Entropy 2011, 13(9), 1730-1745; doi:10.3390/e13091730
Article

Blind Deconvolution of Seismic Data Using f-Divergences

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
* Author to whom correspondence should be addressed.
Received: 15 August 2011; in revised form: 10 September 2011 / Accepted: 14 September 2011 / Published: 19 September 2011
PDF Full-text Download PDF Full-Text [196 KB, Updated Version, uploaded 20 September 2011 17:14 CEST]
The original version is still available [195 KB, uploaded 19 September 2011 16:23 CEST]
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 distributions

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

MDPI and ACS Style

Zhang, B.; Gao, J.-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy 2011, 13, 1730-1745.

AMA Style

Zhang B, Gao J-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy. 2011; 13(9):1730-1745.

Chicago/Turabian Style

Zhang, Bing; Gao, Jing-Huai. 2011. "Blind Deconvolution of Seismic Data Using f-Divergences." Entropy 13, no. 9: 1730-1745.

Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert