On data-independent multicomponent interpolators and the use of priors fo
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  • journal_title:Geophysics
  • Contributor:Kemal Özdemir ; Ali Özbek ; Dirk-Jan van Manen ; Massimiliano Vassallo
  • Publisher:Society of Exploration Geophysicists
  • Date:2010-
  • Format:text/html
  • Language:en
  • Identifier:10.1190/1.3494621
  • journal_abbrev:Geophysics
  • issn:0016-8033
  • volume:75
  • issue:6
  • firstpage:WB39
  • section:SUPPLEMENT - SEISMIC DATA SAMPLING AND WAVEFIELD REPRESENTATION
摘要

In marine acquisition, the interference between the upgoing and downgoing wavefields introduces a receiver ghost which reduces the effective bandwidth of the seismic wavefield. A two-component streamer provides means for removing the receiver ghost by measuring pressure and vertical particle velocity. However, due to nonuniform and relatively sparse sampling in the crossline direction, the seismic data are usually severely aliased in the crossline direction and the deghosting may not be feasible in a true 3D sense. A true multicomponent streamer measures all components of the particle motion wavefield in addition to the pressure wavefield. This enables solving the 3D deghosting and crossline reconstruction problems simultaneously, without making assumptions on the wavefield or the subsurface. We havedeveloped two data-independent algorithms suited for multicomponent acquisition. The first algorithm reconstructs the total pressure wavefield in the crossline direction by using the pressure and the crossline component of particle motion simultaneously. The second algorithm reconstructs the upgoing pressure wavefield by using the pressure, the crossline, and the vertical components of particle motion simultaneously. Both algorithms are optimal in the minimum-mean-squares-error sense and are ideally suited for a small number of irregularly spaced samples, as is common in towed marine acquisition. We find that by using the spectrum of the wavefield as a priori information, these algorithms have the potential to overcome higher-order aliasing than what is predicted by multichannel sampling theorems. Such a priori information can be extracted from an unaliased portion of the seismic data in novel and robust manners.

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