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.