Quantifying_Uncertainty_in_Production_Fo - SPE 62925...

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Copyright 2000, Society of Petroleum Engineers Inc. This paper was prepared for presentation at the 2000 SPE Annual Technical Conference and Exhibition held in Dallas, Texas, 1–4 October 2000. This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435. Abstract A synthetic reservoir model, known as the PUNQ-S3 case, is used to compare various techniques for quantification of uncertainty in future oil production when historical production data is available. Some results for this case have already been presented in an earlier paper 1 . In this paper, we present some additional results for this problem, and also argue an interpretation of the results that is somewhat different from that presented in the earlier paper. The additional results are obtained with the following methods: (i) rejection sampling, (ii) history matching of multiple models using a pilot-point approach, and (iii) Markov Chain Monte Carlo (MCMC). Introduction It is widely recognised that the future production performance of oil and gas reservoirs cannot be predicted exactly. There will always be some uncertainty. Nowadays, more and more effort is being made to quantify this uncertainty. The aim of the work described in this paper is to compare a number of different methods for quantifying uncertainty in future reservoir performance. In particular, it considers reservoirs where some production data (beyond well testing) is available. Such data is particularly difficult to incorporate in an uncertainty analysis because of the time consuming nature of the computations necessary to simulate fluid flow in the reservoir. The work was carried out as part of the PUNQ-2 project 2 , partly funded by the European Union. PUNQ is an acronym for Production forecasting with UN certainty Q uantification. The project involved 10 European universities, research institutes and oil companies.
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  • Winter '14
  • Ms.Hariison
  • oil production, Markov chain Monte Carlo, Lars Holden, Maarten Cuypers

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