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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

Oct 01, 2021
5.68 MB
Publicly accessible
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Authors
Siler, D. et al United States Geological Survey
geothermalenergynmfkbrady hot springsmachine learningmlbhsnonnegative matrix factorization k-meanshydrothermalbradyk-meansclusteringnonnegative matrix factorizationmatrix factorizationgeothermalcloudsmarttensorsunsupervised3d well data3d geologic mapgeologic structurefaultsstressgeologycharacterizationgeologic modelproductioncode

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

Passive Seismic Emission Tomography Results at San Emidio Nevada

Dec 01, 2016
66.54 MB
Publicly accessible
The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic...
Authors
Warren, I. et al Ormat Technologies, Inc.
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalgeospatial dataexcelp-wave velocity modelpassive seismicp-waveprocessed dataseismicvelocityhydrothermalsan emidiogeophysicspsetcharacteriztion

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

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

Sep 01, 2020
109.94 MB
Publicly accessible
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeothermal explorationhydrothermal mineral alterationsland surface temperaturefault densitypsinsarsubsidenceupliftbrady hot springsdesert peaknevadaconvolutional neural networkfallonmachine learningmodelhydrothermalmineraltemperaturerastergeospatial datageotifftraining datatraining dataset

Maps, Models and Data from Southeastern Great Basin PFA

Jun 30, 2017
846.11 kB
Publicly accessible
This submission includes composite risk segment models in raster format for permeability, heat of the earth, and MT, as well as the final PFA model of geothermal exploration risk in Southwestern Utah, USA. Additionally, this submission has data regarding hydrothermally altered are...
Authors
Nash, G. Energy and Geoscience Institute at the University of Utah
geothermalenergyexplorationplay fairway analysisutahheatpermeabilityopalmtmagnetotelluricpfahydrothermal alterationsinterhidden geothermal systemsblind geothermal systemsshapefileshape filearcgisgisgeospatial dataxrdx-ray diffractionmilfordphase 2segbgbgreat basinse great basineasterngeophysicsheat floweastern great basinhydrothermal

Hawthorne Nevada Deep Direct-Use Feasibility Study Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

Apr 05, 2020
4.1 MB
Publicly accessible
This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicl...
Authors
Ayling, B. and Hinz, N. Great Basin Center for Geothermal Energy
geothermalenergyhawthornegeochemistryconceptual modeltemperature logsborehole fracture datahawthorne army depotdirect usenevada2-meter temperaturesalteration mineralsptswell datafluid chemistryddutemperaturefracturexrdwater chemistrysurveycuttingsmodelingcapacityestimatesconceptualhwaad-2hwaad-3hwaad-2ageospatial datalow-tempertaurehydrothermalseservoireservoir compartmentalizationpower capacityimage log

SSGF Mineral Major Elements and Lithium Concentration

May 01, 2023
1.38 MB
Publicly accessible
Presented are major element and lithium concentrations of minerals from the Salton Sea Geothermal Field (SSGF), located in the Imperial Valley, California. With a recent increase in demand for lithium, the area is now being studied as a source of geothermal brine for lithium extr...
Authors
Humphreys, J. et al Lawrence Berkeley National Laboratory
geothermallithiummineralrockssalton sea geothermal fieldbrinelithium isotopteschloritegeologygeochemistryhydrothermalisotope quantificationextractionsalton sealithium valleygeothermal brineimperial countyraw data

DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano

Jun 30, 2023
4.81 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), index models needed to be de...
Authors
Taverna, N. et al National Renewable Energy Laboratory
geothermalenergydeepensuperhotsupercriticalsuperhot egsmagmatichydrothermalindex modelsfavorabilitypfaexplorationcharacterizationnewberry

DEEPEN: Newberry Volcano MT and Gravity Data 2022 and 2023 Acquisition and Processing

Jun 30, 2023
306.16 GB
Publicly accessible
As part of DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments), a 3D play fairway analysis (PFA) was conducted at Newberry Volcano in Central Oregon for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). For use in this PFA, ...
Authors
Schultz, A. et al Enthalpion Energy
geothermalenergydeepennewberrymtgravityresistivitydensitysingle inversionjoint inversioninversionraw dataprocessed datauncertaintyresolution matrixexplorationcharacterizationegshydrothermalsuperhot egssupercriticalmagmaticgeophysicsmt impedance3-d modeldaily reportsoregonpfaplay fairway analysis

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