We introduce a digital waveletlike transform, which is tailored specifically for representing seismic data. The transform provides a multiscale orthogonal basis with basis functions aligned along seismic events in the input data. It is defined with the help of the wavelet-lifting scheme combined with local plane-wave destruction. In the 1D case, the seislet transform is designed to follow locally sinusoidal components. In the 2D case, it is designed to follow local plane-wave components with smoothly variable slopes. If more than one component is present, the transform turns into an overcomplete representation or a tight frame. In these terms, the classic digital wavelet transform is simply a seislet transform for a zero frequency (in one dimension) or zero slope (in two dimensions). The main objective of the new transform is an effective seismic-data compression for designing efficient data-analysis algorithms. Traditional signal-processing tasks such as noise attenuation and trace interpolation become simply defined in the seislet domain. When applied in the offset direction on common-midpoint or common-image-point gathers, the seislet transform finds an additional application in optimal stacking of seismic records.
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Fomel et al. (2010) studied this question.
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