Estimation of mixed-phase wavelet and Q value of nonstationary seismic data using genetic algorithm
Seismic high-resolution processing or inversion is aimed to obtain an accurate reflection coefficient or elastic parameter model.However,the formation filtering effect blurs the formation reflection information in seismic records,so it is necessary to eliminate this filtering effect.Most of the existing resolution enhancement methods can not completely discard some assumptions about seismic wavelet and Q model.In order to obtain more realistic seismic wavelets,while simultaneously adaptively acquiring the Q model,this paper combines the seismic wavelet phase estimation with the Q model estimation,proposing an estimation method of mixed-phase wavelet and Q value for nonstationary seismic data based on genetic algorithm.First,the amplitude information of the initial seismic wavelet is obtained by fitting the well-side seismic record.Then the coding chain for ge-netic algorithm is constructed based on whether the root of the wavelet Z transform moves with the unit circle or not.On the other hand,the binary representation corresponding to the decimal Q model can also be characteri-zed by coded chain,so the global optimization algorithm can be used to simultaneously estimate the seismic mixed-phase wavelet and the Q model.Combining root transformation with genetic algorithms can continuously adjust the phase of the wavelet while adaptively generating the Q model.The time-varying wavelet matrix,along with well logging reflection coefficients,are used to obtain the synthetic seismic record,which is matched with the well-side seismic record.Finally,a reasonable mixed phase wavelet and formation Q model are ob-tained,and then the time-varying wavelet matrix is constructed for time-varying deconvolution.The phase of mixed-phase wavelet obtained by fitting the well-side seismic records and logging data is closer to the actual seis-mic wavelet.The theoretical data and practical data processing results confirm the effectiveness of this method.
high resolution processingquality factor(Q)nonstationary seismic datamixed-phase waveletge-netic algorithm
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