Advancing CO₂ Storage Analysis in Fractured Rocks with Discrete Fracture Network Models

Modeling fluid behavior in fractured rock is essential for geo-resource exploration and geological storage. This study utilizes a Discrete Fracture Network (DFN) approach to evaluate the efficiency of fractured systems in storing supercritical CO₂ (scCO₂). Synthetic fracture networks, generated using the dfnWorks suite (LANL), based on outcrop data, represent a range of fracture densities. Key parameters such as fracture count, volume, porosity, and permeability are statistically analyzed, and their most frequent values are used to create representative DFN models for fluid flow simulations.

Results reveal a direct correlation between increased fracture density and storage capacity, with storage values consistently below 10% of the total injected mass. A Fracture Efficiency Factor (Efr) is introduced, quantifying CO₂ retained in fractures relative to the total injected CO₂. This efficiency reduces theoretical capacity estimates by approximately one order of magnitude, aligning with previous analytical and dynamic reservoir-scale studies (e.g., Nordbotten et al., 2005; Ringrose, 2020; Rutqvist et al., 1998).

This approach enhances CO₂ storage capacity estimates by explicitly accounting for fracture network contributions. While reservoir-scale scCO₂ flow simulations using DFN models remain challenging, this method provides critical insights into the storage potential of fractured media.