Paper Info
Title
Blind estimation of long impulse response and non-minimum phase wavelets application to seismic data
Abstract
In seismic deconvolution, blind approaches must be considered in situations where the reflectivity sequence, the source wavelet signal and the noise power level are unknown. In the presence of long, non-minimum-phase, source wavelets, strong interference of the contributions of reflectors make the wavelet estimation and deconvolution procedure from recorded data complicated. We address this problem in a two step approach. First, a robust, but truncated, estimate of the wavelet is performed using a standard maximum likelihood approach. Then, improved wavelet estimation is achieved by fitting an ARMA model to the initial MA wavelet using the Prony algorithm. The algorithmic problem of wavelet initialization is also addressed. Simulation results and real data experiments show that a significant improvement is brought by this approach.
Year
DOI
Venue
2003
10.1109/ICASSP.2003.1199504
ICASSP '03). 2003 IEEE International Conference
Keywords
Field
DocType
autoregressive moving average processes,deconvolution,geophysical signal processing,interference (signal),maximum likelihood estimation,seismology,transient response,ARMA,Prony algorithm,blind estimation,long impulse response,maximum likelihood estimation,nonminimum phase wavelets,reflectivity sequence,seismic data,seismic deconvolution,source wavelet signal,wavelet impulse response,wavelet initialization
Pattern recognition,Lifting scheme,Computer science,Second-generation wavelet transform,Artificial intelligence,Discrete wavelet transform,Cascade algorithm,Stationary wavelet transform,Wavelet packet decomposition,Wavelet,Wavelet transform
Conference
Volume
ISSN
ISBN
3
1520-6149
0-7803-7663-3
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Benayad Nsiri184.65
Thierry Chonavel224833.28
Jean-Marc Boucher313222.28