do-check-act cycle will bring about optimization of the data gathered, the frequency of the data gathered, how often team meetings should be held, which stimulation methods are the most profitable, which tools are the most reliable, etc. Most people learn best from mistakes. If no checks are made mistakes are not found and are likely repeated. If no action is taken to change the processes and practices that lead to mistakes profits will be reduced. All individuals involved in the surveillance process should be familiar with continuous improvement methods and be held accountable for practicing them. 16

CONCLUSIONS The starting point of a "best practices" surveillance program is to determine the proper data to collect and ^ the frequency with which it should be collected. Modifications can and will most likely be made as the surveillance program matures and changes through continuous improvement. Once the type of data is determined it should be captured once in a common electronic database that is available to every individual that is involved with the surveillance effort. The surveillance process should be structured so that everyone involved understands what is available, what is required, and who is involved with each phase of the effort. The structure should also include what the measures are and what the deliverables are. Standard operating procedures should be developed for various tasks or portions of the process. Standard tools such, as software should be used. Care should be taken to select tools that are robust, have a long expected life and will allow easy transition to new tools when that is needed. Surveillance efforts are best when practiced in a team environment. One individual should be responsible for the team effort and should conduct routine meetings. These meetings should have set agendas that should be followed with action item status being reviewed, and findings and recommendations being electronically captured into the cornmon database. Effective surveillance programs utilize process measurement. Measurements should be made on several factors to ensure that tasks and processes are taking place and that the effort is improving. Individual teams may use one set of measurements. Supervisors may use some of the same measurements as well as additional ones. Management should include various measures to track the surveillance progress and • benefit. Measures include actual costs/BOE vs. planned costs/BOE, number of recommendations, incremental BOE from surveillance efforts, etc. Total surveillance includes not only well and reservoir, but also Facility Surveillance. This is beyond the scope of this study; however, it is a vital link in total program. Surveillance done at any level, when using the appropriate tools, practices and processes, will always increase corporate profits. Finally management must be involved with surveillance to review progress and to give emphasis, direction, and support to the individuals and teams. Without management involvement cohesive focused surveillance efforts are difficult to implement and maintain.

• 17

APPENDIX A ^

BEST PRACTICES SUMMARY

l. All flowing, gas lifted and ESP wells have nodal inflow models 2. Single common database for data storage. 3. Uniform Tools Across Affiliate 4. Team Environment with Management Support 5. Careful Selection and Clear Definition of KPI's 6. Individual Well or Pattern Analysis Process Flow Diagrams 7. Develop customer supplier relationship diagrams for all teams involved in surveillance. 8. Accountability and Results 9. Regular team meetings. (E.g. Weekly well reviews.) 10. Electronic agenda for use at meetings. 11. Electronic capture of action items and review of open action items at meetings. 12. Separate surveillance from development. 13. Single input for each item of datum. 14. Identify the correct data to be gathered. 15. Fewer software applications for data manipulation reduce maintenance and upkeep. 16. Software tools are fed data directly from common database. 17. Key measures are formulated and utilized routinely to monitor the process and measure improvement. 18. Measures include but are not limited to expenses in $/BOE, estimated results vs. actual, number of wells reviewed per time period, and failure frequency. 19. Well Notes and WORKS type products are excellent for capturing and linking analysis, recommendations, implementation, cycle time and post work reviews. 20. Routine follow up on process cycle time. • 21. Metrics could include number of recommendations per review, Number of various types of recommendations, time from recommendation to implementation, estimated result vs. actual result, $/ BOE (expense vs. incremental production), etc. 22. Expected results should be part of all recommendations so the individual responsible for implementation may prioritize them. 23. Quality check recommendation expectations vs. past results of similar jobs. 24. Work (opportunities) should be ranked on expected results. 25. Final too] selection should be done by company personnel not a service company

• 18

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1984

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Data via P0F/tiECC.

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APPENDIX C AERA Energy Six Top Surveillance Measures 0

Measurement Definition

TOP 6 MEASURES 1. Subsurface Injection Conformance Purpose: To compare the desired distribution of injectant to the sandface compared to actual. • Measure 1: % conformance (via profiles and by-layer targets) on a per well or area basis I- E(Abs(Zone % Target - Zone % Actual))/100 • Measure 2: % of limited entry (surface measurements) Actual BDS/Theoretical BDS Theoretical BDS = (open perf. area*4.07*Cd -PSI "')/(vapor fraction) Implementation Plan: This measure will be a result of implementing the "Sub-stnface conformance" best practice. The "Sub-surface conformance "project has been passed on to IT for scoping (with a #1 ranking for priority). Business Lead - BuddY Bothwell; Surveillance VT Contacts - Kim Knolletberg and Dirk Smith. 2. Base + Surveillance Production vs. Plan Purpose: To quantify the difference between base production and the base production forecast. Measures how well we understand the reservoir performance (decline). • Measure 1: BDO above or below plan (Actual BDO - Plan BDO) • Measure 2: % above or below plan ((Actual BDO - Plan BDO)/ Plan BDO) • Base production: production online as of 12/3 1/,yy plus surveillance drilling - Surveillance VT Contacts : Dirk Smith • Plan Production: base forecast put together for Operating- Plan.

Is

Definition of "Base + Surveillance": 1. On 12/31/vyyy of each year, identify all producing wells as "B" (Base) 2. As new wells are drilled, label them as either "S" (Surveillance) or "D" (Development) Possible well types include Exploration, Delineation, Development, Infill, and Replacement. Difficulty arises in standardization across Assets i.e. - Infill wells in Diatomite are considered "Development", Infill wells in Tulare are considered "Surveillance") Implementation Plan: 1. The long term solution for this measure will be tied into the "Planning and Finance" and "Strategic Development" project to integrate the operating plan and evergreen. !AD needs to identify a "Business Lead" 2. In the short ternt, each Asset/field should begin to track this metric.

3. Produced Oil to Injectant Ratio Actual vs. Plan ( Base + Surveillance) Purpose: To measure the effectiveness of the injectant in recovering oil. - Surveillance VT Contacts : Dirk Smith • Measure: (Actual Oil/Actual Steatn)/(Plan Oil/Plan Steam) • Plan: forecast put together for Operating Plan. Implementation Plan (Analog to #2 metric): I.- The long term solution for this measure will be tied into the "Planning and Finance " and "Strategic Development" project to integrate the operating plan and evergreen. IAD needs to identify a "Business Lead " In the short term, each Asset/field should begin to track this metric. 4. Investment Performance Purpose: To measure how cost efficiently production is being added as a result of wellwork or new well drilling opportunities generated through pattern and/or flood surveillance.

^

Implementation Plan: 1. The long term solution for this measure will be tied into the Aera-wide "Investment Tracking" project. 2. Short term - Surveillance VT to define "simple" investment tracking algorithm for well work and new well drilling. Surveillance VT Contacts : Young Kirkwood, and Dave Homestead.

5. # of Pattern/Flood Recommendations by Type 21

Purpose: To measure the type and quantity of revenue generating and cost saving opportunities coming out of pattern and flood reviews. • • Recommendation Types: producer stimulation, producer workover, injector stimulation, injector workover, injector target change, redrill/infill, cycle steam • Standard type definitions and categories to be finalized following asset interviews Implementation Plan: 1. Long Term - Tie into Comment/Action Item DB, Drilling Rig, and Workover Rig Scheduling Programs 2. Short Term - Either use existing Tulare tool or use IT Express Desk to a) Standardize Wellnotes Company wide, and b) Add pattern identifier to MS Access forms. Surveillance VT Contact: Kim Knollenberg 6a. Pattern Reviews Actual vs. Plan Purpose: To ensure patterns are reviewed on the frequency specified when the production forecast was generated. • Measure: Actual # Reviews at a certain time/Plan # Reviews for the same time • Pattern review: as defined by the process flow diagram • Plan: forecast put together for Operating Plan. Implementation Plan: Compile Contpany-wide pattern review schedule into I database, spreadsheet or MS Project timeline (short term, easy,fix). Identify "Business Lead": ? Surveillance VT Contact : Kim Knollenberg 6b. Flood Review Progress vs. Plan Purpose: To track flood review progress as compared to plan so corrective action can he taken as necessary. • Measure: Actual days complete at a certain time/Plan days complete for the same time • Flood Review Progress: days completed for ALL of the steps (PFD) necessary to convert data and information into strategies and recommendations for monetizing resources consistent with Aera's goals • Plan: Gantt type chart showing activities and forecast days required to complete flood review process (created at the beginning of each flood review) ^

Implementation Plan: Compile Cornpany- wide flood review schedules into l database, spreadsheet or MS Project timeline (short tern, easy fix). Identify "Business Lead" : ?. Surveillance VT Contact : Ed Veit/rC

• 22

•

^

•

Field Surveillance Line of Si g ht Fundamental Activities

Team KPl - .*- Levers We..%*-- Team Process Measure

GOM Goal eo

z CD

Recovery Ewwto ^ Decline Curve Ana ;si6 Gas Litt Optimization

Volumes -*-

Pro7 1inventoTy ProJetatad

CT^

Gas LiR Anatysis

-do*--

No. of Slimulations

Review Well chokes Zone Changes Actual Prod. vs. Capacity

Tf

^- Well Review Use Depletion Plan

"^_

T^

M44n Well Analysis

Choke Changes Water Shut Offs

W

Cash Flow

ti [

rTI

Verily Geo"

p`.. ^

ro

Da.vntime Analysis

C'n O S3 ^

Z'

n

v

Fi¢l6UpdateswithFRB's

Runiime

Andl

FquipmenE EfCiciancy

-*t, O.E.E.

