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Empirical Mode Decomposition for Seismic Applications Open Access


Other title
Empirical mode decomposition
Time-frequency analysis
Type of item
Degree grantor
University of Alberta
Author or creator
Han, Jiajun
Supervisor and department
Mirko van der Baan (Physics)
Examining committee member and department
Mirko van der Baan (Physics)
Vicky Zhao (Electrical & Computer Engineering)
Bruce Sutherland (Earth & Atmospheric Sciences)
Vadim Kravchinsky (Physics)
Mauricio D. Sacchi (Physcics)
John Castagna (Earth and Atmospheric Sciences, University of Houston)
Department of Physics
Date accepted
Graduation date
Doctor of Philosophy
Degree level
Empirical mode decomposition (EMD) is a powerful signal analysis technique to analyze non-stationary signal systems, like seismic data. Through the sifting process, EMD splits the non-stationary features of the input signal into individual decomposition modes, which are called intrinsic mode functions (IMFs). Each IMF has a symmetric, narrow-band waveform, which ensures that their instantaneous frequency of them is smooth and positive. However some negative features encumber its direct application namely mode mixing and splitting, aliasing and endpoint artifacts. Two variants, ensemble EMD (EEMD) and complete ensemble EMD (CEEMD) have been recently introduced to overcome some of the negative features associated with EMD. Furthermore, two EMD-like methods are also introduced: first one is the synchrosqueezing transform (SST), which decomposes the input signal into SST modes, and these modes manifest similar features to IMFs; another one is the 2D extension of EMD, bidimensional empirical mode decomposition (BEMD), which can aid image analysis. This thesis focuses on testing the suitability of EMD methods for seismic processing and interpretation, and we present 4 new techniques. The first method is CEEMD combined with instantaneous spectra for seismic spectral decomposition. After CEEMD, the instantaneous frequency spectra manifests visibly higher time-frequency resolution than short time Fourier and wavelet transforms on both synthetic and field data examples. The second method is EEMD thresholding. It is effective for suppressing random noise in each trace, which is highly attractive for microseismic processing. Furthermore, the proposed EEMD thresholding can be extended into the f-x domain as f-x EEMD thresholding, which aims to reduce dip- ping coherent and random noise. The third application is SST for seismic signal time-frequency analysis. It shows comparable results to CEEMD combined with instantaneous spectra; therefore it is highly suitable for high resolution seismic interpretation. The last proposed method is BEMD thresholding, which aims to reduce random noise of 2D seismic images. Utilizing the particular features of IMFs or SST modes, the presented methods manifest excellent performance on seismic spectral decomposition and seismic denoising. The synthetic and real data examples illustrate that EMD methods are highly promising for seismic processing and interpretation.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Han, J. and M. Van der Baan. “Empirical mode decomposition for seismic time-frequency analysis.” Geophysics 78 (2013). Han, J., R.H. Herrera, and M. Van der Baan. “Spectral decomposition by synchrosqueezing transform.” 75th Mtg., EAGE London. 2013. Han, J. and M. Van der Baan. “Empirical Mode Decomposition and Robust Seismic Attribute Analysis.” 2011 CSPG CSEG CWLS Convention 114 (2011). Herrera, RH., J. Han, and M. Van der Baan. “Applications of the synchrosqueezing transform in seismic time-frequency analysis.” Geophysics 79 (2014).

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