A new mixed-phase wavelet extraction and evaluation method based on adaptive segmentation in non-stationary seismogram

Abstract

Traditional wavelet extraction methods are generally based on the hypothesis of time-invariant seismic wavelet with zero or minimum phase. Additionally, the evaluation of wavelet precision is hard to be performed directly. This paper presents a time-varying mixed-phase wavelet estimation method based on adaptive segmentation, in which quadratic spectrum modeling and higher-order cumulants double spectroscopy method are implemented to extract the amplitude and phase of segmented wavelets. Combined with the evaluation of deconvolution results using the estimated wavelets, the method can give a secondary evaluation of wavelet precision. Compared with the mixed-phase wavelet extraction method based on high-frequency attenuation compensation and zero-phase wavelet extraction method based on adaptive segmentation, simulation experiment results proved the correctness and superiority of the proposed method.