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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

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...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
1 Resources
Publicly accessible

Extraction/Injection Well Design for Deep Direct Use at University of Illinois at Urban-Champaign

The large scale Deep Direct Use (DDU) geothermal project in the low temperature environment of the Illinois Basin requires drilling and completing two wells. One well would be the extraction (producing) well and would be built to deliver a flow rate of approximately 6000 barrels ...

Kirksey, J. and Lu, Y. University of Illinois

Mar 31, 2019
1 Resources
Publicly accessible

Environmental Life Cycle Assessment Spreadsheet tool for Deep Direct-Use Geothermal at the University of Illinois at Urbana-Champaign Campus

A Life Cycle Assessment (LCA) spreadsheet tool was developed to analyze potential environmental benefits of a deep direct-use (DDU) geothermal energy system (GES) at the University of Illinois at Urbana-Champaign (U of IL) campus. The LCA spreadsheet tool is a unique contribution ...

Tinjum, J. et al University of Illinois

Jan 31, 2020
2 Resources
Publicly accessible

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

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...

Okwen, R. University of Illinois

May 08, 2018
4 Resources
Publicly accessible

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
4 Resources
Publicly accessible

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

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...