Natural fractures play a key role in controlling fluid flow and heat extraction in carbonate geothermal reservoirs. Due to the high degree of rock fragmentation and strong seismic wave absorption at the top of the carbonate formation, it is difficult to identify the distribution of natural fractures inside the carbonate formation using conventional seismic methods. Additionally, the heterogeneous distribution of permeability and porosity in the geothermal reservoir remains a challenge for the numerical simulation of the geothermal production process. To overcome these difficulties, this study uses the damage mechanics approach to characterize the distribution of natural fractures generated by orogeny in the Wumishan Formation of the JR block. Based on the derived damage field, a finite element model for the geothermal reservoir with spatially heterogeneous porosity was constructed, and empirical relationships between damage variable values and values of permeability of the fractured geothermal reservoir were established. A thermo-hydro-mechanical (THM)-coupled finite element model was then employed to evaluate well transmissibility and porous flow behavior under specified injection–production pressure conditions. The flow capacities of 18 wells were quantified and ranked, providing a basis for optimizing the injection–production well layout. Optimization of well locations and injection–production functions was conducted considering alternating well placement, total flow balance, and target well ratios (1:1 and 3:2). By adjusting well functions and locations, the total injection and production rates were balanced under the given pressure conditions, with the total injection and production capacities increased by 12.1% and 6.73%, respectively. The error tolerance used for convergence in numerical calculation is 2% for the THM model. Numerical results of temperature contours indicate the following: (1) There is no risk of thermal breakthrough with the planned design. (2) The temperature at the wellhead of production wells ranges from 92 °C to 105 °C. The results demonstrate that the combined application of damage mechanics and THM-coupled modeling provides an effective framework for accurately characterizing natural fractures and optimizing injection–production strategies in fractured carbonate geothermal reservoirs.

The Wumishan Formation carbonate buried-hill reservoir in Hejian, Jizhong Depression, is a key geothermal reservoir where natural fractures control high-yield production. However, sparse control wells and seismic attribute non-uniqueness render conventional manual fusion subjective, while complex models tend to overfit under small-sample conditions. This study presents a well-controlled seismic multi-attribute fusion method that uses four-level (I–IV) well-log reservoir fracture interpretation as supervised calibration labels to predict 3D reservoir fracture distribution. Using 3D seismic data and comprehensive well-log fracture interpretation from wells JR1-1 and JR1-6, more than ten fracture-sensitive attributes were computed and systematically compared against well fracture grades through well-seismic calibration. Three complementary attributes—high-resolution eigenvalue coherence, maximum principal component curvature, and maximum likelihood similarity enhancement—were selected as primary fusion channels. An ordinal logistic regression model was then trained on the well-calibrated samples, jointly solving feature weights and ordinal cumulative classification thresholds within a unified likelihood framework to map seismic features onto the four-level reservoir fracture classification. Application to the target block shows that data-driven attribute weights are consistent with expert manual weights, and leave-one-well-out cross-validation yields 80.5–84.1% reproducibility (Kappa = 0.744). The resulting reservoir fracture distribution exhibits pronounced spatial zonation and vertical segmentation, with dominant fractures concentrated at structural highs on the reservoir top surface. This method provides a robust, well-controlled framework for natural fracture characterization and can guide geothermal well target optimization and reservoir stimulation design in deep geothermal fields.