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

Energies

卷:10

Baehyun Min¹  Sanjay Srinivasan²  Krupa Kannan³ 

[1] 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;

[2] Department of Energy and Mineral Engineering, College of Earth and Mineral Sciences, Pennsylvania State University, University Park, PA 16802, USA;

[3] Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, TX 78712, USA;

关键词: oil sands;    trade-off;    ES-SAGD;    Pareto-optimality;    surrogate model;   

DOI  :  10.3390/en10070966

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown