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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
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
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3 Resources
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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
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1 Resources
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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
3 Resources
0 Stars
Publicly accessible
Stanford Thermal Earth Model for the Conterminous United States
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Aljubran, M. and Horne, R. Stanford University
Mar 14, 2024
9 Resources
2 Stars
Publicly accessible
9 Resources
2 Stars
Publicly accessible
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
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1 Resources
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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
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Publicly accessible
4 Resources
0 Stars
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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
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
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3 Resources
0 Stars
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Utah FORGE 5-2615: Determination and Analysis of Thermo-poromechanical Response of Fractured Rock 2024 Annual Workshop Presentation
This is a presentation on the Determination and Modeling-Informed Analysis of Thermo-poromechanical Response of Fractured Rock for Application to FORGE by the University of Oklahoma, presented by Ahmad Ghassemi. This video presentation discusses how to improve understanding and co...
Ghassemi, A. Energy and Geoscience Institute at the University of Utah
Sep 01, 2024
1 Resources
0 Stars
Publicly accessible
1 Resources
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Literature Collection for the Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers
This submission contains links to multiple publications on the Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers. The long-term goal of the project was to safely implement oil and gas industry drilling best-practices, particularly with respect to limit...
Wriedt, J. Geysers Power Company, LLC
Jan 20, 2026
6 Resources
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6 Resources
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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
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11 Resources
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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
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2 Resources
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Identifying Pathways for Enhanced Collaboration between the Mining and Geothermal Industries Techno-Economic Analysis and Data Summaries
These spreadsheets include a Techno-Economic Analysis (TEA) summary and descriptions and links to mining data analyzed as part of this study. The TEA summary includes the results from several mining data-informed geothermal development models analyzed using the DOE's Geothermal El...
Rhodes, G. et al National Renewable Energy Laboratory
Mar 31, 2020
2 Resources
1 Stars
Publicly accessible
2 Resources
1 Stars
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Colorado Heat Flow Data from IHFC
This layer contains the heat flow sites and data of the State of Colorado compiled from the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI) global heat flow database. The data include different i...
E., R. Flint Geothermal, LLC
Feb 01, 2012
1 Resources
0 Stars
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1 Resources
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Utah FORGE 5-2615: Thermo-poromechanical Response of Fractured Rock 2023 Annual Workshop Presentation
This is a presentation on the Experimental Determination and Modeling-Informed Analysis of Thermo-poromechanical Response of Fractured Rock for Application to Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Prof. The project objec...
Ghassem, A. University of Oklahoma
Sep 08, 2023
1 Resources
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1 Resources
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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
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Publicly accessible
2 Resources
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Utah FORGE: Hydraulic Fracture Width Determination Using Stoneley Wave Pressure Testing and Electrical Borehole Scans
This report provides insights into Utah FORGE well 58-32's hydraulic fractures. It utilizes both electrical borehole scans from Schlumberger's Formation Micro-scanner Image tool (FMI) and Stoneley waves from a borehole sonic tool. These methods are combined in a comprehensive work...
Hornby, B. Hornby Geophysical Services, LLC
Oct 06, 2023
1 Resources
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1 Resources
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Utah FORGE: 2024 Annual Report on Activities and Advancements
This 2024 annual report for Phase 3B Year 2 at Utah FORGE provides an in-depth account of activities and advancements made at the site. Key achievements include drilling and stimulating the production well 16B(78)-32, creating a geothermal reservoir, and achieving commercial-scale...
McLennan, J. et al Energy and Geoscience Institute at the University of Utah
Jan 27, 2025
1 Resources
1 Stars
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1 Resources
1 Stars
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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
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3 Resources
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WHOLESCALE: Coordinates of wells at San Emidio, Nevada
This dataset includes position coordinates and elevation information for wells at the WHOLESCALE San Emidio project location. Well positions in the attached file are characterized by UTM coordinates (Easting, Northing) in meters, and WHOLESCALE coordinates (Easting, Northing) rel...
Cardiff, M. et al University of Wisconsin Madison
Sep 25, 2023
1 Resources
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1 Resources
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WHOLESCALE: Mass Flux Rates for Wells at San Emidio in December 2016
This dataset provides mass flux rates in kg/s from six (production and injection) wells at San Emidio at minute intervals from December 1, 2016 December 15, 2016. Files for injection wells are named with "IW", for instance "WellIW42-21SI.csv", and include negative flux rates. Fil...
Cardiff, M. et al University of Wisconsin Madison
Dec 01, 2016
2 Resources
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2 Resources
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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
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1 Resources
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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
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3 Resources
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Passive Seismic Emission Tomography Results at San Emidio Nevada
The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic...
Warren, I. et al Ormat Technologies, Inc.
Dec 01, 2016
2 Resources
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2 Resources
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