Non-Linear Inversion of Seismic Data by Successive Approximation of Model Parameter Probability Distribution Functions

Wood, W. T.; Sen, M. K.

doi:10.1007/978-94-015-8476-0_24

Non-Linear Inversion of Seismic Data by Successive Approximation of Model Parameter Probability Distribution Functions

W. T. Wood⁵ &
M. K. Sen⁶

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Part of the book series: Modern Approaches in Geophysics ((MAGE,volume 12))

Abstract

Inversion of seismic data from a 1-D elastic earth is accomplished by choosing models randomly from a distribution which is the reciprocal of the objective function. Minima in the objective function correspond to peaks in distribution, thereby enhancing the probability that more models will be chosen from this area. Results show good recovery of dominant model parameters values and their uncertainties.

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Authors and Affiliations

Naval Research Laboratory, Code 7432, Stennis Space Center, MS, 39529, USA
W. T. Wood
The University of Texas Institute for Geophysics, 8701 Mopac Blvd., Austin, TX, 78759, USA
M. K. Sen

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W. T. Wood
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M. K. Sen
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Editors and Affiliations

SACLANT Undersea Research Centre, La Spezia, Italy
O. Diachok & P. Gerstoft &
University of Genova, Italy
A. Caiti
Massachusetts Institute of Technology, Cambridge, USA
H. Schmidt

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Wood, W.T., Sen, M.K. (1995). Non-Linear Inversion of Seismic Data by Successive Approximation of Model Parameter Probability Distribution Functions. In: Diachok, O., Caiti, A., Gerstoft, P., Schmidt, H. (eds) Full Field Inversion Methods in Ocean and Seismo-Acoustics. Modern Approaches in Geophysics, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8476-0_24

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DOI: https://doi.org/10.1007/978-94-015-8476-0_24
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4545-4
Online ISBN: 978-94-015-8476-0
eBook Packages: Springer Book Archive

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