Thermo-hydro-mechanical modelling of geothermal energy extraction in deep mines in spatially heterogeneous settings

With the increasing demand for mineral and alternative energy resources, as well as the gradual depletion of shallow resources, the exploitation and utilization of mineral resources and geothermal energy in deep strata is an effective way to solve the problem of resource shortage [1]. In recent years, as a new type of resource mining mode, the co-mining of deep mineral and geothermal energy has developed rapidly [2, 3]. This method can make use of the original equipment of the mine for geothermal exploitation. However, the deep co-mining system faces two significant challenges: the first is the significant uncertainty inherent in subsurface properties, while the second is the high levels of geostress and temperature associated with deep mining. These challenges are adding some constraints on the practicality of exploiting such systems and limit the feasibility of deep resource co-mining, so that modelling efforts are needed for actual risk assessment.
Consequently, we developed a Thermo-Hydro-Mechanical (THM) coupling framework for geothermal energy exploitation in deep mines using COMSOL to quantitatively characterize the temperature field of the geothermal system and predict the stress field of the mining system, considering the joint effects of large uncertainties and THM coupling. Through SGeMS, the uncertainty and spatial heterogeneity distribution of porosity are first generated. Then, the uncertainty of the hydraulic parameter [4] (permeability), mechanical parameter [5] (elastic modulus), and thermal parameter [6] (heat capacity and heat conductivity) was derived from the porosity. 500 samples were generated within a given uncertainty range, by means of Monte Carlo simulations. The spatial and temporal distributions of the temperature field of the geothermal system, and the stress field of the mining system were simulated, for each sample with COMSOL. Using the distance-based global sensitivity analysis [6], the most sensitive parameters for deep mining are identified, the heat storage capacity of the system and evolution of the maximum stress ratio are evaluated, including uncertainty.