The filtering characteristics of HHT and its application in acoustic log waveform signal processing

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Abstract Array acoustic logging plays an important role in formation evaluation. Its data is a non-linear and non-stationary signal and array acoustic logging signals have time-varying spectrum characteristics. Traditional filtering methods are inadequate. We introduce a Hilbert-Huang transform (HHT) which makes full preservation of the non-linear and non-stationary characteristics and has great advantages in the acoustic signal filtering. Using the empirical mode decomposition (EMD) method, the acoustic log waveforms can be decomposed into a finite and often small number of intrinsic mode functions (IMF). The results of applying HHT to real array acoustic logging signal filtering and de-noising are presented to illustrate the efficiency and power of this new method.

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	WANG Zhu-Wen
	LIU Jing-Hua
	YUE Chong-Wang
	LI Xiao-Chun
	LI Chang-Chun

Key words： Hilbert-Huang transform empirical mode decomposition intrinsic mode functions time-frequency filter

Received: 2008-07-27;

Fund:

This research is supported by National Natural Science Foundation of China (Grant No. 40874059) and the National Key Science Engineering Projects of the Ninth Five Year Plan ([1999]1423).

Cite this article:

WANG Zhu-Wen,LIU Jing-Hua,YUE Chong-Wang et al. The filtering characteristics of HHT and its application in acoustic log waveform signal processing[J]. APPLIED GEOPHYSICS, 2009, 6(1): 8-16.

