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GeoDAWN Northwestern Elko County Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Northwestern Elko County, Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation ...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 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
4 Resources
0 Stars
Publicly accessible
GeoDAWN West Central Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Western Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), De...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Utah FORGE: Satellite Imagery and Digital Aerial Photography
This is a link to the USGS Global Visualization Viewer which can be used to locate and download a variety of remotely sensed data including the ASTER multispectral data that was used in the Utah FORGE project.
Moore, J. Energy and Geoscience Institute at the University of Utah
Mar 02, 2016
1 Resources
0 Stars
Publicly accessible
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
3 Resources
0 Stars
Publicly accessible
Memos Relating to High-Priority Geothermal Targets in Colorado Selected for Further Study Flint Geothermal 2012
This dataset contains several memos describing geothermal targets outlined by Flint personnel in Colorado. Phase 1 involved an ASTER and LANDSAT thermal infrared imagery assessment conducted by CIRES of the University of Colorado, which identified areas of warm ground that might i...
Zehner, R. Flint Geothermal, LLC
Feb 27, 2014
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Utah FORGE: 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
Publicly accessible
2 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 2: Laser Scanned 4100 L Drift Map
The EGS Collab project is evaluating a site for Experiment 2 (hydraulic fracturing/shearing) at a depth of 1.25 km in the Sanford Underground Research Facility (SURF) on the 4100 Level. Two early test holes were drilled in an alcove (formerly known as Battery Charging Station) nea...
Neupane, G. et al Idaho National Laboratory
Dec 19, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
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Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA.
Explanation of pair subdirectories:
Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011).
...
Reinisch, E. and Feigl, K. University of Wisconsin
Jun 25, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Utah FORGE: InSAR Data
This is the InSAR dataset used in Utah FORGE Phase 2C to augment ground deformation monitoring. It is accompanied by a README.txt file which contains an explanation of the data in the .zip archive.
Feigl, K. et al Energy and Geoscience Institute at the University of Utah
Jul 01, 2019
2 Resources
0 Stars
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2 Resources
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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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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
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1 Resources
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Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project
The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the material properties are registered on a three-dimensional grid with a spacing of 25 meters between nodes....
Feigl, K. and PoroTomo Team, . University of Wisconsin
Mar 06, 2019
10 Resources
0 Stars
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10 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
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EGS Collab Experiment 2: 4100 Foot Level Elastic Property Data
Static and dynamic elastic properties (Young's modulus, Shear Modulus, P-wave Modulus, and Poisson's Ratio) of amphibolites and rhyolites from the TV4100 and TH4100 boreholes at the Sanford Underground Research Laboratory (SURF). Elastic properties include Young's modulus, Poisson...
Jahnke, B. et al Lawrence Berkeley National Laboratory
Dec 18, 2020
4 Resources
0 Stars
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4 Resources
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Utah FORGE: Well 58-32 Core Analyses
This dataset contains final reports regarding stress measurements, permeability measurements, and mechanical properties from the core testing of well 58-32, in PDF format, and spreadsheets containing tables from the reports as part of Utah FORGE Phase 2B. Please refer to the repor...
McLennan, J. Energy and Geoscience Institute at the University of Utah
May 30, 2018
1 Resources
0 Stars
Publicly accessible
1 Resources
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University of Illinois Campus Deep Direct-Use Feasibility Study Thermal Properties of Geologic Formations in Illinois Basin
Thermal property data for rocks and and minerals and unconsolidated (glacial) sediments units from within and outside the Illinois Basin were compiled for modeling heat transport in the subsurface.
Lin, Y. et al University of Illinois
Mar 30, 2018
6 Resources
0 Stars
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6 Resources
0 Stars
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Numerical Modeling for Hydraulic Fracture Prediction
Numerical modeling on fused silica cylindrical materials for predicting overpressures required to fracture an homogeneous pure (surrogate) material with known mechanical properties similar to igneous rock materials and later compare these values to experimental overpressures obtai...
Gupta, V. Pacific Northwest National Laboratory
Apr 26, 2016
1 Resources
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1 Resources
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Identifying and Delineating Thermally Active Areas in Colorado Using Thermal Remote Sensing Data
This report outlines the approach and methodology of the utilization of thermal satellite imagery to find areas of warm ground that might indicate heat flow from a buried geothermal system. The satellite platforms, modeling equations and corrections to the data are discussed. Some...
Hussein, K. Flint Geothermal, LLC
Dec 26, 2012
1 Resources
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1 Resources
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Geocellular Model of Mt. Simon Sandstone for University of Illinois at Urbana-Champaign DDU feasibility study
The geocellular model of the Mt. Simon Sandstone was constructed for the University of Illinois at Urbana-Champaign DDU feasibility study. Starting with the initial area of review (18.0 km by 18.1 km [11.2 miles by 11.3 miles]) the boundaries of the model were trimmed down to 9.7 ...
Damico, J. University of Illinois
Dec 31, 2018
4 Resources
0 Stars
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4 Resources
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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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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
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4 Resources
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Utah FORGE Well 58-32 Granite Core Thermal Properties Test Results Report (Oct. 2021)
This is a presentaiton from Metarock Laboratories on the thermal properties of Utah FORGE well 58-32 granite core. The presentation includes pictures of core samples, core details for the samples (sample depths and size), sample thermal expansion test results, and radial velocity ...
Laboratories, M. Energy and Geoscience Institute at the University of Utah
Oct 29, 2021
1 Resources
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1 Resources
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Utah FORGE: Rock Properties
This is an Excel spreadsheet that contains rock properties from several wells in the Utah FORGE study area. This includes a map of the wells. Data is described in the Final Topical Report included in the resources below.
Gwynn, M. Energy and Geoscience Institute at the University of Utah
Apr 07, 2018
2 Resources
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2 Resources
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