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Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Moraga, J. et al Colorado School of Mines
Sep 01, 2020
16 Resources
0 Stars
Publicly accessible

GIS Resource Compilation Map Package Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...
Brown, S. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
1 Resources
0 Stars
Publicly accessible

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

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Buster, G. et al Upflow
Jun 30, 2021
11 Resources
0 Stars
Publicly accessible

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Publicly accessible

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

PoroTomo: Brady Geothermal Field InSAR Data

Included are links to compressed InSAR pairs covering Brady Geothermal Field for TerraSAR-X (tracks 53, 91, and 167) and Sentinel-1A data. Pairs from the PoroTomo deployment period and pairs forming a minimum spanning tree according to perpendicular baseline are included for Terr...
Reinisch, E. University of Wisconsin
Jul 11, 2017
6 Resources
0 Stars
Publicly accessible

InSAR Maps of Deformation Covering Raft River, Idaho from 2007 to 2010

This dataset contains maps of deformation covering Raft River, Idaho from 2007 to 2010 calculated from interferometric synthetic aperture radar data. This dataset is used in the study entitled "Inferring geothermal reservoir processes at the Raft River Geothermal Field, Idaho, US...
Reinisch, E. University of Wisconsin
Mar 11, 2007
8 Resources
0 Stars
Publicly accessible

Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Moraga, J. Colorado School of Mines
Apr 27, 2021
11 Resources
0 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
8 Resources
0 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2000
6 Resources
0 Stars
Publicly accessible

Stanford Thermal Earth Model for the Conterminous United States

Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Aljubran, M. and Horne, R. Stanford University
Mar 14, 2024
9 Resources
2 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations

The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal energy production. Phase 1 includes reservoir analyses to determine injector/producer well schemes that balance the generation of economically useful flow rates at the ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
9 Resources
0 Stars
Publicly accessible

GeoVision: Harnessing the Heat Beneath Our Feet Analysis Inputs and Results

This submission includes input and results data from analysis done as part of the Geothermal Technology Office's Geothermal Vision Study (GeoVision). The submission includes data for both analysis of the electricity sector and the heating and cooling sector. For the electricity se...
Geothermal Technologies Office, U. National Renewable Energy Laboratory
Sep 30, 2019
16 Resources
3 Stars
Publicly accessible

Community Geothermal: Soil Conductivity, Borehole Design, Energy Models, and Load Data for a Residential System Development Hinesburg, VT

This dataset contains materials from the Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES) project, which evaluated the techno-economic feasibility of a community geothermal system for a residential development in Hinesburg, VT. The dataset includes ...
Jogineedi, R. et al GTI Energy
Aug 30, 2024
56 Resources
0 Stars
Publicly accessible
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  • The GDR is the submission point for all data collected from research funded by the U.S. Department of Energy's Geothermal Technologies Office.
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