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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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2 Resources
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Mordensky, S. et al United States Geological Survey
Feb 07, 2023
7 Resources
1 Stars
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7 Resources
1 Stars
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Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
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4 Resources
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Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
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3 Resources
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Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
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4 Resources
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Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation 2024 Annual Workshop Presentation
This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, disc...
Dvory, N. Energy and Geoscience Institute at the University of Utah
Sep 15, 2024
1 Resources
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1 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
0 Stars
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Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model
This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation.
A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
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1 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 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement 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 Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the U...
Kelley, M. and Bunger, A. Battelle Memorial Institute
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 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 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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Stimulation at Desert Peak Modeling with the Coupled THM Code FEHM
Numerical modeling of the 2011 shear stimulation at the Desert Peak Well 27-15 using a coupled thermal-hydrological-mechanical simulator. This submission contains the finite element heat and mass transfer (FEHM) executable code for a 64-bit PC Windows-7 machine, and the input and ...
Kelkar, S. et al Los Alamos National Laboratory
Apr 30, 2013
1 Resources
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1 Resources
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EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper
Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...
Guglielmi, Y. Lawrence Berkeley National Laboratory
Sep 24, 2020
9 Resources
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9 Resources
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DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...
Taverna, N. et al National Renewable Energy Laboratory
Jan 24, 2024
14 Resources
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14 Resources
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Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)
Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy.
Objective and Purpose:
Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...
Norbeck, J. et al Fervo Energy
Feb 08, 2023
3 Resources
1 Stars
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3 Resources
1 Stars
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Utah FORGE: Composite 3D Seismic Velocity Model
This is a composite 3D seismic velocity that was constructed from compiled information from several local studies regarding seismic velocities and structural information. This seismic velocity model is provided in NonLinLoc format (slow_len), which is readily usable in NonLinLoc ...
Finger, C. et al University of Utah Seismograph Stations
Feb 09, 2024
1 Resources
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1 Resources
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Newberry Caldera Conceptual Geologic Model
Conceptual model for the Newberry Caldera geothermal area. Model is centered around caldera and evaluates geologic information in tandem with some geophysical datasets to derive a conceptual subsurface model.
Includes:
Geologic information from the USGS geologic map of Newberry...
Moser, M. et al National Energy Technology Laboratory
Mar 04, 2016
1 Resources
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1 Resources
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Newberry Caldera Conceptual Geophysical Model
Conceptual model for the Newberry Caldera geothermal area. Model is centered around caldera and evaluates multiple geophysical datasets to derive a conceptual subsurface model.
Includes:
Conductor layer based on transient electromagnetic data from Fitterman et al., 1988 (figure...
Moser, M. et al National Energy Technology Laboratory
Mar 04, 2016
1 Resources
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1 Resources
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Fallon FORGE: 3D Geologic Model
An x,y,z scattered data file for the 3D geologic model of the Fallon FORGE site. Model created in Earthvision by Dynamic Graphic Inc. The model was constructed with a grid spacing of 100 m. Geologic surfaces were extrapolated from the input data using a minimum tension gridding al...
Blankenship, D. Sandia National Laboratories
Mar 01, 2016
1 Resources
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1 Resources
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West Flank Coso FORGE: 3D Geologic Model
This is an x,y,z file of the West Flank FORGE 3D geologic model. Model created in Earthvision by Dynamic Graphic Inc. The model was constructed with a grid spacing of 100 m. Geologic surfaces were extrapolated from the input data using a minimum tension gridding algorithm.
The da...
Blankenship, D. Sandia National Laboratories
Mar 01, 2016
1 Resources
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1 Resources
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Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report
The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodlogy calibration...
Iovenitti, J. AltaRock Energy Inc
May 15, 2013
2 Resources
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2 Resources
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Three Dimensional Thermal Model of Newberry Volcano, Oregon
Final results of a 3D finite difference thermal model of Newberry Volcano, Oregon. Model data are formatted as a text file with four data columns (X, Y, Z, T). X and Y coordinates are in UTM (NAD83 Zone 10N), Z is elevation from mean sea level (meters), T is temperature in deg C. ...
Frone, Z. and Cladouhos, T. AltaRock Energy Inc
Jan 30, 2015
3 Resources
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3 Resources
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Fallon FORGE: Thermal-Hydrological-Mechanical Models
Archive contains thermal-mechanical simulation input/output files. Included are files which fall into the following categories:
( 1 ) Spreadsheets with various input parameter calculations
( 2 ) Final Simulation Inputs
( 3 ) Native-State Thermal-Hydrological Model Input File Fol...
Blankenship, D. and Sonnenthal, E. Sandia National Laboratories
Mar 12, 2018
2 Resources
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2 Resources
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Utah FORGE: Earth Model Mesh Data for Selected Surfaces
This submission contains a number of data files with vertices of meshed/interpolated surfaces used in the Phase 2B earth model. Examples include land surface (based on 10-meter DEM), the granitoid-basin fill contact, several faults, and also interpolated temperature isosurfaces f...
Podgorney, R. Idaho National Laboratory
Dec 07, 2018
6 Resources
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6 Resources
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