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Utah FORGE 3-2514: A Strain Sensing Array to Characterize Deformation at the FORGE Site Workshop Presentation

This is a presentation on the Strain Sensing Array to Characterize Deformation at the FORGE Site project by Clemson University, presented by Lawrence Murdoch. The project's objective was to evaluate the feasibility of measuring and interpreting tensor strain data to improve the pe...

Murdoch, L. et al Clemson University

Sep 08, 2023
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Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32

This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for dow...

Pankow, K. University of Utah

Mar 18, 2020
5 Resources
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Utah FORGE: Well 16B(78)-32 Distributed Temperature Sensing Data from April and May 2024

This dataset includes Neubrex Energy Services fiber optic distributed temperature sensing (DTS) data from well 16B(78)-32 during stimulation and circulation, including interaction with well 16A(78)-32, during April and May 2024. The DTS data are stored in HDF5 file format and are ...

Jurick, D. and Guzik, A. Energy and Geoscience Institute at the University of Utah

Jul 08, 2024
1 Resources
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Utah FORGE: High-Resolution DAS Microseismic Data from Well 78-32

This regards a high-resolution DAS microseismic dataset produced by Silixa from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. It is a very large dataset and as such it is currently not directly available on GDR. However, it is availabl...

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

Oct 20, 2019
5 Resources
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Thermal Drawdown Induced Flow Channeling in Fractured Geothermal Reservoirs: Rock Mechanics and Rock Engineering

We investigate the flow-channeling phenomenon caused by thermal drawdown in fractured geothermal reservoirs. A discrete fracture network-based, fully coupled thermal "hydrological" mechanical simulator is used to study the interactions between fluid flow, temperature change, and t...

Fu, P. et al Lawrence Livermore National Laboratory

Nov 15, 2015
1 Resources
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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
3 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
1 Resources
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Full Moment Tensor Inversion Software

The link points to a website at NCEDC to download the full moment tensors inversion software The moment tensor analysis conducted in the current project is based on the full moment tensor model described in Minson and Dreger (2008). The software including source, examples and tut...

Gritto, R. and Dreger, D. Array Information Technology

Oct 31, 2018
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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
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EGS Collab Experiment 1: Microseismic Monitoring

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...

Schoenball, M. et al Lawrence Berkeley National Laboratory

Jul 29, 2019
46 Resources
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EGS Collab: Modeling and Simulation Working Group Teleconference Series (99-128)

This submission contains the presentation slides and recordings from EGS Collab Modeling and Simulation Working Group (MSWG) teleconferences number 99 through 128. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field acti...

White, M. et al Pacific Northwest National Laboratory

Jun 07, 2022
31 Resources
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Utah FORGE: Distributed Acoustic Sensing Data 2022

This is a link to the website where Distributed Acoustic Sensing (DAS) seismic data, collected from wells 78-32 and 78B-32 during the Utah FORGE 2022 stimulation, is available for download. The data can be accessed at "Well 16A78-32 2022 Stimulation Seismicity Data" link in the su...

Pankow, K. University of Utah Seismograph Stations

Apr 29, 2022
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Utah FORGE: 2022 Well Stimulation Seismicity Data Including SeGY Data

This is a link to the Utah FORGE seismic data distribution site hosted by the University of Utah Seismograph Stations. The data was collected from downhole geophone strings in wells 56-32, 58-32 and 78B-32 during the 2022 stimulation of well 16A(78)-32. This dataset, which was upd...

Pankow, K. University of Utah Seismograph Stations

Apr 14, 2023
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EGS Collab Experiment 1 Stimulation Data

Stimulation data from Experiment 1 of EGS Collab, which occurred on the 4850 ft level of the Sanford Underground Research Facility (SURF). A detailed description of the stimulation data is provided in the StimulationDataNotes.docx and is also available on the EGS Collab Wiki. A M...

Knox, H. et al Pacific Northwest National Laboratory

Aug 13, 2020
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EGS Collab Experiment 1: Well Locations and Orientations.

The EGS Collab is conducting experiments in hydraulic fracturing at a depth of 1.5 km in the Sanford Underground Research Facility (SURF) on the 4850 Level. A total of eight ~60m-long subhorizontal boreholes were drilled at that depth on the western rib of the West Access Drift. S...

Neupane, G. et al Idaho National Laboratory

Sep 05, 2018
12 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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Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32

Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, f...

DeWolf, S. and Murdoch, L. Clemson University

Sep 15, 2022
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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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Cape EGS: Frisco 2-P Well Stimulation Microseismic Data

This dataset contains microseismic data acquired during the Frisco 2-P well stimulation project led by Fervo Energy, conducted between June 1 and June 11, 2024, near the Utah FORGE geothermal site. The microseismic data was collected from various Utah FORGE wells: via Distributed ...

Dadi, S. and Titov, A. Fervo Energy

Sep 19, 2024
26 Resources
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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
10 Resources
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Utah FORGE: Wells 16A(78)-32 and 16B(78)-32 Stimulation Pressure and Circulation Data April, 2024

This dataset consists of all of the pressure pumping data for Utah FORGE Well16A78-32 fracturing stages, Well 16B78-32 fracturing stages, and a 9-hour circulation test which took place after all of the frac plugs were drilled out. Fracturing in the wells took place in stages from ...

England, K. Energy and Geoscience Institute at the University of Utah

Jun 03, 2024
4 Resources
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Utah FORGE: Well 58-32 Injection Test Data

This submission contains pressure and flow time series data from the reservoir testing of Well 58-32. These activities were part of the Utah FORGE Phase 2B site suitability confirmatory testing.

Podgorney, R. and McLennan, J. Idaho National Laboratory

Dec 07, 2018
2 Resources
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Utah FORGE: Well 16A(78)-32 Stimulation Data (April, 2022)

This is a set of data related to the stimulation program at Utah FORGE well 16A(78)-32 during April, 2022. This includes daily reports, 1 second Pason data, tracer data, and shear stimulation data and information including a report of an evolving prognosis for the stimulation oper...

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

May 18, 2022
11 Resources
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Utah FORGE: Neubrex Well 16B(78)-32 DAS Data April, 2024

This dataset comprises Distributed Acoustic Sensing (DAS) data collected from the Utah FORGE monitoring well 16B(78)-32 (the producer well) during hydraulic fracture stimulation operations conducted in April 2024. The data were acquired continuously over the stimulation period at ...

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

Oct 01, 2024
4 Resources
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EGS Collab Experiment 1: Continuous Active-Source Seismic Monitoring (CASSM) Data

Schoenball, M. and Sprinkle, P. Lawrence Berkeley National Laboratory

Apr 25, 2018
6 Resources
1 Stars
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