[1]	Balocchi, R., Menicucci, D., Varanini, M., 2003, Empirical mode decomposition to approach the problem of detecting sources from a reduced number of mixtures: EMBS, Proceedings of the 25th Annual International Conference of the IEEE, 3, 2443 - 2446.
[2]	Champency, C. D., 1987, A handbook of Fourier theorems: Cambridge University Press, London.
[3]	Chen, B. X, and Zhang, Y., 2002, Full wave sonic logging data processing technique and its applications: Well Logging Technology (in Chinese), 26(5), 369 - 372.
[4]	Chu, Z. H., 1985, Principle of acoustic logging: Petroleum Industry Press, Beijing.
[5]	Cohen, L., 1995, Time-frequency analysis: Prentice-Hall, Englewood Cliffs, New Jersey .
[6]	Daubechies, I., 1990, The wavelet transform, time-frequency localization and signal analysis: IEEE Transactions on Information Theory, 36(5), 961 - 1005.
[7]	Deng, Y.J., Wang, W., Qian, C. C., Wang, Z., Dai, D.J., 2001, EMD method and the boundary-problem-processing in Hilbert transform: Chinese Science Bulletin, 41(3), 257 - 263.
[8]	Donnbo, D., 1995, Denoising by soft-thresholding: IEEE Trans on IT, 4(3), 613 - 625.
[9]	Fan, J. R., 2003, Application and research of EMD analysis in fault diagnosis systems: Master Thesis of Wuhan University of Technology, Wuhan, China.
[10]	Flandrin, P., Rilling, G., and Goncalv`es, P., 2004, Empirical mode decomposition as a filter bank: IEEE Signal Processing Letters, 11(2), 112 - 124.
[11]	Huang, N. E., 1997, Computer implemented empirical mode decomposition method, apparatus and article of manufacture: US Patent 5, 983, 162, June - 10 - 1997.
[12]	Huang, N. E., Shen, Z., and Long, S. R., Wu, M.C., Shih,H.H., Zheng, Q., Yen, N. C., Tung, C.C., and Liu, H.H., 1998, The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis: Proc. R. Soc. Lond. A, 454, 903 - 995.
[13]	Huang, N. E., Shen, Z., Long, S. R., 1999, A new view of nonlinear water waves: The Hilbert spectrum: Annual Review of Fluid Mechanics, 31, 417 - 457.
[14]	Huang, N. E., Long, S. R., and Shen, Z., 1996, The mechanism for frequency downshift in nonlinear wave evolution: Advances in Applied Mechanics, 32, 59 - 111.
[15]	Li, C. W., Yu, C. H., and Wang, W. X., 1997, Full wavetrain processing of array acoustic logging data and its application: Well Logging Technology (in Chinese), 21(1), 1 - 8.
[16]	Li, W. Y., Li, Y. S. , Wang, Z. H., He, Z.B., Lu, H.P., 1999, Processing DSI logging data with STC method: Journal of Jianghan Petroleum Institute, 21(4), 36 - 39.
[17]	Liu, T., Su, T. M., and Sun, J., 2005, Study on acoustic diversity attenuation properties of rock and foreground of applying in engineering: Progress in Geophysics (in Chinese), 20(3), 822 - 827.
[18]	Loh, G. H., 2001, Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses: Bulletin of the Seismological Society of America, 91(5), 1339 - 1357.
[19]	Mallat, S., 1989, A theory for multiresolution signal decomposition: The wavelet representation: IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), 674 - 93.
[20]	Shekel, J., 1953, ‘Instantaneous’ frequency: Proceedings of the Institute of Radio Engineers, 41, 548.
[21]	Schlurmann, T., 2002, Spectral analysis of nonlinear water waves based on the Hilbert-Huang transformation: Journal of Offshore Mechanics and Artic Engineering, 124, 22 - 27.
[22]	Tao, G., Zou, H., 2000, A study on methods for processing and interpretation of modern array sonic logging data: Petroleum Exploration and Development, 27(2), 76 - 78.
[23]	Wang, Z. H., and Wang, Z. W., 2004, The development and current situation of acoustic logging: in Zhang, Z. J., Liu, Z.K., Han, L.G., Yang. B.J., Niu, B.H., and Wang, J.M., Eds. The New Developments in Seismic Research, Petroleum Industry Press, Beijing, China.
[24]	Wang, Z. W., Liu, J. H., and Nie, C. Y., 2007a, Time-frequency analysis of array acoustic logging signal based on Choi-Williams energy distribution: Progress in Geophysics (in Chinese), 22(5), 1481 - 1486.
[25]	Wang, Z. W., Liu, J. H., and Nie, C. Y., 2007b, The reassignment method based on time-frequency analysis and its application in the array acoustic logging data processing: Journal of Jilin University (Earth Science Edition), 37(5), 1042 - 1046.
[26]	Wang, Z. W., Liu, J. H., and Nie, C. Y., 2008a, Time-frequency analysis of array acoustic logging waveform signal based on Hilbert-Huang transform: Earth Science Journal of China University of Geosciences, 33(3), 387 - 392.
[27]	Wang, Z. W., Liu, J. H., and Nie, C. Y., 2008b, Application of Hilbert-Huang transform in extracting dynamic properties of array acoustic signals: Progress in Geophysics (in Chinese), 23(2), 450 - 455.
[28]	Wang, Z. W., Liu, J. H., and Nie, C. Y., 2008c, Array acoustic logging signal analysis based on the local correlation energy: Journal of Jilin University (Earth Science Edition), 38(2), 341 - 346.
[29]	Xiong, X. J., Guo, B. H., Hu, X. M., Liu, J.J., 2002, Application and discussion of empirical mode decomposition method and Hilbert spectral analysis method: Advances in Marine Science, 20(2), 12 - 21.
[30]	Zhang, X. T., Wang, Z. W., Yuan, J. H., 2008, Using time-frequency analysis to identify oil and water layers in array acoustic logging: Lithologic Reservoirs, 20(1), 101 - 104.
[31]	Zhang, B. X., and Wang, K. X., 1998, Status quo and development of the acoustic multipole logging in anisotropic formation, Progress in Geophysics (in Chinese), 13(2), 1 - 14.
[32]	Zhu, L. F., and Shen, J.G., 2006, The new method of processing the slowness of P and S-wave from waveforms of array sonic logging: Progress in Geophysics (in Chinese), 21(2), 483 - 488.