Facilities Review

•r^ " -Rustime -00Perc2nt

(Overall Equipment Effectiveness)

T

yZe E q ui pment Perfomtaance

- Debottlenecklag Compression Anafysis

""W-1 Equipment Life

(D ^ O

Gowntime Anatysis

Expense

Predictive Maintenence

$IBC^E $1BOE

prkove^ Costs $fL;OE C te Tlme Uolume Uplitt•Predictd^ ) a Aeh ia

^^'

-^ ^ ReriewlDocument Costs P PCA

Rev;evrlOoCUmen! Resutts

Capturo Learnings Tech. Reviews

UQ ^ ^

•

"BEST" PRACTICES GOM SURVEILLANCE POTENTIAL BEST PRACTICE LIST l.) Production Analyst Can display/produce production curves, contour maps and bubble maps. Also displays wellbore sketch information. 2.) Standard Plots RE Production Analyst production plots are standardized so they can be batch run by one technician. 3.) KPI Spreadsheet Standard SS holds monthly data such as production vs. plan and number of recommendations. It also keeps track of workovers and replacement wells. The information is linked to graphs by area and total field. 4.) Mini Maps (Zone Maps) Well location map showing producers and offsetting wells. Zone size isopach maps showing connectivity. 5.) Bubble Maps (PA) Net oil, gross rate, GOR, WOR, and water cut are shown graphically by the size/color of a bubble at each map well location. 6.) Performance Modeling Use Saphire to model well performance, look for damage, barriers, and predict future performance. 7.) OEDB Integrated system to enhance well research, package preparation and post analysis. Uses PRISM, PETRIS, NOMAD, MAQ'S and AFE info from CBCR. 9.) PPCA All project information captured in one data base. Cost data, production data, estimates, results and learnings.

6 9.) AFS Access to real time production, well test, facilities data.

• 24

•

Field Surveillance Vam - Well Review Proct Zi Identification

Is Preparation Complete,

WHAT YOU NEED

NO i

Performance Data

We] I Data--]

YES N

Evaluation

Documentation

► Completions/Open Interval & Perfs. Permanent vs, Termporary ► (GF2,SP,CAL), (Res,)(N-ti,)(Calculate Petrophysi:cs) ON available ► Saturation Logs-TMD's Ct*iLs, CO, ► CorrelatediMarked ?ones P- Logging Data - All Original & Cased Hole Logs P- Core Data - ( Optional) ► Offset Well Data

sm.

Production PWOR

Recovery s- Workover Histories ► Pressure (FP, BHP) n► s j►

Operator Observations Aug. Pay by Well Zone GOR Offset Well Performance

►

After Studies

X-Sections iViapsfVolumetrics ► Structure ► ►

Net Sand Isopach Net Pay (OriginalfCurrent) Isopach

P- Net/Gross Sand *HC Pore Volume ► "Base Map ► -Drainage Data Volumetrics on an Areal Basis P-

Flow Unit

► '41P, DOIP ► "Bulk Volume, (Net Acre Feet)

• = Critical

Well Review 0 Identification Process Flow Diagram M

0 N T H

Establish Prioritizing C (see list below)

Exit ^"-~"

fentrfy Exit Wells based on

Performance

Well Reviews for Exit Wells

L

Y Determ ine Frequency of Review by Well

W E

Analyze Data Based on Priority Established

E K

Generate Prioritized List

L Y

Move Down List

I No

Yes

>II review within established frequency?

No Ye s

Set date, review well * -I

^ Review wells by field.

Criteria for Prioritizing Wells for Review

4. Pressure changes S_ Gas lift performance 6. Last review date

1. Well production rate 2. Performance below predicted rate 3. Increasing water/sand production rates

26

Well Review Process

Analysis & Documentation PFD Field Surveillance Team ^ Prep Products Review Displayed & H Geology Available

H

Review Well Performance and Depletion Plan

•••^

/ Zone Changes RICorW/O Possible Choke Changes G!L Optimization Results of Prior Recomme Operating Policy Changes

individual Well Review

•

Done

Recovery % WOR Produobon,Trends Perf Depth vs Zone Depth GOR Historical Notes Pressure Data Gas Lift Performance Choke Size Drive Mechanism Competitive Position

Document Well Analysis Conclusions

Ne^ cline Curve Analysis Zones Completed

Fill out form or request for each action (immediate, electronic request whenever possible)

Sand Prod. Sidetracks

Lirnent Actions Due Dates, and o's Responsible

Document Well Analysis H Conclusions

Workover PossibiE"s^" Weilbore Conditions Replacement Possibilities Potential Opportunities

at dilfferent Price Scenar9<

• 27

All Wells

Well Review Complete

Facilities Review Identification Process Flow Diagram Q U A R T

E R L Y M 0 N T H L Y

Establish Prioritizing Criteria (see list below)

' Identify Shut Down Equipment

Exit

Reviews for Shutdown

based on condition, future . production

Determine Frequency of Review by Equipment Type

Analyze Data Based on Priority Established

Generate Prioritized Equipment List Move Down List --7

^ Equipment review within established

...

Yes

No Yes

Set date, review equipment ^ -_ J 1. Capacity of equipment

* Review equipment by field. Criteria for Prioritizing Equipment for Review 4_ Last review date 5. Required safety review 6. Regulatory requirements

2. Age of equipment 3. Potential bott`enecks

• 28

I

G41IIlY I\+V V IV VI 1 4^.av^ n vvv

Anal sis & Documentation PFD Field Surveillance Team • Prep Products Displayed & Available

Review Equipment Design

Review Equipment Performance

'+(

Downtime Ana Ws OEE's Bottlenecks Maintenance Upgrades

PMTS Operating Conditions Run Time Analysis Historical Notes

OEES Modifications New Installations Capacity Changes Results of Prior Recorrnne Operating Policy Changes

Individual Equipment Review

•

Done

Document Equipment . Analysis Conclusions

N°lrt abng Conditions capacities 'd

Fill out form or request for each action ( immediate, electronic request whenever possible)

New Equipment Modifications Replacement

Document Actions and Due Dates. and Who's Responsible

Document Equipment Analysis Conclusions

All Wells

Replacement Possibilities Potential Opportunities

at different Price Scenaric

0 29

Facility Review Complete

•

•

0

Supplier-Input-Process-Qutput- Customer Chart - RSVT Process Team: Su ppliers Data Management Team

Product/Service Data rs^p^rtsraraphs-

t^

Pattern Surveillance Team (PST)

Process

ProductlService ----------------------------

Convert Data & info into strate gies & recommendations

Customers

-- --- --- --- --- --------- --- ---

for maximizing asset vatue

at a pattern level.

-----------------------------

Results Measures Lagging lndicatorsforthe Su liar

Spec

Oust satislaction survey

Meas. Freq qrtl

C cle time

Measure system

Process Measures Who Owns

Leading Indicators

Spec

Mess Freq

Measure System

Results Measures Who Owns

Subsurface In] Conforrnancmonthty

Si}E

Pattern revfews, act vs lanmonthl

RSE

# Rev. recs. by type

PSE

monthl

Lagging indicators for the Supplier

Spec

h4eas Freq

Measure S steni

Who Owns

ii of A.I. Uncompteted

Supplier Boundary

Rec-aclion item that makes 64 Blue=Essential Metric 91ue=Es3enreel MB[HC

Customer Boundary

C^o 0

n

n

•

•

0

Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: P roduct/Service New Wells

Suppliers Aevela menU Constr/DrIlling

------- -- --- --- --- ---. Facillties

Res. Charactedzation .Depletion Slydte9y_.

Results Measures Lagging Indicators Spec tor the Su Iler Act. Vs. Est. Cost Cycle Time PG Rec• ROP Customer Satifaolion Survey

Meas Freq monthly monthly annual

Measure System

Process Convert Data & info into strategies & recommendations for maximizin asset value at a pg1jenn level.

Product/Service Drillinq Recommendations

Who Owns

Meas Measure Leading Freq Spec Indicators 5 tem Subsurface In Conformanemonthly Pattern revfews, act vs planmonthi # Rev. recs. by type monthl rnontttl ]D a, vs. lob submit CT

Rec=ai that makes o]u$ "Dialomite specific Bluea Essential Metric

monthl

Customers Development/ Con rstdDrill ling

--

Results Measures

Process Measures

fYof Al. .Uncompleted

Supplier Boundary

Pattern Surveillance Team (PST)

Who Owns SOE FtSE RSE FtS E

Meas Lagging Indicators Spec Freq for the Su lier Recommendation ohecklist per rec

Measure System

Who Owns

RSE

Customer Boundary

•

•

a

Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: Suppliers

Product/Service

Flood Review Team

Pattern Surveillance Team (PST)

Process Convert Data & info into

Product/Service PST Documentation Currertt knowledLqe of Resv.IArea

strate ies & recommendations for maximizing asset value at a pattern level.

Customers Hood tieview Team

----------------------------------------------

Results Measures

Process Measures

Lagging tJ

lndicatorsfor the Maas Spec Freq --suppler #Recs/ Flood Review per FR

Measure s y stem

Who Owns FRT

Leading

Maas

Measure

Results Measures Who

Spec Freq Indicators S stern Subsurface Ini Gonformancmanthi y

Owns SOE

OSR, OWR esUact.

Qtd

FRT

Patton revlews, act vs ptanrnonthf

RSE

BPD (all types) act/est

atrl

FRT

# Rev. recs, by type

monthl

RSE

Cusr Seristaction SurveyJChec4 per FR

FRT

ID opp_ vs. job submit CT

monthl

RSE

Annual

F RT

ft of A. I. Uncompleted

manthl

RSE

Now W¢Ir Econ_ NPV, EP, $BDE

Supplier Boundary

Fisc=ai that maEcr "Diatomite speci BIue=Essential Metric

Lagging Indicators

Meas

Spec Fraq for the Su lier Document checklist/s urve par FR

Measure S ystem

Who Owns

Customer Boundary

a

•

a

Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: Pattern Surveillance Team (PST) Su p pliers

Product/Service

O p erations

Current Data _--Problem Wall 10 Steam. Water, Oil - Rwondiilioned wells

(Includes CLAM, Steam or Water Teams)

Customers CLAM (Operations)

ProductlService In'ection tar ets b well ._J___-------^-----y ------------

Process Convert Data & info into strateg ies & recommendations for maximizing asset value at a pattern level.

w w

Results Measures Lagging indicators for the Supplier

Spec

Steam Quali ty @ [nj

Meas Freq pYrws.

Measure S tem

Process Measures Who Owns O ns. O ns.

Surtdoe Irij Conformance System Inj Pressure

monthly monthl y

O ns.

Gen BI)W Input vs sum of Inl.

monlhl

O ns.

Leading Indicators

Spec

Subsurface In) Ganforman

1vteas Freq

Measure System

Results Measures Who Owns

monthly

SOE RSE 1ASE RSE SOE

°b Pumped Off & Down Olt

monthly

2ns.

