An approximation of the inverse Ricker wavelet as an initial guess for bidirectional deconvolution

Abstract:

Bidirectional deconvolution is a powerful tool for performing blind deconvolution on a signal that contains a mixed-phase wavelet, such as seismic data. Previously, we used a prediction error filter (PEF) as the minimum-phase filter and an impulse function as the maximum-phase filter as initial guesses. This surprised us by apparent instability as the solution would jump from spiking the first pulse of a Ricker wavelet to get larger middle pulse. In this paper, we propose new initial guesses for the causal and anti-causal deconvolution filters that are more effective on data with a Ricker-like wavelet. We test these on both synthetic data and field data. The results demonstrate that the new starting filters do a better job than the previous initial guesses.