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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

Subsurface Geological Information and Models in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

Oct 27, 2019
3.29 MB
Publicly accessible
This purpose of this set of entries is to group together the materials and analytical methods used in the assessment of the natural rock properties within and surrounding two potential reservoirs.
Authors
Jordan, T. et al Cornell University
geothermalenergycornell universitylow-temperature geothermalreservoir simulationuncertainty analysisdistrict heatingdirect useappalachian basinnew york statetechno-economic analysislevelized cost of heat lcohexternality valuesenvironmental valueeconomic valueddueaenvironmentenvironmentalassessmenttemperaturelcohlevelized cost of heateffective porosityheat pumpghpwell datacharacterizationshale neutron porositycornell

Utah FORGE: Earth Model Native State Simulation Results

Jul 16, 2019
6.69 MB
Publicly accessible
Utah FORGE phase 2C Native State Simulation zip contains the data used for the boundary conditions and subsequent native state simulation results obtained using the simulation code FALCON. Data are from the nodes of the simulation domain, with used a uniform 50m spacing over a 250...
Authors
Podgorney, R. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgeforgeutah geothermalnative state simulationfalconearth modelsimulationmilfordroosevelt hot springsegsanisotropic permeability and porositypermeabilityporositynative statedfnidaho national laboratoryinlmodelingmodellingreservoirparametersproperties

Utah FORGE: Evaluation of Potential Geochemical Responses to Injection in the FORGE Geothermal Reservoir

Apr 03, 2019
324.78 kB
Publicly accessible
Plugging of fracture porosity from mineral precipitation due to injecting cold water into a a geothermal reservoir can impact the overall permeability of the fracture network in the reservoir. This can have serious ramifications on the efficiency of the geothermal resource. Geoche...
Authors
Patil, V. and Simmons, S. Energy and Geoscience Institute at the University of Utah
geothermalenergyforge-utahgeochemistrynumerical modelingfractureinjection testporosityfracture networkmodelingwell 58-32well datastimulationdrillingroosevelt hot springswell 45-3reservoirmineralsthermalaqueousquartzcalciteillitekaolinitephpolythermalreaction pathutah forgeegsmilfordutahenergy geoscience institute

University of Illinois Campus Deep Direct-Use Feasibility Study Geological Characterization of the Mt. Simon Sandstone

Mar 30, 2018
Size unavailable
Publicly accessible
These studies undertook detailed analyses of the Mt. Simon Sandstone in the Illinois Basin for geological storage and sequestration, and brine extraction.
Authors
Lin, Y. et al University of Illinois
geothermalenergyddudeep direct-useuniversity of illinoismt. simon sandstoneco2carbon dioxidesequestrationgeologydiagenesisplumereservoir modelingreservoir characterizationdepositionchampaign countydecaturillinois basin

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

Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models

Oct 02, 2023
7.83 GB
Publicly accessible
This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. Th...
Authors
Finnila, A. Energy and Geoscience Institute at the University of Utah
geothermalenergydfnfracturesutah forgeegs fracture modelwspforgeegslarge upscaled dfnroosevelt hot springswell 16a78-32reservoir engineeringfracmanengineered geothermal systemsstimulationmodellingpermeabilityporosityreservoir modelingdiscrete fracture networkreservoir propertiesfracture modeling

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

Jun 30, 2020
186.36 kB
Publicly accessible
This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investiga...
Authors
Beckers, K. National Renewable Energy Laboratory
geothermalenergyddugeophiresdeep direct uselcoheconomicsabsorption chillersubsurface storagetechno-economiclevelized cost of heatwellboreexperimentcostsimulationmodelingreservoirtemperaturetechnologyabsorptionportland basinillinois basinwvuwest virginia universitywest virginiaportlandoregonchampagne-urbanaillinoisuniversity of illinoisurbana-champaignchampaign-urbanacornellhawthornenevadaporosityflowthermal conductivityinjection testdrillingwell data

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid

Feb 26, 2021
248.07 MB
Publicly accessible
Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on ...
Authors
Smith, J. et al Lawrence Berkeley National Laboratory
geothermalcoolingthermal-hydrological-mechanicalmodelingground sourcesimulationflowcfdflow simulationmodelreservoir coolinginjectionreservoir cooling systemaquifer storage cooling systemgroundground coolinggeothermal coolingreservoirnew jerseystockton universitywithdrawalfea

University of Illinois Campus Deep Direct-Use Feasibility Study Preliminary Geothermal Reservoir Model

May 08, 2018
11.31 GB
Publicly accessible
Preliminary geothermal reservoir simulations were performed using a homogeneous static model to evaluate and understand the effects of fluid and rock properties that could influence the delivery of thermal energy in a doublet system. A 5000 feet by 5100 feet by 500 feet homogeneou...
Authors
Okwen, R. University of Illinois
geothermalenergyddudeep direct-useuniversity of illinoisillinois basinreservoir modelstatic modelvip landmark

Geocellular model of St. Peter Sandstone for University of Illinois at Urbana-Champaign DDU Feasibility Study

Dec 31, 2018
68.79 MB
Publicly accessible
The geocellular model of the St. Peter Sandstone was constructed for the University of Illinois at Urbana-Champaign DDU feasibility study. Starting with the initial area of review (18.0 km by 18.1 km [11.2 miles by 11.3 miles]) the boundaries of the model were trimmed down to 9.7 ...
Authors
Damico, J. University of Illinois
geothermalenergyst. peter sandstoneillinois basinddudeep direct-useuniversity of illinois at urbana-champaign3-dgeocellular modelingfeasibilitycharacterizationillinois3dstructuralgeologymodelreservoirgeologicthermalhydrologicmechanicalpropertiespetrophysicalthermal conductivityspecific heat capacityheat capacityporositydensitypermeabilitythicknessdepthmt simon

Geocellular Model of Mt. Simon Sandstone for University of Illinois at Urbana-Champaign DDU feasibility study

Dec 31, 2018
111.49 MB
Publicly accessible
The geocellular model of the Mt. Simon Sandstone was constructed for the University of Illinois at Urbana-Champaign DDU feasibility study. Starting with the initial area of review (18.0 km by 18.1 km [11.2 miles by 11.3 miles]) the boundaries of the model were trimmed down to 9.7 ...
Authors
Damico, J. University of Illinois
geothermalenergygeocellular modelingmt. simon sandstoneillinois basinddudeep direct-use3-duniversity of illinois at urbana champaignfeasibilitycharacterizationillinoisstructuralgeologygeologicmodeldensityporositypermeabilitythermal conductivityheat capacitythicknessdepthst. peterthermalhydrologicmechanicalpetrophisicalproperties3dreservoir

Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

Oct 29, 2019
229.82 MB
Publicly accessible
This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the...
Authors
Smith, J. Cornell University
geothermalenergycornell universitylow-temperature geothermalreservoir simulationuncertainty analysisthermal datadistrict heatingdirect-use heatingdduappalachian basinnew york statetechno-economic analysislevelized cost of heat lcohexternality valuesenvironmental valuemonte carlo analysismonte carloeconomiceaheat pumpghpshapefilerastercornellgeospatial data