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

TitleA practical workflow for land seismic wavefield recovery with weighted matrix factorization
Publication TypeConference
Year of Publication2021
AuthorsYijun Zhang, Felix J. Herrmann
Conference NameSEG Technical Program Expanded Abstracts
Month09
Keywords3D SEAM Barrett dataset, ground roll, SEG, wavefield reconstruction, weighted matrix factorization
Abstract

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.

Notes

(IMAGE, Denver)

URLhttps://slim.gatech.edu/Publications/Public/Conferences/SEG/2021/zhang2021SEGapw/Yijun2021.html
DOI10.1190/segam2021-3594419.1
Presentation
URL2
Software
Citation Keyzhang2021SEGapw