Résumé:
In seismic deconvolution, blind approches 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 reflectors contributions make the
wavelet estimation and deconvolution procedure from recorded data complicated. In this paper, we address this problem in a two steps 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 by using the Prony algorithm. The algorithmic
problem of wavelet initialization is also addressed. Simulation results and real data experiments show the significant
improvement brought by this approach.
