Best Practices and Methods in Hydrocarbon Resource Estimation, Production and Emissions Forecasting, Uncertainty Evaluation, and Decision Making
- R.M. Jonkman (International Oil & Gas Services Inc.) | C.F.M. Bos (Netherlands Inst. of Applied Geoscience TNO) | J.N. Breunese (Netherlands Inst. of Applied Geoscience TNO) | D.T.K. Morgan (Uncertainty Management Ltd.) | J.A. Spencer (Reserves Management Ltd.) | E. Søndenå (Norwegian Petroleum Directorate)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2002
- Document Type
- Journal Paper
- 146 - 153
- 2002. Society of Petroleum Engineers
- 5.1.5 Geologic Modeling, 7.6.6 Artificial Intelligence, 3.3.6 Integrated Modeling, 4.2 Pipelines, Flowlines and Risers, 5.6.3 Deterministic Methods, 4.5.10 Remotely Operated Vehicles, 5.5.8 History Matching, 7.2.3 Decision-making Processes, 5.6.9 Production Forecasting, 4.3.4 Scale, 5.5 Reservoir Simulation, 7.1.5 Portfolio Analysis, Management and Optimization, 6.1.5 Human Resources, Competence and Training, 7.1.7 Intergated Asset Management, 5.7.6 Reserves Classification, 5.7.3 Deterministic Methods, 5.7.4 Probabilistic Methods
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On behalf of a group of sponsors consisting of the Norwegian Petroleum Directorate (NPD) and most E&P companies active in Norway, a work group was established to author a report on the best practices and methods in hydrocarbon resource estimation, production and emissions forecasting, uncertainty evaluation, and decision making. The work group is part of Norway's forum for Forecasting and Uncertainty evaluatioN (FUN).
Following a detailed data acquisition and interviewing phase used to establish an inventory of the current practice of all sponsors involved, the work group postulated a relationship between a company's practices and its economic performance. A key distinguishing factor between companies is the degree to which probabilistic methods are adopted in integrated multidisciplinary processes aimed at supporting the decision-making process throughout the asset life cycle and portfolio of assets.
Companies have been ranked in terms of this degree of integration, and best practices are recommended. In many companies, a gap seems to exist between available and applied technology. Data and (aggregated) information exchange between governments and companies is also discussed. A best practice based on their respective decision-making processes is recommended.
FUN1 was established in 1997 and has 18 member companies, in addition to NPD. The forum is a Norwegian Continental Shelf (NCS) arena used to determine best practices and methods for hydrocarbon resource and emissions estimation, forecasting uncertainty evaluation, and decision making. It focuses on matters related to forecasting and uncertainty evaluation of future oil and gas production. Its main purpose is to optimize the interplay between the private industry and the national authorities wishing to regulate their national assets.
The basic question that began the FUN Best Practices project was whether the accuracy of Norway's historical production forecasts has been disappointing because of erroneous contributions from the companies or because of wrong aggregation by NPD. Which best practices could improve this situation? Whereas reserves form the basis for production, capital expenditures, operating expenditures, and emissions forecasting, the decision-making process in the various companies and national authorities links the various components together. Using the latest guidelines created by SPE, the World Petroleum Congresses (WPC), and the American Assn. Of Petroleum Geologists (AAPG)2 for reserves reporting (allowing the use of probabilistic methods), the project concentrated on assessing the potential advantages of probabilistic techniques when used in combination with fully integrated asset management workflow processes.
After a discussion of the current practices of the various companies and authorities visited, best practices are formulated in the fields of estimating reserves, production, costs and emissions forecasting, decision making, planning, and communications. The paper concludes with recommendations on how to move from the current practices to the desired best practices.
Methodology of the Study
The methodology used by the FUN Best Practices Team involved a series of interviews with:
The Norwegian Operating Units of the oil companies sponsoring the project to obtain their views on the current practices.
The Norwegian authorities.
The headquarters of several major oil companies to obtain their views on best practices in production and emissions forecasting and decision making.
Government officials in other major oil- or gas-producing countries to learn from their experiences.
The interview comments were analyzed, and a set of best practices was formulated. A project currently in progress concentrates on disseminating the best practices through workshops and elearning combined with classical training courses.
All companies trading on the New York Stock Exchange (NYSE) use the U.S. Securities and Exchange Commission (SEC) reporting standards, which are encumbered with anomalies as to changes in (end-year) oil prices, novel contracts (production sharing), and a modification for North Sea fields (by exception). They are difficult to change because such changes would have consequences for financial reporting by means of the (unit of production) depreciation of capital assets by the oil companies.
Most companies adhere to the SEC rules for reporting proved reserves as a single, deterministic number. Commonly, however, probabilistic methods are used internally; only recently did a few governments start to ask for probabilistic reserves reporting from the companies. In response, SPE, WPC, and AAPG have formulated guidelines that include the option for probabilistic reserves reporting.
The standard adopted by NPD3 relates reserves to their maturity and is, with a few minor modifications, eminently suitable to be linked with business processes, as is done internally by several oil companies. It appears that, for a number of companies, the NPD classification is not too different from the systems used internally, which are indeed linked, in some cases, to a business process. For some companies with simpler classifications, additional work will be required to comply with the NPD standards.
In Table 1, the various standard classifications and those used by the companies are compared.
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