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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: Source Imaging DAS-Based Seismic Event Catalog April 2024 Stimulation

Aug 26, 2025
140.41 kB
Publicly accessible
This catalog contains microseismic event locations recorded during the April 2024 stimulation at the Utah FORGE site. Events were detected and located using a DAS-specific source imaging workflow that avoids conventional phase picking. Instead, STA/LTA-transformed DAS and downhole...
Authors
Dvory, N. et al The University Of Utah
geothermalenergyforgeutahmicroseismic event locationsutah forgeuniversity of utahseismicaimachine learningdata-driven decisionscommunity safteyinfrastructure protectionproactive risk mitigationimproved safteyimmediate responsestimulationfracingground motionseismic hazardsegsevent catalogmlprocessed datareservoir characterizationapril 2024 stimulation

Sentinel-1 Input Data for PSInSAR Analysis

Apr 29, 2021
305.43 GB
Publicly accessible
Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert Peak geothermal areas. The original titles are included for the Sentinel-1 data. The naming guide is included as a l...
Authors
Moraga, J. Colorado School of Mines
geothermalenergyinsarpsinsarsentinel-1synthetic aperture radarsatellite imagingaiartificial intelligencedeep learningmachine learningaerial photographyremote sensingsite detectionanomaly detectioninput datageologydisplacementsubsoilphenomenaprocessed dataradarimaginginterferometricanalysissoil deformationgeospatial data

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Mar 29, 2021
179.87 MB
Publicly accessible
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Authors
Vesselinov, V. Los Alamos National Laboratory
geothermalenergymachine-learningnew mexicobradynevadagreat basinsouthwest new mexicomulti-physicsbrady hot springssmarttensorsgeothermalcloudgeothermal cloudlos alamos national laboratorysite datasimulationmachine learningmodel

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

Apr 15, 2022
113.79 MB
Publicly accessible
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Authors
Jin, W. et al Idaho National Laboratory
reservoir thermal energy storagestochastic simulationgeotesmachine learningmodelingtesht-rtescharacterizationnumerical modelstochastichydrogeologic formationsimulated datasimulation datahigh-temperaturethermal energy storageoptimizationartificial neural network regressionannneural networkoperation scenariosseasonal-cyclepareto frontsseasonal operationcontinuous operationfalconmoose

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