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.
Citation Formats
TY - DATA
AB - 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.
AU - Moraga, Jim
A2 - Cavur, Mahmut
A3 - Soydan, Hilal
A4 - Duzgun, H. Sebnem
A5 - Jin, Ge
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/1797283
KW - geothermal
KW - energy
KW - geodatabase
KW - Salton Sea
KW - artificial intelligence
KW - ai
KW - deep learning
KW - machine learning
KW - seismic
KW - remote sensing
KW - hyperspectral
KW - hyperspectral imaging
KW - geospacial database
KW - exploration
KW - site detection
KW - geothermal site detection
KW - anomaly detection
KW - short wavelength infrared
KW - SWIR
KW - support vector machine
KW - SVM
KW - land surface temperature
KW - LST
KW - well
KW - raw data
KW - processed data
KW - California
KW - ArcGis
KW - GIS
KW - model
KW - database
KW - hydrothermal
KW - geophysics
KW - radar
KW - blind
KW - blind system
KW - deformation
KW - geophysical
KW - conceptual model fault
KW - preprocessed
KW - raster
KW - vector
KW - field data
KW - geospatial data
LA - English
DA - 2021/04/27
PY - 2021
PB - Colorado School of Mines
T1 - Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
UR - https://doi.org/10.15121/1797283
ER -
Moraga, Jim, et al. Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. Colorado School of Mines, 27 April, 2021, GDR. https://doi.org/10.15121/1797283.
Moraga, J., Cavur, M., Soydan, H., Duzgun, H., & Jin, G. (2021). Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. [Data set]. GDR. Colorado School of Mines. https://doi.org/10.15121/1797283
Moraga, Jim, Mahmut Cavur, Hilal Soydan, H. Sebnem Duzgun, and Ge Jin. Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. Colorado School of Mines, April, 27, 2021. Distributed by GDR. https://doi.org/10.15121/1797283
@misc{OEDI_Dataset_7424,
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.},
url = {https://gdr.openei.org/submissions/1306},
year = {2021},
howpublished = {GDR, Colorado School of Mines, https://doi.org/10.15121/1797283},
note = {Accessed: 2025-05-09},
doi = {10.15121/1797283}
}
https://dx.doi.org/10.15121/1797283
Details
Data from Apr 27, 2021
Last updated Sep 7, 2021
Submitted Apr 28, 2021
Organization
Colorado School of Mines
Contact
Jim Moraga
303.273.3768
Authors
Original Source
https://gdr.openei.org/submissions/1306Research Areas
Keywords
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 dataDOE Project Details
Project Name Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning
Project Lead Mike Weathers
Project Number EE0008760
