By Topic

Bayesian parametric separation applied to multicomponent seismic data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Essebbar, A. ; CEPHAG-CNRS, Saint-Martin d''Heres, France

The article addresses the parametric estimation of multicomponent seismic waves. The approach of parametric separation based on the maximum likelihood estimator (MLE) is introduced, and the a priori information is obtained by the down-going waves in vertical seismic profile (VSP) data. First, we recall the MLE method. Then the Bayesian approach is introduced, and finally, we show on synthetic seismic data that the estimation of velocities of up-going waves is improved.

Published in:

Signal Processing Letters, IEEE  (Volume:3 ,  Issue: 7 )