Data conditioning of legacy seismic using migration-driven 5D interpolation

Legacy seismic surveys cover much of the midcontinent USA and Texas, with almost all 3D surveys acquired in the 1990s considered today to be low fold. Fortunately, recent advances in 5D interpolation have not only enhanced the quality of structural and stratigraphic images, but they have also improved the data sufficiently to allow more quantitative interpretation, such as impedance inversion. Although normal-moveout-corrected, common-midpoint-based 5D interpolation does an excellent job of amplitude balancing and the suppression of acquisition footprint, it appears to misinterpolate undercorrected diffractions, thus smearing fault and stratigraphic edges. We described a least-squares migration-driven 5D interpolation workflow, in which data were interpolated by demigrating the current subsurface image to the missing offsets and azimuths. Such demigration accurately interpolates fault edges and other diffractors, thereby preserving lateral discontinuities, while suppressing footprint and balancing the amplitudes. We have applied this workflow to a highly aliased low-fold survey acquired in the early 1990s now of use in mapping the newly reinvigorated Mississippi Lime play. This workflow improves reflector continuity, preserves faults delineated by coherence, balances the amplitude, and provides improved well ties.

Highly aliased ground-roll suppression using a 3D multiwindow Karhunen-Loève filter: Application to a legacy Mississippi Lime survey

Although modern recording capacity facilitates dense seismic acquisition, many, if not most, legacy 3D land surveys are spatially aliased with respect to ground roll. Irregular topography and weathering zones give rise to ground roll that has piecewise rather than continuous linear moveout (LMO). Dispersion often results in shingled events whose phase velocity cuts across the ground-roll noise cone. We have developed a workflow for the suppression of highly aliased broadband ground roll in which modern [Formula: see text] filters failed. Our workflow began with low-pass filtering and windowing the data, 3D patch by 3D patch. We then applied LMO corrections using an average phase velocity of the ground roll and improved these moveout corrections through the use of local three-shot by three-receiver 3D velocity scans about each sample to account for lateral changes in velocity, thickness, and weathering zone topography. Using a Kuwahara algorithm, we chose the most coherent window within which we applied a structure-oriented Karhunen-Loève filter to model the coherent noise. Finally, we removed the LMO correction and subtracted the modeled ground roll from the original data. We applied our workflow to a legacy data volume consisting of four merged 3D surveys acquired in the 1990s. Application of modern seismic attributes showed improved mapping of faults and flexures. We also validated our workflow using a synthetic gather having the same geometry as our field data.