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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

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...

Vesselinov, V. Los Alamos National Laboratory

Mar 29, 2021
4 Resources
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Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...

Williams, J. Energy and Geoscience Institute at the University of Utah

Sep 17, 2024
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AeroDyn V15.04: Design Tool for Wind and MHK Turbines

AeroDyn is a time-domain wind and MHK turbine aerodynamics module that can be coupled into the FAST version 8 multi-physics engineering tool to enable aero-elastic simulation of horizontal-axis wind turbines. AeroDyn V15.04 has been updated to include a cavitation check for MHK tu...

Murray, R. et al National Renewable Energy Laboratory

Apr 28, 2017
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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

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...

Ahmmed, B. Stanford University

Apr 04, 2022
3 Resources
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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...

Lu, G. et al University of Pittsburgh

Aug 30, 2024
2 Resources
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Simulation Tools for Modeling Thermal Spallation Drilling on Multiple Scales

Widespread adoption of geothermal energy will require access to deeply buried resources in granitic basement rocks at high temperatures and pressures. Exploiting these resources necessitates novel methods for drilling, stimulation, and maintenance, under operating conditions that ...

Walsh, S. et al Lawrence Livermore National Laboratory

Jan 01, 2012
1 Resources
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Surface Meteorological Station ANL 10m, (1) Sonic, Physics site-9 Raw Data

**Overview** Sonic anemometers from Physics Site-3 and Site-9 provide wind components and virtual temperature. The energy balance Bowen ratio (EBBR) station at Physics site-3 provides measurements of the surface fluxes of latent and sensible heat, net radiation, and surface soil ...