The enrichment of geothermal water resources is constrained by numerous factors. To avoid the waste of human, material, and resource costs caused by uninformed exploitation, it is essential to rationally delineate zones with potential geothermal water resources. This paper takes the mid-deep layered geothermal reservoir in Songyuan City, China, as an example. Based on geothermal geological conditions, geophysical conditions, circulation conditions, and heat source conditions, a multi-information-driven model was adopted to identify potential geothermal areas. Based on the factor independence test, the dataset of factors for this study was determined as follows: The Gutenberg-Lister B values, distance to faults, distance to the major grabens, land surface temperature, distance to the water system, and distance to the basement faults. Based on the geographic information system (GIS) supported the traditional information-driven model and the improved weighted information-driven model, the geothermal prediction maps were established using the impact factors maps. The prediction maps categorized the potential geothermal areas in Songyuan City into three levels: better potential area, medium potential area, and poor potential area. The better potential areas of the two models accounted for 10% and 12.4% of the total area, respectively, and are primarily located in the central-western sector, notably in the vicinity of Qian'an County and Ningjiang County. Furthermore, uncertainty analysis indicates that the two information-driven models exhibit a high level of consistency in over 97% of the region, with observable uncertainties confined mainly to the areas along the Second Songhua River and the northern mainstream of the Songhua River. The model comparison results show that the improved weighted information-driven model proposed in this study provides more accurate evaluation results than the traditional information-driven model. This study is expected to provide a foundational framework for the development and utilization of geothermal resources in Songyuan City, while also offering further exploration directions for medium-deep geothermal surveys at a regional scale.
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