Seismic attenuation analysis using ensemble empirical mode decomposition and wavelet transform
Xue Yajuan1,2,3, Cao Junxin1,3
1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu, Sichuan 610059, China;
2. School of Communication Engineering, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China;
3. School of Geophysics, Chengdu University of Technology, Chengdu, Sichuan 610059, China
Abstract：Conventional empirical mode decomposition (EMD) algorithms lead to multiple interpretation results due to mode mixing problems,which affect weak signal identification in gas reservoirs.Therefore,we propose here a mode mixing elimination approach,ensemble empirical mode decomposition (EEMD),combining with wavelet transform to extract new seismic attributes from seismic data.The proposed approach mainly contains the following steps:1 EEMD is applied to seismic traces.Intrinsic mode functions (IMFs) which have strong correlations with the original seismic trace are selected to reconstruct high frequency sub-signals.2 Attenuation gradient is calculated.According to characteristics of IMFs with high frequency after EEMD process,logarithmic energy at each point in wavelet time-frequency maps of the sub-signals is calculated with an improved dynamic window function in the frequency domain.Then attenuation gradient is calculated sample by sample and trace by trace for the seismic volume.3 The least squares method and dynamic adjustable window function algorithm in the frequency domain are used to improve the prediction accuracy of attenuation gradient.Applications in reservoir prediction in Western Sichuan marine carbonate reservoirs show that the proposed approach can depict different strong amplitude anomaly in reservoirs with different facies,especially strong amplitude anomaly in intra platform shoal facies reservoirs.The proposed approach can effectively eliminate formation influence.Hydrocarbon-prone statistical interpretation results obtained by the proposed approach are consistent with well gas testing results.
Castagna J P,Sun S,Siegfried R W.Instantaneous spectral analysis:Detection of low-frequency shadows associated with hydrocarbons.The Leading Edge,2003, 22(2):120-127.
[2]
Mitchell J T,Derzhi N,Lichma E.Energy absorption analysis:A case study.SEG Technical Program Expanded Abstracts,1996,15:1785-1788.
[3]
Tonn R.The determination of the seismic quality factor Q from VSP data:a comparison of different computational methods.Geophysical Prospecting,1991,39(1):1-27.
[4]
Xue Yajuan,Cao Junxing,Tian Renfei et al.Application of the empirical mode decomposition and wavelet transform to seismic reflection frequency attenuation analysis.Journal of Petroleum Science and Engineering,2014,122(7):360-370.
[5]
Huang N E,Shen Z,Long S R et al.The empiricalmode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis.Proceedings of the Royal Society A:Mathematical,Physical and Engineering Sciences,1998,454:903-995.
[6]
Huang N E,Shen Z,Long S R.A new view of nonlinear water waves:The Hilbert spectrum. Annual Review of Fluid Mechanics,1999,31(1):417-457.
[7]
Huang N E,Wu M C,Long S R et al.A confidence limit for the empirical mode decomposition and Hilbert spectral analysis.Proceedings of the Royal Society of London,2003,459:2317-2345.
[8]
Wu Z,Huang N E.Ensemble empirical mode decomposition:a noise-assisted data analysis method.Advances in Adaptive Data Analysis,2009,1(1):1-41.
Liu Xiqiang, Shen Ping, Li Hong et al.Time-frequency energy attenuation factor and its application on the basis of Gauss linear modulation frequency continuous wavelet transform.Earthquake Research in China, 2003,19(3):225-235.
[10]
刘钦圣.最小二乘问题计算方法.北京:北京工业大学出版社,1989.
[11]
Xue Yajuan, Cao Junxing, Tian Renfei. EMD and Teager-Kaiser energy applied to hydrocarbon detection in a carbonate reservoir.Geophysical Journal International,2014,197(1):277-291.
