The optimal fractional Gabor transform based on the adaptive window function and its application
Chen Ying-Pin1, Peng Zhen-Ming1, He Zhen-Hua2, Tian Lin1, and Zhang Dong-Jun3
1. School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, Chengdu 610054, China.
2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, China.
3. Geophysical Exploration Company, Chuanqing Drilling Engineering Co. Ltd., CNPC, Chengdu 610213, China.
Abstract:
We designed the window function of the optimal Gabor transform based on the time–frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time–frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time–frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.
CHEN Ying-Pin,PENG Zhen-Ming,HE Zhen-Hua et al. The optimal fractional Gabor transform based on the adaptive window function and its application[J]. APPLIED GEOPHYSICS, 2013, 10(3): 305-313.
[1]
Almeida, L. B., 1994, The fractional Fourier transform and time-frequency representations: IEEE Transactions on Signal Processing, 42(11), 3084 - 3091.
[2]
Chen, Y. P., Peng, Z. M., 2012, A novel optimal STFrFT and its application in seismic signal processing: The third International Conference on Computational Problem-Solving, Leshan, China, 328 - 331.
[3]
Durak, L., and Ankan, O., 2002, Generalized time bandwidth product optimal short time Fourier transformation: IEEE conference publications, 2, 1465 - 1468.
[4]
Liu, J., and Marfurt, K. J., 2007, Instantaneous spectral attributes to detect channels: Geophysics, 72(2), 23 - 31.
[5]
Liu, X. W., Liu, W. Y., Liu,H., and Li, Y. M., 2007, Generalized seismic signal time-frequency analysis and numerical algorithms: Computing techniques for geophysical and geochemical exploration (in Chinese), 29(5), 386 - 390.
[6]
Montana, C. A., and Margrave, G. F., 2004, Spatial prediction filtering in fractional Fourier domains: SEG Annual, 41(2), 241 - 244.
[7]
Ozaktas, H. M., Ankan, O., Kutay, M. A., and Bozdagt, G., 1996, Digital Computation of the Fractional Fourier Transform: IEEE Transactions on signal processing, 44(9), 2141 - 2150.
[8]
Ozaktas, H. M., and Kutay, M. A., 1999, Introduction to the fractional Fourier transform and its applications: Advances in imaging and electron, volume 106, 239 - 291.
[9]
Sinha, S., Routh, P. S., Anno, P. D., and Castagna, J. P. C., 2005, Spectral decomposition of seismic data with continuous-wavelet transform: Geophysics, 70(6), 19 - 25.
[10]
Xu, D.P. and Guo, K., 2012, Fractional S transform - Part 1: Theory: Applied geophysics, 9(1), 73 - 79.
[11]
Wang, Z. W., Wang, X. L., Xiang, W., Liu, Q. H., Zhang, X. A., and Yang, C., 2012, Reservoir information extraction using a fractional Fourier transform and a smooth pseudo Wigner-Ville distribution: Applied geophysics, 9(4), 391 - 400.
[12]
Wexler, J., and Raz, S., 1990, Discrete Gabor expansions: Signal Processing, 21(3), 207 - 221.