Channel detection using instantaneous spectral attributes in one of the SW Iran oil fields

Instantaneous spectral attributes such as centre frequency and bandwidth are extracted from the time-frequency maps (spectrogram). These attributes are useful tools in interpretation of stratigraphic phenomena and detection of some geological events which normally cannot be observed in the conventional seismic sections, as river-buried channels. Channels filled with porous rocks and surrounded in a non-porous matrix play important role in stratigraphic explorations. Spectrograms are derived from spectral decomposition methods such as Short-Time Fourier Transforms (STFT), S-transform and Matching Pursuit Decomposition (MPD). STFT requires a predefined time window, which causes reduction of the time-frequency resolution. S-transform has better time-frequency resolution than STFT due to use of a varying-frequency window. Since MPD uses an iteration algorithm, so it is expected that instantaneous spectral attributes obtained from MPD have better time-frequency resolution than those from the other methods, though the iteration algorithm increases the time of computation in MPD. In this paper, we applied instantaneous centre frequency attribute from these methods to detect the channels in one of the SW Iran oil fields and then the results were compared with each other.