Inverse data-space multiple elimination with 3D curvelet sparsity promotion

Wang, T.; Wang, D.; Wang, T.; Tian, M.

doi:10.1007/s11600-017-0096-8

Artykuł - szczegóły

Tytuł artykułu

Inverse data-space multiple elimination with 3D curvelet sparsity promotion

Autorzy

Wang T. , Wang D. , Wang T. , Tian M.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-017-0096-8

Warianty tytułu

Języki publikacji

Abstrakty

This paper describes an effective implementation of the inverse data-space multiple elimination method via the three-dimensional (3D) curvelet domain. The method can separate the surface-related operator (A) and primaries (P0) through seismic data matrix inversion. A 3D curvelet transform is introduced to sparsely represent the seismic data in the inverse data space. Hence, this approach is suitable for obtaining an accurate solution because of its multiscale and multidirectional analysis properties. The L1 norm is used to promote sparseness in the transform domain. Then, a high-fidelity separation of the operator (A) and the primaries (P0) is realized. The proposed method is applied to synthetic data from a model containing a salt structure. We compare the results with that of the traditional inverse data-space multiple elimination method and also with that of two-dimensional surface-related multiple elimination. The findings fully demonstrate the superiority of the proposed method over the traditional inverse method; moreover, the proposed method protects the primary energy more effectively than the SRME method.

Słowa kluczowe

multiple elimination inverse data space 3D curvelet sparse inversion

wielokrotna eliminacja odwrócona przestrzeń danych

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2017

Tom

Vol. 65, no. 6

Strony

1197--1205

Opis fizyczny

Bibliogr. 32 poz.

Twórcy

autor

Wang T.

wangtong14@mails.jlu.edu.cn

College of Geoexploration Science and Technology, Jilin University, Changchun, China

autor

Wang D.

College of Geoexploration Science and Technology, Jilin University, Changchun, China

autor

Wang T.

College of Geoexploration Science and Technology, Jilin University, Changchun, China

autor

Tian M.

College of Geoexploration Science and Technology, Jilin University, Changchun, China

Bibliografia

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8. Donoho DL (2006b) For most large underdetermined systems of linear equations the minimal 1-norm solution is also the sparsest solution. Commun Pure Appl Math 59(6):907–934
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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-6192b889-9e5f-44e8-8c67-d06d952ce948