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The development of a geothermal system involves changes in the temperature field (T), seepage field (H), stress field (M), and chemical field (C) and the influence among them and injecting the heat extraction working fluid into the injection well that flows (migrating) through natural fractures and exchanges heat with the geothermal high-temperature rock. At the same time, the injection of low-temperature working fluid will induce thermal stress, resulting in changes in the reservoir temperature field and stress field. To study the influence factors and influence degree of heat production performance and mining life under multi-field coupling in the process of thermal reservoir development, based on THMC multi-field coupling numerical simulation software, this paper deeply studies the control differential equations and boundary coupling conditions of rock mass (fracture) deformation, seepage, heat exchange, the chemical reaction, and other processes based on the numerical solution method of the discrete fracture network model, simulating heat production capacity during the deep geothermal resource extraction process. The reservoir geological model analysis and generalization, parameter setting, boundary conditions, initial condition settings, mesh generation, and other steps were carried out in turn. Two different heat extraction working fluids, water, and CO2 were selected for numerical simulation in the mining process. The changes in the thermal reservoir temperature, net heat extraction rate, and SiO2 concentration during the thirty years of systematic mining were compared. The results show that CO2 has a better heat extraction effect. Finally, the reservoir thermal conductivity, heat capacity, well spacing, injection temperature, fracture spacing, fracture permeability, fracture number, fracture length, and other parameters were set, respectively. The parameter variation range was set, and the parameter sensitivity analysis was carried out. The numerical simulation results show that the engineering production conditions (injection temperature, well spacing) have little effect on the thermal efficiency and mining life, and the properties of fractures (fracture permeability, fracture number, fracture length) have a great influence. [ABSTRACT FROM AUTHOR]

There are rich geothermal resources in China and they are widely distributed. After years of continuous exploration and production, most of the shallow geothermal resources have been explored and the current exploration mainly focuses on deep ones. Among a great many geophysical exploration methods, seismic survey is the most effective means of geothermal resource exploration and production, but its weak seismic reflection signal, low S/N ratio and poor imaging of thermal reservoirs due to the seismic geological conditions restrict the production and utilization of deep geothermal resources. It considers through the analysis of the geophysical characteristics of the thermal reservoir that the main causes for the weak seismic reflection signals from deep thermal reservoirs are (1) the shielding effect of the strong wave impedance interface between the thermal reservoir and the caprocks; (2) the small reflection coefficient inside the thermal reservoir; and (3) the serious absorption and attenuation of high-temperature fluids such as hydrothermal fluids and steam in the thermal reservoirs by seismic waves. Accordingly, a series of seismic data acquisition technologies are proposed based on the high-precision vibroseis low-frequency shooting, high-sensitivity geophones long-spread receiving and small bin size highfold technologies, and their application in the seismic acquisition of dry-hot rocks (HDR) in Gonghe Basin, Qinghai, shows a very good application effect. [ABSTRACT FROM AUTHOR]

Hot dry rocks, as clean and abundant sources of new energy, are crucial in the restructuring of energy. Predicting the temperature field of hot dry rocks is of great significance for trapping the target areas of hot dry rocks. How to use limited logging data to predict the temperature field within a work area is a difficulty faced in hot dry rock exploration. We propose a method to predict the hot dry rock temperature field (using seismic inversion results). The relationship between porosity and transverse wave velocity was established with petrophysical modeling. The difference in porosity calculated from the density and transverse wave velocity was incorporated in the seismic inversion results to find the thermal expansion and predict the temperature field. We applied the method to predict the temperature of hot dry rocks in the Gonghe Basin. The results showed that the temperature in the northeast work area was higher than in the southwest area at the same depth, and a depth of 150 °C of the hot dry rock reservoir was shallower. The thermal storage cover was analyzed from the geological stratigraphic data of the Gonghe Basin. The thermal storage cover in the northeastern part was thicker than in the southwestern part and had better thermal insulation, which is consistent with the prediction of the temperature field. [ABSTRACT FROM AUTHOR]

For the safe development and utilization of hot dry rock resources, it is essential to understand the distribution characteristics of underground faults. However, the commonly used reflection attribute analysis method has an insufficient resolution, and the diffraction attribute analysis method is affected by multiple solutions. Moreover, both are highly dependent on the interpreters' experience and take a long time. Therefore, based on the classical U-Net model, a diffraction attribute fusion model (DAF-U-Net) with 27-layer convolution is proposed. The DAF-U-Net network takes four-channel diffracted attributes as an input and underground fracture distribution as an output. The new network adds a spatial attention and channel attention mechanism to improve the positioning and extraction ability of the U-Net model for the attribute characteristics of diffractions. After optimizing the diffraction attributes of hot dry rock slices in the Gonghe basin, Qinghai, the slices are input into the network to train the model. According to the prediction and identification results of the network model, the DAF-U-Net network has a high reliability in predicting fracture distributions. It has a specific reference role in the subsequent exploitation of hot dry rock. [ABSTRACT FROM AUTHOR]

Hot dry rock (HDR) geothermal energy, as a clean and renewable energy, has potential value in meeting the rapid demand of the social economy. Predicting the temperature distribution of a subsurface target zone is a fundamental issue for the exploration and evaluation of hot dry rock. Numerical finite–element simulation is currently the mainstream method used to study the variation in underground temperature fields. However, it has difficulty in dealing with multiple geological elements of deep and complex hot dry rock models. A Unity networking for hot dry rock temperature (HDRT–UNet) is proposed in this study that incorporates the matrix rock temperature field equation for relating the three parameters of density, specific heat capacity and thermal conductivity. According to the numerical geological structures and rock parameters of cap rocks, faults and magma intrusions, a new dataset simulated by the finite element method was created for training the HDRT–UNet. The temperature simulation results in the Gonghe basin show that the predicted temperatures within faults and granites were higher than their surrounding rocks, while a lower thermal conductivity of the cap rocks caused the temperature of overlying strata to be smaller than their surrounding temperature field. The simulation results also prove that our proposed HDRT–UNet can provide a certain evolutionary knowledge for the prediction and development of geothermal reserves. [ABSTRACT FROM AUTHOR]