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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Utah FORGE: Earth Model Mesh Data for Selected Surfaces
This submission contains a number of data files with vertices of meshed/interpolated surfaces used in the Phase 2B earth model. Examples include land surface (based on 10-meter DEM), the granitoid-basin fill contact, several faults, and also interpolated temperature isosurfaces f...
Podgorney, R. Idaho National Laboratory
Dec 07, 2018
6 Resources
0 Stars
Publicly accessible
6 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
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4 Resources
0 Stars
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Alternative CAES Technology Using Depleted Unconventional Gas Wells and Subsurface Thermal Energy Storage (GeoCAES)
This project assessed the technical viability of a process called GeoCAES. The process stores electrical energy by injecting natural gas into shale gas formations using a compressor, storing it, and producing it through an expander to generate electricity. This data submission inc...
Johnston, H. and Young, D. National Renewable Energy Laboratory
May 23, 2019
8 Resources
0 Stars
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8 Resources
0 Stars
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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
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12 Resources
0 Stars
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Utah FORGE Phase 3 Native State Model: 2022 Update
This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. Thi...
Podgorney, R. and Liu, R. Idaho National Laboratory
Jul 29, 2022
1 Resources
0 Stars
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1 Resources
0 Stars
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Testing LCM on a Large Scale for Geothermal Drilling Applications Using a Novel Experimental Setup
Rheology data obtained from flow loop tests, performed using different lost circulation materials (LCM) to study their effect on fluid rheology and wellbore hydraulics. The sealing performance of different LCM was tested using different fracture sizes. Five academic papers / repor...
Mohamed, A. et al University of Oklahoma
Apr 22, 2022
10 Resources
0 Stars
Curated
10 Resources
0 Stars
Curated
Literature Data on Foam Fracturing Fluid
At the beginning of this project, the Temple team spent significant effort to collect data relevant to foam fracturing. More than 40 articles/reports were found in the open literature that reported the properties of aqueous foams under various testing conditions. The foam properti...
Thakor, V. et al Temple University
Nov 08, 2021
2 Resources
0 Stars
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2 Resources
0 Stars
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EGS Collab Experiment 2: Hydraulic Pressure Test Results
The EGS Collab experiment 2 was focused on testing shear stimulation techniques. Shear stimulation, in this case, means using hydraulic pressure to cause shear slip on preexisting fracture or fault planes such that the hydraulic conductivity of the fracture or fault increases. The...
Burghardt, J. et al Lawrence Berkeley National Laboratory
Feb 17, 2023
1 Resources
0 Stars
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1 Resources
0 Stars
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Utah FORGE 5-2615: Well 58-32 and 78-32 Poroelastic Properties
Lab data on permeability, grain bulk modulus, drained bulk modulus, Skempton's pore pressure coefficient, and Biot's effective stress coefficient for Utah Forge Well 58-32 and Well 78-32.
Work done as part of project number 5-2615 by the University of Oklahoma.
Ghassemi, A. and Zhou, X. University of Oklahoma
Oct 31, 2022
2 Resources
0 Stars
Curated
2 Resources
0 Stars
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Purdue University: Results of B-Value Tests for Rock Saturation
This dataset includes an Excel file with the results of B-value tests to determine the magnitude of the back pressure required for full saturation of Sierra White granite samples. Test were conducted on cylindrical rock specimens of Sierra White granite in a custom water pressuriz...
Han, K. et al Purdue University
Jun 20, 2022
2 Resources
0 Stars
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2 Resources
0 Stars
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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
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Utah FORGE UGS Interactive Geoscience Map
This is a link to the Utah Geological Survey's Utah FORGE Interactive Geoscience Map. The map layers include information on geology, geography, subsurface temperatures, seismicity, gravity and groundwater. Instructions for using the interactive map and a legend for the interactive...
Hill, J. Utah Geological Survey
Jan 01, 2021
1 Resources
0 Stars
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1 Resources
0 Stars
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Steptoe Valley NV Data Compilation: Understanding a Stratigraphic Hydrothermal Resource through Geophysical Imaging
Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. Provided here are a compilation of newly acqu...
Schwering, P. et al Sandia National Laboratories
Nov 01, 2023
8 Resources
0 Stars
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8 Resources
0 Stars
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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
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3 Resources
0 Stars
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Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)
Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy.
Objective and Purpose:
Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...
Norbeck, J. et al Fervo Energy
Feb 08, 2023
3 Resources
0 Stars
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3 Resources
0 Stars
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Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Magnetotelluric Data Collected in 2016 over the San Emidio Geothermal Field in Nevada
This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Usi...
Folsom, M. et al Ormat Technologies, Inc.
Nov 09, 2016
11 Resources
0 Stars
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11 Resources
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DEEPEN: Newberry Volcano MT and Gravity Data 2022 and 2023 Acquisition and Processing
As part of DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments), a 3D play fairway analysis (PFA) was conducted at Newberry Volcano in Central Oregon for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). For use in this PFA, ...
Shultz, A. et al Enthalpion Energy
Jun 30, 2023
8 Resources
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8 Resources
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Mordensky, S. et al United States Geological Survey
Feb 07, 2023
7 Resources
0 Stars
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7 Resources
0 Stars
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DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...
Taverna, N. et al National Renewable Energy Laboratory
Jan 24, 2024
14 Resources
0 Stars
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14 Resources
0 Stars
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DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific e...
Pauling, H. et al National Renewable Energy Laboratory
Jun 30, 2023
22 Resources
0 Stars
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22 Resources
0 Stars
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