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作者机构:Cent S Univ Key Lab Metallogen Predict Nonferrous Met & Geol Minist Educ Changsha Hunan Peoples R China Cent S Univ Sch Geosci & Infophys 932 South Lushan Rd Changsha 410083 Hunan Peoples R China
出 版 物:《MATHEMATICAL GEOSCIENCES》 (数学地质科学)
年 卷 期:2019年第51卷第3期
页 面:319-336页
核心收录:
学科分类:0709[理学-地质学] 081803[工学-地质工程] 07[理学] 08[工学] 0708[理学-地球物理学] 0818[工学-地质资源与地质工程] 0701[理学-数学]
基 金:National Natural Science Foundation of China China Postdoctoral Science Foundation [2017M610507, 2018T110845] Open Research Fund Program of Key Laboratory of Deep Geodrilling Technology, Ministry of Land and Resources [K201701]
主 题:Particle flow code Flat-joint model Particle size distribution Granite Geothermal energy
摘 要:Deep geothermal energy is typically stored in granite reservoirs, and natural granite is highly heterogeneous because it is composed of different sizes and shapes of mineral grains. The mechanical properties of granite are significantly affected by its heterogeneity, and this may affect the fracture initiation pressure and fracture propagation direction during deep geothermal hydraulic fracturing. An extremely important aspect in examining rock heterogeneity corresponds to the relationship between its macromechanical properties and spatial arrangement of its mineral grains. In this study, a flat-joint model (FJM) in a three-dimensional particle flow code is used to examine the effect of heterogeneity [which is associated with the particle size distribution (PSD)] on the macromechanical properties of granite. Macromechanical properties of numerical models are calibrated via laboratory uniaxial compression tests and Brazilian tension tests. The results indicate that the microparameters of the FJM significantly influence rock mechanical properties, and the relationship between the microparameters and macromechanical parameters is affected by PSD.