Modeling and Evaluating CO₂ Storage Capacity in Saline Aquifer with Modified Brine Density Using Electrolyte Perturbed-Channel Statistical Associating Fluid Theory

The emission of greenhouse gases, especially carbon dioxide (CO2), is a major contributor to global climate change and the ecological environment. Geological storage of CO2 in deep saline aquifers is currently a widely recognized method due to its stable storage and strong feasibility. The density of brine plays a crucial role in influencing the diffusion and migration of CO2 in brine aquifers. It further affects the long-term stable storage of CO2 in brine. In the existing brine reservoir models, the importance of density calculation is often overlooked. Therefore, the purpose of this study is to develop a long-term storage model with accurate density and evaluate the performance of the CO2 storage potential. First, the electrolyte perturbed-channel statistical associating fluid theory (ePC-SAFT) equation of state was applied in phase equilibrium of the H2O–NaCl and CO2–H2O–NaCl systems. The results were validated against experimental data, demonstrating that ePC-SAFT can effectively describe the phase behavior of these two systems. The density of brine was then modified and incorporated into the numerical simulation model. Simulation results indicated that the stable CO2 storage potential is underestimated by 7.6%. After that, various factors affecting the CO2 storage efficiency were ranked based on different monitoring periods, including the reservoir temperature, residual gas saturation, horizontal permeability heterogeneity, ratio of vertical to horizontal permeability, and pH. The results indicate that different factors have varying degrees of influence on storage efficiency at different monitoring periods and mechanisms. At the end of 1000 years, the impact of residual gas saturation on the efficiency of stable trapping is particularly pronounced. This study provides a theoretical basis for assessing the potential for CO2 storage in saline aquifers and selecting the optimal storage reservoirs.