Ensemble history matching enhanced with data analytics - A brown field study

E. Tolstukhin*, E. Barrela, A. Khrulenko, J. Halotel, V. Demyanov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


This paper presents a methodology used in a subsurface uncertainty study for redevelopment of an oil field in the North Sea. A fractured chalk reservoir was depleted for more than 30 years with limited water injection. The uncertainty study aims to find an ensemble of geologically consistent scenarios that would honor production history. The scenarios then serve as input for the redevelopment concept selection, well placement and economic evaluation. The challenge in this study was that the field has long production history that must be respected. In addition, the uncertainty that may not be resolved by HM must be preserved in the scenarios in order to estimate all the risks and capture all the potential associated with the remaining oil pockets and future well targets. For the brown field, it is difficult to analyze all the information and utilize its full potential. In this work we use data analytics can improve efficiency of ensemble history matching by analyzing links between the static and dynamic model ensemble update: screening of the initial ensemble, model localization based on spatial analysis dynamic observations to the parameter update and identification of conflicts between groups of production observations that prevent balanced model update.

Original languageEnglish
Title of host publication4th EAGE Conference on Petroleum Geostatistics
PublisherEAGE Publishing BV
ISBN (Electronic)9789462822962
Publication statusPublished - 2019
Event4th EAGE Conference on Petroleum Geostatistics 2019 - Florence, Italy
Duration: 2 Sept 20196 Sept 2019


Conference4th EAGE Conference on Petroleum Geostatistics 2019

ASJC Scopus subject areas

  • Geophysics
  • Statistics, Probability and Uncertainty
  • Geology
  • Geotechnical Engineering and Engineering Geology


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