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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
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Utah FORGE: Stress Logging Data

This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in...

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

Mar 14, 2018
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Utah FORGE: Deep Well 58-32 (MU-ESW1) Core Data

These datasets, images, and graphics were derived from core drilling and core that was extracted from Utah Forge deep well 58-32 (originally called MU-ESW1), near Roosevelt Hot Springs.

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

Apr 11, 2018
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Utah FORGE: Well Data for Student Competition

Well 58-32 (previously labeled MU-ESW1) was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. Well Accord-1 was drilled decades ago for geothermal exploration purposes. While ...

Podgorney, R. et al Idaho National Laboratory

Dec 07, 2018
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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
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Utah FORGE: Drilling Data for Student Competition

Diagnostic drilling data (Pason log files) from Well 58-32 (previously labeled MU-ESW1), which was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. This dataset includes both ...

Podgorney, R. et al Idaho National Laboratory

Dec 07, 2018
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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
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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...

Lu, G. et al University of Pittsburgh

Aug 30, 2024
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Utah FORGE: Well 78B-32 Core Sample Petrographic Analysis Data

This dataset contains an overview of the petrographic, X-ray Diffraction and scanning electron microscopy analyses of core samples from Utah FORGE Well 78B-32 and related data as described in the .zip folder's Description below.

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

Feb 21, 2023
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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
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Utah FORGE: Well 16A(78)-32 Perforation Images and Raw Data

This archive contains raw data of visual and acoustic mapping of perforations in Utah FORGE well 16A(78)-32 acquired during the August 2024 circulation program. The dataset includes downhole images captured by EV, a downhole visual analytics company, providing visual records of ea...

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

Nov 05, 2024
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Seismic Analysis of Spatio-Temporal Fracture Generation During EGS Resource Development Deviatoric MT, Fracture Network, and Final Report

This submission contains 167 deviatoric moment tensor (MT) solutions for the seismicity observed two years prior and three years post start of injection activities at The Geysers Prati 32 EGS Demonstration. Also included is a statistical representation of the properties of 751 fra...

Gritto, R. et al Array Information Technology

Sep 01, 2018
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Utah FORGE: Downhole Geophone Seismic Data (August 2022)

This is a link to downhole geophone data collected by Schlumberger. These data were collected in the Utah FORGE deep seismic monitoring wells 58-32 and 56-32. The format is a standard SEGY and the units are bits. To convert to acceleration (m/s2) multiply by 2.333 x 10-7. Use one ...

Pankow, K. and Schlumberger, S. University of Utah Seismograph Stations

Aug 25, 2022
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Utah FORGE: Powder X-ray Diffraction Data from Well 16A(78)-32 Core

This dataset from Lawrence Livermore National Laboratory (LLNL) consists of four raw X-ray diffraction (XRD) scans and preliminary results of quantitative XRD analysis. The scanned samples were prepared from four subcores, which came from various depths of the FORGE well 16A(78)-3...

Kroll, K. et al Lawrence Livermore National Laboratory

Jul 27, 2023
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Utah FORGE: Well 16A(78)-32 Core Analysis Results

This dataset features petrographic, X-Ray Diffraction (XRD), and Scanning Electron Microscopy Analyses of core samples from well 16A(78)-32, which serves as the injection well for the Utah FORGE Enhanced Geothermal System (EGS) project. In addition to an overview of the analysis,...

Jones, C. et al Energy and Geoscience Institute at the University of Utah

Sep 22, 2023
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Utah FORGE: Phase 2C Topical Report

This is the topical report that wraps up the work and results achieved during Utah FORGE Phase 2C. The zip file includes several folders containing (1) an overview; (2) the results; (3) the lessons learned; and (4) the conclusions. It also contains a folder containing appendices i...

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

Dec 11, 2019
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Utah FORGE: Well 16A(78)-32 Core-Flooding Experiment Results

This dataset contains core-flood experimental results from the Utah FORGE project, generated through laboratory tests at Lawrence Livermore National Laboratory. The experiments were conducted at temperatures of 100C and 200C using core samples from the 16A(78)-32 well. The primary...

Smith, M. et al Lawrence Livermore National Laboratory

Apr 04, 2024
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Utah FORGE: Borehole PSS Tools Status Report

This report summarizes the data quality from the Utah FORGE borehole passive seismic sensors (PSS) tools at well sites 58-32 and 78B-32. Two level Avalon tools were installed on 09-28-2022 and 09-29-2022 by representatives from Avalon, Schlumberger, University of Utah, and Instrum...

Stachnik, J. Instrumental Software Technologies, Inc.

Dec 29, 2022
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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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Utah FORGE: Regional Well Locations

This archive contains a GIS point feature shapefile that shows the locations of wells in the general region of the Utah FORGE project, near Roosevelt Hot Springs. This includes Utah FORGE deep well 58-32 and wells for which data has been uploaded to the Geothermal Data Repository....

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

Feb 22, 2018
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Life Cycle Water Consumption and Water Resource Assessment for Utility-Scale Geothermal Systems: An In-Depth Analysis of Historical and Forthcoming EGS Projects

This report is the third in a series of reports sponsored by the U.S. Department of Energy Geothermal Technologies Program in which a range of water-related issues surrounding geothermal power production are evaluated. The first report made an initial attempt at quantifying the li...

Schroeder, J. et al Argonne National Laboratory

Aug 31, 2013
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Utah FORGE: Seismic Stations and Wells GPS Survey Data, 2021

This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 58-32, and 16A(78)-32 and BOR1, BOR2, BOR3, FOR2, FOR5, FORK, FORU, and FORW seismic stations. These are from a GPS survey conducted by the Utah Geological Survey in Jun...

Erickson, B. Utah Geological Survey

Jun 30, 2021
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Utah FORGE 7-3639: Design and Implementation of a Novel Multi-Frac Stimulation Concept 2024 Annual Workshop Presentation

This is a presentation on the Design and Implementation of a Novel Multi-Frac Stimulation Concept by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the design and implementation of a reservoir stimulation concept improving near-wel...

Ghassemi, A. and Jeffery, R. Energy and Geoscience Institute at the University of Utah

Sep 02, 2024
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First Tracer Test After Circulation in Desert Peak 27-15

Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored ove...

Rose, P. University of Utah

Nov 16, 2013
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Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report

This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...

Mustafa, A. et al Battelle Memorial Institute

Sep 28, 2023
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