Dealiasing bandlimited data using a spectral continuity constraint

Dave Nichols

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ABSTRACT

When aliased data is slant stacked it sums coherently at multiple locations in the slowness-frequency ($p-\omega$) domain. Only one of these locations is the ``true'' location. If the true location can be distinguished from the aliased locations an unaliased representation of the data can be computed. The criterion I use to distinguish between the true dip and the aliased dip is that, for bandlimited data, the amplitude spectrum at the true dip should be a locally continuous function of frequency. Once an unaliased representation of the data has been obtained any slowness domain processing can be performed before transformation back to the space-time(x-t) domain. The data can be transformed back to the x-t domain at any trace spacing to give an dealiased version of the original data.