The growing severity of global climate change has highlighted the importance of CO₂ sequestration as a key strategy for reducing CO₂ emissions and mitigating global warming. To this end, sedimentary basins worldwide contain extensive yet underexplored saline aquifers with substantial sequestration potential for long-term CO₂ sequestration. In this study, the suitability and mechanical responses of CO₂ sequestration in a representative half-graben saline aquifer were systematically unraveled through integrated theoretical analysis and multi-physics-coupled numerical simulations. Key factors, such as temperature, pressure, reservoir properties, and caprock distribution, were evaluated based on well logging and mud logging data. Taking the evaluation results as a basis, optimal reservoir-caprock combinations were identified and classified into three types according to their spatial distribution: Single caprock-reservoir, lower interlayer-caprock-reservoir, and upper interlayer-caprock-reservoir. To simulate the mechanical responses during CO₂ injection and sequestration, corresponding conceptual models were developed. The results indicate that Type Ⅲ reservoir-caprock combinations, featuring upper mudstone interlayers, exhibit the lowest caprock stress, reduced leakage risk and enhanced sequestration security, which should be prioritized in sequestration site selection. Our findings provide valuable insights for selecting safe and effective CO₂ sequestration sites in saline aquifers across regional sedimentary basins.

This study introduces a three-dimensional supervoxel segmentation method to accurately separate solid and fluid phases in X-ray images of porous materials, with applications in energy research. Compared with intelligent segmentation algorithms requiring model training, the proposed method operates as a ready-to-use solution with significantly enhanced efficiency. When benchmarked against conventional approaches such as watershed transformation, our technique demonstrates superior segmentation accuracy. Tested on porous rock and gas diffusion layers under varying wettability, it accurately quantifies fluid saturation, interfacial area, curvature, and contact angles-key parameters for enhanced oil recovery, CO₂ storage, and hydrogen fuel cells. The proposed three-dimensional segmentation method is noise-resistant and annotation-free, improving both the accuracy and efficiency of segmenting diverse micro-structural material datasets and providing reliable measurements of their geometric characteristics.