Quantitative prediction and evaluation of geothermal resource areas in the southwest section of the Mid-Spine Belt of Beautiful China
Zhe Chen, Ruichun Chang, Wenbo Zhao, Sijia Li, Huadong Guo, Keyan Xiao, Lin Wu, Dong Hou, Lu Zou
Abstract
The geothermal resources in the southwest section of the Mid-Spine Belt of Beautiful China are abundant, but the quantitative prediction and evaluation of geothermal resources are very difficult. Based on geographic information system (GIS) and remote sensing (RS) platforms, six impact factors, namely land surface temperature, fault density, Gutenberg–Liszt B value, formation combination entropy, distance to river and aeromagnetic anomaly were selected. Through the establishment of the certainty factor model (CF), weights of the information entropy certainty factor model (ICF) and weights of the evidence certainty factor model (ECF), the geothermal potential in the study area were predicted quantitatively. Based on the ECF results, the six main geothermal resource areas were delineated. The results show that (1) ECF had high prediction accuracy (success index is 0.00405%, area ratio is 0.867); (2) The geothermal resource areas obtained were Ganzi–Ya’an–Liangshan, Panzhihua–Liangshan, Dali–Chuxiong, Nujiang–Baoshan, Diqing–Dali, and Lijiang–Diqing. The results provide a basis for the effective development and utilization of geothermal resources in the southwest section of the mid-ridge belt.