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Warping

Different NMO and migration velocity functions may cause both the traveltime depth and spatial postitioning of imaged reflectors to differ between surveys. Moreover, the degree of mispositioning will vary throughout the 3-D seismic volume. Although static time corrections may provide a partial solution, static corrections will not co-locate reflectors imaged at different lateral positions, nor will they allow for dynamic (as opposed to static) time-shifts that vary as a function of traveltime depth.

Even small shifts (less than a sample interval in magnitude) may cause enough misalignment that false events appear in the difference sections. Without access to the full pre-stack data, there are a limited number of ways such differences can be corrected.

Residual post-stack migration Rothman et al. (1985), or velocity continuation Claerbout (1986); Fomel (1997), provide operators that map between different migration velocities. However, without detailed knowledge of the velocity fields used for NMO and/or migration, and in cases where the migration algorithms differ significantly between surveys, it will be difficult to determine the correct residual migration operator to apply a priori. Instead the operator may have to be estimated from the data.

As an alternative to standard residual migration, we use a `warping' operator Wolberg (1990) to correct for kinematic differences between surveys. A 3-D shift vector, or `warp-function' that maps one survey onto another can be estimated at every point in the data volume, and applied directly.

At node points throughout the seismic data-volume, we calculate local 3-D cross-correlation functions between surveys. Picking the maxima of these functions produces a sparse cube of 3-D shift vectors that map one survey onto the other. Before applying the warp, we median-filter, then smooth, then interpolate the warp-function to fill the volume. To apply the warp, we look back down the shift vector, interpolating a value at every point in the output space.

Grubb and Tura (1997) used a similar algorithm to estimate uncertainty in AVO migration/inversion results. They migrated the same dataset many times with slightly different velocity fields. They then co-located reflectors with a warping algorithm, which allowed them to separate the kinematic and amplitude effects of the different migration velocities.



 
next up previous print clean
Next: Warping as residual migration Up: Rickett & Lumley: Cross-equalizing Previous: Amplitude balancing
Stanford Exploration Project
7/5/1998