Quantitative Characterization and Evaluation on Favorable Structure of CO2 Geological Storage in Oil-Gas Bearing Area

CO2 geological storage is one of the most effective approaches to reduce large-scale CO2 emissions. The capacity of CO2 geological storage is substantial enough to contribute significantly to carbon neutrality. Many favorable structures in oil-gas bearing areas serve as ideal traps for CO2 storage. However, current studies have primarily focused on qualitative descriptions of these structures. This paper proposes a quantitative characterization method to evaluate the suitability of these traps for underground CO2 sequestration. The inverse simulation method is applied to optimize the parameters of anticlinal structures in CO2 geological storage. The core idea is to build a series of anticlinal models with variable geological parameters, including effective thickness, dip angle, and cover area. A uniform set of injection-production parameters is input, and batch numerical simulation tests are conducted to determine the optimal geological parameters. Based on these simulation results, a sequestration structural factor is deduced to identify the optimal traps. The results show that an inflection point is evident in the curve diagram between the storage ratio and the structural factor, which is the product of the dimensionless thickness, dimensionless area, and tangent angle. This point can serve as a critical value to differentiate favorable structures. The critical value is found to be 0.20, and traps with a structural factor above this value are considered favorable for underground CO2 sequestration. Furthermore, an optimized method for recognizing favorable structures has been developed. Using this method, an actual geological model with many large-scale traps was built, and the optimized method was applied to rank the target traps, differentiating favorable and unfavorable structures. The inverse simulation method, which is significantly different from conventional numerical simulation methods, provides a novel way to evaluate geological storage structures and could be beneficial for promoting the deployment of CCUS projects.