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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

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

May 05, 2021
11.59 GB
Publicly accessible
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Authors
Zhu, T. Pennsylvania State University
geothermalenergycodedeep learningmachine learningaiartificial intelligenceegsenhanced geothermal systemsengineered geothermal systemsnewberryoregonnewberry volcanomlraw dataprocessed datamicroseismicitynumpywaveformpreprocessedpythonnewberry volcanic sitemicroearthquakemeqseismicgeophysicsgeophysical

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Apr 04, 2022
1.04 GB
Publicly accessible
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Authors
Ahmmed, B. Stanford University
geothermalenergymachine learningartificial intelligenceaiexplorationmodelmodelingprocessed datatraining datatraining datasetremote sensinghidden geothermal resourcesresource detectiondiscoverydevelopmentresourceneural networkprediction

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

Jun 30, 2021
13.6 MB
Publicly accessible
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Authors
Buster, G. et al Upflow
geothermalenergymachine learningoptimizationoperationssynthetic datapower plantbig kahunagoomlgenetic optimizationforecastinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsneural networkdataprocessed datacodepythonsimulationmodel

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

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

Programs and Code for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
710.72 kB
Publicly accessible
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Authors
Moraga, J. Colorado School of Mines
geothermalenergycodershell scriptsgeothermal aimachine learningself organizing mapk-meanspythonaiartificial intelligencedeep learningexplorationgeothermal explorationremote sensingblindsite detectionlstland surface temperaturenumpyrastertensorflowk meananomaly detectionlandsat adr lstsbatchslurmshell

COMSOL Models and Simulation Results for Closed-Loop Geothermal Systems with Thermal Enhancements

Dec 15, 2023
91.3 MB
Publicly accessible
The Closed-Loop Geothermal Working Group and the National Renewable Energy Laboratory (NREL) have studied the performance of disc-shaped and linear thermal enhancements (conductive material introduced around a wellbore) in closed-loop geothermal systems. COMSOL models were develop...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergythermal enhancementscosmolsimulationmodelclosed-loopsteady-statetransientsimulation resultsassessmentclosed loop geothermal

Applications of Geothermally-Produced Colloidal Silica in Reservoir Management Smart Gels

Jan 31, 2013
3.56 MB
Publicly accessible
In enhanced geothermal systems (EGS) the reservoir permeability is often enhanced or created using hydraulic fracturing. In hydraulic fracturing, high fluid pressures are applied to confined zones in the subsurface usually using packers to fracture the host rock. This enhances r...
Authors
Hunt, J. et al Lawrence Livermore National Laboratory
geothermalzonal isolationreservoir managementfluid diversioncolloidal silicasilicacoproduction

Stanford Thermal Earth Model for the Conterminous United States

Mar 14, 2024
21.57 GB
Publicly accessible
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Authors
Aljubran, M. and Horne, R. Stanford University
thermal earth modeltemperaturegeothermalenergystanfordtemperature-at-depthheat flowrock thermal conductivityinterpignnphysics-informedgraph neural networksmachine learningmodeltemperature modelarcgisapimodel inputsmodel outputsdata-drivenspatial interpolationalgorithmheat conductionbottomhole temperature

DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Jan 24, 2024
1.3 GB
Publicly accessible
Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...
Authors
Taverna, N. et al National Renewable Energy Laboratory
geothermalenergydeepensuperhotsupercriticalsuperhot egsegsnewberrymagmatichydrothermalpfamodelingmodellingexploration3d2dfavorabilityomfleapfrogmodelgeodatauncertaintycomponentvolcanogeodata modelprocessed datageophysicscharacterization

Kilauea Magnetotelluric Dataset

Jun 16, 2022
1.21 MB
Publicly accessible
In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the mag...
Authors
Hoversten, G. and Gasperikova, E. Lawrence Berkeley National Laboratory
geothermalenergymtkilaueamagnetotelluricimpedance tensorsstationsremote sensingprocessed dataeast rift zoneerzhawaiivolcanoresistancelavamagmamagma reservoirsimpedanceelectrical contact resistance
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