Abstract

Traditionally, a time-frequency spectrum of a signal is obtained using the short-time Fourier transform (STFT). The time-frequency resolution in the STFT is fixed by the choice of a window length. However, seismic data, being non-stationary in nature, have varying spectral distribution in time. Therefore, we need a time-frequency decomposition that can provide optimum time-frequency resolution for varying frequencies. The time-frequency spectrum using the continuous wavelet transform achieves this objective avoiding the problem of choosing a window length and provides high frequency resolution at low frequencies and high time resolution at high frequencies. We refer to such a time-frequency from the continuous wavelet transform as TFCWT. Two field examples illustrate that the TFCWT can potentially be utilized to detect frequency shadows caused by hydrocarbons and identify thin beds below the tuning thickness.