Co-Optimization of CO2 Storage and Enhanced Gas Recovery Using Carbonated Water and Supercritical CO2
KAUST DepartmentAli I. Al-Naimi Petroleum Engineering Research Center (ANPERC)
Energy Resources and Petroleum Engineering Program
Physical Science and Engineering (PSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/673317
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AbstractCO2-based enhanced gas recovery (EGR) is an appealing method with the dual benefit of improving recovery from mature gas reservoirs and storing CO2 in the subsurface, thereby reducing net emissions. However, CO2 injection for EGR has the drawback of excessive mixing with the methane gas, therefore, reducing the quality of gas produced and leading to an early breakthrough of CO2. Although this issue has been identified as a major obstacle in CO2-based EGR, few strategies have been suggested to mitigate this problem. We propose a novel hybrid EGR method that involves the injection of a slug of carbonated water before beginning CO2 injection. While still ensuring CO2 storage, carbonated water hinders CO2-methane mixing and reduces CO2 mobility, therefore delaying breakthrough. We use reservoir simulation to assess the feasibility and benefit of the proposed method. Through a structured design of experiments (DoE) framework, we perform sensitivity analysis, uncertainty assessment, and optimization to identify the ideal operation and transition conditions. Results show that the proposed method only requires a small amount of carbonated water injected up to 3% pore volumes. This EGR scheme is mainly influenced by the heterogeneity of the reservoir, slug volume injected, and production rates. Through Monte Carlo simulations, we demonstrate that high recovery factors and storage ratios can be achieved while keeping recycled CO2 ratios low.
CitationOmar, A., Addassi, M., Vahrenkamp, V., & Hoteit, H. (2021). Co-Optimization of CO2 Storage and Enhanced Gas Recovery Using Carbonated Water and Supercritical CO2. Energies, 14(22), 7495. doi:10.3390/en14227495
SponsorsThe authors thank Computer Modelling Group (CMG) Ltd. for providing the academic license of CMG simulators to the King Abdullah University of Science and Technology (KAUST).
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