Exploration of potential geothermal fields using MAXENT and AHP: A case study of the Büyük Menderes Graben

Abstract

In today's world, geothermal energy is essential as one of the alternative energy sources because it is renewable and does not harm the environment or the atmosphere. Büyük Menderes Graben (BMG) has significant geothermal potential in the Aegean Region of Turkey. The Maximum Entropy (MaxEnt) Method and Multi-criteria Decision Analysis (MCDA) were used in this study to define potential geothermal areas. The Geographical Information Systems (GIS) Based Maxent Method is the machine learning method. The decision analysis stage of the MCDA employed the Analytic Hierarchy Process (AHP). A geothermal favorability map was produced by combining weighted layers of standardized data according to the AHP. The Maxent Method created the other geothermal favorability map that self-estimates the weight of criteria. The Natural Breaks Jenks Method was used to categorize both maps. The findings of our study were compared with the locations of the geothermal resources in BMG. Both methods result in high accuracy, but the MaxEnt method has a high sensitivity to the geological parameters (cap rock geology and fault) of the geothermal system. So, the high gain values ensured the target was determined more precisely in the Maxent method. The MaxEnt method in our study is a guide for the exploration of new geothermal fields. Further geothermal explorations in the BMG will increase the potential of thermal tourism, housing heating, greenhouse, and balneological applications and contribute to renewable energy production in Turkey.