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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

An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Geothermal Behavior with Example Simulations on The Treasure Island and UC Berkeley Campus

Aug 01, 2021
186.08 MB
Publicly accessible
This submission contains the source code of the Hydrothermal Finite Element Simulator used for the Treasure Island and UC Berkeley campus geothermal simulation. It contains a report that summarizes the development and validation of this Hydrothermal Finite Element Simulator, with ...
Authors
Chen, K. et al Lawrence Berkeley National Laboratory
geothermalenergyfinite elementcoupled hydrothermal modelingcommunity scaleground source heat pumpparallel computingdeal.iidistrict heating and cooling systemsubsurface heat responsetreasure islanduc berkeley campuscsimulationuc berkeleydistrict heatingdistrict coolingenergy deliverygeothermal storagegoethermal energy storageenergy storage

REopt Lite Geothermal Heat Pump Design Requirements

Mar 08, 2021
277.13 kB
Publicly accessible
This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...
Authors
Olis, D. National Renewable Energy Laboratory
geothermalenergyreoptreopt liteghpgeothermal heat pumpmodelmoduleweb toolweb interfacetooltechno-economiceconomics

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

Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling

Mar 21, 2024
211.86 kB
Publicly accessible
This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for fiv...
Authors
Pauling, H. et al National Renewable Energy Laboratory
geothermalenergygeophireschporcparallel cycletopping cyclepilgrim hot springsalaskatechno-economic analysisfeasibilityteareservoir simulationsheat demandcapitaloperating costsdistrict geothermaldistrict heatingmodelmodelingpythongithubinputsoutputs