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Utah FORGE: Groundwater Data
This submission includes two modeled drawdown scenarios with new supply well locations, a total dissolved solids (TDS) concentration grid (raster dataset representing the spatial distribution of TDS), and an excel spreadsheet containing well data.
Moore, J. Energy and Geoscience Institute at the University of Utah
Jul 20, 2016
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Sedimentary Geothermal Feasibility Colorado Well Database
Well data were mined from Geothermal Prospector (GTP), Southern Methodist University (SMU), the Colorado Oil and Gas Conservation Commission (COGCC), and the Colorado Geological Survey (CGS). The well data gathered was then used to assess sedimentary geothermal feasibility in the ...
Taverna, N. National Renewable Energy Laboratory
Oct 31, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Elevation Grid for top Columbia River Basalt (CRBG) in the Portland Basin used in DDU Feasibility Study
The Portland Basin is a prime location to assess the feasibility of DDU-TES because natural geologic conditions provide thermal and hydraulic separation from overlying aquifers that would otherwise sweep away stored heat. Under the Portland Basin, the lower Columbia River Basalt G...
Bershaw, J. and Scanlon, D. Portland State University
Dec 01, 2018
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Appalachian Basin Play Fairway Analysis: Revised 2016 Combined Risk Factor Analysis
This submission contains information used to compute the combined risk factors for deep geothermal energy opportunities in the Appalachian Basin, in the context of a the Play Fairway Analysis project. The risk factors are sedimentary rock reservoir quality, thermal resource qualit...
E., T. Cornell University
Nov 15, 2016
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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