Spectral Decomposition of Seismic Data via Wigner-ville Distribution and Chirplet Transform

Spectral decomposition has proven to be a very effective tool for seismic interpretation. Wavelet transform has been used as a new way to do spectral decomposition, but the basic element used to do the transform is stationary. The frequency does not change with time. This is in contrast to the actual seismic data. I introduce chirplet transform and combine it with Wigner-Ville distribution to do spectral decomposition. In a chirplet, the frequency changes with time. With this method, many high resolution results can be achieved, and additional useful information is obtained.