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Seismic wavelet estimation using covariation approach
Yue, Bibo1; Peng, Zhenming1; Zhang, Qiheng2
Source PublicationIEEE Transactions on Geoscience and Remote Sensing
Volume52Issue:12Pages:7495-7503
2014
Language英语
ISSN01962892
DOI10.1109/TGRS.2014.2313116
Indexed BySCI ; Ei
WOS IDWOS:000341532100002
Subtype期刊论文
AbstractThis paper proposes a novel covariation approach for seismic wavelet estimation under the assumption that a real seismic signal follows non-Gaussian α-stable distributions. Since the non-Gaussian α-stable signals do not have finite second or higher order moments, the traditional methods of Gaussian distribution may not get a suitable solution. Based on the principle of fractional lower order statistics, the covariation approach deconvolution objective function matrix was given, and the details of wavelet estimation with the covariation approach were presented. Furthermore, computer simulation experiments on theoretical synthetic data and real seismic data were conducted. In the experiments, the effect of moments was considered. Among the estimated wavelets with different moments, the best wavelet should be the one with moment less than characteristic but close to characteristic. To verify the correctness and effectiveness of the proposed method, the extracted real wavelet was applied in real seismic acoustic impedance inversion. The result from the inversion of the 2-D real data set is consistent with the well log interpretation very well. © 2014 IEEE.; This paper proposes a novel covariation approach for seismic wavelet estimation under the assumption that a real seismic signal follows non-Gaussian α-stable distributions. Since the non-Gaussian α-stable signals do not have finite second or higher order moments, the traditional methods of Gaussian distribution may not get a suitable solution. Based on the principle of fractional lower order statistics, the covariation approach deconvolution objective function matrix was given, and the details of wavelet estimation with the covariation approach were presented. Furthermore, computer simulation experiments on theoretical synthetic data and real seismic data were conducted. In the experiments, the effect of moments was considered. Among the estimated wavelets with different moments, the best wavelet should be the one with moment less than characteristic but close to characteristic. To verify the correctness and effectiveness of the proposed method, the extracted real wavelet was applied in real seismic acoustic impedance inversion. The result from the inversion of the 2-D real data set is consistent with the well log interpretation very well. © 2014 IEEE.
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Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/5078
Collection光电探测与信号处理研究室(五室)
Affiliation1. School of Opto-Electronic Information, University of Electronic Science and Technology of China, Chengdu 610054, China
2. Institute of Optics and Electronics, China Academy of Sciences, Chengdu 610209, China
Recommended Citation
GB/T 7714
Yue, Bibo,Peng, Zhenming,Zhang, Qiheng. Seismic wavelet estimation using covariation approach[J]. IEEE Transactions on Geoscience and Remote Sensing,2014,52(12):7495-7503.
APA Yue, Bibo,Peng, Zhenming,&Zhang, Qiheng.(2014).Seismic wavelet estimation using covariation approach.IEEE Transactions on Geoscience and Remote Sensing,52(12),7495-7503.
MLA Yue, Bibo,et al."Seismic wavelet estimation using covariation approach".IEEE Transactions on Geoscience and Remote Sensing 52.12(2014):7495-7503.
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