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

• Published in: IEEE transactions on geoscience and remote sensing Vol. 61; pp. 1 - 12
• Main Authors: Yu, Nian, Liu, Hanghang, Feng, Xiao, Li, Tianyang, Du, Bingrui, Wang, Chenguang, Wang, Wuji, Kong, Wenxin
• Format: Journal Article
• Language: English
• Published: New York IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Apparent resistivity; Boreholes; Carbon dioxide; carbon dioxide (CO2) storage; Carbon dioxide concentration; Carbon sequestration; Caverns; Computation; Conductivity; Correlation; cross-borehole; Current measurement; Electric fields; Electric potential; Electrical resistivity; Electrodes; Feasibility studies; Finite element method; Imaging; Imaging techniques; Jacobi matrix method; Jacobian matrix; Mathematical models; Monitoring; multilayer model; Rational functions; salt caverns; Storage
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2023.3331421

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 (<inline-formula> <tex-math notation="LaTeX">\rho _{a} </tex-math></inline-formula>), carbon dioxide (CO2) resistivity (<inline-formula> <tex-math notation="LaTeX">\rho _{\text {CO2}} </tex-math></inline-formula>), and the volume of the CO2 storage area (<inline-formula> <tex-math notation="LaTeX">V_{\mathrm {CO2}} </tex-math></inline-formula>). Remarkably, the impact of <inline-formula> <tex-math notation="LaTeX">\rho _{\mathrm {CO2}} </tex-math></inline-formula> on <inline-formula> <tex-math notation="LaTeX">\rho _{a} </tex-math></inline-formula> is found to be more pronounced than that of <inline-formula> <tex-math notation="LaTeX">V_{\text {CO2}} </tex-math></inline-formula>, attributed to the repulsion effect emanating from the high-resistance storage area. A robust linear correlation between <inline-formula> <tex-math notation="LaTeX">\rho _{a} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">V_{\text {CO2}} </tex-math></inline-formula> is identified across various multihorizontal layer models, while the relationship between <inline-formula> <tex-math notation="LaTeX">\rho _{a} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">\rho _{\mathrm {CO2}} </tex-math></inline-formula> adheres to a rational function. The intricate correlation between <inline-formula> <tex-math notation="LaTeX">\rho _{a} </tex-math></inline-formula> 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.