Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence


These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.

3 Resources

*downloads since 2019

Related Datasets

Datasets associated with the same DOE project
  Submission Name Resources Submitted Status

Additional Info

DOE Project Name: Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning
DOE Project Number: EE0008760
DOE Project Lead: Mike Weathers
DOI: 10.15121/1797283
Last Updated: 10 months ago
Data from April, 2021
Submitted Apr 28, 2021


Colorado School of Mines



Publicly accessible License 


Jim Moraga
Colorado School of Mines
Mahmut Cavur
Kadir Has Universitesi
Hilal Soydan
Colorado School of Mines
H. Sebnem Duzgun
Colorado School of Mines
Ge Jin
Colorado School of Mines


geothermal, energy, geodatabase, Salton Sea, artificial intelligence, ai, deep learning, machine learning, seismic, remote sensing, hyperspectral, hyperspectral imaging, geospacial database, exploration, site detection, geothermal site detection, anomaly detection, short wavelength infrared, SWIR, support vector machine, SVM, land surface temperature, LST, well, raw data, processed data, California, ArcGis, GIS, model, database, hydrothermal, geophysics, radar, blind, blind system, deformation, geophysical, conceptual model fault, preprocessed, raster, vector, field data, geospatial data


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