Interplay Between Fracture Network Arrangement and Efficiency of CO2 Mineralization in Basaltic Aquifers

Present study investigates how uncertainty in fracture-network architecture and connectivity controls CO2 mineralization efficiency in basaltic formations. A stochastic discrete fracture network (DFN) framework is integrated into a reduced-order hydro-mechanical-chemical (HMC) model for coupled simulation of reactive transport and poroelastic deformation. The reduced-order HMC formulation neglects multiphase flow, aqueous speciation, and secondary mineral reactions to enable computationally tractable stochastic simulations. Validation against observations from the Wallula Basalt Pilot demonstrates that the proposed HMC framework reproduces key features of basalt carbonation, including rapid early-stage mineralization, progressive porosity reduction, nonlinear compaction, and self-limiting permeability evolution. DFN ensembles are generated using Monte Carlo framework constrained by geological characteristics of naturally fractured basaltic systems, including fracture length, orientation, spacing, intensity, and intersection topology. Resulting networks are embedded in HMC simulations to evaluate fluid pressure evolution, rock deformation, porosity attenuation, and carbonate accumulation in geological pore spaces. We evaluate uncertainty associated with fracture-controlled flow pathways and their contribution to HMC feedback during basalt carbonation. Simulation results are analyzed in terms of mineralization patterns, progressive fracture clogging, hydraulic redistribution, and pronounced pore-space reduction within connected fracture clusters. We further employed generalized moment-based global sensitivity analysis to quantify the influence of key DFN descriptors on the temporal evolution of system responses. Results highlight strong nonlinear interaction effects and higher-order variability in system behavior beyond the scope of classical variance decomposition. Fracture-network connectivity is identified as the primary control on mineralization efficiency and uncertainty propagation. Proposed framework can provide a computationally efficient basis for understanding and predicting fracture-controlled CO2 mineralization in naturally fractured basaltic aquifers.