A practical workflow for land seismic wavefield recovery with weighted matrix factorization

While wavefield reconstruction through weighted low-rank matrix factorizations has been shown to perform well on marine data, out-of-the-box application of this technology to land data is hampered by ground roll. The presence of these strong surface waves tends to dominate the reconstruction at the expense of the weaker body waves. Because ground roll is slow, it also suffers more from aliasing. To overcome these challenges, we introduce a practical workflow where the ground roll and body wave components are recovered separately and combined. We test the proposed approach blindly on a subset of the 3D SEAM Barrett dataset. With our technique, we recover densely sampled data from 25 percent randomly subsampled receivers. Independent comparisons on a single shot demonstrate significant improvements achievable with the presented workflow.

https://slim.gatech.edu/Publications/Public/Conferences/SEG/2021/zhang20...

https://github.com/slimgroup/Software.SEG2021