Improved Hilbert-Huang Transform and its Application in Seismic Data Spectrum Decomposition

2012 ◽  
Vol 152-154 ◽  
pp. 920-923
Author(s):  
Ping Ping Bing ◽  
Si Yuan Cao ◽  
Jiao Tong Lu

In the conventional seismic data time-frequency analysis, the wavelet transform, wigner ville distribution and so on, cannot meet the high precision time-frequency analysis requirements because of uncertainty principle and cross-term interference. The recently popular Hilbert-Huang transform (HHT) although overcomes these conventional methods’ deficiencies; it still has some unsolved deficiencies due to the theory imperfect. This paper focuses on an improved HHT so as to ameliorate the defect of original HHT. First of all, the wavelet packet transform (WPT) as the preprocessing will be used to the inspected signal, to get some narrow band signals. Then use the empirical mode decomposition (EMD) on the narrow band signals and get the real intrinsic mode function (IMF) by the method of correlation coefficient. From the numerical study and comparison of improved HHT, wavelet transform and HHT, it proves the validity and advantages of this improved method. At last, the improved HHT is applied to marine seismic data by the spectrum decomposition technology, and it well reveals the low frequency shadow phenomenon of the reservoir. The results show that this new method has effectiveness and feasibility in seismic data spectrum decomposition.

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. O47-O56 ◽  
Author(s):  
Zhiguo Wang ◽  
Bing Zhang ◽  
Jinghuai Gao ◽  
Qingzhen Wang ◽  
Qing Huo Liu

Using the continuous wavelet transform (CWT), the time-frequency analysis of reflection seismic data can provide significant information to delineate subsurface reservoirs. However, CWT is limited by the Heisenberg uncertainty principle, with a trade-off between time and frequency localizations. Meanwhile, the mother wavelet should be adapted to the real seismic waveform. Therefore, for a reflection seismic signal, we have developed a progressive wavelet family that is referred to as generalized beta wavelets (GBWs). By varying two parameters controlling the wavelet shapes, the time-frequency representation of GBWs can be given sufficient flexibility while remaining exactly analytic. To achieve an adaptive trade-off between time-frequency localizations, an optimization workflow is designed to estimate suitable parameters of GBWs in the time-frequency analysis of seismic data. For noise-free and noisy synthetic signals from a depositional cycle model, the results of spectral component using CWT with GBWs display its flexibility and robustness in the adaptive time-frequency representation. Finally, we have applied CWT with GBWs on 3D seismic data to show its potential to discriminate stacked fluvial channels in the vertical sections and to delineate more distinct fluvial channels in the horizontal slices. CWT with GBWs provides a potential technique to improve the resolution of exploration seismic interpretation.


Author(s):  
Yangkang Chen* ◽  
Tingting Liu ◽  
Xiaohong Chen ◽  
Jingye Li ◽  
Erying Wang

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki

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