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Brady's, NV×

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

Brady Hot Springs Seismic Modeling Data for Push-Pull Project

Jul 31, 2018
16.99 GB
Publicly accessible
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.
Authors
Zhang, R. University of Louisiana
geothermalenergyseismicgeophysicsactive sourcevelocitygeophysicaldatamodelingnumericalsyntheticbrady hot springsnevadanvfracturerockgeologicpropertiespropertypush-pullfinite differencenumerical modelingvspvertical seismic profilingboreholefracturednon-fracturedmediaco2saturation

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Feb 18, 2021
4.49 MB
Publicly accessible
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...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergymachine learningsubsurfacecharacterizationbrady hot springspredictionreservoir modelingtime seriespcaprincipal component analysisreservoir managementbradys hot springsporotomoreservoirdual-porositystimulationinjection testmodeltemperatureflowpressuresimulationsingle-fracturedoubletheatmapheat maptensorflow

PoroTomo Distributed Temperature Sensing (DTS) Measurements made in Brady Observation Well 56-1

Jan 09, 2019
105.8 MB
Publicly accessible
This submission is a follow-up to Distributed Temperature Sensing (DTS) measurements made in Brady observation well 56-1 during the PoroTomo field experiment conducted in March, 2016. The measurements in this data set were made on August 24, 2018 over an approximately 20 hour per...
Authors
Kratt, C. et al Oregon State University
geothermalenergydtsbradyporotomoctempsfiber opticsilixadistributed temperature sensingwell 56-1matlabdataporoelastic tomographybrady hot springsnevadanvobservation wellsilixa xt

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Oct 20, 2021
6.41 MB
Publicly accessible
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergymachine learningmlsubsurfacecharacterizationbrady hot springsbhspredictionreservoir modelingtime seriespcaprincipal component analysisreservoir managementreservoirdual-porositystimulationinjection testpdetemperatureflowpressuresimulationsingle-fracturedoubletheat maptensorflowcnnlstmmlphydrothermalopen source reservoirosrnevada