Field development optimization under geological uncertainty

Reza Yousefzadeh*, Alireza Kazemi, Mohammad Ahmadi, Jebraeel Gholinezhad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

Decision making about field development plans has to consider the inherent uncertainties of sub-surface hydrocarbon reservoirs; therefore, the decisions would be stable under different geological scenarios. As described in Sect. 1.5.1, the aim of this kind of uncertainty management is to propagate the uncertainty from inputs to the outputs. Therefore, instead of a single deterministic output, the output will be probabilistic from which some statistical measures, such as the expected value, standard deviation, etc. can be calculated to account for the uncertainty. Therefore, the final decision regarding the field development plan can be taken according to the statistical measures. This kind of uncertainty management is also known as the robust field development optimization as explained in the following. In addition, different risk measures, different approaches to selecting an ensemble of representative geological realizations to be used in robust optimization, decreasing the computational cost of the optimization under geological uncertainty by constrained optimization, and challenges related to these activities are described in this chapter.

Original languageEnglish
Title of host publicationIntroduction to Geological Uncertainty Management in Reservoir Characterization and Optimization
Subtitle of host publicationRobust Optimization and History Matching
PublisherSpringer
Pages93-113
Number of pages21
Edition1st
ISBN (Electronic)9783031280795
ISBN (Print)9783031280788
DOIs
Publication statusPublished - 9 Apr 2023

Publication series

NameSpringerBriefs in Petroleum Geoscience and Engineering
PublisherSpringer
ISSN (Print)2509-3126
ISSN (Electronic)2509-3134

Keywords

  • clustering
  • computational cost
  • constrained optimization
  • geological uncertainty
  • representative realizations
  • risk attitude
  • robust optimization

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