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.
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