Title :
Bayesian parametric separation applied to multicomponent seismic data
Author :
Essebbar, Abderrahman
Author_Institution :
CEPHAG-CNRS, Saint-Martin d´´Heres, France
fDate :
7/1/1996 12:00:00 AM
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;
Journal_Title :
Signal Processing Letters, IEEE