Open AccessData matching for free‐surface multiple attenuation by multidimensional deconvolution
Author(s) -
van der Neut Joost,
Frijlink Martijn,
van Borselen Roald
Publication year - 2012
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2012.05648.x
Subject(s) - multiple , deconvolution , algorithm , computer science , inversion (geology) , blind deconvolution , attenuation , matching (statistics) , data mining , mathematics , geology , statistics , optics , seismology , arithmetic , physics , tectonics
SUMMARY A common strategy for surface‐related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near‐offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first‐order multiples with a time‐gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.