Pattern reviews, act vs lan monthly # Rev. rem by type monthly Do pp. vs. jab subrnit CT monthly Surf & Subsurface IN Conf. monthly

LACT vs AWT Welltests

monthly

op i n$_

Pun Rev HrslAv. His

monthly

SOE

Data Frequency ; cant to s pec YVetlwark CT (submit to compt)

monthly monthly

O ns.

# of A.1. Uncompleted

monthly

HS E

Lagging Indicators for the Su lier

Meas Freq

Rase Production vs. Plan' month[ Produced Oil to Injectant Rati monthl [nvstmt Hs[ts, $1bdc, bde Act month] BSPD or BWPD, Act- Vs . Tar q. montht PSOR and PS[R monthly

O ns.

Rec=ac:tion item that makes aiU$ BIue=EssenGal Metric

Spec

` Non-Development Blue=Essential Metric

Measure system

Who Owns HSE RSE R$E SOE FiSE

•

.

Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: Well Review Team Suppliers CLAM / O r t . s (1) pattern Review Team 2

Product/Service StJrv Data t R (11 Economic Rpt._SIl3 -°---°------ - -----

Process Convert Data & into into strate g ies & recommendations for maximizing asset value

Results Measures Spec

Maas Freq

Cust Satisfaction Surv Qrtl Data Frequency; oonf to spec Monthl

Measure S tem

Process Measures Who Owns DMT OI'NS

Leading Indicators

Spec

Well reviews, act vs plan 4 Rev. recs. by type Prob ID to rac- C-F

Due=Essential Metric

Meas Freq rnonthf monthf Month!

CLAM I Opns

_(3)Failure1ysTpt -------------_-_---------------•

PRT Notes i2lata wel I level. --------------

Lagging Indicators for the Supplier

Customers

Product/Service Work recommendations

Measure gstem

Results Measures Who Owns RSE RSE SOE

Lagging Indicators for the Su tier

Spec

Meas Freq

Measure System

Who Owns

Subsurface In) Conformance, monthly Invslmt Rstts, "de, We Act montttl Surfnce Inf. Confomnsnce Monthi

Blue--Essential Metric

Customer Boundary

SOE RSE SOE

0

0

.

Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: Well Review Team P roduct/Service Surv Data! Rpt_ (1! Econqmic Rpt._i113 Failure Analysis rpt PRT Nvtes_i2l ______

Results Measures Lagging Meas Indicators for the Spec Freq Su lier Gust Sa6staclion Survey Qrtly Data Frequenay; conf to spec f,rtonth1

Process

I

ProductlServiCe Work recommendations

Process Measures

Measure

Who

System

Owns bMT OPNS

Leading Spec Meas Freq Indicators welt revEews, act vs plan monthf if Reva recs. b y typo monthl Prob ID to rec. CT

Blue=Essential Mairic

Supplier Boundary

I

Monthl

Customers CLAM 1 O ns

Results Measures

Measure

Who

system

Owns RSE RSE

Spec Freq for the Supplier Subsurface Inl Conformance, monthly Invsimt Ftslts, S16de, We Act monthl

SOE

co Conformance SurfaInj.

Lagging Indicators

Meas

A1Measure S stem

Who Owns SOE RSE

f4lontt't!

Bluo=Essential Metric

Customer Boundary

SQE

s Supplier-Input-Process-Output-Customer Chart - RSVT Process Team: Well Review Team Suppliers CLAM I d ns (1) Pattern Review Team 2

Product/Service 5uN DatA / RPt_ (11 ECanomio Rpt.-^^/3_ ^ Failure Anat is--t ---- ------- _--

PRT ^lat$s i?^----_-

Process Convert Data & info into strategies & reconirnentiations formaximizin asset value

Lagging Indicators for the supplier

Spec

Maas Freq

Cust Satisfaction Surveyortl Data >=re uerrc : tson f to s ec tytontht

Measure System

-----------------------------------------------------------------

at a well leval.

Results Measures W (71

ProdueVService Work recommendations -

Process Measures Who Owns DMT

OF'NS

Leading Indicators

Spec

Meas Freq

Well reviews, act vs plan

rnonthf

4 Rev. recs. by type

monthf

Prob iD to rec- CCF

Manth!

Blue=Essential Metric

Measure System

Results Measures Who Owns RSE RSFSCJE

Lagging Indicators for the Su tier

Spec

Meas Freq

Measure S stem

Who Owns

Subsurface In Conformanee. monthly Invstmt Rslts, Slbde, bde Act monshi Surface tnj. Conforrt2ance Monthl

Blue--Essential Metric

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SOE RSE SOE

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Meeting Formats (McElmo Creek, MEPUS) MCELAIO CREEK UNIT C02 SURVEILLANCE UPDATE 3/30/99

Completed 2 month effort of data clean-up and improvement of data input/loading processes - Remaining issue with C02/Water injection, # days per month Re-ran C02 diagnostics for all 99 patterns Used 510.68/bo oil realization (adj. for current WTI posting) Corrected initial oil rate at start of C02 for economic and technical base for some patterns Adjusted some starting points for technical/economic base, because C02 was phased in, some patterns began realizing response prior to C02 injection in that pattern

2 nd PASS - C02 DIAGNOSTIC RESULTS: • 29 of 99 patterns with positive 6 month average C02 cash flow • 14 patterns losing less than $50/day • 14 patterns losing more than $200/day

DETAILED PATTERN ANALYSIS COMPLETED: • Plan - 30 patterns completed w/ detailed pattern analysis by 4/1/99; 17 completed to date RECOMMENDATIONS: • Increase Injection - recommended 15 injectors Completed 9 tlowbacks to date • - Recommended 13 "bullhead acid jobs down tbg", completed 1, Work in Progress ($ IM each) •

Increase Production - recommended 2 producers

- Uneconomic at current oil price, need $15 oil realization to justify (hydro-jet horizontal) •

•

Shut-Off Fluid - recommended 5 No additional expense money budgeted for 1999, spending budget on repairing failed NUT injectors Other - recommended 2 1- replace leaking CIBP over Zone 2, losing inj. out bottom, will try to do in 1999

•

No Recommendation - 8 patterns P&A's/TA's - Recommended 3 P&A's, 1 complete, 2 routing for approval TD Checks - Recommended 99, 5 done, Work in Progress

•

Step Rate Tests - Recommended 10 - Work in Progress

•

WA(; Management Changes - Recommended 14, Implemented 14 Increased WAG Ratio - 5 Decreased WAG Ratio - 9

CURRENT PLANS: Continue Detailed Pattern Analysis starting w/ Top 20% Patterns, Bottom 20% Patterns

• 38

0

4.

Well Testing Practices (MEPTEC) SUGGESTIONS FOR WELL TESTING PRACTICES 19-MARCH-1999 (M. C. Amondin, N. D. Ballard, C. V. Chow, and T. S. Nwankwo)

Well Testinjj Practices Data taken from well tests will not have any meaning if there is no routine maintenance preformed on the well test equipment. Even in a benign environment, well test equipment used to measure product must be periodically calibrated. An analogy for this is a cash register at a super-market that is only good to +/- 25% of the price of the goods leaving the store. Well testing equipment is a well's cash reaister. Freguency The frequency of well tests should be determined based on several factors. Some considerations are; how much is the well making, how many wells are being tested by the same equipment, how long required to obtain a good test, how accessible is the test equipment, is the equipment automated or manual, etc. Generally wells making the most oil or gas should be tested more frequently than lower producing wells. All producing wells should be tested on a regular basis. Even in flowing well operations a minimum test frequency of one test per well per month should be considered. . Test frequency should be tracked and the well test spreadsheet developed by M. C. Amondin is a good tool for tracking purposes. Test frequency has been used as a Key Performance Indicator (KPI) in other affiliates and has yielded significant value. A plot of tests per day for each platform/field with a management review weekly should be considered. With modem day computing systems, much of this process can and should be automated to improve cycle time and efficiency. Accuracy The well test spreadsheet should be updated weekly. All new tests should be reviewed using the choke model in the spreadsheet. The person reviewing the test data should ask two questions: 1. Are we getting consistent results? 2. Do the trends make sense? By using this method problems with well equipment and test equipment can be rapidly detected and corrected. One suggested KPI is the sum of the well tests vs. volumes shipped. This KPI is sometimes called the allocation factor (AF) and can be plotted daily (more of a leading indicator). It is a direct indication of the quality of the well test measurements. Another useful presentation of the AF is the monthly average (lagging indicator). Another KPI is gross fluid from a test separator/platform area vs. the sum of the well tests. This last KPI requires a gross meter at the site; an orifice plate will generally suffice since trends are looked at not absolute volumes. This pinpoints the location of production changes. Modeling The goal of modeling is to quantify well performance and level of accuracy of results. Various software tools can be used to model well performance and assist with well test quality control, our tool of choice is PROSPER. Some questions should be asked when using these tools: 39

1. Can the tests be predicted? (Using VLP/IPR relationships.) 2. Does the model reproduce the test results without making gross corrections to reservoir pressure or skin?

• Maintenance Gauges: Pressure gauges are one of the most important pieces of well test equipment for flowing wells. All wellhead and separator gauges should be calibrated on a routine basis? Calibration dates should be record and a file maintained that will not only keep a history, but also notify the responsible person when calibration is required. Gauges should have the proper range and resolution for the operating conditions experienced at the location of use. Most bourdon tube gauges are only accurate for the upper portion of the middle third of the scale. Gauges should be selected to operate in this area. If a gauge experiences overrange damage it should be replaced, as no amount of calibration will make the gauge accurate.

•

Meters: Orifice flow meters should have the orifice plates routinely checked for proper size, straightness and installation. The correct beta ratio of an orifice meter is important to assure accuracy. The beta ratio should be between 0. 15-0.75 for liquids and between 0.20-0.70 for gas. Orifice plates used in gas service should be inspected more frequently than those in liquid service should. Periodically the spring and water column value being used should be evaluated to insure that they are appropriate for the rates and pressures that are being experienced. This mandates that the plates can be changed. Meter tube length is also important, if the design criteria are unknown the meter tube length should be checked and corrected as needed. As with pressure gauges a record of meter inspections should be maintained for history and for notification of pending inspections. Well Test Spreadsheet: Use of the well test spreadsheet will determine where the largest errors are being experienced ( i.e. which platform, separator, AWT, etc.). Maintenance and calibration efforts should be focused on problem areas first. Over time systems will become more accurate and the data will make more sense. Also with time corrective maintenance will decrease as routine maintenance is employed. This process will also find production uplift candidates.

