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|TopOrganization=Department of Energy | |TopOrganization=Department of Energy | ||
|CreationLegislation=None | |CreationLegislation=None | ||
|Purpose=The | |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. | ||
|Website=https://edx.netl.doe.gov/smart/ | |Website=https://edx.netl.doe.gov/smart/ | ||
|ProgramStart=2020 | |ProgramStart=2020 | ||
|InitialFunding=$10 million | |InitialFunding=$10 million | ||
|Duration=Ongoing | |Duration=Ongoing | ||
|Historic= | |Historic=No | ||
}} | }} | ||
The '''Science-informed Machine Learning for Subsurface Applications''' (SMART) initiative is a Department of Energy program launched in 2020 under the [[Office of Fossil Energy and Carbon Management]] (FECM) to harness artificial intelligence (AI) and machine learning (ML) for real-time subsurface energy management. | The '''Science-informed Machine Learning for Subsurface Applications''' (SMART) initiative is a Department of Energy program launched in 2020 under the [[Office of Fossil Energy and Carbon Management]] (FECM) to harness artificial intelligence (AI) and machine learning (ML) for real-time subsurface energy management. | ||
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