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Fluid flow in fractures controls subsurface heat and mass transport, which is essential for developing enhanced geothermal systems and radioactive waste disposal. Fracture permeability is controlled by fracture microstructure (e.g. aperture, roughness, and tortuosity), but in situ values and their anisotropy have not yet been estimated. Recent advances in geophysical techniques allow the detection of changes in electrical conductivity due to changes in crustal stress and these techniques can be used to predict subsurface fluid flow. However, the paucity of data on fractured rocks hinders the quantitative interpretation of geophysical monitoring data in the field. Therefore, considering different shear displacements and chemical erosions, an investigation was conducted into the hydraulic-electric relationship as an elevated stress change in fractures. The simulation of fracture flows was achieved using the lattice Boltzmann method, while the electrical properties were calculated through the finite element method, based on synthetic faults incorporating elastic-plastic deformation. Numerical results show that the hydraulic and electrical properties depend on the rock's geometric properties (i.e. fracture length, roughness, and shear displacement). The permeability anisotropy in the direction parallel or perpendicular to the shear displacement is also notable in high stress conditions. Conversely, the permeability -conductivity (i.e., formation factor) relationship is unique under all conditions and follows a linear trend in logarithmic coordinates. However, both matrix porosity and fracture spacing alter this relationship. Both increase the slope of the linear trend, thereby changing the sensitivity of electrical observations to permeability changes. (c) 2024 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

期刊论文 2024-11-01 DOI: 10.1016/j.jrmge.2024.08.023 ISSN: 1674-7755
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