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When seismic waves propagate through the earth, their high-frequency energy is absorbed by subsurface viscoelastic media. Seismic wavelet appears to be stretched out, as it is dominated by low-frequency components. In order to enhance seismic resolution, we propose here a wavelet compression method that utilizes the scale characteristic in the Fourier transform. The novelty of the scheme is a frequency-dependent scaling that extends the amplitude spectrum to both high- and low-frequency axes simultaneously. This is for the first time to make this frequency-dependent proposal, instead of a constant scaling scheme in the classic Fourier theory. It compresses seismic wavelet in the time domain and also simplifies the wavelet form effectively. This frequency-dependent scaling scheme leads to a transferring filter that is applicable to seismic field data. It results in an improvement in data resolution and in the ability of thin-layer identification, which will facilitate further seismic inversion and reservoir characterization.
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Chen et al. (2018) studied this question.
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