Machine-Learning Models, Guided by Physics, Will Improve Subsurface Imaging

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Los Alamos National Laboratory
Los Alamos National Laboratory

February 21, 2023 | Originally published by Los Alamos National Laboratory on February 7, 2023

A team of scientists at Los Alamos National Laboratory is applying machine-learning algorithms to subsurface imaging that will impact a variety of applications, including energy exploration, carbon capture and sequestration, and estimating pathways of subsurface contaminant transport, according to new research published in IEEE Signal Processing Magazine.

“The subsurface is extremely complex and full of uncertainty, and knowledge of its physical properties is vital for a variety of applications,” said Youzuo Lin of Los Alamos’ Energy and Earth System Science group and lead author of the paper. “This paper is the first systematic survey on physics-guided machine-learning techniques for computational wave imaging.”

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