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DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
27 Resources
0 Stars
Publicly accessible
27 Resources
0 Stars
Publicly accessible
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
Publicly accessible
14 Resources
0 Stars
Publicly accessible
SE Great Basin Play Fairway Analysis PFA Models and Probability Map
This submission includes a Na/K geothermometer probability greater than 200 deg C map, as well as two play fairway analysis (PFA) models. The probability map acts as a composite risk segment for the PFA models. The PFA models differ in their application of magnetotelluric conducto...
Brandt, A. University of Utah
Nov 15, 2015
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
Faulds, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: Baseline Cross-well Seismic
As part of the geophysical characterization suite for the first EGS Collab tesbed, here are the baseline cross-well seismic data and resultant models. The campaign seismic data have been organized, concatenated with geometry and compressional (P-) & and shear (S-) wave picks, and ...
Schwering, P. et al Sandia National Laboratories
Apr 30, 2018
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
Publicly accessible
Basin and Range Investigation for Developing Geothermal Energy: Exploration Data
This data package includes exploration material from the Basin & Range Investigation for Developing Geothermal Energy [in Hidden Systems] project (BRIDGE), which is part of a broader initiative to advance the exploration of hidden geothermal resources in the Basin & Range Province...
Schwering, P. et al Sandia National Laboratories
Jan 03, 2022
11 Resources
1 Stars
Curated
11 Resources
1 Stars
Curated
Potential structures Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid...
Faulds, J. and Coolbaugh, M. Nevada Bureau of Mines and Geology
Feb 20, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Gravity, Granite Springs Valley, Nevada Play Fairway Analysis
All raw data for new data acquired, key grids such as CBA and horizontal derivative, acquisition report, and depth models. This gravity data is associated with the Nevada Play Fairway project.
Faulds, J. Nevada Bureau of Mines and Geology
Sep 14, 2017
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification.
In this study, a machine-learning-assiste...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Geochemistry and paleo-geothermal features Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project.
A submission linking the full GitHub repository for our machine learning Jupyter Notebooks...
Faulds, J. and Ayling, B. Nevada Bureau of Mines and Geology
Nov 01, 2020
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utah FORGE: Milford Site Location, Seismometer Locations, Basin Depth Models, and Potentiometric Contours
This submission includes the geographic extent shapefile of the Milford FORGE site located in Utah, along with a shapefile of seismometer positions throughout the area, and models of basin depth and potentiometric contours.
Moore, J. Energy and Geoscience Institute at the University of Utah
Mar 09, 2016
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Finite Element Analysis (FEA) for Water-Foam Fracturing of Granite Rock
In addition to the foam data that were obtained from literature and that were collected from the current study, simulation data was also generated from finite element analysis (FEA) conducted in this study using COMSOL Multiphysics software. The FEA models were built to simulate t...
Thakor, V. et al Temple University
May 04, 2021
1 Resources
0 Stars
Publicly accessible
1 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
11 Resources
0 Stars
Publicly accessible
Washington Play Fairway Analysis Poly 3D Matlab Fault Modeling Scripts with Input Data to Create Permeability Potential Models
Matlab scripts and functions and data used to build Poly3D models and create permeability potential layers for 1) St. Helens Shear Zone, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.
Swyer, M. et al AltaRock Energy Inc
May 01, 2017
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Washington Play Fairway Analysis Poly 3D Matlab Fault Modeling Scripts with Input Data to Create Permeability Potential Models
Matlab scripts and functions and data used to build Poly3D models and create permeability potential GIS layers for 1) Mount St. Helens seismic zone, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.
Swyer, M. AltaRock Energy Inc
Feb 05, 2015
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Python Codebase and Jupyter Notebooks Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
Brown, S. and Smith, C. Nevada Bureau of Mines and Geology
Jun 30, 2022
4 Resources
0 Stars
Publicly accessible
4 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
6 Resources
0 Stars
Publicly accessible
Utah FORGE: 3D Gravity Data
These resources describe the 3D geophysical inversion modeling of gravity data at the FORGE site near Milford, Utah. FORGE is the Frontier Observatory for Research in Geothermal Energy and the site in Utah has been selected by the U.S. Dept. of Energy for a 5-year R&D program to t...
Hardwick, C. and Witter, J. Energy and Geoscience Institute at the University of Utah
Jun 24, 2019
2 Resources
0 Stars
Publicly accessible
2 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
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
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
9 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
6 Resources
0 Stars
Publicly accessible
Tularosa Basin Play Fairway: Weights of Evidence Models
These models are related to weights of evidence play fairway anlaysis of the Tularosa Basin, New Mexico and Texas. They were created through Spatial Data Modeler: ArcMAP 9.3 geoprocessing tools for spatial data modeling using weights of evidence, logistic regression, fuzzy logic a...
Brandt, A. University of Utah
Dec 01, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible