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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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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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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
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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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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
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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
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Utah FORGE 5-2615: Well 58-32 and 78-32 Poroelastic Properties

Lab data on permeability, grain bulk modulus, drained bulk modulus, Skempton's pore pressure coefficient, and Biot's effective stress coefficient for Utah Forge Well 58-32 and Well 78-32. Work done as part of project number 5-2615 by the University of Oklahoma.

Ghassemi, A. and Zhou, X. University of Oklahoma

Oct 31, 2022
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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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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
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Utah FORGE 5-2615: Thermo-poromechanical Response of Fractured Rock 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
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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
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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
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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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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
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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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Salton Sea Geothermal Development Nontechnical Barriers to Entry Analysis and Perspectives

The report included in this submission details the nontechnical barriers to entry for development of geothermal resources in the Salton Sea. The Salton Sea provides an economically viable opportunity for replacing the energy imported by California which makes up 25 percent of Cali...

Goodman, D. et al Pacific Northwest National Laboratory

Jun 28, 2022
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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
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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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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. The University of Oklahoma

Jun 12, 2024
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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
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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
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Magnetotelluric Data Collected in 2016 over the San Emidio Geothermal Field in Nevada

This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Usi...

Folsom, M. et al Ormat Technologies, Inc.

Nov 09, 2016
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Development of a Downhole Tool Measuring Real-Time Concentration of Ionic Tracers and pH in Geothermal Reservoirs

For enhanced or Engineered Geothermal Systems (EGS) geothermal brine is pumped to the surface via the production wells, the heat extracted to turn a turbine to generate electricity, and the spent brine re-injected via injection wells back underground. If designed properly, the sub...

Hess, R. et al Sandia National Laboratories

Mar 31, 2014
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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021 Version 2.0

This submission includes an update to the WHOLESCALESamples2021January.xls file where the strikes and dips initially reported have been corrected to comply with the right hand rule. The updated excel file and a link to the original submission are included in this report. The ori...

Kleich, S. et al University of Wisconsin Madison

Jan 12, 2021
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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021

This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in ...