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Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
0 Stars
Publicly accessible
12 Resources
0 Stars
Publicly accessible
United States Offshore Wind Supply Curves 2024
This data packet contains supply curves, hourly generation profiles, and composite siting exclusion TIFFs for offshore wind (OSW) in the waters of the EEZ off the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), level...
Geospatial Data Science, N. National Renewable Energy Laboratory (NREL)
Jan 01, 2024
15 Resources
0 Stars
Curated
15 Resources
0 Stars
Curated
Water Use in Enhanced Geothermal Systems (EGS): Geology of U.S. Stimulation Projects, Water Costs, and Alternative Water Use Policies
According to the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE), geothermal energy generation in the United States is projected to more than triple by 2040 (EIA 2013). This addition, which translates to more than 5 GW of generation capacity, is anti...
Harto, C. et al Argonne National Laboratory
Dec 16, 2014
13 Resources
0 Stars
Publicly accessible
13 Resources
0 Stars
Publicly accessible
Unified Field Study 1 (UFS-1)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the UFS-1 experiment, performed October to December 201...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 27, 2016
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)
This submission contains information used to compute the risk factors for the GPFA-AB project. The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking ...
E., T. Cornell University
Sep 30, 2015
191 Resources
0 Stars
Publicly accessible
191 Resources
0 Stars
Publicly accessible