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Abstract

Summary

The common-reflection-surface stack was shown to be a powerful tool for data analysis and enhancement. While the increased signal-to-noise ratio and the regularization and interpolation capabilities are virtues on their own, the physically meaningful wavefront attributes acquired during the stack can be used for sophisticated subsequent processes such as wavefield characterization and separation. In this work, we review the largely data-driven normal-incidence-point (NIP) tomography, which likewise makes use of the wavefront parameter estimates. Whereas in previous works, NIP tomography has been applied mainly to reflection data, resulting in smooth velocity models suitable for migration of targets with moderately complex overburden, this work has the emphasis on using diffracted contributions in the wavefield for velocity inversion. Based on recently formulated diffraction symmetries, we motivate a two-step strategy, in which tomographic models gained via application to reflection data are subsequently refined using diffractions. Simple synthetics as well as an industrial field data example confirm the general finding that diffraction-based wavefront tomography can lead to increased lateral resolution in the velocity inversion.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.201600833
2016-05-30
2024-04-20

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References

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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201600833
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Utilizing Diffractions in Wavefront-based Tomography
Conference Proceedings 2016, 1 (2016); https://doi.org/10.3997/2214-4609.201600833
/content/papers/10.3997/2214-4609.201600833
/content/papers/10.3997/2214-4609.201600833
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