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Utah FORGE 6-3712: Report on Building a Recurrent Neural Network Framework for Induced Seismicity October, 2025

This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of designing a recurrent neural network (RNN) to predict induced seismicity. Background material is included t...
Williams, J. et al Global Technology Connection, Inc.
Oct 13, 2025
1 Resources
0 Stars
Curated

Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 May 2025

These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
Lu, G. et al University of Pittsburgh
Jun 05, 2025
2 Resources
0 Stars
Curated

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...
Williams, J. Energy and Geoscience Institute at the University of Utah
Sep 17, 2024
1 Resources
0 Stars
Publicly accessible

Utah FORGE: Focal Mechanism Catalog from Stage 3 of the April 2022 Stimulation Test

This submission includes focal-mechanism solutions derived from the Utah FORGE April 2022 Stage-3 stimulation. Waveforms were extracted around each event (short windows bracketing origin times) from the downhole three-component arrays in wells 58-32, 78-32, and 56-32 and the surfa...
Mohammadi, A. et al Texas A and M University
Sep 15, 2025
1 Resources
0 Stars
Curated

Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model

This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation. A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
0 Stars
Publicly accessible

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
2 Resources
0 Stars
Publicly accessible

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
Publicly accessible

Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation 2024 Annual Workshop Presentation

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, disc...
Dvory, N. Energy and Geoscience Institute at the University of Utah
Sep 15, 2024
1 Resources
0 Stars
Curated

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
Publicly accessible

Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation 2025 Workshop Presentation

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by Dr. No'am Zach Dvory. This video slide presentation, by the University of Utah, d...
Dvory, N. University of Utah
Sep 18, 2025
3 Resources
0 Stars
Curated

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS...
Bunger, A. Energy and Geoscience Institute at the University of Utah
Sep 04, 2024
1 Resources
0 Stars
Publicly accessible

Utah FORGE 6-3656: Real-Time Traffic Light System and Reservoir Engineering with Seismicity Forecasting and Ground Motion Prediction 2025 Workshop Presentation

This is a presentation on Real-Time Robust Adaptive Traffic Light System and Reservoir Engineering with Machine-Learning-Based Seismicity Forecasting and Data-Driven Ground Motion Prediction (RT Forecast) by Lawrence Berkeley National Laboratory, presented by Nori Nakata. This vid...
Nakata, N. Lawrence Berkeley National Laboratory
Sep 18, 2025
3 Resources
0 Stars
Curated

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
1 Stars
Publicly accessible

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2025 Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to esti...
Williams, J. GTC Analytics
Sep 18, 2025
3 Resources
0 Stars
Curated

Utah FORGE 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress 2025 Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by University of Pittsburgh, presented by Dr. Andrew Bunger. The project's objective was to characterize stress i...
Bunger, A. University of Pittsburgh
Sep 18, 2025
3 Resources
0 Stars
Curated

Utah FORGE 5-2419: Final Report and Presentation on Seismicity Permeability Relationships Probed via Nonlinear Acoustic Imaging

This submission contains the final technical report and closeout presentation for Utah FORGE Project 5-2419, which investigates the coupled evolution of permeability and induced seismicity in enhanced geothermal systems using laboratory experiments, field observations, and nonline...
Elsworth, D. Pennsylvania State University
Sep 30, 2025
2 Resources
0 Stars
Curated

Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement 2023 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the U...
Kelley, M. and Bunger, A. Battelle Memorial Institute
Sep 08, 2023
1 Resources
0 Stars
Curated

Utah FORGE 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress Final Report

This comprehensive technical report documents a multi-component approach to in-situ stress characterization at the Utah FORGE EGS site that integrates Machine Learning (ML) methods for predicting near-well principal stresses around geothermal wells with the physics-based finite el...
Bunger, A. et al University of Pittsburgh
Dec 22, 2025
1 Resources
0 Stars
Curated

Utah FORGE: Source Imaging DAS-Based Seismic Event Catalog April 2024 Stimulation

This catalog contains microseismic event locations recorded during the April 2024 stimulation at the Utah FORGE site. Events were detected and located using a DAS-specific source imaging workflow that avoids conventional phase picking. Instead, STA/LTA-transformed DAS and downhole...
Dvory, N. et al The University Of Utah
Aug 26, 2025
1 Resources
0 Stars
Curated

Utah FORGE: Deep Wells Temperature Surveys as of September 2022

This Excel spreadsheet contains temperature survey results for Utah FORGE wells 58-32, 78-32, 56-32, 16A(78)-32 and 78B-32. It also contains charts and comparisons, along with a "Data Summary" which provides links to previous GDR submissions with temperature data for each well.
Jones, C. Energy and Geoscience Institute at the University of Utah
Sep 16, 2022
1 Resources
0 Stars
Publicly accessible

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes 2023 Annual Workshop Presentation

This is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University, presented by Distinguished Professor of Physics & Astronomy, Laura J. Pyrak...
Pyrak-Nolte, L. Purdue University
Sep 08, 2023
1 Resources
0 Stars
Curated

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
3 Resources
0 Stars
Publicly accessible

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
5 Resources
0 Stars
Publicly accessible

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
2 Resources
0 Stars
Publicly accessible

Utah FORGE: Milford Deep Test Well 58-32 (MU-ESW1) Pressure and Temperature Logs

This archive consists of a pdf graphic log and a LAS text file representing the results of the pressure and temperature logs measured on Nov. 8th, 2018 from the Utah FORGE deep test well 58-32 (MU-ESW1). The logs were taken by DI Drill Survey Services.
Moore, J. Energy and Geoscience Institute at the University of Utah
Nov 08, 2018
1 Resources
0 Stars
Publicly accessible
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