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Multiples attenuation in the presence of blending noise

YATONG ZHOU,  WEIXUE HAN
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School of Electronic and Information Engineering, Hebei University of Technology, Xiping Road 5340, Beichen District, Tianjin 300401, P.R. China.,
JSE 2018, 27(1), 69–88;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Zhou, Y.-T. and Han, W.-X., 2018. Multiples attenuation in the presence of blending noise. Journal of Seismic Exploration, 27: 69-88. Simultaneous-source acquisition is a modern seismic acquisition breakthrough that greatly increases the acquisition efficiency and spatial sampling ratio. Because of the extremely strong blending interference caused by simultaneous shooting, most traditional seismic data processing and imaging procedures need to be modified to deal with the noise issue in the new acquisition paradigm. For multiples attenuation, two common ways exist for processing the blended data, i.e., 1) multiples attenuation can be implemented on deblended data in a conventional way and 2) new algorithms for multiples attenuation can be developed to remove multiples directly from the blended data. In this paper, we propose a multi-dip seislet frame based sparse inversion algorithm to iteratively remove multiples directly from blended data. The multiples attenuation problem can be formulated as an inverse problem with regularization applied on both primaries and multiples components. For the noise issue, we propose to use a robust dip estimation approach that is based on velocity-slope transformation. Instead of calculating the local slope using the plane-wave destruction (PWD) based method, we first apply NMO-based velocity analysis approach and obtain NMO velocities for multi-dip components that correspond to different orders of multiples, then a fairly accurate slope estimation can be obtained using the velocity-slope conversion equation. We use both synthetic and field data examples to demonstrate the performance of the proposed algorithm framework.

Keywords
multiples attenuation
sparse inversion
slope estimation
simultaneous-source acquisition
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