Multi-objective optimization of CO2 enhanced oil recovery and storage processes in low permeability reservoirs

被引:15
作者
Ding, Shuaiwei [1 ,2 ]
Wen, Fenggang [3 ]
Wang, Ning [3 ]
Zhang, Yuelei [4 ,5 ]
Lu, Ranran [6 ]
Gao, Yanfang [1 ,2 ]
Yu, Hongyan [1 ,2 ]
机构
[1] Northwest Univ, Dept Geol, Shaanxi Key Lab Carbon Neutral Technol, Xian 710069, Peoples R China
[2] Northwest Univ, State Key Lab Continental Dynam, Xian 710069, Peoples R China
[3] Shaanxi Key Lab Carbon Dioxide Sequestrat & Enhanc, Xian 710065, Peoples R China
[4] Chongqing Inst Geol & Mineral Resources, Natl & Local Joint Engn Res Ctr Shale Gas Explorat, Chongqing 401120, Peoples R China
[5] Chongqing Inst Geol & Mineral Resources, Key Lab Shale Gas Explorat, Minist Nat Resources, Chongqing 401120, Peoples R China
[6] Shell Explorat & Prod Co, 701 Poydras St, New Orleans, LA 70139 USA
关键词
Multi-objective optimization; CO2-EOR and storage processes; Co-optimization and synergy-optimization; Multi-objective particle swarm optimization; Low permeability reservoirs; CARBON-DIOXIDE; WELL PLACEMENT; SEQUESTRATION; ALGORITHM; DESIGN;
D O I
10.1016/j.ijggc.2022.103802
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
CO2 enhanced oil recovery (CO2-EOR) is a mature technology to improve production from low permeability reservoirs. The CO2-EOR process has the potential of both improving oil recovery and sequestering large volumes of injected CO2. The performance of CO2 flooding can be affected significantly by CO2 injection modes (continuous gas injection, CGI, or water alternating gas, WAG); types of optimizations (co-optimization or synergy optimization); and several operational parameters, e.g., injection rates, etc. This paper presented an integrated numerical framework for co-optimization and synergy-optimization of CO2-EOR performance and CO2 storage performance in low permeability reservoirs and provided a comparison of CGI and WAG injection modes. In co-optimization, we maximized cumulative oil production (COP) and CO2 storage capacity (CO2SC) simul-taneously (i.e., bi-objective optimization) using multi-objective particle swarm optimization (MOPSO). In synergy-optimization, we maximized a weighted sum of COP and CO2SC (i.e., single objective optimization) using PSO. The optimization results provide significant insight to the decision-making process of coupled CO2-EOR and storage projects when multiple objective functions are considered. We also compared the influence of dimensionless objective functions on the optimization results for different types of optimizations, and the results proved dimensionless objective functions had no impact on the results of co-optimization, but had great influence on the results of synergy-optimization. Considering the tax credit of CO2 stored can obtain higher NPV due to balance out some of the operating cost. Synergy-optimization can approximately obtain partial optimization results of co-optimization when different weight of index is considered.
引用
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页数:11
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