• 40

5. ,e

KPI

Lou F Marczynski 09/24/98 08:56 AM

To:Doug Owens/Houston/Mobil-Notes@ Mobil cc: Subject:Action Item: Reservoir Management KPI's

FYI ---------------------- Forwarded by Lou F Marczynski/Houston/Mobil- Notes on 09/24/98 08:52 AM ---Lou F Marczynski 09/23/98 03:19 PM

To:Mark H Meeks/Houston/Mobil-Notes@ Mobil, Marc Calvin/Houston/Mobil-Notes @Mobil cc: Subject: Action Item: Reservoir Management KPI's

At our meeting on August 20th, we set an action item to recommend KPI's for East Mallet. Please see my e-mail on KPI's and depletion plan. I have come up with the following recommendations for KPI's. Please review, I would like to meet and discuss the week of September 28th. 1.

Lease Level Overview KPI's updated weekly using the daily data in M. Deer's SUM-DATA.XLS file. All 7 day averages. Weekly meeting and conference call with Sundown to review KPI's. Primary emphasis on maintaining ^ C02 Injection Rate and spotting trends early so as to investigate further. a. C02 Injection Rate vs Target Rate in Mcfpd. b. Oil Production Rate in Bopd vs Plan c. Gas Rate in Mcfpd vs Plan volume d. GOR (cu ft/bbl) vs Plan volume e. Current WAG Ratio vs Target f. Processing Rate (total withdrawals in Rbpd) vs Target g. I/W Ratio vs Control Limits Performance Charts of daily performance at each battery and updated weekly from the Sundown Server using daily data. Also reviewed at the weekly meeting and conference call. Need to have FSR's annotate charts to account for facility upsets, well failures, routine maintenance, workovers, etc. a. Oil Production (Bopd) b. Water Production (Bwpd) c. Gas Production (Mcfpd) d. Oil Cut (%) e. Gas Cut (Rbpd as a percent of total withdrawals of oil, water and gas) f. GOR (cu ft/bbl) and GLR 3. Pattern Diagnostics updated monthly using data from PA or OFM to detect trends or anomalies and evaluate WAG decisions and Injection rate targets. Only for the "new" pattern configurations that include multi-injector patterns (approximately 17 WAG patterns). Monthly WAG Meeting to discuss patterns that have unfavorable Diagnostics. Diagnostic a. Pattern processing rate (Rbpd) vs; field average. b. GOR (cu ft./bbl and GLR ^ c. Gas Production (Mcfpd) d. Monthly I/M Ratio with a 6 month moving average

Unfavorable Condition Declining processing rate, much lower than field avg. Increasing GOR or GLR Significant increase in gas Outside control limits of .75 and 1.25 for more than 3 mos.

41

e. Oil Production Rate (Bopd) Significant decrease in oil rate f. C02 Utilization Mcf/Bo (both gross cumulative Instantaneous util. increase and crossing utilization and gross instantaneous utilization) over cum util. g. Current cashflow/day ($) Negative or decreasing cashilow h. Injection rate (both C02 in Mcfpd and H20 in Bwpd) Outside target range or lower injectivity i. Oil production incremental response Pattern produc tion at or below the technical base 4.

Surveillance Process KPI's recorded on a monthly basis to evaluate effectiveness of the process and measure activitv level. a. Number of patterns or injectors with a kh distribution. b. Number of WRC jobs completed for the month. c. Number of WRC recommendations under evaluation. d. Number of injectors outside target volume range. e. Number of pattern changes made on slug size, target rate, or WAG Ratio. f. Number of patterns outside I/W range. g. Number of patterns with declining processing rate. h. Number of patterns with increasing instantaneous C02 utilization. i. Number of patterns with negative cashflow. j. Number of patterns with declining oil rates. k. Number of injectors exceeding the maximum wellhead injection pressures for water.

I don't know if all of this is necessary. I tried to include everything that I thought might be important. Please look it over and give it some serious thought. Since we need to get back with Dan Callens on KPI's prior to October 6th, I would recommend that we meet Wednesday September 30th in my off ice at 9:00 AM. Please let me know as to your availability. Regards, I Lou M. Lou F Marczynski

To: cc: Subject:

10/01/98 04:09 PM

Mark H M eeks/Houston/Mobil- Notes@ Mobil, Marc Calvin/Houston/Mobil-Notes@ Mobil East Mallet KPI's

The following is a summary of what we agreed on for KPI's. Please review and let me know if your understanding was different. Lease Level Overview KPI's Updated at least monthly using the daily data in M. Deer's SUM-DATA.XLS. Use a 7-day average and the plot the items la through lg as shown in my previous e-mail. The plan number for the KPI's would be the projected values needed to meet the oil production volumes in the TERAS run for 1999. Performance Charts by Satellite Data is desirable, but not currently available. It might be possible to add up sporadic producer well tests in OFM for the wells in each satellite. However, this may not be possible if OFM is scraped and I don't know if DSS can perform this function. Pattern Diagnostics Updated monthly either in OFM or from downloads from PA. Changes made were as follows: 03a. - Add injection data to help interpret changes in processing rate. Processing rate along with field average plotted Vs time. 3b through 3f plotted vs time.

42

3g - Current cashflow/day plotted vs time using 1999 plan oil price. Add 3j - Technical base oil cum incremental recovery plotted vs C02 hcpvi along with the lease average curve or model curve. Unfavorable condition would occur when oil cum drops below field average or model prediction. • Surveillance Process KPI's Recorded monthly with the following changes: 4a. - % patterns with a kh distribution 4b. - year-to-date total of WRC jobs completed. 4c. - year-to-date number of recommendations coming from pattern analysis. This would include WRC, lift optimization, WAG ratio and slug size changes, target rates on wells, etc. 4d. - will be tracked by the FRS's not Midland 4e. - included in 4c above. 4f,4g,4h,4i and 4j - should be lumped together as the number of patterns each month with unfavorable conditions based on the monthly pattern diagnostics. 4k - will or is being tracked by the FRS's and not by Midland. This is how I remember it. Any comments, changes or suggestions.

Regards, Lou

•

.

43

•

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•

APPENDIX E DATA •

1.

Steamflood Guidelines (AERA Energy) Steamflood Reservoir Management ♦ 423

Steamflood Monitoring Program Steamflood reservoir management requires a large amount of data to be collected, processed, and interpreted. For the data to produce meaningful information, it is important to: 1. Collect the data before the project is initiated to establish baseline levels 2. Formulate a monitoring program during the project's design phase 3. Maintain the program throughout the project life. To determine the types of data needed, it is helpful to use Figure 9-75, a reproduction of Figure 9-4. The exact data required to understand the Steamflood process, however, varies from project to project. It is recommended that as a minimum the following data be collected for the heat and material balance analysis: 1. 2. 3. 4. 5. 6.

Oil production volume and temperature Water production volume and temperature Heat injection Steam injection volume Casing effluent rate and temperature Temperature profile (heat accumulation).

Data such as revenue, margin, and operating costs must also be collected and analyzed to determine the economic viability of the project. Data Collection Guidelines The frequency of collection must be balanced between the cost and value of the information. Figure 9-75 gives some general guidelines regarding the frequency of data collection. However, the frequency is dependent on the goals and operating cost limitations of the project. Pilot projects require more frequent measurements than established stearnfloods. It is desirable to use a statistically representative sample of wells to obtain heat injection and casing effluent data. Data from sampled wells can yield the same conclusions as data from all wells but at a reduced cost.

• 52

0 424 ♦ Chapter 9 Figure 9-75 ♦ Steamflood Monitoring Data

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The following recommendations are given with regard to the type of data and the frequency required to understand the process in established steamfloods. Injection Wellhead Tests Well Selection Guidelines Wellhead rate and quality should be measured periodically on 10% to 20% of the project injection 1. strings. Monitored wells should be distributed across the project area, but an emphasis should be placed 2. on injectors in patterns with observation wells. Monitored wells should include injectors that are near the steam generator facilities as well as at 3. the end of the steam distribution network. A monitoring program should include injectors that are at low and high elevation relative to the 4. generators. It is necessary to test both strings of a dual injector because there are usually unequal splits 5. between the upper and lower strings. Collection Frequency Guidelines Measure the steam rate and quality of the candidate monitoring wells when project steam injection 1. is initiated. 2. Continue to monitor the steam rate and quality at these injection strings at least on an annual basis.

53

3.

The steam rate and quality should also be monitored whenever a significant change in the steam distribution system is made or when steam rate reductions result in low steam velocities in the distribution system.

It is recommended that the steam quality be measured downstream of the choke. Consideration should be given to utilizing a surveillance tester to ensure that the generators are running at normal conditions throughout the quality measurements. Shut-In Injector Pressures Well Selection Guidelines 1. For mature, low-pressure steamfloods (like most Kern River projects), measure the stabilized shut-in wellhead pressure for every injection string. 2. For less mature or high pressure projects where shut-in injection results in a liquid column above the injection interval, run pressure surveys on 10% to 15% of the injectors. 3. These candidate wells should be selected so that they represent downdip and updip structural positions, as well as confined and unconfined patterns. Collection Frequency Guidelines 1.

When sandface pressures can be approximated by measuring shut-in pressures at the wellhead, take measurements twice a year at every injector.

2. 3.

When pressure surveys are required, run the pressure transients on candidate wells once a year. Consider running these pressure transients prior to project start-up and just prior to terminating injection. Casing Effluent Tests Well Selection Guidelines 1. Casing effluent tests should be performed on at least 10% to 15% of the project producers in a time-lapse manner. 2. These monitoring wells should be representative of the project area. 3. Focus on selecting wells that are in observation well patterns. 4. Pick both corner and infill wells in order to monitor if infill wells break through first. 5. These candidate wells should be representative of the different completion types (e.g., slotted liners that are open at the top of the drive zone vs. selectively perforated wells). Collection Frequency Guidelines I. Test the candidate wells just prior to vertical expansion start-up to establish baseline effluent rate from existing drive. 2. Casing effluent rates should be tested again when flowline temperature and casing pressure indicate that breakthrough has occurred. 3. Run tests at least annually on all candidate wells that exhibit steam breakthrough. 4. Run casing effluent tests just prior to significant steam rate reductions in order to establish baseline. It is important to record the corresponding separator pressure because effluent rates are highly sensitive to backpressure. Observation Well Temperature Profiles Well Selection Guidelines 1. Run temperature surveys in all observation wells that have good mechanical integrity. Collection Frequency Guidelines 1. Run temperature surveys every two months for the majority of the observation wells. 54

^ 2. It maybe desirable to survey some Wells on a monthly basis in order to ensure timely identification of areal steam-zone coverage. 3. Consider running temperature surveys once every three months for maturing projects that exhibit little change in heat content vs time. Observation Well Gas Saturation Logs Well Selection Guidelines 1.

