Evaluation of Geothermal Resource Potential Based On Geographic Information System (gis) Integration Models: Case Study of Xiong’An New Area, North China

To alleviate the energy depletion and environmental pollution, it is urgent to promote the development of renewable energy. As one of the most realistic and competitive renewable energy, geothermal resources have the advantages of abundant reserves, wide distribution, stable supply, and high utilization efficiency. The development of geothermal resources is increasingly valued by governments and industries. Recognizing the favorable geothermal areas is conducive to reduce the economic risk of geothermal exploitation projects. This work is based on a case study from Xiong’an New Area, North China, which is rich in geothermal fluids in carbonate reservoirs. Three spatial data integration models (the Weights of Evidence Model, the Weighted Information Content Model and the Index Overlay Model) are established in Geographic Information System (GIS) environment to evaluate the geothermal resource potential of Xiong’an New Area. Faults distribution, Bouguer gravity anomaly, magnetic anomaly, geothermal gradient and terrestrial heat flow are five geothermal evidence factors. Based on the five criteria layers generated from the evidence factors, the geothermal favorability map is developed by analyzing the spatial association between the known geothermal occurrences and the evidence factors. The performance of the model is evaluated by kappa coefficient analysis, success index analysis and receiver operating characteristic curve analysis. The results reveal that the Weighted Information Content Model is more effective and accurate. The geothermal favorability map is classified into four classes. The extremely high favorable area and the high favorable area in Xiong’an New Area cover 105.78 km2 and 145.27 km2, accounting for 6% and 8% of the total area, respectively. Moreover, the amount of thermal energy in four classes of geothermal favorable areas is also calculated by the unit volumetric method. The insights from this study provide a low-cost and efficient approach for evaluating the geothermal potential of regions lacking sufficient exploration data.