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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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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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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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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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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
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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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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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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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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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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
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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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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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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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Utah FORGE: Deep Wells Temperature Surveys as of September 2022

This Excel spreadsheet contains temperature survey results for Utah FORGE wells 58-32, 78-32, 56-32, 16A(78)-32 and 78B-32. It also contains charts and comparisons, along with a "Data Summary" which provides links to previous GDR submissions with temperature data for each well.

Jones, C. Energy and Geoscience Institute at the University of Utah

Sep 16, 2022
1 Resources
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Utah FORGE: Downhole Geophone Seismic Data (August 2022)

This is a link to downhole geophone data collected by Schlumberger. These data were collected in the Utah FORGE deep seismic monitoring wells 58-32 and 56-32. The format is a standard SEGY and the units are bits. To convert to acceleration (m/s2) multiply by 2.333 x 10-7. Use one ...

Pankow, K. and Schlumberger, S. University of Utah Seismograph Stations

Aug 25, 2022
3 Resources
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Utah FORGE: Deep Well 58-32 (MU-ESW1) Core Data

These datasets, images, and graphics were derived from core drilling and core that was extracted from Utah Forge deep well 58-32 (originally called MU-ESW1), near Roosevelt Hot Springs.

Nash, G. and Moore, J. Energy and Geoscience Institute at the University of Utah

Apr 11, 2018
5 Resources
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Utah FORGE: Deep Wells Water and Gas Sampling with Analyses by ThermoChem (October, 2022)

This data includes a document that describes the effort to collect and analyze water and gas samples from deep Utah FORGE wells 16A(78)-32, 58-32, 56-32 and 78B-32 along with additional pdf files showing ThermoChem's analyses attached as an appendix.

Joness, C. Energy and Geoscience Institute at the University of Utah

Oct 26, 2022
2 Resources
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Geothermometry Mapping of Deep Hydrothermal Reservoirs in Southeastern Idaho: Final Report

Geothermometry Mapping of Deep Hydrothermal Reservoirs in Southeastern Idaho. Project final report with detail appendices.

Mattson, E. et al Idaho National Laboratory

Aug 15, 2016
1 Resources
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Utah FORGE: Milford Deep Test Well 58-32 (MU-ESW1) Pressure and Temperature Logs

This archive consists of a pdf graphic log and a LAS text file representing the results of the pressure and temperature logs measured on Nov. 8th, 2018 from the Utah FORGE deep test well 58-32 (MU-ESW1). The logs were taken by DI Drill Survey Services.

Moore, J. Energy and Geoscience Institute at the University of Utah

Nov 08, 2018
1 Resources
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Utah FORGE: Seismic and Other Shapefiles from the Roosevelt Hot Springs Area

Three shapefiles in this submission show the position of proposed seismic line surveys. The mid-crustal velocity anomaly file shows the extent of an anomalously low P-wave velocity zone in the subsurface. Two other files show the extent of known hydrothermal systems in the Rooseve...

Moore, J. Energy and Geoscience Institute at the University of Utah

Mar 22, 2016
7 Resources
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Utah FORGE: Logs and Data from Deep Well 58-32 (MU-ESW1)

Data, logs, and graphics associated with the drilling and testing of Utah FORGE deep test well 58-32 (MU-ESW1) near Roosevelt Hot Springs.

Nash, G. and Moore, J. Energy and Geoscience Institute at the University of Utah

Apr 11, 2018
11 Resources
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Validation of Innovative Exploration Technologies for Newberry Volcano: Geochemistry Data from Wells 55-29 and 46-16

Validation of Innovative Exploration Technologies for Newberry Volcano: DOE Geochemistry data from deep wells 55-29 and 46-16 at Newberry 2012

Jaffe, T. Davenport Newberry Holdings, LLC

Jan 01, 2012
1 Resources
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Deep Direct-Use Feasibility Study Development of 3-D Structural Surface Model for the Tuscarora Sandstone, Morgantown, WV

This dataset contains grid files for subsurface maps created in GES interpretation software and exported as Zmap formated grid files. Depth values in SSTVD (subsea true vertical depth). The methods used for analysis and a detailed discussion of the results are presented in a paper...

McCleery, R. et al West Virginia University

Dec 19, 2019
3 Resources
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Utah FORGE: 58-32 Injection and Packer Performance, April and May 2019

This is a PDF format summary report regarding the performance of a packer, which failed, and bridge plug used during the injection program in Utah FORGE deep Well 58-32, April and May, 2019.

McLennan, J. and Podgorney, R. Energy and Geoscience Institute at the University of Utah

Mar 22, 2020
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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