DocumentCode :
1082603
Title :
Bayesian parametric separation applied to multicomponent seismic data
Author :
Essebbar, Abderrahman
Author_Institution :
CEPHAG-CNRS, Saint-Martin d´´Heres, France
Volume :
3
Issue :
7
fYear :
1996
fDate :
7/1/1996 12:00:00 AM
Firstpage :
218
Lastpage :
220
Abstract :
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.
Keywords :
Bayes methods; geophysical signal processing; maximum likelihood estimation; seismic waves; seismology; Bayesian parametric separation; MLE; down-going waves; maximum likelihood estimator; multicomponent seismic data; parametric estimation; up-going waves; velocity estimation; vertical seismic profile data; Additive noise; Bayesian methods; Delay estimation; Frequency estimation; Linear antenna arrays; Maximum likelihood estimation; Propagation delay; Radar signal processing; Seismic waves; Sensor arrays;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/97.508170
Filename :
508170
Link To Document :
بازگشت