Influencing Factors of the Carbon Sequestration Coefficient in Saline Aquifers--Based on Multiphase Flow Displacement Experiments

Wentao Zhao¹Chenglong Zhang^2*Jing Tieya¹Junbin Zhao^1,3Jian Zhang¹Wei Mingyi^4,5Juan Zhou¹Lei Fu^6*

• ¹China Huaneng Clean Energy Research Institute, Beijing, China
• ²China Geological Survey Center for Hydrogeology and Environmental Geology Survey, Baoding, China
• ³Shanxi Institute of Technology, Yangquan, China
• ⁴Inner Mongolia University of Technology, Hohhot, China
• ⁵National Renewable Energy Laboratory, Golden, United States
• ⁶China Geological Survey, Beijing, China

The volumetric method is the primary approach for calculating geological CO2 storage potential, with its accuracy largely dependent on the pore volume of reservoir rocks and the effective storage coefficient. While the precision of reservoir rock pore volume can be enhanced through more sophisticated geological exploration techniques, the current selection of effective storage coefficients lacks a theoretical foundation. Thus, obtaining a more accurate effective storage coefficient is crucial for improving the evaluation precision of CO2 geological storage potential. To explore the factors influencing the effective carbon sequestration coefficient in saline aquifers and accurately assess their storage potential, 9 sets of multiphase flow core displacement experiments were conducted using orthogonal design, with porosity, confining pressure, and pressure difference as variables. The results indicate that among these 3 factors, porosity has the most significant impact on maximum residual CO2 saturation. Qualitative analysis of water migration in cores during displacement was performed using nuclear magnetic resonance (NMR) T2 curves, revealing a close correlation between water movement and pore structure: water in mesopores and macropores is preferentially displaced, whereas water in nanopores and micropores is more resistant to displacement. Additionally, NMR was employed to analyze the maximum residual CO2 saturation of artificial cores under different conditions, leading to the establishment of a multiple linear regression equation for maximum residual CO2 saturation. By incorporating the volume coefficient derived from numerical simulations, the geological CO2 storage coefficient for actual engineering sites can be estimated.