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| | 講演要旨(英文) | | It is hard to know a detailed exact distribution of fractures in a rock mass based on only limited information. Recently, a statistical stochastic model of fracture distribution is adopted for interpretation of geophysical data. In this study, we focus on the discrete fracture network (DFN) modeling and rock-physics modeling, jointly used to interpret geophysical data, such as electrical resistivity data, for hydraulic studies. Our target area in this study is the fractured granite exposed along an underground gallery in the Mizunami Underground Research Laboratory in the Tono area, central Japan. The DFN model can be constructed from geological information (e.g., fracture density), then can be converted to resistivity model based on several assumptions. The assumed parameters can be confirmed by electrical resistivity data obtained based on DC resistivity surveys. Finally, based on Archie's and Kozeny-Carman equations, a distribution of hydraulic permeability of fractures can be estimated from electrical resistivity data. The inferred hydraulic permeability is thought to be rational compared with in-situ hydraulic permeability measured by hydraulic tests in the study area. We propose the applicability of our stochastic rock-physics model to predict hydraulic permeability in a fractured rock mass. |
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