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Science-informed Machine Learning for Subsurface Applications: Difference between revisions

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Science-informed Machine Learning for Subsurface Applications (view source)

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|TopOrganization=Department of Energy
|TopOrganization=Department of Energy
|CreationLegislation=None
|CreationLegislation=None
|Purpose=The SMART program develops AI and machine learning tools to enhance real-time decision-making for subsurface energy systems like carbon storage and geothermal energy. It aims to integrate physics-based models with data-driven approaches to improve forecasting, monitoring, and management of subsurface resources.
|Purpose=SMART, run by devs via AI & ML tools, enhances real-time decisions for subsurface energy like carbon storage & geothermal, integrating physics-based models with data-driven methods to boost forecasting, monitoring, & management.
|Website=https://edx.netl.doe.gov/smart/
|Website=https://edx.netl.doe.gov/smart/
|ProgramStart=2020
|ProgramStart=2020
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