# Full Information Numerical Simulation of Two-Dimensional Steady Ground Temperature Field  
[PERSON]  
1 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China; [EMAIL_ADDRESS] (F.J.); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.T.) [PERSON]  
1 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China; [EMAIL_ADDRESS] (F.J.); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.T.) [PERSON]  
1 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China; [EMAIL_ADDRESS] (F.J.); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (H.T.) [PERSON]  
1 Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China; [EMAIL_ADDRESS] (H.T.) Footnote 1: email: {[EMAIL_ADDRESS], [EMAIL_ADDRESS], jing. Current approaches to solving geothermal field problems primarily include analytical methods, numerical methods, and machine learning techniques integrated with geological and geophysical features to predict geothermal resource distribution. However, in practical scenarios, geothermal models are often highly complex, and analytical solutions can only be derived by neglecting numerous secondary processes and mutual interactions. Machine learning requires extensive real-world geological datasets to train models for achieving accurate and rapid predictions of geothermal resource distribution [2; 3]. In contrast, numerical methods are more widely applied in practical problems due to their capability to adapt to complex geological conditions. The numerical simulation methods of geothermal field mainly include the finite element method, finite difference method, and finite volume method. [PERSON] used the finite element method to explore the influence of the convective effect on the distribution of the ground temperature field in groundwater [4]. [PERSON] proposed two finite element algorithms suitable for the numerical simulation of geothermal reservoirs [5], and the comparison with the finite difference method showed that the proposed algorithms had certain competitiveness. [PERSON] systematically described the application of the finite element method in the numerical simulation of geothermal field [6], and analyzed the heat transfer process by using the finite element method; in Chapter 8 of the book Finite Element Method in Geophysics [7], [PERSON] derived the relevant calculation formulas of the finite element method of geothermal field in detail; [PERSON] constructed a new weight function on the basis of the linear basis function of the standard finite element method to eliminate the numerical oscillation caused by the convection term [8; 9], suggesting that the characteristic line method and the improved characteristic line method were affected by grid generation and time step selection. [PERSON] successfully simulated the evolution process of the magmatic reservoir by establishing a two-dimensional finite difference thermodynamic model [10]. [PERSON] proposed a new thermal reservoir modeling method [8], which realized the numerical simulation of the heat transfer process in geothermal reservoirs by using the finite difference discrete grid. [PERSON] used the finite volume method to study the three-dimensional model of the Las Tres Virgenes geothermal system in Mexico [11]. These methods are all solved in the spatial domain. When the medium is large in scale, it is often necessary to carry out fine subdivision of the model to achieve high accuracy, and the number of subdivision units is large, the memory requirement is large, and the calculation time is long.