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Utah FORGE: QuantumPro Well 16A(78)-32 and 16B(78)-32 Stimulation and Circulation Tracer Test Results 2024

This dataset includes results and supporting documentation from tracer tests conducted in 2024 at Utah FORGE. The tests involved injecting nanoparticle tracers into injection well 16A(78)-32 and monitoring their recovery in production well 16B(78)-32 to assess hydraulic connectivi...

Guo, Q. et al QuantumPro Inc.

Jan 07, 1970
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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: Deep Wells Water and Gas Sampling with Analyses by ThermoChem (October, 2022)

This data includes a document that describes the effort to collect and analyze water and gas samples from deep Utah FORGE wells 16A(78)-32, 58-32, 56-32 and 78B-32 along with additional pdf files showing ThermoChem's analyses attached as an appendix.

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

Oct 26, 2022
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Utah FORGE: RESMAN Well 16A(78)-32 and 16B(78)-32 Stimulation and Circulation Tracer Test Results 2024

This dataset contains tracer test results from stimulation and circulation experiments conducted on the Utah FORGE wells 16A(78)-32 and 16B(78)-32 during 2024. The data was collected by RESMAN Energy Technology and includes detailed tracer analysis from flowback, short and extende...

Hartvig, S. et al RESMAN Energy Technology

Jan 14, 2025
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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
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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: Triggered DAS and Continuous Downhole Geophone Data from April 2024 Stimulations

This dataset contains distributed acoustic sensing (DAS) and downhole geophone data collected during the April 2024 stimulation experiments at the Utah FORGE site. DAS data were acquired from well 16B(78)-32 by Neubrex and processed by GeoEnergie Suisse (GES), covering the period ...

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

Apr 01, 2024
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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
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Utah FORGE: Well 16A(78)-32 Stimulation DFN Fracture Plane Evaluation and Data

This dataset includes files used to fit planar fractures through the preliminary earthquake catalogs of the three stages of the April 2022 well 16A(78)-32 stimulation which is linked bellow. These planar features have been used to update the FORGE reference Discrete Fracture Netwo...

Finnila, A. WSP Golder

Oct 27, 2022
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EGS Collab Experiment 2: Shear Stimulation ERT Monitoring Data

This repository contains the electrical resistivity tomography (ERT) monitoring data that was collected before, during, and after shear stimulation attempts were conducted at EGS Collab. These tests were carried out on the SURF 4100 level during Experiment 2 in March, 2022. Flow a...

Johnson, T. Pacific Northwest National Laboratory

Mar 06, 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
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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
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EGS Collab Experiment 1: Circulation Testing

These data and test descriptions comprise a chilled circulation test conducted at the 164' fracture in the EGS Collab Experiment 1 testbed on the 4850 ft level of the Sanford Underground Research Facility. Descriptions of the meta data, design drawings for the flow testing system,...

Knox, H. et al Lawrence Berkeley National Laboratory

Apr 01, 2019
11 Resources
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EGS Collab Experiment 2: Continuous Active Source Seismic Monitoring (CASSM)

The dataset contains continuous active-source seismic monitoring (CASSM) data collected during EGS Collab Experiment 2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to investigate enhanced geoth...

Hopp, C. et al Lawrence Berkeley National Laboratory

Jan 06, 2025
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Utah FORGE: GeoThermOPTIMAL Presentation 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
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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
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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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EGS Collab Experiment 2: Microseismic Monitoring

This dataset contains continuous seismic waveform data recorded during stimulation and thermal circulation tests for the Enhanced Geothermal Systems (EGS) Collab Experiment #2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Da...

Hopp, C. Lawrence Berkeley National Laboratory

May 28, 2024
4 Resources
1 Stars
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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
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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
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EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper

Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...

Guglielmi, Y. Lawrence Berkeley National Laboratory

Sep 24, 2020
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EGS Collab Experiment 1: In-situ observation of pre-, co and post-seismic shear slip preceding hydraulic fracturing

Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the...

Guglielmi, Y. et al Lawrence Berkeley National Laboratory

May 22, 2018
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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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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...