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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible

Mineralogical and Lithological Data from Great Basin Geothermal Systems

Mineralogical and lithological data from core samples taken at various geothermal wells in the Great Basin: Dixie Valley, Beowawe, Roosevelt, Mammoth, Steamboat Springs, Coso
Simmons, S. Colorado School of Mines
Aug 08, 2013
1 Resources
0 Stars
Publicly accessible

Nevada Great Basin Play Fairway Analysis Regional Data

This project focused on defining geothermal play fairways and development of a detailed geothermal potential map of a large transect across the Great Basin region (96,000 km2), with the primary objective of facilitating discovery of commercial-grade, blind geothermal fields (i.e. ...
Faulds, J. Nevada Bureau of Mines and Geology
Oct 28, 2015
47 Resources
0 Stars
Curated

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible