Applied Geophysics

, Volume 14, Issue 4, pp 551–558 | Cite as

Nonlinear Rayleigh wave inversion based on the shuffled frog-leaping algorithm

  • Cheng-Yu Sun
  • Yan-Yan Wang
  • Dun-Shi Wu
  • Xiao-Jun Qin


At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm (SFLA), into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems.


Shuffle frog-leaping algorithm Rayleigh wave dispersion curves non-linear inversion shear wave velocity 


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We would like to show our gratitude to Paul Michaels for providing the field data, and we thank Khiem Tran for allowing us to use his crosshole result and for his encouragement with the inversion results. We would like to thank the editors and reviewers for their constructive comments and suggestions on this manuscript.


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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Cheng-Yu Sun
    • 1
  • Yan-Yan Wang
    • 1
  • Dun-Shi Wu
    • 1
  • Xiao-Jun Qin
    • 2
  1. 1.China University of Petroleum (East China)QingdaoChina
  2. 2.Youxin Exploration and Development Co. of Huabei oilfieldRenqiuChina

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