High-Efficiency Prediction of Surface-Related Multiples by Inverse Scattering Series in the Curvelet Domain

Surface-related multiples prediction by inverse scattering series (ISS) is a completely data-driven method, which does not require a priori subsurface velocity information, and has the advantage of being suitable for complex structures compared with model-driven methods based on wave equations. But...

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Bibliographic Details
Published inPure and applied geophysics Vol. 179; no. 6-7; pp. 2201 - 2214
Main Authors Zhang, Bo, Geng, Jianhua
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.07.2022
Springer Nature B.V
Subjects
Algorithms
Computation
Computer applications
Data imaging
Domains
Earth and Environmental Science
Earth Sciences
Efficiency
Geophysics/Geodesy
Inverse scattering
Methods
Numerical experiments
Predictions
Subtraction
Transformations (mathematics)
Velocity
Wave equations
curvelet
high efficiency
Surface-related multiple
inverse scattering series
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Summary:Surface-related multiples prediction by inverse scattering series (ISS) is a completely data-driven method, which does not require a priori subsurface velocity information, and has the advantage of being suitable for complex structures compared with model-driven methods based on wave equations. But its computation and memory requirement are substantial. We propose a high-efficiency algorithm for the prediction of surface-related multiples by ISS in the curvelet domain. Firstly, we perform curvelet transform (CT) on shot gathers; secondly, we select few curvelet coefficient matrices for surface-related multiple prediction by ISS; thirdly, we perform inverse CT to the predicted multiples in the curvelet domain; lastly, we use matched filtering and subtraction to obtain primaries. Numerical experiments show that the proposed method not only improves computational efficiency and saves memory, but also achieves the same results compared with conventional ISS.
ISSN:0033-4553
1420-9136
DOI:10.1007/s00024-022-03033-9