Multichannel prediction deconvolution method based on primary wave sparsity constraint

Abstract

The invention belongs to seismic signal processing field in seismic prospecting technology and specifically discloses a multichannel prediction deconvolution method based on primary wave sparsity constraint. The method comprises steps of: determining a limited support domain and a corresponding mathematic model of a 2D prediction filter in multichannel prediction deconvolution; decreasing the number of coefficients of the solved 2D prediction filter; constructing an optimization problem applying sparsity constraint to a primary wave and solving the 2D prediction filter by suing a fast iteration shrinkage threshold algorithm so as to achieve multiple suppression. Compared with a conventional multichannel prediction deconvolution method which needs to estimate all filter coefficients in a filter coefficient space and which applies energy minimization constraint to the primary wave to solve the 2D prediction filter, the method may decrease the number of coefficients of the solved 2D prediction filter, effectively balances primary wave protection and multiple suppression, and reduces the computation complexity of optimization problem solution.

Description

technical field [0001] The invention belongs to the field of seismic signal processing in seismic exploration technology, and in particular relates to a multi-channel prediction deconvolution method based on primary wave sparse constraints. Background technique [0002] In marine seismic exploration, predictive deconvolution is used to remove water layer multiples. Multi-channel predictive deconvolution methods can better eliminate multiple waves than single-channel predictive deconvolution methods (M.T. Taner, "Longperiodsea-floor multiples and their suppression," GeophysicalProspecting, vol.28, no.1, pp.30-48, Feb. .1980.). Multi-channel prediction deconvolution methods use 2D prediction filters to combine multiple channels of raw data to predict multiples. To avoid possible primary impairments, multi-trace predictive deconvolution uses the same 2D predictive filter to simultaneously predict multiples in multiple traces. Therefore, multi-trace prediction deconvolution c...

AI Technical Summary

Problems solved by technology

However, the traditional multi-channel predictive deconvolution method needs to solve all the filter coefficients in the filter coefficient space, and imposes energy minimization constraints on the primary wave to solve the 2D predictive filter, which cannot effectively balance the protection of the primary wave and the multiple wave suppression

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