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Quick Screening of Pareto-Optimal Operating Conditions for Expanding Solvent–Steam Assisted Gravity Drainage Using Hybrid Multi-Objective Optimization Approach

Author

Listed:
  • Baehyun Min

    (Department of Climate and Energy Systems Engineering, Division of Sustainable Systems Engineering, Ewha Womans University, 52 Ewhayeodae-gil, Daehyeon-dong, Seodaemun-gu, Seoul 03760, Korea)

  • Krupa Kannan

    (Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, TX 78712, USA)

  • Sanjay Srinivasan

    (Department of Energy and Mineral Engineering, College of Earth and Mineral Sciences, Pennsylvania State University, University Park, PA 16802, USA)

Abstract

Solvent–steam mixture is a key factor in controlling the economic efficiency of the solvent-aided thermal injection process for producing bitumen in a highly viscous oil sands reservoir. This paper depicts a strategy to quickly provide trade-off operating conditions of the Expanding Solvent–Steam Assisted Gravity Drainage (ES-SAGD) process based on Pareto-optimality. Response surface models are employed to evaluate multiple ES-SAGD scenarios at low computational costs. The surrogate models play a role of objective-estimators in the multi-objective optimization that provides qualified ES-SAGD scenarios regarding bitumen recovery, steam–energy efficiency, and solvent-energy efficiency. The developed hybrid approach detects positive or negative correlations among the performance indicators of the ES-SAGD process. The derived Pareto-optimal operating conditions give flexibility in field development planning and thereby help decision makers determine the operating parameters of the ES-SAGD process based on their preferences.

Suggested Citation

  • Baehyun Min & Krupa Kannan & Sanjay Srinivasan, 2017. "Quick Screening of Pareto-Optimal Operating Conditions for Expanding Solvent–Steam Assisted Gravity Drainage Using Hybrid Multi-Objective Optimization Approach," Energies, MDPI, vol. 10(7), pages 1-21, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:966-:d:104213
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