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Introduction

Imaging the subsurface by migration of seismic data may give rise to aliasing problems that can generate artifacts in the final image. In Kirchhoff migration, effective solutions to the problem of operator aliasing have been developed and widely implemented by practitioners Lumley et al. (1994); Silva (1992); Sun and Bernitsas (1999). However, wavefield continuation migration is often considered unaffected by operator aliasing, which is only true for zero-offset applications. Accordingly, with the increasing use of prestack wave-equation migrations, it is important to understand the ramifications of data-space sampling choices on the potential aliasing of the image-space.

Aliasing can arise in wave-equation migration during the application of the imaging condition even when propagating wavefields are alias free. Imaging condition aliasing, as discussed by Zhang et al. (2003), occurs when the image space is inappropriately discretized. We address an aliasing problem that arises when, during the application of the imaging condition, wavenumbers improperly map into the image-space due to sampling changes of the data axes. This situation is analogous to the operator aliasing problem in Kirchhoff migration Biondi (2001).

We identify two methods of removing aliased energy from the image-space. We derive the criteria for determining the appropriate Nyquist boundaries for the image due to subsampling a data axis. To illustrate these ideas we present a simple case where aliased energy is introduced into the image due to subsampling the shot axis, and show the efficacy of our methods in removing these artifacts. Two important applications are readily identified: 1) calculating the dip information sacrificed when migrating a decimated data set to save computational costs; and 2) optimizing acquisition direction over complex targets in marine towed array surveys.


next up previous print clean
Next: METHODOLOGY Up: Artman et al.: Aliasing Previous: Artman et al.: Aliasing
Stanford Exploration Project
7/8/2003