Local capillary trapping (LCT) of CO₂ is caused by the intrinsic heterogeneity of storage aquifers. It is computationally intensive to model LCT using conventional reservoir flow simulators. This work proposes a fast proxy method. We decouple the LCT modeling into two parts: permeability-based flow simulation using a connectivity analysis, and identification of local capillary traps (capillary entry pressure-based) using a geologic criterion. The connectivity analysis is employed to rapidly approximate CO₂ plume evolution through estimating the arrival time of CO₂. This analysis uses the geostatistical realization of permeability fields as input. The geologic criteria algorithm is used to estimate the potential local capillary traps from a given capillary entry pressure field. This field, through the Leverett j-function, is correlated to the permeability field used in the connectivity analysis. We then quantify the total volume of local capillary traps identified within the capillary entry pressure field that can be filled during CO₂ migration. We conduct several simulations in the reservoirs with different levels of heterogeneity under various injection scenarios. We demonstrate the reservoir heterogeneity affects the optimal injection rate in maximizing LCT during CO₂ injection. This work enhances our understanding of the effects of injections strategies on LCT.

CO _2的局部毛细管捕集（LCT）是由储层含水层的固有异质性引起的。使用常规油藏流量模拟器对LCT进行建模需要大量的计算。这项工作提出了一种快速代理方法。我们将LCT建模分为两个部分：使用连通性分析的基于渗透率的流动模拟，以及使用地质标准识别局部毛细管阱（基于毛细管进入压力）。通过估计CO ₂的到达时间，采用连通性分析来快速估算CO ₂羽流的演化。该分析使用渗透率场的地统计学实现作为输入。地质标准算法用于根据给定的毛细管入口压力场估算潜在的局部毛细管阱。通过Leverett j函数，该字段与连通性分析中使用的渗透率字段相关。然后，我们对在CO ₂迁移过程中可以填充的毛细管入口压力场内确定的局部毛细管阱的总体积进行量化。我们在不同注入情况下，在具有不同非均质性水平的油藏中进行了几次模拟。我们证明了油藏的非均质性会在CO ₂最大化LCT的过程中影响最佳注入速率注射。这项工作增进了我们对注射策略对LCT效果的理解。