Run gas saturation logs in all observation wells that have a good cement bond across the zones of interest.

Collection Frequency Guidelines 1. Run baseline gas saturation logs prior to initiating steam injection. 2. Run gas saturation logs at least annually once steam injection is initiated (it may not be necessary to run the gas saturation log if the temperature profile infers that a steam zone has not developed). 3. Schedule gas saturation logs so that they are run with in several days, of the temperature log. 4. Consider decreasing the frequency to once every two years for maturing steamfloods. 5. Run gas saturation logs just prior to shutting-in a steam injection project in order to establish a baseline prior to blowdown. Steamflood Monitoring Program Document An effective technique to communicate and document the monitoring strategy is to prepare a Steatnf'iood Monitoring Prograrn Document (SMPD). The SMPD communicates the goals and objectives of the project to the personnel involved. All personnel, from engineers to field staff, should be involved 0 with the creation of the SMPD before tile project starts. An SMPD is prepared once the sources and respective types of data collection have been determined. The SMPD ensures that the necessary data are collected with a frequency that enables the reservoir, production, and facilities engineers, as well as the EOR geologists, to evaluate project performance in a timely manner. The document also simplifies the transfer of information whenever a team member is reassigned. The document is periodically revised as needed. An SMPD should include the following information: 1. A summary of the goals and objectives 2. Location maps of the project 3. Geologic cross-section 4. Rate and cumulative production and injection forecasts 5. Forecast economics 6. Reservoir parameters 7. Heat balance and heat requirements 8. Forecast temperature profile 9. Brief list of monitoring requirements 10. Functional work group assignments 11. Definitions and purposes of the various data types. Additional items that could be included in the SMPD are: 1. Cost estimates for the data collection . 2. Documentation of how the data is stored (well files, monitoring program databases, etc.).

55

^ Each individual involved with the project should have a laminated copy of the SMPD for reference. The SMPD information sheets have been extremely effective, especially with field personnel. The SMPD helps field personnel understand: 1. 2.

Why well or operating work is required How important their work is to the success of the project.

The success of the SMPD depends on the participative efforts of each of the functional work groups. Team members should meet regularly. Required remedial work is often identified as a result of the monitoring-program data evaluation process. As a result, the economics of the project are enhanced. Data Collection and Transfer A large volume of data needs to be collected on a routine basis in order to effectively monitor a steamflood project. Although the collection frequency for routine data varies, the frequency is generally based on minimizing the cost of acquiring data, while providing adequate information in a timely manner. Many types of nonroutine data are also collected, depending on the performance characteristics of each steamflood (see previous sections "Injection Well Monitoring..." through "Cross Well Tomography" for discussion on the mechanics of data collection). The most important measure of the success of a steamflood project is the oil production rate. Therefore, attention should be placed on developing a process for collecting, transferring, evaluating, and interpreting liquid production data accurately. Automatic Well Test units (AWTs) are used to meter oil and water production rates at regular intervals. Each well is tested for oil and water production about once a week_ . Once the AWT gauges the production of a particular well, that gauge must be transferred to the data storage base. In computerized database systems, there are three distinct components involved with transferring gauges from the AWT site to the host computer: 1. AWT site computer Communication software Host computer. The host computer is the central computer where the data is stored and processed. Each AWT site retains its own computer and program. The collected gauges and data are stored on the AWT computer. The site computer stores: The gauge sequence 1. 2. Test duration 3. Baseline criteria for determining the success status of each test. The AWT site computers act independently, and they are not in constant communication with the host computer. Each site is assigned a. "hardwired" number as its address. Communications between the site and the host computer are always initiated by the host computer calling the site's number. The AWT site computer stores the completed gauge. The host computer contacts each site in some sequence. Contact is made with a site when the site recognizes the number being broadcast. The gauge data is transmitted to the host computer where it is stored in the main data base. This process can be continuous; that is, the host computer continually and sequentially communicates with the AWT site computer. The communication between the site and host computers is facilitated with radio wave, microwave, or telephone lines.

Data Storage and Processing 56

Figure 9-75 shows the many steamflood-monitoring data types that require collection and subsequent storage at a given frequency. Collected data also require processing so that they can be presented in a format that simplifies interpretation. Hence, computer systems are employed to manage effectively the storage and processing of monitoring data. Oil/water production and steam injection rates are considered essential data because they are required to operate the steamflood on a daily basis. These data are stored on mainframe or on microcomputer systems. In most steamflood operations, the transfer of production data is accomplished by automatic means, such as the transfer system previously described. This system also transfers and stores other types of data. These data types include: 1. 2. 3. 4.

Steam injection pressures Casing pressures Flowline temperatures Casing effluent rates.

Routine processing, report writing, and data plotting are performed by a database management system. Databases are developed for each data type that is required to evaluate and understand the steamflood process. It is useful to divide the monitoring databases into two categories: 1. Data collected vs depth (e.g., temperature profiles) 2. Data collected at surface vs time (e.g., casing effluent rates). Monitoring databases, designed for data vs depth applications, are similar to those used for managing digitized open-hole logs. The typical depth-recorded surveys for steamfloods are: 1. Temperature surveys 2. Pressure surveys 3. Neutron logs. Consider the following when designing the database for the depth-recorded surveys: 1. Digitized temperature and pressure data, provided by the contractor on a floppy disk, can be directly loaded onto the database via a PC terminal. 2. Geologic markers, well completions, and other well information are also maintained on the database. 3. Plotting routines should be available so that all data types can be plotted vs depth. 4. Routines should be available to automatically process and report average temperatures per interval. Computer support groups can generate useful contour maps of operating data to evaluate a steamflood's performance. An example of this is shown in Figure 9-76, which gives contours of oil and water production rates, well flowline temperature, and casing backpressure for a steamflood project area. A visual inspection of these types of plots can quickly identify a close relationship between fluid production and temperature trends. When dealing with large amounts of monitoring data, specialized manipulation of the data can be cumbersome. In most cases, personal computer and workstation software are more adept and useful for special evaluations. These database manipulators, such as OGCI's Production Analyst (PA) and Eclipse's Oracle Database Management, have many useful features. Large volumes of data can be stored and manipulated, including: 1. 2. 3.

Production/ injection histories Log traces Well completions 57

• 4.

Other depth- or time-varying data.

The data can be processed and displayed on map, cross section, or 3-D cubes. OGCI's PA software was specifically designed as a data manager for oil recovery projects. This software can store, manipulate, and report data. The most significant data storage and processing features of PA are: 1. Production plots can be generated by well group of wells, or project. 2. Contour, bubble, and grid maps can be generated for a specified area. 3. Log data can be stored and cross-sections can be developed. 4. Completion data and diagrams can be created and stored. Figure 9-76 ♦ Production, Flowline, Temperature, and Casing Pressure Distributions in a Steamflood Project

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Figure 9-77 is a PA production plot for a well in Field A, California. Contour maps like the one shown in Figure 9-76 can also be generated using PA. Other types of plots that can be generated by PA include: 1. Cumulative oil/water production bubble maps 2. Geologic maps 3. Log traces and correlations.

•

• 59

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Subsurface Data Requirements

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q APPENDIX F TOOLS 1.

GRACE Tool (Midland, MEPUS)

Objective:

The GRACE program generates an optimal correlation between a dependent variable (say, y) and multiple independent variables (say, x , x2, x3 ...up to x30). This is accomplished through non-parametric transformations of the dependent and independent variables. Non-parametric implies that no functional form is assumed between the dependent and independent variables and the transformations are derived solely based on the data set. The final correlation is given by plotting the transformed dependent variable against the sum of the transformed independent variables. The correlation thus obtained can be shown to be optimal (Breiman and Friedman, 1985; Xue et al, 1996).

Installation: You need Win'95. Unzip the GRACE.ZIP file by clicking it. The following files will be created: GRACE.EXE (this is the program) perm.dat and pvt.dat (these are sample data files) and • PERSONAL.XLS (how to use this file will be discussed later.) You may wish to put this stuff into a separate folder.

Steps in running GRACE:

(1.) Create a data file arranging your data in columns. The first line should contain the names of the columns. If possible, use simple names for columns without spaces and other fancy characters inside (underscore is allowed.) Use space and/or tabulator to separate columns. Sample data files are included. Any data line can be temporarily left out from calculations by putting an asterisk at the beginning. (2.) Start GRACE. Input your data using the input menu. You can either select the variable itself or for positive data, you can select the natural logarithm of the variable. (3.) Execute calculations using the RUN menu item. (4.) The program generates and plots optimal transformations for the dependent and independent variables. (Several options are available for these transformations. The default option for the dependent variable is 'monotonic' transformation and for the independent variables is simply 'orderable' transformation. You can select the appropriate transformations using the option menu and ^ repeating the RUN command. The monotonic transformation is more restrictive but is necessary if you are interested in back transformations.)

62

• (5.) The program generates a plot of transformed dependent variable and sum of transformed independent variables. This is the optimal correlation. (6.) The program generates a plot of observed vs. predicted values of the dependent variable based on the correlation developed. Mean absolute deviation and standard errors are computed. (If youselected the In of a variable (7.) Finally, the GRACE program generates an EXCEL file that summarizes the results for use in generating functional forms as discussed below.

Deriving functional forms:

The non-parametric approach adopted by GRACE program generates a transformed value corresponding to each data point for the dependent and independent variables. However, it does not give you a functional form for these transformations. In order to generate a functional form for the final correlation, you must fit these transformations using appropriate functions. In our experience, simple polynomials are generally good enough to fit these transformations. This is accomplished using the EXCEL macro that is provided in the disk. To open EXCEL ( ver. 7) it is enough to click on the Gracetr.xls file created by the last run of the Grace program. (It is in the same folder where your data file was.) . If your EXCEL macro file is properly installed, you should see a GRACE command in the TOOLS menu as the last item. Clicking the GRACE command will start the macro. The macro will generate the plots and polynomial fits to the transformations. The default order of the polynomials is 2. You may change this by putting the appropriate orders (1,2, ..6) into subsequent empty cells (starting with cell Cl) on the first line of the spreadsheet and rerunning the macro. If you like what you see, save it under a unique name as an EXCEL (.xls) file.

