Hondori, Ehsan Jamali (Kyoto University) | Mikada, Hitoshi (Kyoto University) | Goto, Tada-nori (Kyoto University) | Takekawa, Junichi (Kyoto University) | Siahkoohi, Hamid Reza (University of Tehran)
There are numerous methods which make use of different algorithms to solve the well-known deconvolution problem in seismic data processing. Most of these solutions require restrictive assumptions to seismic wavelet and reflectivity series, in particular wavelet to be known and/or the seismic reflections to be white. Here we use a different approach in the deconvolution that is not sensitive to the phase characteristics of wavelet nor to the whiteness of reflectivity series. We define an inversion problem for deconvolution to avoid from computing the inverse of the seismic wavelet. First, we locate spikes by means of Adaptive Simulated Annealing (ASA) and then compute the amplitudes of them by Least Square method. A comparison between this method and Minimum Entropy Deconvolution (MED) shows that although both methods try to simplify the seismic model, this method yields better results.