Crossline-direction reconstruction of multi-component seismic data with shearlet sparsity constraint. (7th June 2018)

• Record Type: Journal Article
• Authors: Liu, Chengming; Wang, Deli; Sun, Jing; Wang, Tiexing
• Is Part Of: Journal of geophysics and engineering. Volume 15:Number 5(2018:Oct.)
• Page Start: 1929
• Page End: 1942
• Publication Date: 2018-06-07
• Subjects: shearlet transform -- multi-component -- wavefield reconstruction -- crossline interpolation -- sparsity constraint; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1088/1742-2140/aac097
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: In towed-steamer marine seismic acquisition, crossline data are fairly sparse which makes crossline wavefield reconstruction very difficult. Therefore, reconstructing the sparse wavefield becomes a fundamental and crucial step in seismic processing flow. Recently, compressed sensing has provided new insights into the data recovery problem, which combines a sparsifying transform, a sampling strategy, and a sparsity promoting algorithm. Shearlet transform is provided with a fairly good sparse representation of seismic data, and is very robust in the application of seismic wavefield reconstruction. Using multi-component measurement techniques, we propose a multi-component crossline wavefield reconstruction method based on sparse shearlet constraint inversion. By combining the pressure wavefield and its crossline gradient obtained through V y measurements, the proposed method can effectively reduce the multiplicity caused by a limited number of samples. Both synthetic and field data have demonstrated that the method proposed in this paper, compared with the traditional wavefield reconstruction method, achieves better reconstruction resolution in the case of extremely sparse samplings and effectively suppresses the aliasing effect.