We consider a new trial of spectral decomposition carried out with the use of Paul wavelet-based Continuous Wavelet Transform (CWT) to seismic data. Despite of its complicated formulation and physically non-intuition, the Paul wavelet has its superiority over those commonly used wavelet functions due to its flexibility in controlling the time-frequency resolution. It can be even regarded as a generalized waveform or an alternative choice with respect to both Ricker and Morlet wavelets. Synthetic seismic trace analysis shows that the Paul wavelet-based CWT gives a better performance of time-frequency localization in both low and high ends of spectral band than other conventional tools in capturing the nonlinear and non-stationary features of input signals. It also offers new possibilities in producing more reliable seismic attributes in the field of reservoir characterization. We implement spectral decomposition using the proposed method upon a dataset from a deep-buried carbonate gas reservoir in the southwestern China. Combining the energy absorption analysis method, we obtain the attenuation gradient attribute section indicating gas accumulation. The field data example demonstrates the effectiveness in direct hydrocarbon detection using CWT based on the Paul wavelet.


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