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
Colorado School of Mines. (2021). Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence [data set]. Retrieved from https://dx.doi.org/10.15121/1797283.
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence. United States: N.p., 27 Apr, 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. https://dx.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. https://dx.doi.org/10.15121/1797283. https://gdr.openei.org/submissions/1306.
@div{oedi_4125, title = {Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence}, author = {Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, 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}, url = {https://gdr.openei.org/submissions/1306}, journal = {}, number = , volume = , place = {United States}, year = {2021}, month = {04}}
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
