Objective  Under the strategic background of reaching the goals of peak CO₂ emissions and carbon neutrality, there is an urgent need to address the core issue of geologic CO₂ storage (GCS) siting in the advancement of large-scale GCS deployment. Establishing a decision support platform based on a global GCS case database can provide key data and historical experience references for GCS siting, reduce storage risks and costs, and accelerate industrial layout. Furthermore, the platform can offer a scientific basis for formulating related policies and conducting technological R&D.

Methods  This study proposed and developed a comprehensive evaluation system for GCS siting. This system integrates three core techniques: a case analogy algorithm based on improved cosine similarity, a suitability assessment model relying on fuzzy comprehensive evaluation, and a method for selecting favorable geobodies by combining 3D geological models. By constructing a quantitative case database and linking multi-source parameters, this study established a unified spatial database model. Using the ArcGIS platform, it developed a range of functional modules integrating the comparison and selection of similar cases, the suitability assessment of storage sites, and the selection of favorable geobodies. Consequently, a systematic technical support system for GCS siting was formed.

Results and Conclusions Using the resulting framework, this study developed a decision support platform for quantitative selection of optimal GCS targets, which integrated an improved cosine similarity algorithm, a suitability assessment model based on a random forest algorithm, and 3D geological modeling. Through algorithm-driven systematic scanning of the entire data volume, this platform significantly enhances the case matching accuracy from qualitative to quantitative and improves the objectivity of geobody evaluation, effectively reducing the subjective bias and limited vision inherent in traditional manual methods. This platform enables a unified quantitative evaluation and hierarchical ranking of various trap types such as anticlines and fault blocks, substantially improving both the efficiency of GCS target identification and the comparability of results. The practical application in the Gaoyou Sag within the Subei Basin demonstrates that this platform can provide precise, efficient digital solutions that provide direct support for GCS siting, thereby significantly enhancing the scientific rigor and prospective planning for large-scale CO₂ storage deployment.