Abstract
Wavefront tomography is known to be an efficient and stable approach for velocity inversion that does not require accurate starting models and does not interact directly with the prestack data. Instead, the original data are transformed to physically meaningful wavefront attribute fields. These can be automatically estimated using local-coherence analysis by means of the common-reflection-surface (CRS) stack, which has been shown to be a powerful tool for data analysis and enhancement. In addition, the zero-offset wavefront attributes acquired during the CRS stack can be used for sophisticated subsequent processes such as wavefield characterization and separation. Whereas in previous works, wavefront tomography has been applied mainly to reflection data, resulting in smooth velocity models suitable for migration of targets with moderately complex overburden, we have emphasized using the diffracted contributions in the data for velocity inversion. By means of simple synthetic examples, we reveal the potential of diffractions for velocity inversion. On industrial field data, we suggest a joint inversion based on reflected and diffracted contributions of the measured wavefield, which confirms the general finding that diffraction-based wavefront tomography can help to increase the resolution of the velocity models. Concluding our work, we compare the quality of a reverse time migrated result using the estimated velocity model with the result based on the inversion of reflections, which reveals an improved imaging potential for a complex salt geometry.
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