Ground-roll attenuation through quaternionic inversion with sparsity constraints

Bahia, Breno; Papathanasaki, Illiana; Sacchi, Mauricio D.

doi:10.1190/segam2020-3405908.1

Cited by 2 publications

(1 citation statement)

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“…Because ground roll is slow, it is often spatially aliased, complicating subsequent processing efforts to remove this coherent noise component with f − k or Radon filtering [Yilmaz, 2001, Trad et al [2003]. Unfortunately, it is financially unfeasible to decrease the periodic receiver sampling interval to avoid aliasing [Bahia et al, 2020], and we have to resort to alternative randomized acquisition methodologies [Mosher et al, 2014] that are in principle conducive to in silico unaliased wavefield reconstruction. While this has proven to work, the presence of strong-amplitude ground roll complicates wavefield reconstruction.…”

Section: Impact Of Ground Rollmentioning

confidence: 99%

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

Zhang¹,

Herrmann²

2021

Preprint

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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.

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Section: Impact Of Ground Rollmentioning

confidence: 99%