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GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples
This submission includes example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Kahunanui (KHN) fictional geothermal power plant, which uses synthetic data to model a fictional plant. Includes data curation, histo...
Taverna, N. et al Upflow
Jan 30, 2023
10 Resources
0 Stars
In progress
10 Resources
0 Stars
In progress
SMP Preparation, Programming, and Characterization
The problem of loss circulation in geothermal wells is inherently challenging due to high temperatures, brittle rocks, and presence of abundant fractures. Because of the inherent challenges in geothermal environments, there are limitations in selecting proper lost circulation mate...
Salehi, S. et al University of Oklahoma
Oct 01, 2021
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
SMP and Fracture Modeling
The problem of loss circulation in geothermal wells is inherently challenging due to high temperatures, brittle rocks, and presence of abundant fractures. Because of the inherent challenges in geothermal environments, there are limitations in selecting proper lost circulation mate...
Salehi, S. et al University of Oklahoma
Oct 01, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible