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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
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Far-Field Stress Predictions for Utah FORGE Well 16B(78)-32 Under Thermal and Pore Pressure Variations

Report documenting completion of Milestones 4.2.2 and 4.3.1 of Utah FORGE Project 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress at the U.S. DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement We report (1) the far-field stress predictions at fiv...

Lu, G. et al University of Pittsburgh Pittsburgh, PA

Jun 05, 2025
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Awaiting curation

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
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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
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
4 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
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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
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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
2 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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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
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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
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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
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Seismic Survey 2016 Metadata at San Emidio, Nevada

1301 Vertical Component seismic instruments were deployed at San Emidio Geothermal field in Nevada in December 2016. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in o...

Lord, N. et al University of Wisconsin

Dec 05, 2016
10 Resources
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GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples

This dataset contains example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) framework, specifically for the fictional Kahunanui (KHN) geothermal power plant. The dataset includes synthetic time series data, confi...

Taverna, N. et al Upflow

Jan 30, 2023
10 Resources
0 Stars
In curation

Utah FORGE: Roosevelt Hot Springs Analytical Well-Based Temperature Model Data

This submission contains a cumulative record of one-dimensional temperature modeling based off of well data in the vicinity of the Utah FORGE site. Temperature log data from wells used, and in some cases were extrapolated below the bottom of a number of wells. The data were corre...

Podgorney, R. and Allis, R. Idaho National Laboratory

Dec 07, 2018
2 Resources
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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
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Community Geothermal: Borefield Design, Thermal Conductivity, and Subsurface Modeling Data Chicago, IL

This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes therm...

Baser, T. et al Saint Louis University

Dec 04, 2023
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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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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
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Deep Direct-Use Feasibility Study Energy Demand Characterization and Surface Plant Modeling for West Virginia University

This dataset provides information gathered to determine end use load and assessment of existing district heating systems (DHS). It also provides Aspen simulation files used to model hybrid natural gas geothermal district heating and cooling (GDHC) system along with Exchange Design...

Garapati, N. West Virginia University

Jan 09, 2020
4 Resources
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Snake River Plain FORGE: Site Characterization Data

The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater,...

Moos, D. and Barton, C. Idaho National Laboratory

Apr 18, 2016
49 Resources
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Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States

This dataset presents the results of techno-economic simulations performed using the Distributed Geothermal Market Demand Model (dGeo) to evaluate the feasibility of Enhanced Geothermal Systems (EGS)-based district heating in the Northeastern United States. Developed by the Nation...

Pauling, H. National Renewable Energy Laboratory

Sep 30, 2024
2 Resources
1 Stars
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Geomechanical Modeling for Thermal Spallation Drilling

Wells for Engineered Geothermal Systems (EGS) typically occur in conditions presenting significant challenges for conventional rotary and percussive drilling technologies: granitic rocks that reduce drilling speeds and cause substantial equipment wear. Thermal spallation drilling,...

Walsh, S. et al Lawrence Livermore National Laboratory

Aug 24, 2011
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EPRI Report: Enhancing Geothermal Representation in EPRI's US-REGEN Model

This report examines improvements to the representation of geothermal resources and technologies, including hydrothermal, near-field, and deep enhanced geothermal systems (EGS), in EPRI's US-REGEN capacity expansion model. Using updated datasets from the National Renewable Energy ...

Molar-Cruz, A. and Johnson, N. National Renewable Energy Laboratory

Dec 13, 2024
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Finite Volume Based Computer Program for Ground Source Heat Pump System Final Scientific Report

The goal of this project was to develop a detailed computer simulation tool for GSHP (ground source heat pump) heating and cooling systems. Two such tools were developed as part of this DOE (Department of Energy) grant; the first is a two-dimensional computer program called GEO2D ...

Menart, J. and Frederick, J. Wright State University

Jul 31, 2013
3 Resources
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