Installation of the EXCEL macro: If you have never worked with macros, you may put the PERSONAL.XLS file into the EXCEL startup folder (most likely called MSOffice\EXCEL^XLS TART\). The procedure is more complicated if you have already a PERSONAL.XLS file in that folder, but then you should know what to do!) You need EXCEL ver. 7.0 or higher.

Sample runs: 1)

Run the perm.dat data set. Select permeability as dependent and porosity as independent variable. You may experiment with selecting the logarithm as well. (Note that some questionable observations are commented out in the data file.)

• 63

2) •

Run the PVT data set. Select _In_Rsb ( the In of the solution gas ratio at the bubble point) as the dependent variable. Select API, Gas_gravity, Temperature and the _ln_pb (the In of the bubble point pressure as independent variables.)

Feedback: Let us know how you like it by sending email to the following address: [email protected] References: Breiman, L. and Friedman, J. H., Estimating Optimal Transformations for Multiple Regression and Correlation, Journal of the American Statistical Association (September, 1985) 580. Xue, G., Datta-Gupta. A., Valco, P. and Blasingame, T. A., Optimal Transformations for Multiple Regression: Application to Permeability Estimation from Well Logs, SPE/DOE 35412, presented at the Improved Oil Recovery Symposium, Tulsa, OK, April 21, 1996.

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9813.86

all b

190630 0.6000

uates

15000U

to0 100000

100% 1D 50000

914984

Peroent of

Cum. TerYlaryOil Prod., MB0

100/0 Tests Used. A . Fit = 60 bo d off

15758.6

A.06°k

0

spPO """AcWaIWOR -Caico4,i®d _.......----...-._.WOR -Catcalated Oil -PrOCCSSing Rate -

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attern Analysis Best Practice Example: hevron Diagnostic Plots Figure 1 ^ActuaE, Base Economic, and Base Technical Oil Production C02kr1ecblonAPRtt 1994

PATTERSVC C552W Match Parameters qti: 3521 Qai: 149

,® -

Di-. 16.37 I- nio w •

ey

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f

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Wag Management Best Practice Example: Target Rate / Wag Ratio

Battery

Pattern

C^ 0C

i324^9g

Type

^r,

:,

Phase

Wag Group

°^ r:

Inrreasa

l3a ^o r^ t far. `

a

SQrt a Grou^

CO2 Target

1121) 1 C02 Schedul e Schedule

Water Target

Target Wag

Rate 4200 5809

Ratio

^ _._ 65DD

4250

5000

5.00

5

d965 4250 :._...

2.00 5000 5.00 _ . .. .. . .. . _._ ._. i _.._....---.. .. Iry pressure = 7500 psi indicatlng

4

6000

7000

1.98

6

3570 4335 3400 .. . ..

4200

3.00 3.00 7.00

5270

200

.00

2850

3400

7.00

2041)

24UO

7 . 00

~

E

AWAG

AW02

1

1

-

B053W I

F F

AWAG AVt^AG

5

E31OW

B

AWAG

..: :.......... ..^.._. --- - - . . _. i.. ..._..-...-._ . + 1 AW02 2 4

AWD2 ^

1

1

AW02

2

1

AM3 AV03 AWM

2 2 1

1

s

i

Comments

7U0 _ 1.E7 . ' ... .. ..... . . .. .. 3 00.. ..... . ...... . 3.D0

. . . . ...... . _. _.. . .. _. ._-_..__ . . a _.... ...._.._._.. ..._r-._._......_......... . --- . ?-. ........_..._...._._. ,i--_ ..............I --- - ........._... . 1 ..._...._.._.;..._... C565W

ryt^Uaal

Irtcrease ! li3r-rease Wet Wap

Rate AWOI ' 3570 ? . _._.._.._......... .... .._ ^ .... ._..,. i . ...._ 3 4930 I 5 11 -- ^.. AV1I01 AW01 6 395 ? . - - - . .._. .... ... .. .. 2.._.. 3-.. --^-- - .... .. .. ..:.. .^ ; - 1 AWtli a 6 2 5525

k

®47W i

Decrease ^IZes[ease^Ay,sl.easej

increase

^FR^2{^NV^:':^

B052W AWAG .. F...... .... a _.._... E _.. .ii . AVsIAG E037AW ^. AWAG _ . __ . _AW _ .... .. . ,. H061 E3 1 5W E AWAG ^^ ` -

crease

;Chav.a

Salt Creek Field Unit Target Rates ;Last Uoda led

i

9Q0

!N pressure ^ 7100 psi Indicding k^ Is going beyond pattem unctanes

. ..

-

.

...

IN is going beyond pattern boundaries.

®36W E . f . AWAG '• AWAC C069W ,. C HO63PtUV _..._..^C ...................... AWAG FO?2W AWAG 8055W' ..__._F ._ ._...- AWAG ..--•--._..__..._ -- F AWAG 8051 W

.. . ...

I..... 1 .... .. ... 1

AW113

.

,

7

7 _ ._. _7.. ...

AVW3 AM ;

!

1

7

51QR

4000

.

VVW'ng Wag seemed to help f-417 breaEAhrough problems

`

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Conformance Best Practice Example: Zonal Allocation of Injection

ISM HCPV MRBBL

CUM H20 ISM

°lo TTL PATRN HCP'+!

CUM C02 ISM % HCPV

% HCPV

6201 CIsCO f

.3. yr

6301

^

1

- ----j-----

CS C3

ff

r28

6401

: -----^----^ ^ : ^

---- '----

T"i v ....

-

----;----C2A CJ B

v

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---_

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6609 :•

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Fl^^`l^ s{ \

STRA

^ `' ^,

STP,B STRC R7f19

0

500

1000 1500 0

8

16

24

0

200

400

600

0

30

60

9a

•

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•

FM - Gr id Mapping Production Car+tours

DA7<;A 987112

c

It wt o-<. em7tbhla ^

! Om> • a.i • a.+n • e+:, • 11.2 i> rX,s 0c-M> +a.a ron. zxca Cs 252.0-- AR* a. 29<1.>< Dd3, z5u><7rssS re5i5> ^ 14111e

^ !6526

5!t Jo

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•

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obilShare Used for Best Practices Implementation

2 SpreadstieetAvallahle forCslculaiin4 Donfarmance Faclors Clarificafion for iCPI fUr Conformance Measures

4 28 Atay 9998 tp Phillips PhiUiAs O 13 May 1996

Pattern Analysis nfa Chevron piagnaslics Spreadsheet Chevron Diagnostics SPNadll3hevt Drilting - 1999 Sceping Figures 'MvbiY' Diagnostics Spreadsheet

0 O 0 0

3,1=1998 Phillips 3Jun 1908 Phillips 3,1=1998 Phillips 30Apr1898 J- Phillips

Performance Prediudows ^ n/a Y Effect of Of] 5aturation on 002 U1111xa6oa C02 Ulilitaliari (Lou F Marczynsld-18 May 1998) WAG Process

^ ► n!a New topic C02 Fiaod Strjitqgy- Slaughter Field WAG Slug 1Yaclaing Spr2adsheel

AV 3JUn 79ss Phillips •!!] 2914ay1998 cA Deer 0 29 Rpr 9 998 Marczynskl

Aclfon Required Response Requested FYI

•

•

i

xplanation of Best Practices with Link to Actual Best Practice Tool(s) ^'Mnbil" Diagnostics Spreadsheet, JSP, 43098

sub ^at The Chevron Pattern Diagnostics have been recommended by the Best Practices Team as an Industry Best Practice. In order to utilize these diagnostics, you must first determine the tertiary oil "twedge'j for a given pattern or area. SPE 36695 discusses a new decline analysis technique that will more accurately predict base waterflood response. TerryAnthcnyhas developed a spreadsheet whicli uses the Solver in Excel to minimize the sum of least squares between the actual and predicted oil rates for a given history match period. The solver modifies Qti (Initial Total Processing Rate, rbpd)? Di (Initial Decline Rate), and b; (Hyperbolic Exponent) in order to forecast water-oil-ratio. The predicted base waterflo od forecast is then generated from the forecasted water-oil-ratio and the total processing rate. Steve Pl-^illip$ has modified the spreadsheet to streamline the process and to read data fron2 OFM. Before using the spreadsheet you will need to create areport format in QFM. An example of the Salt Creek report, i°chevron.rpt" is available in the Salt Creek OFM Database. You may access the database by clicking on the following path: Wid- do 1\d atc^AP P DATA^QFI^^^^ QnSALTQRK. OFM once you have created the report format, simply load an individual well, a pattern, or an area of the field yo u are interested in evaluating. Then simply click on i` Edif', "Copy" iiihile you are reviewing the rep ort and launch the spreaclsheet: \1IUIID -DOI}.Data\Share^EQ Mi spcllevron.xls Then., click on the macro-button "Import Data from 0 FM" to begin the analysis. I have atternpted to put ahote in many of the input cells to explain their imp ortance.

0

a

a

9est P ractice Classification UI : Good Id e a

^Unproven or not yet substantiated by data, but makes sense intuitively and could have a positive impact on the business performance. Requires further review and analysis.

♦ GP :Good Practice #Techniquey methodology, procedure, or process that has been implemented and has improved business results for the team. This is substantiated by data collected by the team, but with little arnount of comparative data from other teams or organizations.

^► LBP : Local Best Practice ♦ A good practice that has been determined to be the best approach for

teams in the business unit based on analysis of performance data within or outside the organization.

* IBP : Industry Best Practice ^ A practice that has been determined to be the best approach for all teams based on both internal and external benchmarking and the analysis of performance data. .

0

•

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Best Practices Identified _ ..

Parrnian flil: Slrrerds6eel: , Best pracHces ......... ..... ......_....... . . . . . Recommendations

and-ca.. , 5ori:..... ,..By Spansor ...... .le^ory

..

,

.

.. . . . .

. ..... . .r.

.....---_. .... . - ... . r.r

.

