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Multi-objective optimization of WAG injection using machine learning and data-driven Proxy models

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  • Bocoum, Alassane Oumar
  • Rasaei, Mohammad Reza

Abstract

In complex optimization processes such as CO2-water alternating gas (CO2-WAG), several iterative steps are needed before finding an optimal or sub-optimal set of solutions. This leads to time-consuming operations, especially when the simulation is run with a compositional simulator. Proxy models have been used to tackle this issue as they can replicate efficiently and accurately reservoir simulators in specific studies. However, the construction of such a proxy model, its basic database in particular, differs according to the designer and the objective function(s).

Suggested Citation

  • Bocoum, Alassane Oumar & Rasaei, Mohammad Reza, 2023. "Multi-objective optimization of WAG injection using machine learning and data-driven Proxy models," Applied Energy, Elsevier, vol. 349(C).
    • Handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923009571
    DOI: 10.1016/j.apenergy.2023.121593
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    References listed on IDEAS

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    1. Pål Østebø Andersen & Jan Inge Nygård & Aizhan Kengessova, 2022. "Prediction of Oil Recovery Factor in Stratified Reservoirs after Immiscible Water-Alternating Gas Injection Based on PSO-, GSA-, GWO-, and GA-LSSVM," Energies, MDPI, vol. 15(2), pages 1-35, January.
    2. Menad Nait Amar & Noureddine Zeraibi & Ashkan Jahanbani Ghahfarokhi, 2020. "Applying hybrid support vector regression and genetic algorithm to water alternating CO2 gas EOR," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(3), pages 613-630, June.
    3. Si Le Van & Bo Hyun Chon, 2017. "Applicability of an Artificial Neural Network for Predicting Water-Alternating-CO 2 Performance," Energies, MDPI, vol. 10(7), pages 1-20, June.
    4. You, Junyu & Ampomah, William & Sun, Qian, 2020. "Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework," Applied Energy, Elsevier, vol. 279(C).
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