Entropy theory-integrated information model for the assessment of geothermal potential: a case study of Tengchong County,Southwest China

Geothermal energy remains a largely undeveloped natural resource because of the high risk associated with its development. An accurate prediction model for easy identification of potential regions can help to lower the risk and cost associated with development. In this study, geothermal potential regions were identified through the relationship between geothermal emergencies and their controlling factors in Tengchong County, China. Publicly available databases for this analysis including epicenters, active faults, Bouguer gravity, Landsat7 Enhanced Thematic Mapper Plus images, the magnetic data and digital elevation model data were extracted as the b-value map, distance to faults map, distance to main grabens map, land surface temperature map, magnetic anomaly map and distance to rivers map, respectively. Based on the platforms within geographic information system, an entropy theory-integrated information model was established to evaluate the geothermal potential sites within the region. Moreover, factor analysis method was applied to test the conditional independence between the map pairs before modeling application. The results of the weighted information model show that the model shows perfect performance in discovering potential geothermal regions. In the final maps, undeveloped or unexploited geothermal regions can be observed along the Mingguang River and Nu River. Undeniably, these models will help to find undiscovered geothermal regions with limited geological information publically available.