Measuring image focusing for velocity analysis |

**Biondo Biondi**

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.

- Introduction
- Unbiased measure of image focusing
- Image curvature and residual migration
- Image curvature and residual migration in the pseudo-depth domain

- Synthetic-data example
- Field-data example
- Zero-offset synthetic-data example
- Discussion and conclusions
- APPENDIX A
- Curvature correction
- Bibliography
- About this document ...

Measuring image focusing for velocity analysis |

2009-05-05