A Novel Workflow for Geothermal Prospectively Mapping Weights-of-Evidence in Liaoning Province, Northeast China

Abstract

Geological faults are highly developed in the eastern Liaoning Province in China, where Mesozoic granitic intrusions and Archean and Paleoproterozoic metamorphic rocks are widely distributed. Although the heat flow value in eastern Liaoning Province is generally low, the hot springs are very developed. It is obvious that the faults have significant control over the distribution of hot springs, and traditional methods of spatial data analysis such as WofE (weight of evidence) usually do not take into account the direction of the distribution of geothermal resources in the geothermal forecast process, which seriously affects the accuracy of the prediction results. To overcome the deficiency of the traditional evidence weight method, wherein it does not take the direction of evidence factor into account, this study put forward a combination of the Fry and WofE methods, Fry-WofE, based on geological observation, gravity, remote sensing, and DEM (digital elevation model) multivariate data. This study takes eastern Liaoning Province in China as an example, and the geothermal prospect was predicted respectively by the Fry-WofE and WofE methods from the statistical data on the spatial distribution of the exposed space of geothermal anomalies the surface. The result shows that the Fry-WofE method can achieve better prediction results when comparing the accuracy of these two methods. Based on the results of Fry-WofE prediction and water system extraction, 13 favorable geothermal prospect areas are delineated in eastern Liaoning Province. The Fry-WofE method is effective in study areas where the geothermal distribution area is obviously controlled by the fault. We provide not only a new method for solving the similar issue of geothermal exploration, but also a new insight into the distribution of geothermal resources in Liaoning Province.

Advances in Thermal Infrared Remote Sensing Technology for Geothermal Resource Detection

“…Moreover, the integration of residual gravity anomalies, aeromagnetic data, seismic data, and TIR remote sensing information in the spatial modeling for the geothermal potential assessment is a prevalent methodological approach in geothermal resource exploration [72,[75][76][77]. Abdel et al ( 2018) used various tools such as remote sensing, seismic events, aeromagnetic, and gravity data to evaluate the geothermal potential of the Ferrara Oasis and its applicability for geothermal development in the western desert [78].…”

Analysis of geothermal potential in Hangjiahu area based on remote sensing and geographic information system

“…Rock porosity, faults and fractures in different lithological distribution areas have different development characteristics, which are important factors affecting geothermal (Sang et al, 2017). Geothermal resources may exist in various geological environments composed of limestone, volcanic rock and granite (Moghaddam et al, 2014).…”

“…Water is an ideal medium for heat exchange, and the existence of water is a necessary condition for the development of geothermal fields and hot springs (Sang et al, 2017). The field survey shows that the surface water system can provide sufficient water for hydrothermal activities, which should be regarded as an important factor in geothermal resources exploration.…”

Structural Controls on Copper Mineralization in the Tongling Ore District, Eastern China: Evidence from Spatial Analysis

“…The WofE analysis is a data-driven Bayesian statistical method that offers a quantitative measurement of spatial association between a set of given geological features and the target occurrences (e.g., mineral deposits, prospects or geological anomalies) [58,59].…”