A new approach for extracting the amplitude spectrum of the seismic wavelet from the seismic traces. (19th June 2017)

• Record Type: Journal Article
• Authors: Gao, Jinghuai; Zhang, Bing; Han, Weimin; Peng, Jigen; Xu, Zongben
• Is Part Of: Inverse problems. Volume 33:Number 8(2017:Aug.)
• Publication Date: 2017-06-19
• Subjects: seismic inversion -- seismic wavelet -- seismic data processing -- contraction mapping; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/1361-6420/aa59e0
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: In reflection seismology, knowing the seismic wavelet is important both for processing seismic data and for modeling the seismic response. There are two approaches to obtain the seismic wavelet. One approach is deterministic and the other is statistic. This work belongs to the second category. A seismic wavelet is determined by the product of amplitude spectrum and phase spectrum. A conventional method uses a two-step procedure to estimate the seismic wavelet. The first step is for the amplitude spectrum, and the second step is for the phase spectrum. So extracting the amplitude spectrum of a seismic wavelet (ASSW) from the amplitude spectrum of a seismic trace is a key step. The commonly used methods are correlation-based method, the log-spectrum-averaging method and spectrum-shaping method. All these methods assume the reflection coefficient sequence is white, which may not be valid under some conditions. In this paper, we propose a new approach to obtain ASSW without the whiteness assumption about reflectivity. We define an operator on a properly chosen function space and prove that the operator is contractive in this space. Then, we convert the problem of estimating the ASSW into one of finding the fixed point of the operator. We give the algorithm in detail based on the contraction operator mapping (COM method). We compare our method with the widely used methods by synthetic signals in which the reflectivity is not white. The results show that our method performs satisfactorily for nonwhite reflection series, on which other methods do not work well. Moreover, our method is robust for the noise and the frequency interval on which COM works.