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USGS Geophysics, Heat Flow, and Slip and Dilation Tendency Data used in Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Jun 01, 2021
Size unavailable
Publicly accessible
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...
Authors
DeAngelo, J. et al Nevada Bureau of Mines and Geology
geothermalenergygeophisicsnevadaslipdilationheat flowgravitymagneticsfaultsgeotiffsmachine learningexplorationcharacterizationhydrothermalgreat basingeophysicspfa

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
59.5 GB
Publicly accessible
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasenevadadesert peakartificial intelligenceairaw dataprocessed dataremote sensinghyperspectralmachine learningdeep learningexplorationarcgismodelsite detectionanomaly detectiongeothermal site detectiondatabasehydrothermalgeophysicsradarshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellgisblindblind systemhyperspectral imaginggeophysicaldeformationconceptual modelfaultpreprocessedgeospatial data

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
148.82 GB
Publicly accessible
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasesalton seaartificial intelligenceaideep learningmachine learningseismicremote sensinghyperspectralhyperspectral imaginggeospacial databaseexplorationsite detectiongeothermal site detectionanomaly detectionshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellraw dataprocessed datacaliforniaarcgisgismodeldatabasehydrothermalgeophysicsradarblindblind systemdeformationgeophysicalconceptual model faultpreprocessedrastervectorfield datageospatial data

Utah FORGE 5-2557: Final Report and Presentation for the Role of Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes for Enhanced Geothermal Systems

Nov 30, 2025
163.74 MB
Publicly accessible
This contains a final technical report and closeout presentation recording summarizing the results from Utah FORGE Project 5-2557 on the role of fluid pressure and temperature in fracture mechanics and coupled thermo-hydro-mechanical-chemical (THMC) processes relevant to enhanced ...
Authors
Pyrak-Nolte, L. Purdue University
geothermalenergythermo-hydro-mechanical-chemicalthmcutah forgeegstechnical reportlaboratory experimentstheoretical developmentsnumerical simulationscirculation testsfracture slippermeability evolutionseismicaseismicmoose farmfriction theoryaijoint inversion

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

INGENIOUS Great Basin Regional Dataset Compilation

Jun 30, 2022
116.98 MB
Publicly accessible
This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while re...
Authors
Ayling, B. et al GBCGE, NBMG, UNR
geothermalenergy2-meter probetemperaturegeochemistryquaternary falutsquaternary volcanicsgeodeticsseismicitypaleogeothermalwellsspringsslip and dilationingeniousplay fairway analysisgreat basinnevadautahidahocaliforniaoregonthermal conductivitymagnetotelluricsgravitymagneticsheat flowshapefilesgridssinterslipdilationearthquakesshearconductivityconductancegeotiffgeospatialcompilationdataregionaltufavolcanicsexplorationplay fairwaymodelingundiscovered systemsdiscoveryfavorabilityfaultsmachine learningelevation trenddetrended elevationseismic dataraw datasoda lake

Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

Aug 30, 2024
973.4 kB
Publicly accessible
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-...
Authors
Lu, G. et al University of Pittsburgh
geothermalenergyutah forgein-situ stress estimationphysics-based modelingfinite element methodmachine learning modelthermo-poro-mechanical effectwell loggingvelocity-to-stress relationshipmachine learningfemreporttechnical report16a78-32mlegs2-2439v2principal stressstress predictionfar-fieldpre-cooling

Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 May 2025

Jun 05, 2025
20.34 MB
Publicly accessible
These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
Authors
Lu, G. et al University of Pittsburgh
geothermalenergyutah16b78-32in-situ stressultrasonic velocityutah forgeegs16bmachine learningtrue triaxial testingsonic logsstress predictionfar-field stressthermo-poro-mechanicalmodelingdeep learningfinite element modelgeothermal reservoirstress profilingstress anisotropytechnical report

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes 2023 Annual Workshop Presentation

Sep 08, 2023
64.42 MB
Publicly accessible
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...
Authors
Pyrak-Nolte, L. Purdue University
geothermalenergyannual workshop2023utah forgeegsrupture alogorithmwave motion algorithmmachine learninggeophysicsfalconthmcufalconsimulatorjoint inversioninjectionfracturingshearingpermeability evolutionpore pressure diffusiondynamic crack evolutionslipwave generationpresentation

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
179.02 GB
Publicly accessible
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasebrady hot springsbradyartificial intelligenceaibrady wellseismicremote sensinghyperspectralgeospatial databasedeep learningmachine learningexplorationsite detectiongeothermal site detectionanomaly detectionshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellraw dataprocessed datanevadaarcgismodeldatabasehydrothermalgeophysicsradargisblindblind systemdeformationgeophysicalhyperspectral imagingconceptual modelfaultpreprocessedrastervectorfield datageospatial data

Programs and Code for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
710.72 kB
Publicly accessible
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Authors
Moraga, J. Colorado School of Mines
geothermalenergycodershell scriptsgeothermal aimachine learningself organizing mapk-meanspythonaiartificial intelligencedeep learningexplorationgeothermal explorationremote sensingblindsite detectionlstland surface temperaturenumpyrastertensorflowk meananomaly detectionlandsat adr lstsbatchslurmshell