Blind estimation of long impulse response and non-minimum phase wavelets application to seismic data

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.