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Abstract

Summary

Previously we proposed an advanced Genetic Algorithm and successfully applied it to large-scale static correction problems. In this paper we introduce an enhanced Genetic Algorithm which further improves both the global search and the local search capabilities of our previous algorithm, dramatically boosting the convergence speed. Our enhanced Genetic Algorithm adds two modifications to our previous algorithm: the “island model” gives a big uplift on the global search capability, and the “self-adaptive differential evolution fine tuning scheme” greatly benefits the local search capability. We first demonstrate the improved convergence speed of the enhanced Genetic Algorithm over our advanced Genetic Algorithm using three multi-modal test functions, and next successfully apply our enhanced Genetic Algorithm to two nonlinear geophysical problems, namely receiver-side static corrections and common reflection surface stacking.

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/content/papers/10.3997/2214-4609.201901453
2019-06-03
2024-04-24
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References

  1. Gong, Y. and A.Fukunaga
    , 2011. Distributed island-model genetic algorithms using heterogeneous parameter settings: 2011 IEEE Congress on Evolutionary Computation, 820–827.
    [Google Scholar]
  2. Holland, J. H.
    , 1975. Adaptation in natural and artificial systems. Ann Arbor: The University of Michigan Press.
    [Google Scholar]
  3. Jäger, R., J.Mann, G.Höcht and P.Hubral
    , 2001. Common-reflection-surface stack: Images and attributes: Geophysics, 66, 97–109.
    [Google Scholar]
  4. Mazzotti, A., N.Bienati, E.Stucchi, A.Tognarelli, M.Aleardi and A.Sajeva
    , 2016. Two-grid genetic algorithm full-waveform inversion: The Leading Edge, 35, 1068–1075.
    [Google Scholar]
  5. Porsani, M. J, P. L.Stoffa, M. K.Sen, R.Chanduru and W. T.Wood
    , 1993. A combined genetic and linear inversion algorithm for seismic waveform inversion: SEG Expanded Abstracts, 692–695.
    [Google Scholar]
  6. Ronen, J. and J. F.Claerbout
    , 1985. Surface-consistent residual statics estimation by stack-power maximization: Geophysics, 50, 2759–2767.
    [Google Scholar]
  7. Sambridge, M. and K.Mosegaard
    , 2002. Monte Carlo methods in geophysical inverse problems: Reviews of Geophysics, 40, 1–29.
    [Google Scholar]
  8. Storn, R. and K.Price
    , 1997. Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces: Journal of Global Optimization, 11, 341–359.
    [Google Scholar]
  9. Sun, Y. and D. J.Verschuur
    , 2014. A self-adjustable input genetic algorithm for the near-surface problem in geophysics: IEEE Transactions on Evolutionary Computation, 18, 309–325.
    [Google Scholar]
  10. Sun, Y., E.Verschuur and J. W.Vrolijk
    , 2014. Solving the complex near-surface problem using 3D data-driven near-surface replacement: Geophysical Prospecting, 62, 491–506.
    [Google Scholar]
  11. Sun, Y., T.Tonellot, B.Kamel, A.Bakulin
    , 2016. A 2D automatic converted-wave statics correction method: The Leading Edge, 35, 280–284.
    [Google Scholar]
  12. , 2017. A two-phase automatic static correction method: Geophysical Prospecting, 65, 711–723.
    [Google Scholar]
  13. Villa Acuna, Y.
    , 2018. An enhanced Genetic Algorithm and its application on two non-linear geophysical problems: Master Thesis, Delft University of Technology.
    [Google Scholar]
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