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Production Well Placement and History Matching by Hyperparametric Optimization and Machine Learning

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Abstract

This article explores methods for resolving two practical issues in reservoir engineering: discovering an optimal position for the production well on a grid, and recovering unknown fracture position based on the historical production data. To speed up the conventional approach (numerical simulation and the full grid search), we assess application of optimization techniques from the Hyperopt package as well as several machine learning models.

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ACKNOWLEDGMENTS

We would like to thank Yulia Ershova (Gubkin University) and Ilya Ukhin (MSU), the participants of a previous school of Sirius university, for exploring the Hyperopt optimization approach.

Funding

Supported by the Ministry of Science and Higher Education of the Russian Federation (Agreement 075-10-2021-093, Project MMD-RND-2265).

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Authors and Affiliations

  1. Sirius University of Science and Technology, 354340, Sochi, Russia

    A. Donskoi, A. Medvedev, T. Shchudro, K. Terekhov & Yu. Vassilevski

  2. Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences, 119333, Moscow, Russia

    K. Terekhov & Yu. Vassilevski

  3. Sechenov First Moscow State Medical University, 119991, Moscow, Russia

    Yu. Vassilevski

Authors
  1. A. Donskoi
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  2. A. Medvedev
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  3. T. Shchudro
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  4. K. Terekhov
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  5. Yu. Vassilevski
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Correspondence to A. Donskoi, A. Medvedev, T. Shchudro, K. Terekhov or Yu. Vassilevski.

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Donskoi, A., Medvedev, A., Shchudro, T. et al. Production Well Placement and History Matching by Hyperparametric Optimization and Machine Learning. Lobachevskii J Math 45, 166–176 (2024). https://doi.org/10.1134/S1995080224010116

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