blind deconvolution of seismic data using f-divergences使用f-divergences盲反褶积的地震数据.pdfVIP

Entropy 2011, 13, 1730-1745; doi:10.3390/ OPEN ACCESS entropy ISSN 1099-4300 /journal/entropy Article Blind Deconvolution of Seismic Data Using f-Divergences Bing Zhang * and Jing-Huai Gao National Engineering Laboratory for Offshore Oil Exploration, Wave and Information Institute, School of Electronics and Information Engineering, Xi’an Jiao Tong University, No. 28 of West Xian’ning Road, Xi’an 710049, Shaanxi, China; E-Mail: jhgao@ * Author to whom correspondence should be addressed; E-Mail: xawslhh@163.com. Received: 15 August 2011; in revised form: 10 September 2011 / Accepted: 14 September 2011 / Published: 19 September 2011 Abstract: This paper proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data characterized by low dominant frequency and short data records, based on Csiszár’s f-divergence. In order to model the probability density function of the deconvolved data, and obtain the closed form formula of Csiszár’s f-divergence, mixture Jones’ family of distributions (MJ) is introduced, by which a new criterion for blind deconvolution is constructed. By applying Neidell’s wavelet model to the inverse filter, we then make the optimization program for multivariate reduce to univariate case. Examples are provided showing the good performance of the method, even in low SNR situations. Keywords: blind deconvolution; f-divergence; mixture Jones’ family of