Inversion of reflection seismograms by differential semblance analysis: algorithm structure and synthetic examples1

Abstract : Seismograms predicted from acoustic or elastic earth models depend very non-linearly on the long wavelength components of velocity. This sensitive dependence demands the use of special variational principles in waveform-based inversion algorithms. The differential semblance variational principle is well-suited to velocity inversion by gradient methods, since its objective function is smooth and convex over a large range of velocity models. An extension of the adjoint state technique yields an accurate estimate of the differential semblance gradient. Non-linear conjugate gradient iteration is quite successful in locating the global differential semblance minimum, which is near the ordinary least-squares global minimum when coherent data noise is small. Several examples, based on the 2D primaries-only acoustic model, illustrate features of the method and its performance.
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Geophysical Prospecting, Wiley, 1994, 42 (6), pp.49. 〈10.1111/j.1365-2478.1994.tb00231.x〉
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Soumis le : lundi 2 février 2015 - 02:46:30
Dernière modification le : vendredi 25 mai 2018 - 12:02:06

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William W. Symes, Michel Kern. Inversion of reflection seismograms by differential semblance analysis: algorithm structure and synthetic examples1. Geophysical Prospecting, Wiley, 1994, 42 (6), pp.49. 〈10.1111/j.1365-2478.1994.tb00231.x〉. 〈hal-01111969〉

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