Reconnaissance exploration of favorable geothermal regions is under study in southeastern part of central Iranian volcanic belt in Kerman Province which is one of the promising geothermal zones in Iran. In this paper, a Geospatial Information System (GIS)-based multi criteria decision analysis method was used to explore geothermal favorability in the central part of Kerman Province. Geological, remote sensing, and aeromagnetic data were used to produce nine layers of information including hot springs, faults, intrusive bodies, volcanic units, alteration zones, temperature difference of land surface, apparent thermal inertia, magnetic anomalies, and Curie depth. All data layers were then combined in GIS using weighted sum method (WSM) and fuzzy logic method. Analytical Hierarchy Process (AHP) was used for calculating the weights for the factors. The results detected eight favorable geothermal zones in the study area which were highly correlated in both maps obtained from WSM and fuzzy logic methods. The results show that the southeastern part of the study area is the most promising zone to design future detailed studies.

A gis-based multi-criteria decision analysis method to explore geothermal favorability in the southeastern part of central iranian volcanic belt

Hojat A.;
2020-01-01

Abstract

Reconnaissance exploration of favorable geothermal regions is under study in southeastern part of central Iranian volcanic belt in Kerman Province which is one of the promising geothermal zones in Iran. In this paper, a Geospatial Information System (GIS)-based multi criteria decision analysis method was used to explore geothermal favorability in the central part of Kerman Province. Geological, remote sensing, and aeromagnetic data were used to produce nine layers of information including hot springs, faults, intrusive bodies, volcanic units, alteration zones, temperature difference of land surface, apparent thermal inertia, magnetic anomalies, and Curie depth. All data layers were then combined in GIS using weighted sum method (WSM) and fuzzy logic method. Analytical Hierarchy Process (AHP) was used for calculating the weights for the factors. The results detected eight favorable geothermal zones in the study area which were highly correlated in both maps obtained from WSM and fuzzy logic methods. The results show that the southeastern part of the study area is the most promising zone to design future detailed studies.
2020
3rd Asia Pacific Meeting on Near Surface Geoscience and Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1156772
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