Spectral decomposition is a powerful tool for analysis of seismic data. The spectral decomposition of seismic data is a process that transforms seismic amplitudes as a function of space and time to spectral amplitudes as a function of frequency, space and time. So it can be defined as a continuous time-frequency analysis that provides a frequency spectrum for each time sample of a seismic trace. In this way, it decomposes the seismic trace into its constituent frequencies, allowing individual target reflection events to be analyzed spectrally in every single frequency. There are several time-frequency spectral decomposition methods. In this paper, we used the S-transform method, which is a type of time-frequency analysis transform composed of some concepts of short time Fourier transform (STFT) and wavelet transform. A scalable Gaussian window which provides time-frequency resolution is used to localize the spectrum of time-frequency series. Since hydrocarbon is detectable in low frequency, we have tried to study performance of S-transform in time-frequency analysis of seismic sections related to one of the reservoirs in SW-Iran to detect gas bearing zones and low frequency shadows. In our study area, we applied successfully this method as hydrocarbon attribute in 10 and 15 Hz single frequency sections.

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