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. KEY WORDS: mode mixing, ensemble empirical mode decomposition (EEMD), damped instantaneous frequency (DIF), frequency estimation, seismic instantaneous attributes.

Noncontact Measurement and Detection of Instantaneous Seismic Attributes Based on Complementary Ensemble Empirical Mode Decomposition

“…This paper is not going to cover the basic principles of HHT which have been introduced in much of the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. We will focus only on mode mixing problems of the EMD method in HHT.…”

“…HHT can process any signal without prior knowledge and is not be limited by the Heisenberg uncertainty principle. However, HHT also has some disadvantages, such as mode mixing, endpoint effect, instantaneous frequency error and so on [5]. The key part of the method is the empirical mode decomposition (EMD), which can decompose the signal into a finite number of intrinsic mode functions (IMF) in the temporal domain, with each IMF being a narrow-band signal [6,7].…”

“…The key part of the method is the empirical mode decomposition (EMD), which can decompose the signal into a finite number of intrinsic mode functions (IMF) in the temporal domain, with each IMF being a narrow-band signal [6,7]. However, the EMD method can not guarantee orthogonality between the decomposed IMF and aliasing between IMFs, which is unfavorable for seismic data analysis and may lead to an incorrect interpretation [5,8]. The mode mixing problem of EMD will be described in detail in Section 2.…”

“…Han et al used EMD for seismic time-frequency analysis [15]. Wang et al proposed the improved HHT algorithm, which can effectively overcome the shortage of HHT [5]. Xue et al studied the EMD-based highlight volume methods, which can be used for hydrocarbon detection [16].…”