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Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report
Grid-scale energy storage has been identified as a needed technology to support the continued build-out of intermittent renewable energy resources. As of April 2017, the U.S. had approximately 24.2 GW of energy storage on line, compared to 1,081 GW of installed generation capacity...
McLing, T. et al Idaho National Laboratory
May 31, 2019
11 Resources
0 Stars
Publicly accessible
11 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
3 Resources
0 Stars
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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
Kelley, M. et al Battelle Memorial Institute
Jun 19, 2023
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
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
11 Resources
0 Stars
Publicly accessible
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
0 Stars
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3 Resources
0 Stars
Curated
Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
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4 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
Recovery of Rare Earths, Precious Metals and Other Critical Materials from Geothermal Waters with Advanced Sorbent Structures
The work evaluates, develops and demonstrates flexible, scalable mineral extraction technology for geothermal brines based upon solid phase sorbent materials with a specific focus upon rare earth elements (REEs). The selected organic and inorganic sorbent materials demonstrated h...
Addleman, R. et al Pacific Northwest National Laboratory
Sep 30, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
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Advanced Sorbent Structure Recovery of Rare Earths, Precious Metals and Other Critical Materials from Geothermal Waters and Its Associated Technoeconomics
The work evaluates, develops and demonstrates flexible, scalable mineral extraction technology for geothermal brines based upon solid phase sorbent materials with a specific focus upon rare earth elements (REEs). The selected organic and inorganic sorbent materials (silica and MOF...
Addleman, R. et al Pacific Northwest National Laboratory
Sep 21, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
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Publicly accessible
Fallon FORGE: Seismic Reflection Profiles
Newly reprocessed Naval Air Station Fallon (1994) seismic lines: pre-stack depth migrations, with interpretations to support the Fallon FORGE (Phase 2B) 3D Geologic model.
Data along seven profiles (>100 km of total profile length) through and adjacent to the Fallon site were re-...
Blankenship, D. et al Sandia National Laboratories
Feb 01, 2018
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Advanced Sorbent Structure Recovery of REEs, Precious Metals and Other Valuable Metals from Geothermal Waters and Its Associated Technoeconomics
This work evaluates, develops and demonstrates flexible, scalable mineral extraction technology for geothermal brines based upon solid phase sorbent materials with a specific focus upon rare earth elements (REEs). The selected organic and inorganic sorbent materials demonstrated h...
Addleman, S. et al Pacific Northwest National Laboratory
May 25, 2017
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model
This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation.
A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
0 Stars
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1 Resources
0 Stars
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Hawthorne Nevada Deep Direct-Use Feasibility Study 3D Seismic
The objective of this project is to use a multi-disciplinary, three-tiered approach to assess the geothermal resource and determine the feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the various town and county facilities in H...
Lowry, T. et al Nevada Bureau of Mines and Geology
Mar 29, 2018
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: Core Logs
Core logs from the EGS Collab project Experiment 1 for the stimulation (Injection) well (E1-I), the Production well (E1-P), and monitoring wells (E1-OT, E1-OB, E1-PST, E1-PSB, E1-PDT, and E1-PDB) on the 4850 Level of SURF (the Sanford Underground Research Facility), single PDF fil...
Dobson, P. et al Lawrence Berkeley National Laboratory
Apr 02, 2019
17 Resources
0 Stars
Publicly accessible
17 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography
This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
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7 Resources
0 Stars
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EGS Collab: Modeling and Simulation Working Group Teleconference Series (1-98)
This submission contains the presentation slides and recordings from the first 98 EGS Collab Modeling and Simulation Working Group teleconferences. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and resul...
White, M. et al Pacific Northwest National Laboratory
Feb 04, 2020
100 Resources
0 Stars
Publicly accessible
100 Resources
0 Stars
Publicly accessible