Abstract
In this paper, we propose a novel seismic blind deconvolution approach based on the Spearman’s rho in the case of band-limited seismic data with a low dominant frequency and short data records. The Spearman’s rho is a measure of the dependence between two continuous random variables without the influence of the marginal distributions, by which a new criterion for blind deconvolution is constructed. The optimization program for new criterion of blind deconvolution is performed by applying Neidell’s wavelet model to the inverse filter. The noise-free and noisy synthetic data, onshore seismic trace in the Ordos Basin, and offshore stacked section in the Bohai Bay Basin examples show good results of the method.
Highlights
A recorded seismic trace is often represented as the result of a superposition of wavelets of constant shape weighted by the reflectivity series, it can be modeled as a convolution between the source signature and the reflectivity series
In the case that the wavelet has the zeros on the unit circle, blind deconvolution is an ill posed problem, one of the criterions to apply to inverse filter is to maximize the independence between the samples from the deconvolved output [6]
Neidell’s wavelet model to constructing an inverse filter, which is derived from practical observation, and its z transform has the form [10]: WN ( z) = (1− z)n (1+ z)m n, m > 0
Summary
A recorded seismic trace is often represented as the result of a superposition of wavelets of constant shape weighted by the reflectivity series, it can be modeled as a convolution between the source signature and the reflectivity series. (2015) Blind Deconvolution of Seismic Data Based on the Spearman’s Rho. Journal of Computer and Communications, 3, 20-26. In the case that the wavelet has the zeros on the unit circle, blind deconvolution is an ill posed problem, one of the criterions to apply to inverse filter is to maximize the independence between the samples from the deconvolved output [6]. The overall objective of this paper is to construct a new criterion based on Spearman’s rho for seismic deconvolution, and propose a new blind deconvolution algorithm. This new method can handle the data with small samples, which means it has ability to deal with nonstationary data
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