Pore Network Modelling to Predict CO2 Injection Efficiency

According to previous research results that carbon dioxide (CO2) emitted through various industrial activities causes global warming, interest in carbon dioxide storage is increasing. Carbon capture and storage (CCS) in the ground requires geotechnical understanding, such as rock stability and fluid flow in porous media. The injection efficiency of CO2 varies depending on the CO2 state, the type and concentration of additives, and the pore geometry. In this study, we developed a pore network model to predict CO2 injection efficiency. Additionally, we validated the pore network model compared with the micromodel injection test with a similar condition. We conduct a sensitivity analysis of CO2 injection efficiency concerning the above factors based on the developed pore network model. The analysis revealed that the interfacial tension and contact angle characteristics of the additive resulted in an increase in injection efficiency, consequently leading to a reduction in capillary pressure. A pore network model developed in this study is anticipated to predict the efficiency of CO2 injection based on the ground conditions.