Time-frequency analysis of seismic data using synchrosqueezing wavelet transform
Chen, Y., Liu, T., Chen, X., Li, J. and Wang, E., 2014. Time-frequency analysis of seismic data using synchrosqueezing wavelet transform. Journal of Seismic Exploration, 23: 303-312. Time-frequency (TF) decomposition is used for characterizing the non-stationary relation between time and instantaneous frequency, which is very important in the processing and interpretation of seismic data. The conventional time-frequency analysis approaches suffer from the contradiction between time resolution and frequency resolution. A new time-frequency analysis approach is proposed based on the synchrosqueezing wavelet transform (SSWT). The SSWT is an empirical-mode-decomposition-like tool but uses a different approach in constructing the components. With the help of the synchrosqueezing techniques, the SSWT can obtain obvious higher time and frequency resolution. Synthetic examples show that the SSWT based TF analysis can exactly capture the variable frequency components. Field data tests show the potential of the proposed approach in detecting anomalies of high-frequency attenuation and detecting the deep-layer weak signal.
- Castagna, J., Sun, S. and Siegfried, R.W., 2003. Instantaneous spectral analysis: Detection oflow-frequency shadows associated with hydrocarbons. The Leading Edge, 22: 120-127.
- Daubechies, I., Lu, J. and Wu, H.-T., 2011. Synchrosqueezed wavelet transforms: An empiricalmode decomposition-like tool. Appl. Computat. Harmonic Analys., 30: 243-261.
- Fomel, S., 2013. Seismic data decomposition into spectral components using regularizednonstationary autoregression. Geophysics, 78: 069-076.
- Huang, N.E., Shen, Z., Long, $.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tung, C.C.and Liu, H.H., 1998. The empirical mode decomposition and the Hilbert spectrum fornonlinear and non-stationary time series analysis. Proc. Roy. Soc. London Ser. A, 454: 903-
- Lin, T., Wan, Z., Zhang, B., Guo, S., Marfurt, K. and Guo, Y., 2013. Spectral decomposition oftime-vs. depth-migrated data. Expanded Abstr., 83rd Ann. Internat. SEG Mtg., Houston:1384-1388.
- Liu, G., Chen, X., Du, J. and Song, J., 2011. Seismic noise attenuation using nonstationarypolynomial fitting. Appl. Geophys., 8: 18-26.
- Partyka, G.A., Gridley, J.M. and Lopez, J., 1998. Interpretational applications of spectraldecomposition in reservoir characterization. The Leading Edge, 18: 353-360.
- Reine, C., van der Baan, M. and Clark, R., 2009. The robustness of seismic attenuationmeasurements using fixed- and variable-window time-frequency transforms. Geophysics, 74:123-135. ;
- Shang, S., Han, L. and Hu, W., 2013. Seismic data analysis using synchrosqueezing wavelettransform. Expanded Abstr., 83rd Ann. Internat. SEG Mtg., Houston: 4330-4334.
