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"sevier thermal anomaly"×
Brady's, NV×

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

Understanding Constraints on Geothermal Sustainability Through Reservoir Characterization at Brady Geothermal Field, Nevada

Jul 11, 2018
4.46 MB
Publicly accessible
The vast supply of geothermal energy stored throughout the Earth and the exceedingly long time required to dissipate that energy makes the world's geothermal energy supply nearly limitless. As such, this resource holds the potential to provide a large supply of the world's energy ...
Authors
Patterson, J. University of Wisconsin
geothermalenergyhydrogeologydtsreservoir characterizationnevadabrady hot springsborehole pressureborehole temperaturedistributed temperature sensingporotomosustainabilitysustainable usesubsurface propertiesresorceidentificationassessmentproductioncharacterizationtemperaturepressurethermalhydraulicpropertiesanalyticalmodelnumericalanalysisreservoirsensitivityflow pathsfracturesflowpathwayspreferentialheattransportparameterssimulationpower production

Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project

Mar 06, 2019
242.91 MB
Publicly accessible
The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the material properties are registered on a three-dimensional grid with a spacing of 25 meters between nodes....
Authors
Feigl, K. and PoroTomo Team, . University of Wisconsin
geothermalenergyporotomoseismologygeodesyhydrologynevadabrady hot springsporoelastic tomographyinversionmodeling3dmaterialpropertiesunconsolidatedfracturedshallowstructuraltrendsgeologystrikedipthermal contractionpressuresubsidencepumpinghydraulic conductivityrateseismic amplitudefaultzonepermeableconduitfluidreservoirconceptualmodelpropertydensityp-waves-waveseismicvelocityyoungs moduluspoissons ratiointerferometrytemperaturelithologystrain rate

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