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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
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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
0 Stars
Curated
26 Resources
0 Stars
Curated
Utah FORGE: Neubrex Well 16B(78)-32 Circulation Test Fiber Optics Monitoring Data and Reports July, 2023
This dataset features Distributed Acoustic Sensing (DAS) and fiber optics monitoring data acquired by Neubrex Energy Services during the Utah FORGE Well 16B(78)-32 circulation test in July 2023. DAS and fiber optic monitoring data include absolute strain, strain change, strain ch...
Juric, D. and Guzik, A. Energy and Geoscience Institute at the University of Utah
Oct 31, 2023
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Cape EGS: Frisco Pad Wells Flow Test Microseismic Data
This dataset contains microseismic data acquired during the Frisco pad flow test project led by Fervo Energy, conducted between July 17th Aug 12th 2024, near the Utah FORGE geothermal site. The microseismic data was collected from various Utah FORGE wells: via Distributed Acoustic...
Dadi, S. and Kanu, O. Fervo Energy
Nov 06, 2024
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
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
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Utah FORGE: Well 16A(78)-32 2022 Stimulation Microseismic Report
This is a Utah FORGE well 16A(78)-32 stimulation microseismic detection and event location report from Silixa LLC. The report covers the digital acoustic sensing (DAS) data acquisition and analysis used to study microseismic events during the April, 2022 stimulations at well 16A(7...
LLC, S. Energy and Geoscience Institute at the University of Utah
Sep 26, 2022
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
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
0 Stars
Curated
4 Resources
0 Stars
Curated
Utah FORGE 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity
This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the t...
Ward-Baranyay, M. et al Rice University
Jan 01, 2023
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
Utah FORGE: Neubrex Well 16B(78)-32 Cementing and Circulation Fiber Optics Monitoring Reports July, 2023
Included here are two fiber optics monitoring reports on Utah FORGE well 16B(78)-32 from Neubrex Energy Services. These reports review the fiber optics monitoring during both the cementing and circulation test periods of the well. Cementing as well as post-cementing monitoring a...
Jurick, D. et al Neubrex Energy Services (US), LLC
Oct 21, 2023
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utah FORGE 3-2417: Fiber-Optic Geophysical Monitoring of Reservoir Evolution 2024 Annual Workshop Presentation
This is a presentation on the Fiber-Optic Geophysical Monitoring of Reservoir Evolution by Rice University, presented by Jonathan Ajo-Franklin. This video slide presentation discusses the development of an end-to-end fiber-optic sensing approach for EGS to track the (1) initial zo...
Ajo-Franklin, J. et al Energy and Geoscience Institute at the University of Utah
Aug 13, 2024
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE: Reports on Northwestern Nevada Well Doublet Drilling and Testing by Fervo Energy
These reports review Fervo Energy's construction of a commercial enhanced geothermal system (EGS). Fervo has qualified full functionality of the system through production testing at commercially relevant operating conditions. The project site is located in a nearfield setting ad...
Dadi, S. et al Fervo Energy
Sep 05, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utah FORGE 2439: Report on Minifrac Tests for Stress Characterization
This report describes minifrac tests conducted in the 16B(78)-32 well at the Utah FORGE site to characterize subsurface stresses, including the magnitude and orientation of the minimum and maximum horizontal stresses and the magnitude of the vertical stress. A minifrac test was co...
Kelley, M. et al Battelle Memorial Institute
Feb 22, 2024
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE: Milford Triaxial Test Data and Summary from EGI labs
Six samples were evaluated in unconfined and triaxial compression, their data are included in separate excel spreadsheets, and summarized in the word document. Three samples were plugged along the axis of the core (presumed to be nominally vertical) and three samples were plugged ...
Moore, J. Energy and Geoscience Institute at the University of Utah
Mar 01, 2016
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
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
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utah FORGE: GeoThermOPTIMAL Video
This is a project description video by Dr. William W. Fleckenstein related to their "Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores" R&D project at Utah FORGE which is linked...
Fleckenstein, W. Colorado School of Mines
Dec 12, 2022
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utah FORGE: Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores
This paper discusses the progress on a project funded by the DOE Utah FORGE (Frontier Observatory for Research in Geothermal Energy) for the development of a subsurface heat exchanger for Enhanced Geothermal Systems (EGS) using unique casing sleeves cemented in place and are used ...
Fleckenstein, W. et al Colorado School of Mines
Oct 05, 2022
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Utah FORGE 1-2551: Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores Workshop Presentation and Report
Included here are a presentation recording, slides, and report on the Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores project by Colorado School of Mines, presented by Dr. William W. Fleckenstei...
Fleckenstein, W. et al Colorado School of Mines
Sep 08, 2023
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Utah FORGE 4-2492: Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery 2024 Annual Workshop Presentation
This is a presentation on the Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Efficiency by The University of Texas at Austin, presented by Mukul M. Sharma. This video slide presentation discusses the following objectives: (1) to place fr...
Sharma, M. Energy and Geoscience Institute at the University of Utah
Sep 16, 2024
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE 3-2417: Well 16B(78)-32 Fiber-Optic Cable Installation Report
This is an installation report detailing placement of the integrated fiber-optic cable behind casing in Utah FORGE well 16B(78)-32. These activities occurred in July of 2023 immediately after the drilling of 16B. This report was prepared by the FOGMORE R&D project (Fiber Optic MOn...
Ajo-Franklin, J. et al Rice University
May 15, 2024
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
Kelley, M. et al Battelle Memorial Institute
Jun 19, 2023
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated