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Utah FORGE×

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
Publicly accessible

Utah FORGE: InSAR Data 2019

This dataset contains Interferometric Synthetic Aperture Radar (InSAR) data used for ground deformation monitoring during Phase 2C of the Utah FORGE project. The dataset includes measurements of the mean rate of range change and associated standard errors, provided in both CSV and...
Feigl, K. et al Energy and Geoscience Institute at the University of Utah
Jul 01, 2019
2 Resources
0 Stars
Publicly accessible

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 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 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 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 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement 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
Publicly accessible

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 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 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: 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 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes 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
Publicly accessible

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

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 4-2541: Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design Workshop Presentation

This is a presentation on the Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design at Utah FORGE project by Fervo Energy, presented by Sireesh Dadi. The project's objective was to develop a multistage hydraulic stimulation approach designed specifically to t...
Dadi, S. and Norbeck, J. Fervo Energy
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

Utah FORGE: Updated Discrete Fracture Network Model 2025

The Utah FORGE 2025 v1 DFN (fracture model) includes 131 discrete planar fractures which were identified using combined site data sets to capture flow pathways between wells 16A(78)-32 and 16B(78)-32 following stimulation activities in 2022 and 2024. It also includes stochastic fr...
Finnila, A. WSP
Jul 24, 2025
3 Resources
0 Stars
Curated

Utah FORGE: Phase-Picking Based Microseismic 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 phase-picking workflow that integrates downhole geophones (wells 56 and 78B) and downhole DAS (well 16B). P and S-wave arr...
Zhu, W. et al University Of Utah
Feb 19, 2026
2 Resources
0 Stars
Awaiting curation

Cape EGS: Gold 4-PB: Mudlog, Mass Spectrometry, Triple Combo, and Dipole Sonic-Derived Geomechanical data

This dataset includes geological and geophysical well logs from the Gold 4-PB well at the Cape EGS site near Utah FORGE, collected between December 2024 and January 2025. The dataset covers lithological, geochemical, and petrophysical data acquired during and after drilling. Data ...
Dadi, S. and Adams, T. Fervo Energy
Apr 30, 2025
6 Resources
0 Stars
Curated

Cape EGS and Utah FORGE: Empirical 3D Seismic Velocity Model

This dataset provides an empirical three-dimensional P and S-wave velocity model covering a 30 x 30 km area and extending to 10 km depth around the Cape Modern EGS and Utah FORGE sites. It incorporates three-dimensional topography and a sediment/basement contact derived from geoph...
Nakata, N. et al Lawrence Berkeley National Laboratory
Nov 12, 2025
3 Resources
0 Stars
Curated

Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events

This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Williams, J. et al Global Technology Connection, Inc.
Jan 21, 2025
3 Resources
0 Stars
Publicly accessible
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