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Applied Geophysics

, Volume 15, Issue 3–4, pp 448–465 | Cite as

Prestack AVA joint inversion of PP and PS waves using the vectorized reflectivity method

  • Wei Liu
  • Yan-Chun WangEmail author
  • Jing-Ye Li
  • Xue-Qing Liu
  • Wei Xie
Article
  • 30 Downloads

Abstract

Most current prestack AVA joint inversion methods are based on the exact Zoeppritz equation and its various approximations. However, these equations only reflect the relation between reflection coefficients, incidence angles, and elastic parameters on either side of the interface, which means that wave-propagation effects, such as spherical spreading, attenuation, transmission loss, multiples, and event mismatching of P- and S-waves, are not considered and cannot accurately describe the true propagation characteristics of seismic waves. Conventional AVA inversion methods require that these wave-propagation effects have been fully corrected or attenuated before inversion but these requirements can hardly be satisfied in practice. Using a one-dimensional (1D) earth model, the reflectivity method can simulate the full wavefield response of seismic waves. Therefore, we propose a nonlinear multicomponent prestack AVA joint inversion method based on the vectorized reflectivity method, which uses a fast nondominated sorting genetic algorithm (NSGA II) to optimize the nonlinear multiobjective function to estimate multiple parameters, such as P- wave velocity, S-wave velocity, and density. This approach is robust because it can simultaneously cope with more than one objective function without introducing weight coefficients. Model tests prove the effectiveness of the proposed inversion method. Based on the inversion results, we find that the nonlinear prestack AVA joint inversion using the reflectivity method yields more accurate inversion results than the inversion by using the exact Zoeppritz equation when the wave-propagation effects of transmission loss and internal multiples are not completely corrected.

Keywords

Reflectivity method fast nondominated sorting genetic algorithm multiple parameters prestack AVA joint inversion 

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Notes

Acknowledgements

We would like to thank Liu Hai-Hao, Hu Rui-Qing, and Yue Zhan-Wei for assistance and advice. We also grateful to the reviewers for their helpful comments and suggestions.

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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Wei Liu
    • 1
  • Yan-Chun Wang
    • 1
    Email author
  • Jing-Ye Li
    • 2
  • Xue-Qing Liu
    • 3
  • Wei Xie
    • 1
  1. 1.School of Geophysics and Information TechnologyChina University of GeosciencesBeijingChina
  2. 2.College of Geophysics and Information EngineeringChina University of PetroleumBeijingChina
  3. 3.Beijing Energy Oil & Gas Resources Development Co. Ltd.BeijingChina

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