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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

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible

Utah FORGE 3-2535: Final Report on Joint Electromagnetic, Seismic, and InSAR Imaging of Fracture Growth During EGS Resource Development

This dataset contains the final technical report for the project Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development, carried out from 2021 to 2025 by Lawrence Berkeley Natio...
Alumbaugh, D. Lawrence Berkeley National Laboratory
May 30, 2025
1 Resources
0 Stars
Curated

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

Simulation Tools for Modeling Thermal Spallation Drilling on Multiple Scales

Widespread adoption of geothermal energy will require access to deeply buried resources in granitic basement rocks at high temperatures and pressures. Exploiting these resources necessitates novel methods for drilling, stimulation, and maintenance, under operating conditions that ...
Walsh, S. et al Lawrence Livermore National Laboratory
Jan 01, 2012
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

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Buster, G. et al Upflow
Jun 30, 2021
11 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 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: 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

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: 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

Utah FORGE 1-2551: Final Report and Presentation on Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores

This dataset contains the final technical report for the CSM project, conducted by the Colorado School of Mines and project partners to address materials and wellbore challenges in high-temperature geothermal environments. The report documents research activities carried out to de...
Fleckenstein, W. Colorado School of Mines
Jul 08, 2025
2 Resources
0 Stars
Curated

Project Data for Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers

This dataset contains project data generated by the project "Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers." It includes drilling, downhole drilling dynamics, bit records, daily drilling reports, directional surveys, lithology and mineralogy data, ...
Wriedt, J. and So, P. Geysers Power Company, LLC
Mar 31, 2026
20 Resources
0 Stars
In curation

Utah FORGE 7-3639: Design and Implementation of a Novel Multi-Frac Stimulation Concept 2025 Workshop Presentation

This is a presentation on the Design and Implementation of a Novel Multi-Frac Stimulation Concept by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the design and implementation of a reservoir stimulation concept improving near-wel...
Ghassemi, A. The University of Oklahoma
Sep 18, 2025
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

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

Hawthorne Nevada Deep Direct-Use Feasibility Study 3D Seismic

The objective of this project is to use a multi-disciplinary, three-tiered approach to assess the geothermal resource and determine the feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the various town and county facilities in H...
Lowry, T. et al Nevada Bureau of Mines and Geology
Mar 29, 2018
6 Resources
0 Stars
Publicly accessible

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes 2025 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, Dr. Laura J. P...
Pyrak-Nolte, L. Purdue University
Sep 18, 2025
3 Resources
0 Stars
Curated

Utah FORGE 6-3712: Curated and Fused 2022 and 2024 Stimulation Injection Datasets and Processing Report February 2026

This submission contains curated injection parameter datasets from the 2022 and 2024 stimulation experiments conducted at the Utah FORGE site, along with the report documenting the data processing workflow. The datasets were developed as part of Project 6-3712: Probabilistic Estim...
Williams, J. et al Global Technology Connection, Inc.
Feb 25, 2026
3 Resources
0 Stars
Curated

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
0 Stars
Publicly accessible

Utah FORGE 5-2615: Laboratory Data for Insights on Hydraulic Fracture Closure and Stress Measurement

This dataset includes data from injection/fall-off experiments conducted in controlled laboratory settings. The aim is to investigate the physics governing fracture closure and the associated stress measurements during hydraulic fracturing. These time series data include flow rat...
Ye, Z. and Ghassemi, A. University of Oklahoma
Jun 12, 2024
6 Resources
0 Stars
Publicly accessible

Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: Data used in Geosphere Journal Article

This data submission is for Phase 2 of Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations, which focuses on multi-fluid (CO2 and brine) geothermal energy production and diurnal bulk energy storage in geologic settings that are suitable for ...
A., T. Lawrence Livermore National Laboratory
Jun 01, 2015
2 Resources
1 Stars
Publicly accessible

Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress

Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizi...
Bunger, A. et al Battelle Memorial Institute
Dec 13, 2022
4 Resources
0 Stars
Publicly accessible

Synthetic Lithium Prize Brine for Finalists of the Geothermal Lithium Extraction Prize Competition

The Department of Energy (DOE), Geothermal Technologies Office (GTO) launched a multi-phase funding program to advance technologies for extraction of lithium from geothermal brines. This initiative, known as American-Made Geothermal Lithium Extraction Prize (GLEP), had objectives ...
Neupane, G. and Smith, R. Idaho National Laboratory
Sep 29, 2023
1 Resources
0 Stars
Publicly accessible
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