CO₂ geological storage is considered as an important measure to reduce anthropogenic CO₂ emissions to the atmosphere for addressing climate change. The key prerequisite for long-term CO₂ geological storage is the sealing capacity of caprock. This study investigates the evolution of sealing capacity of caprock induced by geochemical reactions among CO₂, water and caprock using TOUGHREACT code based on the Heshanggou Formation mudstone at the Shenhua Carbon Capture and Storage (CCS) demonstration site of China. The results show that the self-sealing phenomenon occurs in the lower part of the caprock dominated by the precipitation of dawsonite, magnesite, siderite, Ca-smectite and illite. While the self-dissolution occurs in the upper part of caprock mainly due to the dissolution of kaolinite, K-feldspar, chlorite and Ca-smectite. Sensitivity analyses indicate that the precipitation of dawsonite, magnesite, siderite is highly advantageous leading to self-sealing of caprock, with albite and chlorite dissolution providing Na⁺, Mg²⁺ and Fe²⁺. The dissolution of K-feldspar dominates illite precipitation by providing required K⁺, and albite affects Ca-smectite precipitation. The self-sealing and self-dissolution of caprock are enhanced significantly with increasing temperature, while the effect of salinity on caprock sealing capacity is negligible perhaps due to the low salinity level of formation water.

CO₂ geological storage combined with deep saline water recovery technology (CO₂-EWR) is one of the most effective ways to reduce carbon emissions. Due to the complex structural features, it is difficult to use CO₂-EWR technology in Huaiyin Sag, Subei basin, East China. In this study, the multi-source information superposition evaluation technology of GIS was utilized for the selection of CO₂ storage sites and water displacement potential target areas in this area, which mainly focused on the sandstone reservoirs of Cretaceous Pukou Formation. Based on the results, a three-dimensional injection–extraction model was established. Various scenarios with different production/injection well ratios (PIR) were simulated. Research has shown that the suitability of the surrounding site of Huaiyin Power Plant can be divided into two levels: relatively suitable and generally suitable; the area in the generally suitable level accounts for more than 80%. At a PIR of 1, CO₂ is distributed asymmetrically, whereas at PIRs of 2 or 4, CO₂ is distributed symmetrically. When the number of production wells is constant, a higher injection rate results in a faster expansion rate of the CO₂ plume. This means that the time taken for the CO₂ plume to reach the production wells is shorter. Reservoir pressure increases rapidly after more than 60 years of CO₂ injection at lower PIR values, while at higher PIRs, reservoir pressure eventually stabilizes. Higher PIR values correspond to higher gas saturation, indicating a greater capacity for CO₂ sequestration with more producing wells. When PIR = 4, the total CO₂ injection increased by 55.73% compared to PIR = 1. However, the extraction of saline decreases with an increase in the number of producing wells, resulting in a decrease in replacement efficiency. This study provides a theoretical basis and technical support for the implementation of large-scale CO₂-EWR engineering and technology demonstration in this region.

Geological storage of carbon dioxide is receiving more and more attention as one of the efficient carbon reduction technologies, as China’s carbon-neutral strategic plan moves forward. There is an increasing demand for more effective and thorough methodologies to assess the potential of CO₂ storage in deep saline aquifers. This study proposes a method for evaluating the geological storage potential of CO₂ in deep saline aquifers and constructs an automatic evaluation system for the comprehensive potential of CO₂ geological storage using ArcGIS Model Builder visual modeling technology. The automatic evaluation system consists of four functional parts: information collating and database constructing, data pre-processing, model building evaluation and result validation evaluation. First, structured and unstructured data including underlying geology, tectonic geology, oil and gas geology, and drilling data are collated and established in a geodatabase. Second, pre-processing models of the deep saline reservoir-caprock data are established based on the analysis of the geological evolution history of the study area to determine the effective storage thickness, effective porosity, and the influence range of faults; kriging methods are then used to realize the spatial interpolation of the evaluation parameters. Third, the volume coefficient method is adopted to construct the underground storage space model and to establish the density distribution model of the supercritical CO₂ with nonlinear function while taking into account four evaluation factors (i.e. area, effective porosity, effective thickness, effective coefficient) and two limiting factors (i.e. fault, burial depth). Finally, the geological storage potential of CO₂ in the study area is evaluated with the classification of the potential level and compared with the numerical simulation results to verify the model’s accuracy. The model is first applied in this paper using a suitable target in China as a case study. The results show that this target area’s anticipated storage potential value reaches 52.557 Mt. The total precision error, according to a comparison of the numerical simulation results, is 8.20%. Based on the results obtained, it can be concluded that the automatic GIS-based modeling approach is suitable for a comparable study of potential evaluation of CO₂ geological storage in deep saline aquifers.