EOR SuNeilIdnCf

No. ITesui Kion

Praciice

18

Midland Sits Trainin g for C02 redictior, methods

GP

Catvin

Cslvin

C02 Prediction

2

3

16 15 17 3 1

C42 Pro he1 Model performance prediclicros C02 Analo g p read sheet mudat; Ott LAN Directo ry LAN Location for all PO TERAS CCfl flood forecasts and assum p tions 3-D DistributiCn of De p ositional Environments ( Lithofacias 3-0 Resenrair model in Stratarnodel isualization

I BP GP l.sP I BP I BP

Catvin Calvin Cat41it Harman Harman

Anthon y Calvin MaTkle y Harrnan,BEG MEP'EEC 6EG,Southwell

C02 Prediction 002 Prediction Data hlana omont Ras. Char. Res. Char.

2 3 3 1 1

2 4 3 2 1

Res- Char.

6

J 4^-

S p onsor

Source

Cate o

Irn act Difficul

3•0 hydraulic Flow Uni1 Model based on fluid! erformance data

IBP

Harman

BEG

1

1

2 6 4 B 7 23 22 19 34

Chronoslrati ra hic Fran-^era•nrks for Reserooir Architecture 3•0 Parmeabilil Modal non aramelric slalistics Addifive.Rtlutti licative rid-to- «d Geoto ic Ma in Volumetric Sensitevil Runs 3•D Saturation Model based on etro p h y sic airtluid analysis J-curves PO,r,ccass Database for p attern notes. o. ortundies, recs and M's Chavron Paltert't Diagnoslics in OFM SCF S raailsheet for for p attern ri¢ritization and surveillance 5Jau hler "Pair-Ana1 sis rasiq OFM

IBP LBP IBP GI GP L BP UP L8P GP

Harman Harman Harman Harman Harman Horne Horne Horne Horne

Harrnan H^G,MEPTEC Res. Char. Sharma Res. Char. Harman Pas. Char. Harman Res. Char. BEG Res. Char. Fussell Da1a Mana ornant Hinds/Calvin /Anthony Fussell Pattern F,nal sis Paltem Anal y sis Deer

2 .Z 3 3 3 2 1 2 2

2 1 4 4 2 2 3

12

Stauqruar "Cluster Meetings or producer well reviavrs

LOP

Home

Deer

Paltem Anal sis

3

3

SCF Pattem Anal y sis data reuest form Unit-wide WAG ratio and half-c ete slu g size a pp roach at Postle.lSlaa hter Yearly to monlhly production schedulin g for "Permian Oil Production PlanPatlern p erformance p redictions in OFM (B ase WF and C02 Linear Pr G rarnrTlin Model to allocate C02 in'¢clion b y attarn to ntaXim729 CF Sim. model sensitivit y runs and economicsfor slu g sizet WAG ratio schemes

LBP IBP GP L OP GI IBP

Home Home Marczynski Marcz nski tvtarcz nski tylarcryneki

Horne OeerlHinds Owens Hinds Marcz mski Mancz nski

Paitam .r',nal sis W,r.f_+ Procass CCr2 Prediction Dala Mana ement Patio mAnal sis WAG Process

4 2 4 1 1 1

4 3 4

WAG Meetin gs with FRSs

LHP

Marcr nski Marcz mski

WAG Process

2

4

tvtarcz nski M2rcryuski Phillips Phirli s Philli p s Phillip s Philli p s Philli p s Philli p s Phillips

Phillip s Veer CaNin Shaw Philli p s Philti s Jones Phillip s Phillip s Phillips

WAG Process 'NAG Process Conformance Conformance Conformance Conformance Conformance Conformance Conf3rmanee Conformance

2 3 1 1 2 2 3 3 3 4

3 3 2 1

Phillips

Philli p s

Data Mana emenl

2

3

Phlti s

Phillip s

Crate Mana amenl

2

2

20 ^ 24 35 14 36 9

13

it SCF S reacishaaifurLVAG chan g es and tar et iri eelion roles LOP 10 Slau htar g ra p hical a roach Io halFcyole slug size evaluation GP 33 Use Strearrdine ro ramtor.alculateOFMd y namic atternallocation fa ctor s LHP 32 Profile injection aficianc y nankin u:inq'Larenz Coefficient a pp roach" L8P 27 Vandar re• rofila re aralion roC9dures and data L f3P 31 OFM - Aflocate" Is track C02 inlection b y zone and dis p la y as % HCPV I_ 8P 24 Forurn on injection p rofile inter retalion Gt 29 Modify "Kumar" p rocedure lo a field•s pecitie tat L BP 26 Document field-specific irf rrofile schadnlin fra uenc . - usliFtalion & riorilization G P 2 Theoretical and Weal injection p tofle deGnllions BP 3Injection rofite header data in PO F,ccess D8 L BP L 6P H Inieclion rofire data stora e and filirn

3 2

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3 4 4 3 4

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PERTINENT DATA FOR G216 8/8ths Workover Cost Gross WI Workover Cost Starting Oil Price Starting Gas Price Starting NGL Price Rig Days

$46,000 $34,861 $9.57 $0.00 $0.00 6

MOBIL OIL SHARE ECONOMIC INDICATORS P / I Undiscounted P/1 Discounted (0.12)

7.00 6.16

NPV (0.12) ROR Payout - Undiscounted ( Months ) Payout - Discounted (Months ) Net WI Incremental Oil Reserves (MBBLS) Net WI Incremental Gas Reserves (MMcf) Net WI Incremental NGL Reserves (MBBLS)

Risked Data for Well G216

•

• 79

$214,640 -9904.9% 3 1 73.4 -30.7 -1.6

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Responsible Person 821269

Besly JA Jason

Well Name BL2161-12

Task Dat 2/8/99

Due Date

Oil Benefit

Task RDR Parted Rods

(AL) No production: well was pulled 1/8/99 for a polish rod change. Operator found well tapping down. Try to respace. FACT sheet in 2/8/99 for rod part. (John unable to get pumping on 2/9. Pritchard suggested high pressure hot water wash) BL3011-11

2122/99

QEN Review: Engineering

Monitor for pump off - run dyno if neccessary. If prodcution rate continues to decline reapidly, perform high rate water flush. BL3062-11

1/29/99

SPH Acidize - increase rate

Acid dump, making sure to pump away with pressure to get below. (May not be pumped off after AD.) BL3086-11

1/28/99

25

SPH Acidize - increase rate

Expect 100-200 gross increase from acid dump. ( soaked 3 times, never dumped) BL3112A-2

3/1/99

15

DRT RTP

Submitted FACTS on 3/1/99 for 40g/15n. BL3134-11

2/19/99

QEN Review: Engineering

Check for plugged casing line. If not plugged and well is pumped off, pressure wash. BL3137-11

1114199

10

SPH

Acidize - increase rate

Have Champion pull sample before acid dump. ( No water concerns). BL3164-11

1/8/99

20

SSS Steam Soak

Soak 10 MBS with cups below 910'. (wait unlit RTP of 3165A, 3165) Kim says the well needs it really bad! •

BL3165A-11

2/19/99

0

QEN Review: Engineering

Last pull 1/21/99 pump was raised to 1111' because of running sand at 1154'. Reconsider Steam soak with cups? (taken out of STUD) BL3184-11

2/19/99

CHP High Casing Pressure

check for plugged casing line. If no plug is found, try pressure wash. BL3191-11

118/99

1/14199

100

AMU Mechanical Failure Uneconomic to Repair

Coded uneconomic 11/24/98 due to repeated pump failures due to sanding. Acid dump has killed this well & NPO. Did scab (2' above OWC) breakdown? Yes. Mike P. confirmed. [Unable to pay for liner pull (S20k), so no caliper run.] BL3226-2

2/11/99

CHP High Casing Pressure

Closed casing vent WHP=16 psi. CVR=19 psi. (Looks like vent needs to opened after first test since CCV. ) BL3300A-1

2/17/99

CHP High Casing Pressure

CCV after blow down of CVR line. (Success. Gained 200g. Why did cut drop?) BL3321-1

2/17/99

CHP High Casing Pressure

CCV after blow down of CVR line. (Success. Increased 400g.) BL3326-2

2/11/99

SPH Acidize - increase rate

acid dump (submit for high pressure hot water wash) BL3426-1

2122199

QEN Review: Engineering

well is cold, is there a reason not to steam soak? Well is low net, how do offset wells compare?

Access Database - C:WROGRA-11wELLNO-1lWelNotas.mde

3l2199 g16:27 AM

Report = 210_Open_Taskjpt

•

85

Page 1 of 3

^

Responsible Person BL3455-2

PWB Pump Wash Back

2122/99

Well had big decline (unnatural) end of 1/99. Appears to have inflow problem. Possible Biiumen. (Try pressure wash) BL3551-2

USD Decrease SPM

2/17/99

CCV after blow down of CVR line. (oil improved 5 bond on 1st test) BL3664A-2

2/22199

QEN Review: Engineering

Well appears to be goad steam cycle candidate. Based on weil commnets, Perhaps use cups to isolate hot E4 sand? Check with Kim and Jim. BL3579A-2

2122/99

QEN Review: Engineering

Make sure that casing is not plugged and that well is pumped off. Decline after soak is very steep. BL3582A-2

QEN Review: Engineering

2/22/99

Confirm well is pumped off, run dyno If necessary. Consider acid dump- with acid, not water followed by 5000 BSPD. BL3604-2

2J19/99

QEN Review: Engineering

Check to see if well is pumped off. Have Caldwell complete earlier action items BL4255-2

NMD Move Packer Down

2/4/99

Isolate top perfs. Do we cmt sqz top perfs? Set packer below 676' perf; but leave 694'. 756', 764', 970' open. [Saves 417 bspd]. BL4255-2

214/99

NRS Injector Run Survey

Request survey from Pat after packer lowered. BL4283-2

NRS Injector Run Survey

2/5/99

Get injection profile survey after lowering packer and reducing steam target BL4283-2

2/5/99

NMD Move Packer Down

Lower packer below perf @ 756', leaving only the perfs @ 778', 796', 840'. 939', 970' open. (Saves 400 bspd) BL4307-2

2118/99

NRS Injector Run Survey

Get injection profile survey after target reduction to ensure most of steam is going into B3. If not, evaluate lowering packer and/or plugging back the C pers. BL4327A-2 is

