Measuring image focusing for velocity analysis

Measuring image focusing for velocity analysis

Biondo Biondi

Abstract:

I present a method for extracting velocity information by measuring the focusing and unfocusing of migrated images. It measures image focusing by evaluating coherency across structural dips, in addition to coherency across aperture/azimuth angles. The inherent ambiguity between velocity and reflectors' curvature is directly tackled by introducing a curvature correction into the computation of the semblance functional that estimates image coherency. The resulting velocity estimator provides velocity estimates that are: 1) unbiased by reflectors' curvature, and 2) consistent with the velocity information that we routinely gather by measuring coherency over aperture/azimuth angles.

The application of the method to a 2D synthetic data set and a 2D field data set confirms that it provides consistent and unbiased velocity information. It also suggests that velocity estimates based on the new image-focusing semblance may be more robust and have higher resolution than estimates based on conventional semblance functionals. Preliminary tests on two 2D zero-offset synthetic data sets show that velocity information can be extracted from zero-offset data in presence of reflectors with arbitrary curvature, and not only in presence of point diffractors as previously published methods require.

Measuring image focusing for velocity analysis