Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: Theory and practical implications

Abstract Multidimensional up-down deconvolution effectively eliminates surface-related multiples from ocean-bottom seismic data. Recently, several down-down deconvolution methods have been introduced as attractive alternatives. Whereas multidimensional up-down deconvolution fully accounts for lateral variations of the medium parameters, the underlying theory of some of the down-down deconvolution methods is essentially based on the assumption that the medium is horizontally layered. Using reciprocity theory, this assumption is circumvented. This leads to representations for either receiver-side or source-side multidimensional down-down deconvolution. Compared with multidimensional up-down deconvolution, receiver-side down-down deconvolution only utilizes the downgoing part of the wavefield that better samples the shallow subsurface, but it is not entirely data-driven. Source-side down-down deconvolution benefits from the better sampled source array, but in the presence of sparsely sampled receivers it requires solving an underdetermined system of linear equations.

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Publication Details

Journal
Geophysics
Published
2026-06-16
DOI
https://doi.org/10.1190/geo-2025-1024
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: Theory and practical implications

Kees Wapenaar, Claudio Bagaini, Matteo Ravasi
Geophysics
Seismic Imaging and Inversion Techniques
article

Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: Theory and practical implications

Kees Wapenaar, Claudio Bagaini, Matteo Ravasi
article en

Abstract

Abstract Multidimensional up-down deconvolution effectively eliminates surface-related multiples from ocean-bottom seismic data. Recently, several down-down deconvolution methods have been introduced as attractive alternatives. Whereas multidimensional up-down deconvolution fully accounts for lateral variations of the medium parameters, the underlying theory of some of the down-down deconvolution methods is essentially based on the assumption that the medium is horizontally layered. Using reciprocity theory, this assumption is circumvented. This leads to representations for either receiver-side or source-side multidimensional down-down deconvolution. Compared with multidimensional up-down deconvolution, receiver-side down-down deconvolution only utilizes the downgoing part of the wavefield that better samples the shallow subsurface, but it is not entirely data-driven. Source-side down-down deconvolution benefits from the better sampled source array, but in the presence of sparsely sampled receivers it requires solving an underdetermined system of linear equations.

Geophysics
OHB (Italy) (IT), R&G Associates (GB), Delft University of Technology (NL)
Openalex Percentile: Top 100%
Seismic Imaging and Inversion Techniques
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