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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 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
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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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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
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6 Resources
0 Stars
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Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2026 Workshop Presentation
This is a presentation on Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics (Global Technology Connection), presented by Dr. Jesse Williams. The project is developing machine-learning and physics-informed models to impro...
Williams, J. GTC Analytics
Sep 30, 2026
3 Resources
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Publicly accessible
3 Resources
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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
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1 Resources
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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
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2 Resources
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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
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9 Resources
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TEAMER: Reliability Analysis and New Technology Qualification of an Infinitely Variable Transmission for Tidal Energy Converters
This project leverages the complementary expertise of American Bureau of Shipping (ABS) and Idaho National Laboratory (INL) to establish a comprehensive qualification and reliability assessment framework for an infinitely variable transmission (IVT). INL will implement an advanced...
Zhang, X. et al Mississippi State University
Aug 21, 2026
15 Resources
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15 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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4 Resources
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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
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1 Resources
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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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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
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3 Resources
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Programs and Code for Geothermal Exploration Artificial Intelligence
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Moraga, J. Colorado School of Mines
Apr 27, 2021
11 Resources
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11 Resources
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Dataset of Generative AI Workload Power Profiles
This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of r...
Vercellino, R. et al National Laboratory of the Rockies
Mar 31, 2026
1 Resources
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1 Resources
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Airfoil Computational Fluid Dynamics 2k shapes, 25 AoA's, 3 Re numbers
This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes w...
Ramos, D. et al National Renewable Energy Laboratory (NREL)
Feb 10, 2023
3 Resources
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3 Resources
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Airfoil Computational Fluid Dynamics 9k shapes, 2 AoA's
This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes ...
Ramos, D. et al National Renewable Energy Laboratory (NREL)
Feb 10, 2023
3 Resources
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3 Resources
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Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets
This dataset contains turbine and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in ...
Ramos, D. et al National Renewable Energy Laboratory
Feb 12, 2021
5 Resources
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5 Resources
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INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements
The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...
Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)
May 04, 2021
8 Resources
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8 Resources
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Automated Fish Detection and Wildlife Tracking for Marine Energy Applications: Final Report and Review
This submission contains two technical resources produced for the U.S. Department of Energy Water Power Technologies Office (WPTO) that evaluate and advance automated methods for underwater wildlife detection, tracking, and monitoring around marine energy systems. The project anal...
Slater, W. et al Booz Allen Hamilton Inc.
Dec 08, 2025
2 Resources
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2 Resources
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Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
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12 Resources
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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
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1 Resources
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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
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3 Resources
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Utah FORGE 5-2557: Final Report and Presentation for the Role of Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes for Enhanced Geothermal Systems
This contains a final technical report and closeout presentation recording summarizing the results from Utah FORGE Project 5-2557 on the role of fluid pressure and temperature in fracture mechanics and coupled thermo-hydro-mechanical-chemical (THMC) processes relevant to enhanced ...
Pyrak-Nolte, L. Purdue University
Nov 30, 2025
2 Resources
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2 Resources
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Surface Meteorological Station ANL 10m, (1) Sonic, Physics site-9 Raw Data
**Overview**
Sonic anemometers from Physics Site-3 and Site-9 provide wind components and virtual temperature. The energy balance Bowen ratio (EBBR) station at Physics site-3 provides measurements of the surface fluxes of latent and sensible heat, net radiation, and surface soil ...
Cook, D. Wind Energy Technologies Office (WETO)
Mar 28, 2016
1 Resources
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1 Resources
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