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Velocity model estimation for depth imaging: Comparison of three tomography methods on a 2D real data set

Abstract : The estimation of velocity models is still crucial in seismic reflection imaging as it controls the quality of the depth-migrated image, which is the basis of geological interpretation. Among the numerous existing methods for velocity determination, tomographic methods are very attractive for their efficiency and ability to retrieve heterogeneities of the medium. We present three tomographic methods in order to estimate heterogeneous velocity models from 2D prestack PP reflection data: a traveltime tomography in the time-migrated domain, a traveltime and slope tomography in the non-migrated time domain, and a slope tomography in the depth-migrated domain. The first method (traveltime tomography in the time domain) is based on continuous picked events, whereas the two slope tomographic methods, one in the time domain and the other in the depth domain, are based on locally coherent events, with no assumptions about reflector geometry or the unknown velocity field. The purpose of this paper is not to describe in detail the theoretical basis and implementation of the methods, but to apply and compare their output using the same marine real data set. Based on the estimated velocity models, the migrated images and the common-image gathers from the three processing routes, the relative strengths and weaknesses of the methods are discussed. Finally, similarities are indicated and potential alternative approaches are proposed.
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Contributor : Mark Noble Connect in order to contact the contributor
Submitted on : Thursday, February 5, 2015 - 11:13:38 AM
Last modification on : Wednesday, November 17, 2021 - 12:31:20 PM

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Soazig Le Begat, Hervé Chauris, Vincent Devaux, Sylvain Nguyen, Mark S. Noble. Velocity model estimation for depth imaging: Comparison of three tomography methods on a 2D real data set. Geophysical Prospecting, Wiley, 2004, 52 (5), pp.427-438. ⟨10.1111/j.1365-2478.2004.00427.x⟩. ⟨hal-01113373⟩



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