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Play Fairway Analysis (PFA)×

Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Jun 01, 2021
590.94 MB
Publicly accessible
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
Authors
Faulds, J. et al Nevada Bureau of Mines and Geology
geothermalenergyneural networkbayesianannelmbnnprincipal componentpcanmfmachine learningalgorithmplay fairwaynevadapfagreat basingeotiffexplorationcharacterizationinputsoutputsrasterfeature settraining sites

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

Geochemistry and paleo-geothermal features Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Nov 01, 2020
249.84 kB
Publicly accessible
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project. A submission linking the full GitHub repository for our machine learning Jupyter Notebooks...
Authors
Faulds, J. and Ayling, B. Nevada Bureau of Mines and Geology
geothermalenergygeochemistrysintertravertinetufapaleo-geothermalnevadamachine learninggeothermometryplay fairwaygeospatial datageospatialcodegeophysicscharacterization

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

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

Python Codebase and Jupyter Notebooks Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Jun 30, 2022
8.37 GB
Publicly accessible
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
Authors
Brown, S. and Smith, C. Nevada Bureau of Mines and Geology
geothermalenergymachine learningnevadapythonjupytergitcodealgorithmmodelpytorchpandasscriptgeotiffbayesian neural networkartificial neural networkpcanmfkbnnannprincipal component analysisnon-negative matrix factorizationpfaexplorationcharaterizationjupyter notebookgreat basinresultsdatadocumentation

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

Jun 30, 2023
1.03 MB
Publicly accessible
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Authors
Taverna, N. et al National Renewable Energy Laboratory
geothermalenergydeepensuperhotsupercriticalsuperhot egsmagmatichydrothermalweightspfapcaunsupervisedstandardizedexplorationcharacterizationglobal

DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

Jun 30, 2023
62.15 kB
Publicly accessible
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Authors
Taverna, N. et al National Renewable Energy Laboratory
geothermalenergydeepensuperhotsupercriticalsuperhot egsmagmatichydrothermalweightspfapcaexpertahpanalytical hierarchy processexplorationcharacterization

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

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