1887

Abstract

Summary

Probabilistic inversion of subsurface elastic properties using seismic reflection data is considered. The methodology makes use of data partitioning as a divide-and-conquer strategy, while the conditioning to data makes use of an iterative ensemble Kalman smoother. Augmenting the ensemble Kalman framework with an variational approach is found suitable when conditioning on larger sets of seismic waveform data. The methodology is exemplified using a synthetic case for the inversion of acoustic- and shear velocity and density.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201902267
2019-09-02
2024-03-29
Loading full text...

Full text loading...

References

  1. Asch, M., Bocquet, M. and Nodet, M. [2016] Data Assimilation: Methods, Algorithms, and Applications.Society for Industrial and Applied Mathematics, Philadelphia, PA.
    [Google Scholar]
  2. Bocquet, M. and Sakov, P. [2012] Combining inflation-free and iterative ensemble Kalman filters for strongly nonlinear systems. Nonlin. Processes Geophys., 19(3), 383–399.
    [Google Scholar]
  3. Bocquet, M. and Sakov, P. [2014] An iterative ensemble Kalman smoother. Quarterly Journal of the Royal Meteorological Society, 140(682), 1521–1535.
    [Google Scholar]
  4. Kennett, B. [2011] Seismic Wave Propagation in Stratified Media.ANU Press.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201902267
Loading
/content/papers/10.3997/2214-4609.201902267
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error