Optimization and Engineering

, Volume 17, Issue 1, pp 3–26 | Cite as

A parallel evolution strategy for an earth imaging problem in geophysics

  • Y. Diouane
  • S. Gratton
  • X. Vasseur
  • L. N. Vicente
  • H. Calandra


In this paper we propose a new way to compute a rough approximation solution, to be later used as a warm starting point in a more refined optimization process, for a challenging global optimization problem related to earth imaging in geophysics. The warm start consists of a velocity model that approximately solves a full-waveform inverse problem at low frequency. Our motivation arises from the availability of massively parallel computing platforms and the natural parallelization of evolution strategies as global optimization methods for continuous variables. Our first contribution consists of developing a new and efficient parametrization of the velocity models to significantly reduce the dimension of the original optimization space. Our second contribution is to adapt a class of evolution strategies to the specificity of the physical problem at hands where the objective function evaluation is known to be the most expensive computational part. A third contribution is the development of a parallel evolution strategy solver, taking advantage of a recently proposed modification of these class of evolutionary methods that ensures convergence and promotes better performance under moderate budgets. The numerical results presented demonstrate the effectiveness of the algorithm on a realistic 3D full-waveform inverse problem in geophysics. The developed numerical approach allows us to successfully solve an acoustic full-waveform inversion problem at low frequencies on a reasonable number of cores of a distributed memory computer.


Evolution strategy Global convergence Earth imaging Inverse problem High performance computing (HPC) Search space reduction Full-waveform inversion 



The authors would like to acknowledge GENCI (Grand Equipement National de Calcul Intensif) for letting us used the CURIE computer at CCRT, Bruyères-le-Châtel, France. This work was granted access to the HPC resources of CCRT under allocation 2014065068 made by GENCI. Support for L. N. Vicente was provided by FCT under Grants PTDC/MAT/116736/2010 and PEst-C/MAT/UI0324/2011 and by the Réseau Thématique de Recherche Avancée, Fondation de Coopération Sciences et Technologies pour l’Aéronautique et l’Espace, under the grant ADTAO.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Y. Diouane
    • 1
  • S. Gratton
    • 2
  • X. Vasseur
    • 3
  • L. N. Vicente
    • 4
  • H. Calandra
    • 5
  1. 1.Institut Supérieur de l’Aéronautique et de l’Espace (ISAE-SUPAERO)Universit de ToulouseToulouse Cedex 4France
  2. 2.ENSEEIHT, INPTToulouse Cedex 7France
  3. 3.CERFACSToulouse Cedex 1France
  4. 4.CMUC, Department of MathematicsUniversity of CoimbraCoimbraPortugal
  5. 5.TOTAL E&P Research and Technology USAHoustonUSA

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