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Optimization of subsurface models with multiple criteria using Lexicase Selection

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  • He, Yifan
  • Aranha, Claus
  • Hallam, Antony
  • Chassagne, Romain

Abstract

Seismic History Matching (SHM) is a key problem in the geosciences community, requiring optimal parameters of a subsurface model that match the observed data from multiple in-situ measurements. Therefore, the SHM problems are usually solved with Multi-Objective Evolutionary Algorithms (MOEAs). This group of algorithms optimize multiple objectives simultaneously, considering the trade-off between objectives. However, SHM requires the solutions that are good on all objectives rather than a trade-off. In this study, we propose a Differential Evolution algorithm using Lexicase Selection to solve the SHM problems. Unlike the MOEAs, this selection method pushes the solutions to perform well on all objectives. We compared this method with two MOEAs, namely Non-dominated Sorting Genetic Algorithm II and Reference Vector-guided Evolutionary Algorithm, on two SHM problems. The results show that this method generates more solutions near the ground truth.

Suggested Citation

  • He, Yifan & Aranha, Claus & Hallam, Antony & Chassagne, Romain, 2022. "Optimization of subsurface models with multiple criteria using Lexicase Selection," Operations Research Perspectives, Elsevier, vol. 9(C).
    • Handle: RePEc:eee:oprepe:v:9:y:2022:i:c:s2214716022000124
    DOI: 10.1016/j.orp.2022.100237
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    References listed on IDEAS

    as
    1. Chassagne, Romain & Aranha, Claus, 2020. "A pragmatic investigation of the objective function for subsurface data assimilation problem," Operations Research Perspectives, Elsevier, vol. 7(C).
    2. Jaejun Kim & Joe M. Kang & Changhyup Park & Yongjun Park & Jihye Park & Seojin Lim, 2017. "Multi-Objective History Matching with a Proxy Model for the Characterization of Production Performances at the Shale Gas Reservoir," Energies, MDPI, vol. 10(4), pages 1-16, April.
    3. Cristina C B Cavalcante & Célio Maschio & Antonio Alberto Santos & Denis Schiozer & Anderson Rocha, 2017. "History matching through dynamic decision-making," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-32, June.
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