DOE Data Explorer title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

Abstract

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence 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 Desert Peak Geothermal Field.

Authors:
ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo
Publication Date:
Other Number(s):
1305
DOE Contract Number:  
EE0008760
Research Org.:
USDOE Geothermal Data Repository (United States); Colorado School of Mines, Golden, CO (United States)
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
Keywords:
geothermal; energy; geodatabase; Nevada; Desert Peak; artificial intelligence; AI; raw data; processed data; remote sensing; hyperspectral; machine learning; deep learning; exploration; ArcGIS; model; site detection; anomaly detection; geothermal site detection; database; hydrothermal; geophysics; radar; short wavelength infrared; SWIR; Support Vector Machine; SVM; land surface temperature; LST; well; GIS; blind; blind system; hyperspectral imaging; geophysical; deformation; conceptual model; fault; preprocessed; geospatial data
Geolocation:
39.95,-118.75|39.55,-118.75|39.55,-119.15|39.95,-119.15|39.95,-118.75
OSTI Identifier:
1797282
DOI:
https://doi.org/10.15121/1797282
Project Location:


Citation Formats

Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence. United States: N. p., 2021. Web. doi:10.15121/1797282.
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, & Jin, Ge. Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence. United States. doi:https://doi.org/10.15121/1797282
Moraga, Jim, Cavur, Mahmut, Soydan, Hilal, Duzgun, H. Sebnem, and Jin, Ge. 2021. "Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence". United States. doi:https://doi.org/10.15121/1797282. https://www.osti.gov/servlets/purl/1797282. Pub date:Tue Apr 27 00:00:00 EDT 2021
@article{osti_1797282,
title = {Desert Peak 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 the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence 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 Desert Peak Geothermal Field.},
doi = {10.15121/1797282},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 27 00:00:00 EDT 2021},
month = {Tue Apr 27 00:00:00 EDT 2021}
}