U.S. Department of EnergyOffice of Scientific and Technical Information
Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
Abstract
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.
- Publication Date:
- Other Number(s):
- 1306
- DOE Contract Number:
- EE0008760
- Research Org.:
- DOE Geothermal Data Repository; Colorado School of Mines
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
- Collaborations:
- Colorado School of Mines
- Subject:
- 15 GEOTHERMAL ENERGY; ArcGis; California; GIS; LST; SVM; SWIR; Salton Sea; ai; anomaly detection; artificial intelligence; blind; blind system; conceptual model fault; database; deep learning; deformation; energy; exploration; field data; geodatabase; geophysical; geophysics; geospacial database; geospatial data; geothermal; geothermal site detection; hydrothermal; hyperspectral; hyperspectral imaging; land surface temperature; machine learning; model; preprocessed; processed data; radar; raster; raw data; remote sensing; seismic; short wavelength infrared; site detection; support vector machine; vector; well
- OSTI Identifier:
- 1797283
- DOI:
- https://doi.org/10.15121/1797283
Citation Formats
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. United States: N. p., 2021.
Web. doi:10.15121/1797283.
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, & Jin, Ge. Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. United States. doi:https://doi.org/10.15121/1797283
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. 2021.
"Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence". United States. doi:https://doi.org/10.15121/1797283. https://www.osti.gov/servlets/purl/1797283. Pub date:Tue Apr 27 00:00:00 EDT 2021
@article{osti_1797283,
title = {Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence},
author = {Moraga, Jim and Cavur, Mahmut and Soydan, Hilal and Duzgun, H. Sebnem and Jin, Ge},
abstractNote = {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.},
doi = {10.15121/1797283},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 27 00:00:00 EDT 2021},
month = {Tue Apr 27 00:00:00 EDT 2021}
}