This study presents an approach to screen sedimentary basins for their CO₂ geological storage potential based on a 3D grid with geological data. The 3D grid-based screening was applied to the Gunsan Basin, offshore Korea, for selecting potential sub-basins. Six sub-basins were recognized and prioritized using a set of quantifiable criteria, reflecting storage capacity, geological risk, and socio-economic aspects. Nine criteria were defined and weighed to reflect local priority and geological characteristics. Every grid cell was populated with geological and geometrical properties, scored and ranked for each criterion. Typically, the storage capacity is used for evaluating the storage potential of a basin, which, however, was not estimated here due to the low quantity of available data. Instead, the capacity potential was quantified by combining the pore volume and Gravitational Number for each grid cell. Mean score values for each sub-basin indicate that the East Sub-basin is the most promising region, containing a suitable aquifer with an estimated storage capacity of a few hundreds of MtCO₂. Therefore, we suggest that the Gunsan Basin is suitable for implementing a CCS program with an injection rate of 4 MtCO₂/year for 30 years. Moreover, we suggest that the 3D grid-based screening process could be used to quickly screen different sub-basins or potential aquifers by depth.

这项研究提出了一种筛选沉积盆地中CO _2的方法基于带有地质数据的3D网格的地质储藏潜力。基于3D网格的筛选已应用于韩国近海的群山盆地，以选择潜在的子盆地。六个子流域使用一套可量化的标准得到认可并确定了优先级，这些标准反映了存储能力，地质风险和社会经济方面。定义并衡量了九项标准，以反映当地的优先级和地质特征。每个网格单元都填充有地质和几何属性，并针对每个标准进行评分和排名。通常，存储容量用于评估盆地的存储潜力，但是由于可用数据量少，因此此处未进行估计。取而代之的是，通过结合每个网格单元的孔体积和重力数来量化容量潜力。₂。因此，我们建议群山盆地适合实施CCS计划，注入速率为4 MtCO ₂ /年，持续30年。此外，我们建议基于3D网格的筛选过程可用于按深度快速筛选不同的子流域或潜在含水层。