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Utah FORGE 3-2417: DAS Microseismic Event Catalog from the 16A/16B Circulation Test, 2023

This preliminary data archive includes the relocated microseismic event catalog, 1D velocity model, and methods report from DAS acquisition conducted during the Well 16A and 16B circulation test (July 19th and 20th, 2023) at Utah FORGE. The methods report describes all processing ...

Vera Rodriguez, I. et al Rice University

Jun 12, 2024
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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
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Utah FORGE: Fiber Optic Cumulative Strain Change and Strain Change Rate Data From Well 16A Stimulation at Well 16B

This dataset includes Rayleigh Frequency Shift (RFS) Distributed Strain Sensing (DSS) cumulative strain change and change rate data. The data was acquired during the stimulation of Utah FORGE Well 16A(78)-32 in April 2024 via fiber installed in Well 16B(78)-32. The fiber optic da...

Khatara, S. et al Neubrex Energy Services (US), LLC

Nov 06, 2024
2 Resources
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Utah FORGE: Well 16A(78)-32 Simplified Discrete Fracture Network Data

The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...

Finnila, A. Golder Associates Inc.

Jun 01, 2021
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Utah FORGE: Phase Native State FALCON Model Files

The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...

Podgorney, R. Idaho National Laboratory

Jun 06, 2019
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Utah FORGE: Well 16B(78)-32 Extended Dual Well Circulation Testing Fiber Optic Monitoring Report August 2024

This report documents the post-hydraulic fracturing extended circulation test between Utah FORGE wells 16A and 16B conducted in August 2024. In well 16B, fiber optic measurements of Rayleigh frequency shift distributed strain sensing (RFS-DSS) and distributed temperature sensing ...

Jurick, D. et al Neubrex Energy Services (US), LLC

Aug 30, 2024
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Utah FORGE: Milford Gravity Data Shapefile

This is a zipped GIS compatible shapefile of gravity data points used in the Milford, Utah FORGE project as of March 21st, 2016. The shapefile is native to ArcGIS, but can be used with many GIS software packages. Additionally, there is a .dbf (dBase) file that contains the dataset...

Moore, J. Energy and Geoscience Institute at the University of Utah

Mar 13, 2016
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Utah FORGE: GES Well 16A(78)-32 and Well 16B(78)-32 Stimulation Seismic Event Catalogs

This dataset contains seismic event catalogs from the hydraulic stimulation of wells 16A(78)-32 and 16B(78)-32 at the Utah FORGE site in April 2024. The data was collected by Geo Energy Suisse (GES) using a variety of seismic monitoring technologies, including 3-component (3C) geo...

Dyer, B. et al University of Utah Seismograph Stations

Apr 30, 2024
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Utah FORGE: Geochemical Data for Cold Groundwaters and Produced Geothermal Fluids

Geochemical data for cold groundwaters and produced geothermal fluids around the Utah FORGE site. The data is compiled into four tables in the attached Excel File. Table 1 is a compilation of compositions (anions, cations, weak acids, oxygen, hydrogen, and carbon isotopes) for c...

Simmons, S. and Kirby, S. Energy and Geoscience Institute at the University of Utah

Aug 16, 2024
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EGS Collab Experiment 2: Earth Model Datasets

The EGS Collab Project performed a series of tests to increase the understanding the response of crystalline rock mass to stimulations and fluid circulation to efficiently implement enhanced geothermal systems (EGS) technologies. The EGS Collab team created two underground testbed...

Neupane, G. et al Idaho National Laboratory

May 29, 2022
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Utah FORGE: TEM and Gravity Data

This submission includes a gravity data in text format and as a GIS point shapefile and transient electromagnetic (TEM) raw data. Each text file additionally contains location data (UTM Zone 12, NAD83) and elevation (meters) data for that station. The gravity data shapefile was i...

Hardwick, C. and Nash, G. Energy and Geoscience Institute at the University of Utah

Feb 05, 2018
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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
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Utah FORGE: GIS Well Temperature Data

This is a GIS point feature shapefile representing wells, and their temperatures, that are located in the general Utah FORGE area near Milford, Utah. There are also fields that represent interpolated temperature values at depths of 200 m, 1000 m, 2000 m, 3000 m, and 4000 m. in deg...

Gwynn, M. et al Energy and Geoscience Institute at the University of Utah

Feb 28, 2018
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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
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EGS Collab Experiment 2: Distributed Fiber Optic Temperature Data (DTS)

Distributed fiber optic sensing was an important part of the monitoring system for EGS Collab Experiment #2. A single loop of custom fiber package was grouted into the four monitoring boreholes that bracketed the experiment volume. This fiber package contained two multi-mode fiber...

Rodriguez Tribaldos, V. et al Lawrence Berkeley National Laboratory

Nov 08, 2022
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Utah FORGE: InSAR Data Best Pairs

This submission provides Interferometric Synthetic Aperture Radar (InSAR) data covering the Utah FORGE site via the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). Data was collected between 2019/01/01 and 2023/06/30. Interferometric pairs (...

Batzli, S. and Feigl, K. University of Wisconsin Madison

May 31, 2023
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Utah FORGE: Temperature Contours at 200 m

The individual shapefiles in this dataset delineate estimated temperature contours (20, 40, 60, and 80 deg C) at a depth of 200 m in the Milford, Utah FORGE area. Contours were derived from 86 geothermal, gradient, and other wells drilled in the area since the mid-1970s with dept...

Moore, J. Energy and Geoscience Institute at the University of Utah

Feb 01, 2016
7 Resources
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Utah FORGE: Well 58-32 Stimulation Data

Pressure, temperature, and flow data from open-hole, upper perforation, and lower perforation well stimulations gathered from various tools collected at well 58-32 during phase 2C.

Best, S. Geothermal Resource Group

Apr 20, 2019
16 Resources
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Fallon FORGE: Geophysics and Geochemistry

The data is associated to the Fallon FORGE project and includes mudlogs for all wells used to characterize the subsurface, as wells as gravity, magnetotelluric, earthquake seismicity, and temperature data from the Navy GPO and Ormat. Also included are geologic maps from the USGS a...

Blankenship, D. Sandia National Laboratories

May 23, 2016
5 Resources
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EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for we...

Chai, C. et al Oak Ridge National Laboratory

Jun 01, 2020
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Utah FORGE: Report and Associated Data from Measuring and Modeling Deformation 2018 through 2024

The report provided here describes research activities between August 16th, 2018 and July 30th, 2024. The goals of the research activities are to conduct an Interferometric Synthetic Aperture Radar (InSAR) analysis and Ground Surface Deformation Modeling at the Utah FORGE site. In...

Feigl, K. and Batzli, S. University of Wisconsin Madison

Aug 16, 2018
6 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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Utah FORGE: 2024 Discrete Fracture Network Model Data

The Utah FORGE 2024 Discrete Fracture Network (DFN) Model dataset provides a set of files representing discrete fracture network modeling for the FORGE site near Milford, Utah. The dataset includes four distinct DFN model file sets, each corresponding to different time frames and ...

Finnila, A. and Jones, C. Energy and Geoscience Institute at the University of Utah

Sep 08, 2024
5 Resources
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Utah FORGE: Well 58-32 Stimulation Conference Paper and Data

The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...

Best, S. Energy and Geoscience Institute at the University of Utah

Apr 24, 2019
2 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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