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"Hydraulic stimulation"×
Brady's, NV×

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

Brady 1D Seismic Velocity Model Ambient Noise Prelim

Oct 25, 2013
0.97 kB
Publicly accessible
Preliminary 1D seismic velocity model derived from ambient noise correlation. 28 Green's functions filtered between 4-10 Hz for Vp, Vs, and Qs were calculated. 1D model estimated for each path. The final model is a median of the individual models. Resolution is best for the top 1 ...
Authors
J., R. Lawrence Livermore National Laboratory
seismicvelocity modelbradysseismic velocitygeothermalnevada

Brady's Geothermal Field Analysis of Pressure Data

Mar 17, 2017
10.13 MB
Publicly accessible
*This submission provides corrections to GDR Submissions 844 and 845* Poroelastic Tomography (PoroTomo) by Adjoint Inverse Modeling of Data from Hydrology. The 3 *csv files containing pressure data are the corrected versions of the pressure dataset found in Submission 844. The ...
Authors
Lim, D. University of Wisconsin
geothermalenergyproduction flow rate datainjection flow rate datapressure datahydrologyhydrogeologybrady hot springsporotomoporoelastic tomographyegsenhanced geothermal systemsengineered geothermal systemsdeployment databradybradys geothermal fieldpressureflow rateboreholedownholewell datapressure sensorobservation wellspumping testwater pressureobservation well

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

Oct 01, 2021
7.12 MB
Publicly accessible
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Authors
Siler, D. and Pepin, J. United States Geological Survey
geothermalenergypca3d geologic modelgeologic modelgeologycharacterizationmachine learningmlbhsbrady hot springsprincipal component analysisproductionstressfaultsrbradyhydrothermalgeologic structureunsupervised3d well datacodegeothermicgeophysics

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

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