Time-frequency analysis of seismic data using synchrosqueezing wavelet transform

Published as Journal of Seismic Exploration, 23, no. 4, 303-312, (2014)

Time-frequency analysis of seismic data using synchrosqueezing wavelet transform

Yangkang Chen, Tingting Liu, Xiaohong Chen, Jingye Liand Erying Wang
Bureau of Economic Geology
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8924
ykchen@utexas.edu
+1-5125478899
ykchen@utexas.edu

State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Fuxue Road 18th
Beijing, China, 102200
liutingjiy@126.com

PetroChina Changqing Oilfield Company
Weiyang Road 35th
Xi'an,Shaanxi Province,China
wswey2008@126.com

Abstract:

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.

Time-frequency analysis of seismic data using synchrosqueezing wavelet transform