Suppressing Aliased Noise Using Preconditioned Least - Squares Prestack Time Migration - Application to the Mississippi Lime of Oklahoma

Kurt Marfurt
University of Oklahoma

Room: REC103

Feb 20, 2013 3:30 PM EST

3D surface seismic data are almost always aliased. Sparse source and receiver patterns give rise to aliased signal as well as to aliased noise. Noise aliases from ground roll or shallow scatterers that fall within the wavenumber pass band can migrate into coherent artifacts. Attempts to image steep dips can produce operator aliasing, generating steeply-dipping artifacts. Suboptimal acquisition results in spatial variations in fold, which appears as acquisition footprint, which is worse on lower-fold angle- and azimuth-limited stacks. Footprint not only mask linear faults and fractures important to structural and stratigraphic interpretation, but also contaminates AVO, AVAz and elastic inversion. 

There are currently two approaches to minimizing such artifacts. The more common approach is to carefully interpolate the prestack 5D (t, x, y, azimuth, offset) data volume to fill in acquisition gaps, thereby reducing both data aliasing and fold artifacts. A more computationally intensive method is through least-squares migration, which compensates for lateral variability in fold, but does little to suppress aliasing artifacts. 

We address these data limitation problems through preconditioned least-squares migration that suppresses both fold and aliasing artifacts. We implement least-squares migration by minimizing the difference between the original data and the modeled demigrated data using an iterative conjugate gradient scheme. During each iteration, we precondition the results by applying a 3D prestack structure-oriented LUM filter to each common offset and common azimuth gather, rejecting artifacts that are structurally inconsistent with the current version of the stacked image. 

We apply this workflow to a survey designed to image the relatively shallow Mississippi Lime resource play of Oklahoma and Kansas, USA. We demonstrate the effectiveness of preconditioned least-squares migration by generating a suite of seismic attributes that illuminate fractures, karst, and diagenetic limestone alteration to tripolitic chert.