We can often suppress short-period multiples by predictive deconvolution. W
e can often suppress coherent noise with significantly different moveout by
time-invariant dip filtering on common-shot, common-receiver or NMO-correc
ted common-midpoint gathers. Unfortunately, even time variant dip filtering
on NMO-corrected data breaks down in the presence of strong lateral veloci
ty variation where the underlying NMO correction breaks down. Underattenuat
ed multiples, converted waves, and diffracted head waves can significantly
impede and/or degrade prestack migration-driven velocity analysis and ampli
tude variation with offset analysis as well as the quality of the final sta
cked image. Generalization of time-variant dip filtering based on conventio
nal NMO corrections of common-midpoint gathers also breaks down for less co
nventional data processing situations where we wish to enhance data having
nonhyperbolic moveout, such as converted wave energy or long-offset P-wave
reflections in structurally deformed anisotropic media.
We present a methodology that defines a depth-variant velocity filter based
on an approximation to the true velocity/depth structure of the earth deve
loped by the interpreter/processor during the normal course of their presta
ck imaging work how Velocity filtering in the depth domain requires the des
ign and calibration of two new least-squares transforms: a constrained leas
t-squares common offset Kirchhoff depth migration transform and a transform
in residual migration-velocity moveout space. Each of these new least-squa
res transforms can be considered to be generalizations of the well-known di
screte Radon transform commonly used in the oil and gas exploration industr
y.