Advancing CO₂ Storage Monitoring via Cross-Borehole Apparent Resistivity Imaging Simulation

Conventional resistivity inversion methodologies encounter constraints in perpetual monitoring owing to the necessity for recurrent measurements. In response, this research leverages a 3-D finite element method to formulate an approximate geometry imaging of cross-borehole resistivity during forward modeling, circumventing the direct computation of Jacobian matrix equations in the electric field. This study meticulously explores the complex relationship among apparent resistivity ( $\rho _{a}$ ), carbon dioxide (CO2) resistivity ( $\rho _{\text {CO2}}$ ), and the volume of the CO2 storage area ( $V_{\mathrm {CO2}}$ ). Remarkably, the impact of $\rho _{\mathrm {CO2}}$ on $\rho _{a}$ is found to be more pronounced than that of $V_{\text {CO2}}$ , attributed to the repulsion effect emanating from the high-resistance storage area. A robust linear correlation between $\rho _{a}$ and $V_{\text {CO2}}$ is identified across various multihorizontal layer models, while the relationship between $\rho _{a}$ and $\rho _{\mathrm {CO2}}$ adheres to a rational function. The intricate correlation between $\rho _{a}$ and CO2 concentration is dissected, offering a quantitative perspective for inferring the resistivity of the CO2 storage area. These findings are further validated through field formation models featuring salt caverns, highlighting the effectiveness of cross-borehole resistivity imaging for CO2 storage monitoring. Beyond enhancing our understanding of subsurface geological behavior, our study underscores the feasibility of using salt caverns for CO2 storage, presenting a pioneering approach towards navigating the monitoring of subsurface CO2 storage.