Direct, nonlinear inversion algorithm for hyperbolic problems via projection-based model reduction

Vladimir Druskin, Alexander V. Mamonov, Andrew E. Thaler, Mikhail Zaslavsky

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


We estimate the wave speed in the acoustic wave equation from boundary measurements by constructing a reduced-order model (ROM) matching discrete time-domain data. The state-variable representation of the ROM can be equivalently viewed as a Galerkin projection onto the Krylov subspace spanned by the snapshots of the time-domain solution. The success of our algorithm hinges on the data-driven Gram-Schmidt orthogonalization of the snapshots that suppresses multiple re-ections and can be viewed as a discrete form of the Marchenko-Gel'fand-Levitan-Krein algorithm. In particular, the orthogonalized snapshots are localized functions, the (squared) norms of which are essentially weighted averages of the wave speed. The centers of mass of the squared orthogonalized snapshots provide us with the grid on which we reconstruct the velocity. This grid is weakly dependent on the wave speed in traveltime coordinates, so the grid points may be approximated by the centers of mass of the analogous set of squared orthogonalized snapshots generated by a known reference velocity. We present results of inversion experiments for one-and two-dimensional synthetic models.

Original languageEnglish (US)
Pages (from-to)684-747
Number of pages64
JournalSIAM Journal on Imaging Sciences
Issue number2
StatePublished - May 17 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Society for Industrial and Applied Mathematics.


  • Full waveform inversion
  • Galerkin method
  • Gel'fand-Levitan
  • Model reduction
  • Optimal grids


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