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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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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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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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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
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
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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Publicly accessible
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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Utah FORGE 2439: A Multi-Component Approach to Characterizing In-Situ Stress
Core-based in-situ stress estimation, Triaxial Ultrasonic Velocity (labTUV) data, and Deformation Rate Analysis (DRA) data for Utah FORGE well 16A(78)-32 using triaxial ultrasonic velocity and deformation rate analysis. Report documenting a multi-component approach to characterizi...
Bunger, A. et al Battelle Memorial Institute
Dec 13, 2022
4 Resources
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4 Resources
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Utah FORGE 2-2446: Closing the Loop Between In-Situ Stress Complexity and EGS Fracture Complexity 2024 Annual Workshop Presentation
This is a presentation on Closing the Loop Between In-Situ Stress Complexity and EGS Fracture Complexity by Lawrence Livermore National Laboratory, presented by Matteo Cusini. The video discusses the combination of high-fidelity simulations and true-triaxial block fracturing tests...
Cusini, M. et al Energy and Geoscience Institute at the University of Utah
Aug 26, 2024
1 Resources
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1 Resources
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Utah FORGE: Stress Logging Data
This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in...
McLennan, J. Energy and Geoscience Institute at the University of Utah
Mar 14, 2018
1 Resources
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1 Resources
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Utah FORGE 2-2446: Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity Workshop Presentation
This is a presentation on the Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity project by Lawrence Livermore National Laboratory, presented by Dr. Matteo Cusini. The project's objective was to employ a combination of high-fidelity simulations and true...
Cusini, M. and Bunger, A. Lawrence Livermore National Laboratory
Sep 08, 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 2-2404: Determination of Reservoir-Scale Stress State Presentation Slides
This PowerPoint summarizes the integration of multiple approaches and data to constrain wellbore stress models at Utah FORGE. This stress determination used faulting theory, breakouts, and drilling-induced cracks detected in image logs. Wellbore stress profiles were established f...
Ghassemi, A. et al The University of Oklahoma
Jul 31, 2022
1 Resources
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1 Resources
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Utah FORGE 2-2404: Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE Workshop Presentation
This is a presentation on the Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Professor. The project's objective was to develop a methodology ...
Ghassemi, A. University of Oklahoma
Sep 08, 2023
1 Resources
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1 Resources
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Utah FORGE 2-2404: Application of Advanced Techniques for Determination of Reservoir-Scale Stress State 2024 Annual Workshop Presentation
This is a presentation on the Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at FORGE by the University of Oklahoma, presented by Ahmad Ghassemi. This video discusses how magnitude and orientation of natural in-situ principal stresses at dept...
Ghassemi, A. et al Energy and Geoscience Institute at the University of Utah
Aug 28, 2024
1 Resources
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1 Resources
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Utah FORGE 2-2446: Report on Phase Field Modelling of Near-Wellbore Hydraulic Fracture Nucleation and Propagation
This is a report that describes the modelling of fracture nucleation and propagation in the near-wellbore region to understand the relationship between in situ stress and fracture patterns. A novel phase field formulation is described here, which represents fractures as a diffuse ...
Cusini, M. and Fei, F. Lawrence Livermore National Laboratory
Dec 31, 2023
1 Resources
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1 Resources
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STRESSINVERSE Software for Stress Inversion
The STRESSINVERSE code uses an iterative method to find the nodal planes most consistent with the stress field given fault frictional properties. STRESINVERSE inverts the strike, rake and dip from moment tensor solutions for the in-situ state of stress. The code iteratively solves...
Gritto, R. Array Information Technology
Oct 31, 2018
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
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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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Utah FORGE 2439: Report on Minifrac Tests for Stress Characterization
This report describes minifrac tests conducted in the 16B(78)-32 well at the Utah FORGE site to characterize subsurface stresses, including the magnitude and orientation of the minimum and maximum horizontal stresses and the magnitude of the vertical stress. A minifrac test was co...
Kelley, M. et al Battelle Memorial Institute
Feb 22, 2024
1 Resources
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1 Resources
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Utah FORGE: Well 58-32 Core Analyses
This dataset contains final reports regarding stress measurements, permeability measurements, and mechanical properties from the core testing of well 58-32, in PDF format, and spreadsheets containing tables from the reports as part of Utah FORGE Phase 2B. Please refer to the repor...
McLennan, J. Energy and Geoscience Institute at the University of Utah
May 30, 2018
1 Resources
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1 Resources
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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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Newberry EGS Demonstration: Initial Project Report and Induced Seismicity Mitigation Plan, 2011
This is the first project report and induced seismicity mitigation plan for the Newberry Enhanced Geothermal Systems (EGS) Demonstration project. The primary objectives of this first phase were to obtain necessary permits and comply with all regulations, including NEPA, communica...
Cladouhos, T. et al AltaRock Energy Inc
May 05, 2024
4 Resources
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4 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. The University of Oklahoma
Jun 12, 2024
5 Resources
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5 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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