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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...

Marone, C. et al Pennsylvania State University

May 14, 2021
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Appalachian Basin Play Fairway Analysis Thermal Risk Factor and Quality Analyses

*This submission revises the analysis and products for Thermal Quality Analysis for the northern half of the Appalachian Basin (https://gdr.openei.org/submissions/638)* This submission is one of five major parts of a Low Temperature Geothermal Play Fairway Analysis. Phase 1 of the...

Jordan, T. Cornell University

Aug 02, 2016
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CO2 Push-Pull Dual (Conjugate) Faults Injection Simulations

This submission contains datasets and a final manuscript associated with a project simulating carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley- sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis. Datas...

Oldenburg, C. et al Lawrence Berkeley National Laboratory

Jul 20, 2017
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Numerical Modeling for Hydraulic Fracture Prediction

Numerical modeling on fused silica cylindrical materials for predicting overpressures required to fracture an homogeneous pure (surrogate) material with known mechanical properties similar to igneous rock materials and later compare these values to experimental overpressures obtai...

Gupta, V. Pacific Northwest National Laboratory

Apr 26, 2016
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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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Alternative CAES Technology Using Depleted Unconventional Gas Wells and Subsurface Thermal Energy Storage (GeoCAES)

This project assessed the technical viability of a process called GeoCAES. The process stores electrical energy by injecting natural gas into shale gas formations using a compressor, storing it, and producing it through an expander to generate electricity. This data submission inc...

Johnston, H. and Young, D. National Renewable Energy Laboratory

May 23, 2019
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Development of a Neutron Diffraction Based Experimental Capability for Investigating Hydraulic Fractures for EGS-like Conditions

Understanding the relationship between stress state, strain state and fracture initiation and propagation is critical to the improvement of fracture simulation capability if it is to be used as a tool for guiding hydraulic fracturing operations. The development of fracture predict...

Polsky, Y. et al Oak Ridge National Laboratory

Feb 01, 2013
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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
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Mt. Simon Sandstone Brine Chemistry for DDU Technology at the U of IL Campus

A review of brine chemistry data for the Mt. Simon Sandstone in the Illinois Basin is provided for calculations to predict the potential for mineral scaling and precipitation. The assessment includes expected changes in temperature, pressure, and/or exposure to air or other materi...

Lu, Y. and McKaskle, R. University of Illinois

Mar 31, 2019
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
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Oregon Cascades Play Fairway Analysis: Maps

The maps in this submission include: heat flow, alkalinity, Cl, Mg, SiO2, Quaternary volcanic rocks, faults, and land ownership. All of the Oregon Cascade region. The work was done by John Trimble, in 2015, at Oregon State University.

Trimble, J. University of Utah

Dec 15, 2015
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Utah FORGE: 2022 Seismic Workshop Report

Utah FORGE held a two-day seismic workshop on the University of Utah campus in Salt Lake City, Utah on September 26 and 27, 2022 to share what was learned from the seismic monitoring during the 2022 stimulation. This is a report documenting this workshop. The meeting was structure...

Pankow, K. University of Utah Seismograph Stations

Dec 19, 2022
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WISE-CASING: Seismic Experiment at Richmond Field Station, CA

This experiment is testing the tube waves reflected from the bottom of the well. We put six single-channel geophones on the surface and a 24-channel downhole hydrophone into the well. The well is about 30 meters deep. Just a steel casing in the sand formation, no cement.

Wu, Y. et al Lawrence Berkeley National Laboratory

Apr 25, 2018
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Brady Hot Springs Seismic Modeling Data for Push-Pull Project

This submission includes synthetic seismic modeling data for the Push-Pull project at Brady Hot Springs, NV. The synthetic seismic is all generated by finite-difference method regarding different fracture and rock properties.

Zhang, R. University of Louisiana

Jul 31, 2018
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WISE-CASING: Surface Seismic Survey at Cymric Field, California Central Valley

This test was conducted at the Chevron Cymric oilfield in the California central valley near Bakersfield. A reflected seismic signal was observed in all three components (x, y, z) of the 3-component Episensor geophone, as well as all phones on the single component array. The arriv...

Wu, Y. et al Lawrence Berkeley National Laboratory

Apr 02, 2018
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Utah FORGE: Seismic Activity from April, 2019

This dataset contains seismic event detections acquired using the 151 Nodal geophones deployed at the Utah FORGE site in April 2019. Details regarding the publishing are available in the paper linked below (Mesimeri, M. and K. L. Pankow et al. 2020). A frequency-domain-based algor...

Pankow, K. University of Utah Seismograph Stations

May 01, 2019
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Utah FORGE: 2023 Induced Seismicity Mitigation Plan

This is the updated Utah FORGE Phase 3B induced seismicity mitigation plan (ISMP) covering the general Utah FORGE area. This new version incorporates newly collected seismic data, including data collected during the 2022 stimulation and a probabilistic seismic hazard assessment (...

Pankow, K. et al University of Utah Seismograph Stations

Aug 09, 2023
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Utah FORGE: Orientation of Borehole and Surface Seismic Stations

The University of Utah Seismograph Stations (UUSS) are responsible for the seismic monitoring of the experiments and have installed a series of permanent surface and borehole seismic instruments around the Utah FORGE project site. This report discusses the methods used for proper ...

Bradshaw, P. et al University of Utah Seismograph Stations

Jun 21, 2023
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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
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Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study

This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model was developed using RMS velocities of the seismic reflection su...

Vasco, D. and Chan, C. Array Information Technology

Apr 30, 2022
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Utah FORGE: Seismic Reflection Data

This is 2D and 3D seismic reflection data from Utah FORGE reprocessed during Phase 2c. The readme file containing an explanation of the data including data formats, software that can be used, processing, and projection and datum used. The Reprocessing document gives the rationale ...

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

Jun 19, 2019
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Seismic Line Location Map File, Hot Pot Project, Humboldt County, Nevada 2010

Location of seismic lines carried out under DOE funded project Advanced Seismic Data Analysis Program (The Hot Pot Project). ArcGIS map package containing topographic base map, Township and Range layer, Oski BLM and private leases at time of survey, and locations, with selected sh...

Lane, M. Oski Energy LLC

Jan 01, 2010
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Utah FORGE: Seismic Risk Trafic Light System Version 2

The report outlines the updated Traffic Light System (TLS) for the Utah FORGE project, which aims to mitigate seismic risks associated with Enhanced Geothermal Systems (EGS) operations. It integrates lessons from past operations, including stimulation and circulation experiments a...

Pankow, K. et al University of Utah Seismograph Stations

Jan 24, 2025
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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
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2D Seismic Profiles, Nevada Play Fairway Granite Springs Valley

This data is associated with the Nevada Play Fairway project and contains 2D seismic profile data in cropped jpegs and tiffs, both interpreted and uninterpreted. Seismic data owned or controlled by Seismic Exchange, Inc.; interpretation is that of the University of Nevada, Reno.

Faulds, J. Nevada Bureau of Mines and Geology

Sep 14, 2017
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