Instantaneous attributes analysis of seismic signals using improved HHT

Abstract

As the key technique of improved Hilbert-Huang transform (HHT), ensemble empirical mode decomposition (EEMD) has a good performance of eliminating mode mixing phenomenon, which has a strong impact on the observation of seismic information. However, the intrinsic mode functions (IMF) obtained from EEMD contain noises, so that it is required to find a more robust frequency estimation method to calculate the instantaneous frequency (IF) of IMF. For this reason, the improved HHT algorithm based on the damped instantaneous frequency (DIF) is proposed to overcome the shortage of EEMD. Compared with other IF estimation methods, the DIF has strong antinoise ability and high estimation accuracy. The test results of synthetic and real seismic data show that the proposed algorithm is feasible and effective for extracting seismic instantaneous attributes.

Keywords

mode mixing / ensemble empirical mode decomposition (EEMD) / damped instantaneous frequency (DIF) / frequency estimation / seismic instantaneous attributes

References

[1] Battista B. M., Knapp C. M., Gee T., . Application of the Empirical Mode Decomposition and Hilbert-Huang Transform to Seismic Reflection Data. Geophysics, 2007, 72(2): H29-H37.

[2] Boashash B. Estimating and Interpreting the Instantaneous Frequency of a Signal. Proceedings of the IEEE, 1992, 80(4): 540-568.

[3] Chen C. S., Jeng Y. Nonlinear Data Processing Method for the Signal Enhancement of GPR Data. Journal of Applied Geophysics, 2011, 75(1): 113-123.

[4] Chen C. S., Jeng Y. Natural Logarithm Transformed EEMD Instantaneous Attributes of Reflection Data. Journal of Applied Geophysics, 2013, 95: 53-65.

[5] Chen L., Song H. B. The Estimation of Instantaneous Frequency of Seismic Signal. Chinese Journal of Geophysics, 2009, 52(1): 206-214.

[6] Chen Y. P., Peng Z. M., He Z. H., . The Optimal Fractional Gabor Transform Based on the Adaptive Window Function and Its Application. Applied Geophysics, 2013, 10(3): 305-313.

[7] Cohen L. Time-Frequency Analysis: Theory and Applications, 1995 New York: Prentice Hall

[8] Deering R., Kaiser J. F. The Use of a Masking Signal to Improve Empirical Mode Decomposition. IEEE, ICASSP, 2005, 485-488.

[9] Flandrin P., Rilling G., Goncalves P. Empirical Mode Decomposition as a Filter Bank. IEEE Signal Processing Letters, 2004, 11(2): 112-114.

[10] Han J. J. v d, Baan M. V. D. Empirical Mode Decomposition for Seismic Time-Frequency Analysis. Geophysics, 2013, 78(2): O9-O19.

[11] Huang N. E. S. Z., Long S. R. A New View of Nonlinear Water Waves: The Hilbert Spectrum 1. Annual Review of Fluid Mechanics, 1999, 31(1): 417-457.

[12] Huang N. E., Shen Z., Long S. R., . The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995.

[13] Huang N. E., Wu M. L. C., Long S. R., . A Confidence Limit for the Empirical Mode Decomposition and Hilbert Spectral Analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2003, 459(2037): 2317-2345.

[14] Huang Y. P., Geng J. H., Zhong G. F., . Seismic Attribute Extraction Based on HHT and Its Application in a Marine Carbonate Area. Applied Geophysics, 2011, 8(2): 125-133.

[15] Li G. H. The Research and Application of Signal Analysis Based on HHT and Its Improved Method: [Dissertation]. Chengdu University of Technology, 2012

[16] Liu Y. P., Li Y., Lin H. B., . An Amplitude-Preserved Time-Frequency Peak Filtering Based on Empirical Mode Decomposition for Seismic Random Noise Reduction. IEEE Geoscience and Remote Sensing Letters, 2014, 11(5): 896-900.

[17] Shi H., Li G. L., Wang W., . Random Noise Attenuation Based on Ensemble Empirical Mode Decomposition. Progress in Geophysics, 2011, 26(1): 71-78.

[18] Song H. B., Bai Y., Pinheiro L., . Analysis of Ocean Internal Waves Imaged by Multichannel Reflection Seismics, Using Ensemble Empirical Mode Decomposition. Journal of Geophysics and Engineering, 2012, 9(3): 302-311.

[19] Tian L., Peng Z. M. Determining the Optimal Order of Fractional Gabor Transform Based on Kurtosis Maximization and Its Application. Journal of Applied Geophysics, 2014, 108: 152-158.

[20] Wang T., Zhang M. C., Yu Q. H., . Comparing the Applications of EMD and EEMD on Time-Frequency Analysis of Seismic Signal. Journal of Applied Geophysics, 2012, 83: 29-34.

[21] Wu A. X. HHT Time-Frequency Analysis of Digital Seismic Waveform Signals. FSKD, 2012, 9: 1802-1806.

[22] Wu Z. H., Huang N. E. Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.

[23] Wu Z., Huang N. E. A Study of the Characteristics of White Noise Using the Empirical Mode Decomposition Method. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2004, 460(2046): 1597-1611.

[24] Zhao C. X. The Research of Time-Frequency Analysis Method Based on Hilbert-Huang Transform: [Dissertation]. China University of Petroleum, 2011

[25] Zhou Y. H., Chen W. C., Gao J. H., . Application of Hilbert-Huang Transform Based Instantaneous Frequency to Seismic Reflection Data. Journal of Applied Geophysics, 2012, 82: 68-74.