2/11/99

NRS Injector Run Survey

get injection profile survey after stimulation BL4327A-2

2/11/99

20

SPI

Acidize - Profile Improvement

Clean out fill and stimulate perfs @ 940' & 952' only. Perfs have never been broken down. Risked 20 BOPD uplift. BL4330A•2

NDT Injector Decrease Target

2/19/99

Decrease target from 549 to 250 BSPD while waiting on cleanout and stimulation.. BL4330A-2

NIT

2/19199

Injector Increase Target

After cleaning out to TD and stimulating bottom 4 perfs, increase target from 250 to 500 BSPD. BL4330A-2

2/19/99

NRS Injector Run Survey

After cleanout and stimulation and target increase, get injection profile survey. BL4330A-2

2/19/99

SPI

Acidize - Profile Improvement

Cleanout to TD (possible bitumen) and stimulate perfs from 738'-919' (4 1/4" perfs). Perfs have never been broken down. BL4330A-2

2/19/99

YMN Monitor

Profile survey (1/98) shows injector taking 1/3 of ERP rate. Current pressure of 100 psi is unbelievably low unless there is split casing. Need to check and confirm choke size, rate, and WHP before lowering target. BL4379A-2

2119/99

NRS

Injector Run Survey

DOGGR may need profile after the job? (Ask pat.) Moses Database - C:WROGRA-71wELLNO-1iWeilNaes.mde

3f2/99 416:28 AM

Report- 210-oWjasX_ribt

•

86

Page 2 of 3

•

Responsible Person BL4379A-2

2119/99

NMD Move Packer Down

Lower pkr to 620'. Plan on getting steam to 3 B3 perfs (634'.644',660') and hope for some steam to reach 2 C perfs @ 709' and 732'. BL4382-2

NMD Move Packer Down

2/25/99

Cleanout to Td. Lower pkr to xxx' BL4456-2

2/16/99

2123/99

SPH Acidize - increase rate

Request high-priority Ballout. Expect 490 bspd increase to return to 100% target. Drive pressure=890ps1. Prefer WHP<650psi. BL5108A-2

2/16/99

SPH Acidize - increase rate

Submit as 4th candidate since 4456-2 down for Diatomite drilling this week. 5004A-1 1 had lower chance of success. 1/8l99

BL5166-11

5i1/99

NRS Injector Run Survey

get profile survey after CTU/cups (jet wash done to save money) 214/99

BL5255-2

NDT Injector Decrease Target

Decrease target to 280 bspd. (previously 386 bspd). BL5405A-2

NDT Injector Decrease Target

2/25/99

Decrease target to 260 bspd (from 643 bspd) BL5405A-2

2/25/99

NMD Move Packer Down

Cleanout to TD. Lower pkr to 650' (covers 4 ports @ 592',613',629, and 645'). Remaining perfs from 663-TD open. 3 bigs, 3 smalls. Breakdown 895' and 890' with water if money permits. BL5405A-2

2/25199

NRS Injector Run Survey

Get profile after pkr lowered. Last profile during questionable rate/pressure transition. BL58A-2

2/4/99

SPH Acidize - increase rate

Acid dump. OK to produce steam since B-injection reduced today. BLC3112A-2 .

311/99

15

DIRT

RTP

Submitted FACTS on 3/1/99 for 40g/15n. BLC3455-2

2/22/99

PWB Pump Wash Back

Well had big decline ( unnatural) end of 1/99. Appears to have inflow problem. Possible Bitumen. (Try pressure wash) BLC58A-2

2/4/99

SPH Acidize - increase rate

Acid dump. OK to produce steam since B-injection reduced today. Count of tasks for Besly JA Jason = 48

Access Database • C:WROGRA-11wELLNO-7tweNhotes.mde

321999:16:26PJd

Report = 210_Open_Task_rpt

•

87

Page 3 oi3

APPENDIX G OTHER READING

Gunton,e Field: Development and Management of a Multiple- Reservoir Offshore Waterflood Amran Nong Chik, SPE, Sainsuddin Selamat, SPE, Mohd Rohani Elias, J. P. White, SPE, M.T. Wakatake, SPE, Esso Production Malaysia - JPT December 1996

2

Measuring Engineered Oil Recovery Benjamin F. Sloat, SPE, Tiorco, Inc - JPT January 1991

3

Reservoir Management of the Prudhoe Bay Field Andrew D. Simon SPE, ARCO Exploration and Production Technology; Eric J. Petersen, SPE, ARCO Exploration and Production Technology - Presented at SPE Exhibition at San Antonio 5 - 8 October 1997

4

An Overview of Water flood Surveillance and Monitoring A. W. Talash, SPE, Mobil E&P Services Inc - JPT December 1988

5

Water flood Surveilliance Techniques - A reservoir Management Approach G. C. Thakur, SPE, Chevron U. S. A. Inc. - JPT October 1991

6

Measuring the Quality of a Reservoir Management Program E. D. Holstein, SPE; A. R. Berger, SPE, Exxon Co. U.S.A - JPT January 1997

9

7

Brief.• Reservoir Manazement in the Ninian Field, UK North Sea - A Case History Z. S. Omoregie, SPE, West Australian Petroleum Pty. Ltd.; G. R. King, SPE, Cevron Overseas Petroleum Inc.; Christopher Strang, SPE; Peter Hodgson and R. A. Pressney, SPE, Chevron U. K. Ltd - JPT December 1996

A Focus Development for Heavy Oil Reservoird: The Last Frontier At The South Belridize Field C. S. Chiou, SPE; S. D. Badger, SPE; M.M Carlsen; K.S. Pereira; AERA ENERGY Presented at SPE Western Regional Meeting, Anchorage Alaska, 26-28 May 1999

Innovative Reservoir Management - Key to Highly Successful Jay/LEC Waterflood E.P. Langston, SPE, Exxon Co. U.S.A.; J..A. Shirer, SPE, Exxon Co. U.S.A.; D.E. Nelson, SPE, Exxon Co. U.S.A - SPE publication, 1981

10

Data-Gathering System To Optimize Production Operations: A 14-Year Overview S.M. Bucaram, SPE and B.J. Yeary, ARCO Oil & Gas Co - JPT April 1987

11 •

Innovative Engineering Boosts Wasson Denver Unit Reserves W. K. Ghauri Shell Oil Co. Houston - Petroleum Engineer, December 1974

88

12

Areal Pattern Distribution Of RemaininQ Oil Saturation in a Mature West Texas Waterf lood -A Case History Arun K. Sharma, SPE, Mobil Exploration & Producing, U.S. Inc., Anil Kumar, SPE, Mobil Exploration & Producing Technical Center - Presented at Midland Texas, 27-29 March 1996

13

An Expert System For Analyzing well Performance L.A. Hutchins, BP Exploration (Alaska) Inc., R.K. Burton Ph. D and D.J. MacIntosh Ph. D., Computing Visions Inc - SPE Meeting at Anchorage Alaska, 22-24 May 1996

14

Recommended Practices For Heat ManajZement Of Steam flood Projects V.M Ziegler, R.B. Crookston and S.J. Sanford, Chevron USA Production Co., and J.M Merrell, Chevron Overseas Petroleum Inc - SPE Symposium at Bakersfield 8 - 10 February 1993.

15

A Case Study of a Multi-Disciplinary Asset Management Team, With Special J.M Wade, SPE Phillip Petroleum Company Norway, and V. 1. Fryer, Phillips Petroleum Company - SPE Annual Technical conference at San Antonio Texas, 5 - 8 October 1997

16

A systems Approach to Production Management: Beryl Field Case Study M.C. Arnondin, SPE, Mobil North Sea Limited, and M.A. Jackson, SPE, Petroleum Experts Limited - SPE conference at Stavanger, Norway 16 - 17 April 1996.

17

Reservoir Management: Principles and Practices Rafi Al-Hussainy, SPE, Mobil E&P Technical Center, and Niel Humphreys, SPE, Mobil New Business Development - JPT December 1996

18

Intejzrated Reservoir Management for The Lon,- Term (synopsis of paper SPE 38284 by E.M. Whitney et - JPT December 1997)

• 89

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M Optimum GLR Sensitiv ity Plot

r

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q --{]----GOR (scf/b) Rate (b/d) -O-WHP (psig) -0- -Total GLR (sct/b) -0-- Gas Lift Rate ( Mscf/d) -M••-- Casing Pressure (psig) --fl-Water Cut (9^0)

40

9/13A-A44 Well Performance

4000 -

20

3500

17.5

3000

15

2500

12.5

2000

10

1500

7.5

1000

5

J as

x

O C7 ai

n

2.5

500

01 15/7/94

12/8/94

9/9/94

7/10/94

4/11/94

30/12/94

2/12/94 Date

27/1/95

24/2/95

24/3/95

21/4/95

0 19/5/95

^71

ul

to

r

M

M

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ETIM WELL TEST Measured/Predicted Mass Flow Rates 0.35

0.30

0.25

0.2t)

0.15

0.10

0.05

0.00

AML

Il Z

1.0

1.7

2.3

3.0

3.7

4.4

5.1

5.8

6.5

7.2

Measured/Predicted Mass Flow Rates

7.9

8.6

9.2

9.9

10.6

11.3

r

to

to

PVT Matching

T^nperatw ^ depresei little POW 4375 0 ww" ede

Flash Liberation Experiment Quality Control Oil Density - most significant component of the pressure drop prediction

Tune PVT to measured data Beryl - 14 PVT regions generated from 150+ matched experiments using EOS

Pill

049 up now

we rrr

:dlSTB

RR/SIR

N C"PpifE

253 7

1 1914

2000 0

495 2

1 3029

0 7875

2500 0

624 2

1 3604

0.6695

3000 0

761 3

1 A208

0.5721

3500 0

908.0

1 4845

0.4916

4000 0

1065.6

F-5524

0.4247

4375 0

1132 2

1 6L164

0 3816

4500 0

1192.2

1 6D29

0 3BB5

5000 0

„9Z.2

1 5898

0 4166

6D00 U

1192 2

1 5667

0 4737

1 10000

1.1048

^

^

40

Integrated Production System Data Validation - Flow Correlation Matching Similar process as PVT Uses FBHP survey results

Head and friction component tuned < 10% correction of head term indicates good data ^Eatrnr;

> 10% may indicate poor quality PVT, test data or pressure measurement Flow correlations use in quality control x l(

tocffted µ

^ 7

+f1

0961911 1 09691

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0,960439

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