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GIS Resource Compilation Map Package Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Jun 01, 2021
831.16 MB
Publicly accessible
This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...
Authors
Brown, S. et al Nevada Bureau of Mines and Geology
geothermalenergynevadamachine learningmap packagegispcanmfbnnannelmgeochemistrygeophysicsheat flowslip and dilationstructureplay fairwaypfaexplorationcharacterizationgreat basindlipdilationgeodatabasehydrothermaldatamodelsprocessed datapaleo-geothermal featurestest sittessupervisedunsupervisedcultural

Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

Feb 07, 2023
Size unavailable
Publicly accessible
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...
Authors
Mordensky, S. et al United States Geological Survey
geothermalenergypfahydrothermalenergy assessmentresource assessmentretrospectivemachine learninggeosciencewestern usdata-drivenbias reductionfavorabilitymappingegslow tempprocessed dataresourcecharacterization

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

May 14, 2021
6.01 MB
Publicly accessible
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...
Authors
Marone, C. et al Pennsylvania State University
geothermalenergymatlabgeophysicsseismiccodeprocessed datamicroseismicityaiartificial intelligencedeep learningmachine learningacousticsacoustic emissionsseismic forcastingseismic predictionfaultfault propertiesshear stresstime to failureexperimentexperimental datalab databiaxial shear experimentbiaxial shear apparatusfriction

Utah FORGE: Well 16B(78)-32 Reinterpretation of Thrubit FMI Log

May 23, 2023
437.72 kB
Publicly accessible
This dataset contains a reinterpretation of the trip 3, Thrubit FMI log from Utah FORGE well 16B(78)-32, covering measured depths from 6,254 to 10,839 feet. Acquired by Schlumberger on May 23, 2023, this version includes newly interpreted tensile drilling-induced fractures, in add...
Authors
Wray, A. and Hamilton, D. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgewell16b78-3216bthrubit fmi logfmi logfmitrip 3 fmifmi reinterpretationtensile induceded fracturestensile fracturesfracturesinduced fracturesegsfromation microimagerborehole imagingfracture analysisschlumbergerthrubitsubsurface characterizationazimuthprocessed datainterpreted

Utah FORGE: Neubrex Well 16B(78)-32 Circulation Test Fiber Optics Monitoring Data and Reports July, 2023

Oct 31, 2023
3.36 GB
Publicly accessible
This dataset features Distributed Acoustic Sensing (DAS) and fiber optics monitoring data acquired by Neubrex Energy Services during the Utah FORGE Well 16B(78)-32 circulation test in July 2023. DAS and fiber optic monitoring data include absolute strain, strain change, strain ch...
Authors
Jurick, D. and Guzik, A. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgewell 16b78-3216b78-3216bfiber opticstemperaturestrainstrain change rateacousticdtsdssdasmicro-strainpressureacoustic sensingegsstrain ratedistributed temperature sensingfbeneubrexdistributed acoustic sensingprocessed datareport

EGS Collab Experiment 2: Earth Model Datasets

May 29, 2022
747.89 MB
Publicly accessible
The EGS Collab Project performed a series of tests to increase the understanding the response of crystalline rock mass to stimulations and fluid circulation to efficiently implement enhanced geothermal systems (EGS) technologies. The EGS Collab team created two underground testbed...
Authors
Neupane, G. et al Idaho National Laboratory
geothermalenergyegs collabegssurfsanford underground research facilityleadsouth dakotacollabraw dataprocessed datageologyconceptual model

Appendices for Geothermal Exploration Artificial Intelligence Report

Jan 08, 2021
2.76 GB
Publicly accessible
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...
Authors
Duzgun, H. et al Colorado School of Mines
geothermalenergyartificial intelligencehydrothermally altered mineralsmineral markerssvmgeodatabasewellfaultseismicaiborderbradydesert peaksalton sealand surface temperaturedeformationgeophysicalgeophysicssupport vector machinehyperspectralhyperspectral imagingcalifornianevadaegsblindblind systemdeep learningmachine learningexplorationgeospatial datashort wavelength infraredswirdatabaseanomaly detectionsite detectionradarhydrothermalmodelconceptual modelzoteroraw datapreproccessedprocessed dataenhanced geothermal systemengineered geothermal systemremote sensingarcgisgisinsarmorphologymorphologicalmorphological featurestirvnirvisible near infraredthermal infraredcodepython

Utah FORGE: 16B(78)-32 RFS DSS Strain Change Rate and Selected FDIs During 16A(78)-32 Stimulation

Mar 02, 2025
2.11 MB
Publicly accessible
This dataset contains strain change rate versus depth data acquired using a Rayleigh frequency shift (RFS) distributed strain sensing (DSS) system during hydraulic stimulation of well 16A(78)-32 at the Utah FORGE site in April 2024. The data were collected from an optical fiber in...
Authors
Jurick, D. et al Neubrex Energy Services (US), LLC
geothermalenergyutah forgeneubrexstrain frac logfiber opticsmicrostrainstraincumulative strain change ratestrain change16a78-3216b78-32egshydraulic stimulationfiber optic sensingstrain change raterfsdssrayleigh frequency shiftdepth profileprocessed datafrac loggeomechanicsfracture driven interactionsfdifrac hitsperforation clustercross-well strain monitoring

WHOLESCALE: Seismic Survey Data from San Emidio Nevada 2021

Apr 06, 2021
1.67 TB
Publicly accessible
This dataset includes raw and processed seismic data from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 N, 119.409019 W. The first...
Authors
Lord, N. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalsacraw dataprocessed datageophysicssiesmic datasmartsolodatacubeseismographdata lakesan emdidionevadapumpingtri-axialdld

Hybrid machine learning model to predict 3D in-situ permeability evolution

Nov 22, 2022
5.58 MB
Publicly accessible
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...
Authors
Elsworth, D. and Marone, C. Pennsylvania State University
geothermalenergyegsnewberryhydraulicstimulationprocessed datamachine learningpermeability evolutionhydraulic fracturinginduced seismicityegs collabseismic data analysiswellhead pressureflow ratefracture permeabilitymicroearthquakeenhanced geothermal systems

DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Jan 24, 2024
1.3 GB
Publicly accessible
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...
Authors
Taverna, N. et al National Renewable Energy Laboratory
geothermalenergydeepensuperhotsupercriticalsuperhot egsegsnewberrymagmatichydrothermalpfamodelingmodellingexploration3d2dfavorabilityomfleapfrogmodelgeodatauncertaintycomponentvolcanogeodata modelprocessed datageophysicscharacterization
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