Multiple subtraction using an expanded multichannel matching filter
By Yanghua Wang. 2003
90 citations recorded by the source corpus.
An expanded multichannel matching (EMCM) filter is proposed for the adaptive subtraction in seismic multiple attenuation. For a normal multichannel matching filter where an original seismic trace is matched by a group of multiple-model traces, the lateral coherency of adjacent traces is likely to be exploited to discriminate the overlapped multiple and primary reflections. In the proposed EMCM filter, a seismic trace is matched by not only a group of the ordinary multiple-model traces but also their adjoints generated mathematically. The adjoints of a multiple-model trace include its first derivative, its Hilbert transform, and the derivative of the Hilbert transform. The convolutional coefficients associated with the normal multichannel filter can be represented as a 2D operator in the time-space domain. This 2D operator is expanded with an additional spatial dimension in the EMCM filter to improve the robustness of the adaptive subtraction. The multiple-model traces are generated using moveout equations to afford efficiency in the multiple attenuation application.
Subfields: Geophysics, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/902a0878143323ecd9e902448f31ff3634d29938
How researchers see this paper
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In Geophysics
- Yang Liu
- Cai Liu
- Felix J. Herrmann
- Sergey Fomel
- Urs Böniger
- Dirk Jacob Verschuur
- Jianwei Ma
- Xiaohong Chen
In Ocean Engineering
- Yang Liu
- Cai Liu
- Felix J. Herrmann
- Sergey Fomel
- Urs Böniger
- Dirk Jacob Verschuur
- Yangkang Chen
- Xiaohong Chen
Citations in the corpus
- Signal and noise separation in prestack seismic data using velocity-dependent seislet transform (2015, background): “…algorithms for attenuating multiples have rapidly developed since the 1990s and usually consist of two steps, namely, multiple prediction (Verschuur et al., 1992; Berkhout and Verschuur, 1997; Weglein et al., 1997) and adaptive subtraction (Wang, 2003b; Guitton and Verschuur, 2004; Fomel, 2009a).”
- Non-linear primary-multiple separation with directional curvelet frames (2007, methodology): “Another example is the approach taken by Wang (2003) who improves the adaptive subtraction by introducing additional local time and phase shifts.”