1887
Volume 23 Number 9
  • ISSN: 0263-5046
  • E-ISSN: 1365-2397

Abstract

Cost effective 2D (or 3D) data collection may require sparse sampling and can lead to spatial aliasing of seismic data. There are two distinct causes of spatial aliasing that need to be distinguished. Firstly, aliasing may occur due to sparse collection geometry. Secondly, aliasing occurs in seismic data processing by trace sorting to form common midpoint (CMP) and common offset gathers. This type of aliasing arises due to the ‘sampling paradox’ (Vermeer, 1990) and we will refer to it as CMP aliasing. Both types of spatial aliasing pose problems for prestack and poststack processes such as migration, DMO, Radon transform, and f-k filtering. Spatial aliasing also leads to undesirable effects (see, for example, ‘The checkerboard effect’ in Vermeer, 1990) on stacked seismic sections. Hence dealiasing procedures are desirable. Using Petersen and Middleton’s (1962) sampling theorem, which is presented for the 2D case by Bardan (1997), we describe an efficient exact trace interpolation algorithm for the removal of CMP aliasing and discuss aspects of its use.

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/content/journals/10.3997/1365-2397.2005017
2005-09-01
2022-11-30
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  • Article Type: Research Article
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