A comparative study on hydrocarbon detection using three EMD-based time–frequency analysis methods

Abstract Due to strong heterogeneity of marine carbonate reservoir, seismic signals become more complex, thus, it is very difficult for hydrocarbon detection. In hydrocarbon reservoir, there usually exist some changes in seismic wave energy and frequency. In their instantaneous spectrums there often exist such phenomena that show the characteristics of attenuation of high frequency energy and enhancement of low-frequency energy. The three EMD-based time-frequency analysis methods' instantaneous spectra all have certain oil and gas detection capability. In this paper, we introduced the Normalized Hilbert Transform (NHT) and a new method named the HU method for hydrocarbon detection. The model results in the Jingbian Gas Field which is located in the eastern Ordos Basin, China, show that NHT and HU methods can be adopted. They also detect the gas-bearing reservoir efficiently as the HHT method does. The three EMD-based methods, that is, the Hilbert–Huang transformation (HHT) and NHT and HU methods, were respectively applied to analyze the seismic data from the Jingbian Gas Field. Firstly, the seismic signals were decomposed into a finite number of intrinsic mode functions (IMFs) by empirical mode decomposition (EMD) method. The second IMF signal (IMF2) of the original seismic section better indicates the distribution of the reservoir. Information on hydrocarbon-bearing reservoir is mainly in IMF2. Secondly, the HHT, NHT and HU methods were respectively used to obtain different frequency division sections from IMF2. Hydrocarbon detection was realized from the energy distribution of the different frequency division sections with these three EMD-based methods. The practical application results show that the three EMD-based methods can all be employed to hydrocarbon detection. Frequency division section of IMF2 using NHT method was better for the seismic data from the Jingbian Gas Field than when using the HHT method and HU method.

[1]  P. Xu,et al.  Crustal Velocity Structure of the Deep Continental Subduction Zone — A Wide Angle Reflection/Refraction Seismic Study on the Eastern Dabie Orogen , 2003 .

[2]  Thomas M. Daley,et al.  Seismic low-frequency effects in monitoring fluid-saturated reservoirs , 2004 .

[3]  Lalu Mansinha,et al.  Localization of the complex spectrum: the S transform , 1996, IEEE Trans. Signal Process..

[4]  A. Nuttall,et al.  On the quadrature approximation to the Hilbert transform of modulated signals , 1966 .

[6]  Richard G. Baraniuk,et al.  Empirical mode decomposition based time-frequency attributes , 1999 .

[7]  Li Changchun,et al.  The filtering characteristics of HHT and its application in acoustic log waveform signal processing , 2009 .

[8]  Yang Shi.  STUDY ON THE METHOD OF EMD-BASED VIBRATION SIGNAL TIME-FREQUENCY ANALYSIS , 2008 .

[9]  Joshua R. Smith,et al.  The local mean decomposition and its application to EEG perception data , 2005, Journal of The Royal Society Interface.

[10]  S. Qian,et al.  Joint time-frequency analysis , 1999, IEEE Signal Process. Mag..

[11]  Jing-Hua Gao,et al.  Generalized S Transform and Seismic Response Analysis of Thin Interbedss Surrounding Regions by Gps , 2003 .

[12]  E. Bedrosian.  A Product Theorem for Hilbert Transforms , 1963 .

[13]  Chih Sung Chen,et al.  Nonlinear data processing method for the signal enhancement of GPR data , 2011 .

[14]  Hassan H. Hassan.  Empirical Mode Decomposition (EMD) of Potential Field Data: Airborne Gravity Data As an Example , 2005 .

[15]  Bai Yang,et al.  A preliminary study of application of Empirical Mode Decomposition method in understanding the features of internal waves in the northeastern South China Sea , 2010 .

[16]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[17]  Norden E. Huang,et al.  On Instantaneous Frequency , 2009, Adv. Data Sci. Adapt. Anal..

[18]  Huang De-ji.  Application of the Hilbert-Huang transform to the analysis of seismic signal , 2005 .

[19]  Reservoir detection based on EMD and correlation dimension , 2009 .

[20]  Bradley Matthew Battista,et al.  Application of the Empirical Mode Decomposition and Hilbert-Huang Transform to Seismic Reflection Data , 2007 .