Pressure Matching for Hydrocarbon Reservoirs: A Case Study in the Use of Bayes Linear Strategies for Large Computer Experiments

  • Peter S. Craig
  • Michael Goldstein
  • Allan H. Seheult
  • James A. Smith
Part of the Lecture Notes in Statistics book series (LNS, volume 121)

Abstract

In the oil industry, fluid flow models for reservoirs are usually too complex to be solved analytically and approximate numerical solutions must be obtained using a ‘reservoir simulator’, a complex computer pro­gram which takes as input descriptions of the reservoir geology. We describe a Bayes linear strategy for history matching; that is, seeking simulator in­puts for which the outputs match closely to historical production. This approach, which only requires specification of means, variances and covari­ances, formally combines reservoir engineers’ beliefs with data from fast approximations to the simulator. We present an account of our experiences in applying the strategy to match the pressure history of an active reservoir. The methodology is appropriate in a wide variety of applications involving inverse problems in computer experiments.

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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • Peter S. Craig
  • Michael Goldstein
  • Allan H. Seheult
  • James A. Smith

There are no affiliations available

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