Inicio  /  Energies  /  Vol: 10 Núm: 7 Par: July (2017)  /  Artículo
ARTÍCULO
TITULO

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

Xuejia Sang    
Linfu Xue    
Jiwen Liu and Liang Zhan    

Resumen

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.

 Artículos similares

       
 
Deeraj Nagothu, Ronghua Xu, Yu Chen, Erik Blasch and Alexander Aved    
With the fast development of Fifth-/Sixth-Generation (5G/6G) communications and the Internet of Video Things (IoVT), a broad range of mega-scale data applications emerge (e.g., all-weather all-time video). These network-based applications highly depend o... ver más
Revista: Future Internet

 
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia and Paolo Trunfio    
Workflows are largely used to orchestrate complex sets of operations required to handle and process huge amounts of data. Parallel processing is often vital to reduce execution time when complex data-intensive workflows must be run efficiently, and at th... ver más
Revista: Future Internet

 
Yingjing Huang, Teng Fei, Mei-Po Kwan, Yuhao Kang, Jun Li, Yizhuo Li, Xiang Li and Meng Bian    
In recent years, with the growing accessibility of abundant contextual emotion information, which is benefited by the numerous georeferenced user-generated content and the maturity of artificial intelligence (AI)-based emotional computing technics, the e... ver más

 
Wouter B. Verschoof-van der Vaart, Karsten Lambers, Wojtek Kowalczyk and Quentin P.J. Bourgeois    
This paper presents WODAN2.0, a workflow using Deep Learning for the automated detection of multiple archaeological object classes in LiDAR data from the Netherlands. WODAN2.0 is developed to rapidly and systematically map archaeology in large and comple... ver más

 
Luigi Barazzetti, Mattia Previtali and Marco Scaioni    
The identification of deterioration mechanisms and their monitoring over time is an essential phase for conservation. This work aimed at developing a novel approach for deterioration mapping and monitoring based on 360° images, which allows for simple an... ver más