Hierarchical stochastic modeling and optimization for petroleum field development under geological uncertainty

Honggang Wang, Bin Gong

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Real-world simulation optimization (SO) problems entail complex system modeling and expensive stochastic simulation. Existing SO algorithms may not be applicable for such SO problems because they often evaluate a large number of solutions with many simulation calls. We propose an integrated solution method for practical SO problems based on a hierarchical stochastic modeling and optimization (HSMO) approach. This method models and optimizes the studied system at increasing levels of accuracy by hierarchical sampling with a selected set of principal parameters. We demonstrate the efficiency of HSMO using the example problem of Brugge oil field development under geological uncertainty.

Original languageEnglish (US)
Pages (from-to)23-32
Number of pages10
JournalComputers and Industrial Engineering
Volume80
DOIs
StatePublished - Feb 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

Keywords

  • Energy production
  • Numerical optimization
  • Petroleum field development
  • Stochastic and simulation
  • System uncertainty

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