Machine-learning models, guided by physics, will improve subsurface imaging
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…