Volume 28, Issue 1
Interface Controlled Multiple Elimination by Sparsity Inversion

Lanshu Bai, Yike Liu & Huiyi Lu

Commun. Comput. Phys., 28 (2020), pp. 459-476.

Published online: 2020-05

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  • Abstract

Removing internal multiples remains an important but challenging problem in seismic processing. The generalized Estimation of Primaries by Sparsity Inversion (EPSI) method minimizes data residuals between the calculated and observed waveform using the sparse constraint of primary impulse responses to predict multiples and remove them directly, instead of using the conventional adaptive subtraction method. Even though the generalized EPSI method provides a good estimate of the primaries and multiples when they overlap, it is limited by intensive computational cost.
In this paper, we introduce two strategies to improve computational efficiency. First, the interface-controlled strategy is introduced by only selecting high-amplitude primary responses related to the interfaces with strong impedance contrasts to estimate multiples. The computational time is approximately proportional to the number of involved reflectors and usually, most of the internal multiple energy in the data is only related to a few strong reflectors. Therefore the modified method can remove most of the internal multiples in fewer computations than in the generalized EPSI, which loops through all the interfaces. Next, an approximate formula for estimating primary impulse responses is proposed by neglecting a computationally intensive term which corresponds to the primary responses estimated from internal multiples. According to our analyses and experiments, in most cases, the contribution of this term is negligible because the internal multiples are weak. Therefore, the computational efficiency can be improved without significantly losing quality when estimating most primaries and multiples.
In order to demonstrate this, multiple elimination of a two-layered simple data and the Pluto data are implemented. We find that the modified method can yield reliable results that require fewer computations. The improvements of the modified method may encourage the use of the generalized EPSI method in industry.

  • Keywords

Multiple, internal multiple, interface-controlled multiple elimination, estimation of primaries by sparsity inversion.

  • AMS Subject Headings

86-08, 86A15, 86A22

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

bailanshu@cea-igp.ac.cn (Lanshu Bai)

ykliu@mail.iggcas.ac.cn (Yike Liu)

lhy061981@163.com (Huiyi Lu)

  • BibTex
  • RIS
  • TXT
@Article{CiCP-28-459, author = {Bai , Lanshu and Liu , Yike and Lu , Huiyi }, title = {Interface Controlled Multiple Elimination by Sparsity Inversion}, journal = {Communications in Computational Physics}, year = {2020}, volume = {28}, number = {1}, pages = {459--476}, abstract = {

Removing internal multiples remains an important but challenging problem in seismic processing. The generalized Estimation of Primaries by Sparsity Inversion (EPSI) method minimizes data residuals between the calculated and observed waveform using the sparse constraint of primary impulse responses to predict multiples and remove them directly, instead of using the conventional adaptive subtraction method. Even though the generalized EPSI method provides a good estimate of the primaries and multiples when they overlap, it is limited by intensive computational cost.
In this paper, we introduce two strategies to improve computational efficiency. First, the interface-controlled strategy is introduced by only selecting high-amplitude primary responses related to the interfaces with strong impedance contrasts to estimate multiples. The computational time is approximately proportional to the number of involved reflectors and usually, most of the internal multiple energy in the data is only related to a few strong reflectors. Therefore the modified method can remove most of the internal multiples in fewer computations than in the generalized EPSI, which loops through all the interfaces. Next, an approximate formula for estimating primary impulse responses is proposed by neglecting a computationally intensive term which corresponds to the primary responses estimated from internal multiples. According to our analyses and experiments, in most cases, the contribution of this term is negligible because the internal multiples are weak. Therefore, the computational efficiency can be improved without significantly losing quality when estimating most primaries and multiples.
In order to demonstrate this, multiple elimination of a two-layered simple data and the Pluto data are implemented. We find that the modified method can yield reliable results that require fewer computations. The improvements of the modified method may encourage the use of the generalized EPSI method in industry.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2018-0077}, url = {http://global-sci.org/intro/article_detail/cicp/16850.html} }
TY - JOUR T1 - Interface Controlled Multiple Elimination by Sparsity Inversion AU - Bai , Lanshu AU - Liu , Yike AU - Lu , Huiyi JO - Communications in Computational Physics VL - 1 SP - 459 EP - 476 PY - 2020 DA - 2020/05 SN - 28 DO - http://doi.org/10.4208/cicp.OA-2018-0077 UR - https://global-sci.org/intro/article_detail/cicp/16850.html KW - Multiple, internal multiple, interface-controlled multiple elimination, estimation of primaries by sparsity inversion. AB -

Removing internal multiples remains an important but challenging problem in seismic processing. The generalized Estimation of Primaries by Sparsity Inversion (EPSI) method minimizes data residuals between the calculated and observed waveform using the sparse constraint of primary impulse responses to predict multiples and remove them directly, instead of using the conventional adaptive subtraction method. Even though the generalized EPSI method provides a good estimate of the primaries and multiples when they overlap, it is limited by intensive computational cost.
In this paper, we introduce two strategies to improve computational efficiency. First, the interface-controlled strategy is introduced by only selecting high-amplitude primary responses related to the interfaces with strong impedance contrasts to estimate multiples. The computational time is approximately proportional to the number of involved reflectors and usually, most of the internal multiple energy in the data is only related to a few strong reflectors. Therefore the modified method can remove most of the internal multiples in fewer computations than in the generalized EPSI, which loops through all the interfaces. Next, an approximate formula for estimating primary impulse responses is proposed by neglecting a computationally intensive term which corresponds to the primary responses estimated from internal multiples. According to our analyses and experiments, in most cases, the contribution of this term is negligible because the internal multiples are weak. Therefore, the computational efficiency can be improved without significantly losing quality when estimating most primaries and multiples.
In order to demonstrate this, multiple elimination of a two-layered simple data and the Pluto data are implemented. We find that the modified method can yield reliable results that require fewer computations. The improvements of the modified method may encourage the use of the generalized EPSI method in industry.

Lanshu Bai, Yike Liu & Huiyi Lu. (2020). Interface Controlled Multiple Elimination by Sparsity Inversion. Communications in Computational Physics. 28 (1). 459-476. doi:10.4208/cicp.OA-2018-0077
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