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Shallow EGS Regional Resource Potential and Map Snake River Plain
SMU Geothermal Lab developed a methodology to estimate shallow (1 km to 4 km) Enhanced Geothermal Systems (EGS) resource potential using an approach that utilizes recent geology and geophysical research along with new well data to improve the thermal conductivity model, mitigate i...
Batir, J. et al Southern Methodist University Huffington Department of Earth Sciences
Oct 30, 2020
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2 Resources
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Analysis of Geothermal Resources in Three Texas Counties
This project updates the geothermal resources beneath our oil and gas fields, as part of the research for the Texas GEO project. This report "Analysis of Geothermal Resources in Three Texas Counties" (October 2020) improves on previous mapping of the Texas resources for the counti...
Richards, M. and Batir, J. Southern Methodist University Huffington Department of Earth Sciences
Oct 30, 2020
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3 Resources
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Utah FORGE: Well 16A(78)-32 Logs
This dataset contains all well logs from Utah FORGE well 16A(78)-32. This includes the mud log, Sanvean Technologies logs, and Schlumberger logs. Please see the file descriptions below for information about each log.
Gilmour, B. et al Energy and Geoscience Institute at the University of Utah
Mar 08, 2021
7 Resources
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7 Resources
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REopt Lite Geothermal Heat Pump Design Requirements
This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...
Olis, D. National Renewable Energy Laboratory
Mar 08, 2021
6 Resources
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6 Resources
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Utah FORGE: Seismic Velocity Models, February 2021
This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. T...
Pankow, K. Energy and Geoscience Institute at the University of Utah
Feb 28, 2021
3 Resources
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3 Resources
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Utah FORGE: Well 56-32 Drilling Data and Logs
This dataset consists of drilling data (Pason data spreadsheets, daily reports, days v. depth, mud logs), Schlumberger logs (FMI, shear anisotropy analysis, memory, sonic, array induction/spectral density/dual spaced neutron/gamma ray/caliper, spectral GR/temperature, and Gardner ...
Bristol, J. et al Energy and Geoscience Institute at the University of Utah
Mar 19, 2021
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18 Resources
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Utah FORGE: Well 16A(78)-32: Summary of Drilling Activities
This is a 74 page detailed summary of the drilling activities of Utah FORGE 16A(78)-32, a highly deviated well completed on February 2nd, 2021, as part of the Utah FORGE project. This well was deviated at 65 degrees from vertical after reaching 6000 feet in depth had a total measu...
Winkler, D. et al Energy and Geoscience Institute at the University of Utah
Mar 20, 2021
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1 Resources
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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
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4 Resources
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GEOPHIRES files for DDU techno-economic simulations
During 2017-2019, the U.S. Department of Energy funded six geothermal deep direct-use (DDU) projects to investigate feasibility of DDU for heating, cooling and thermal storage in the United States. In a follow-on study conducted at the National Renewable Energy Laboratory (NREL), ...
Beckers, K. and Kolker, A. National Renewable Energy Laboratory
Mar 31, 2021
1 Resources
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1 Resources
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Utah FORGE: Well 58-32 (MU-ESW1) FMI Log Fracture Results
A Schlumberger Fullbore Formation Micro-Imager (FMI) log was run from 7390 feet to 7527 feet depth in well 58-32, originally known as well MU-ESW1. Well 58-32 was completed in 2017 as part of Utah FORGE Phase 2. It reached a depth of 7536 feet and recorded a bottom hole temperatur...
BLOCHOWICZ, A. Energy and Geoscience Institute at the University of Utah
Mar 06, 2021
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1 Resources
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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
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1 Resources
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EGS Collab Experiment 1: Circulation Testing Processed data
This submission includes processed and reduced data for circulation testing that was conducted at the 164' fracture on the 4850 ft level of the Sanford Underground Research Facility. The circulation tests were done to test the flow through the 164' fracture in the EGS Collab Exper...
Fu, P. et al Lawrence Livermore National Laboratory
Apr 01, 2021
7 Resources
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7 Resources
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Directional Cooling-Induced Fracturing Westerly Granite Test Results
Directional Cooling-Induced Fracturing (DCIF) experiments were conducted on a short, cylindrical sample of Westerly granite (diameter = 4 inches, height ~ 2 inches). Liquid nitrogen was poured in a copper cup attached to the top of the sample, and the resulting acoustic emissions ...
Nakagawa, S. Lawrence Berkeley National Laboratory
Dec 18, 2020
5 Resources
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5 Resources
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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
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12 Resources
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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
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3 Resources
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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
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3 Resources
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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
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3 Resources
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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
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11 Resources
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Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...
Marone, C. Pennsylvania State University
May 05, 2021
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1 Resources
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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
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4 Resources
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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
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4 Resources
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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
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3 Resources
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Geothermal Mineral Alterations in Brady and Desert Peak
Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas.
This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.
Moraga, J. Colorado School of Mines
May 15, 2021
22 Resources
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22 Resources
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GDR Data Management and Best Practices for Submitters and Curators
Resources for GDR data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of the GDR. The Data Management and Submission Best Practices document also contains API access and metadata schema information for develo...
Weers, J. et al National Renewable Energy Laboratory
Mar 31, 2021
3 Resources
1 Stars
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3 Resources
1 Stars
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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
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11 Resources
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