Seismic Spectral Decomposition Method and Application based on 3D Continuous Wavelet Transform

Seismic spectral decomposition plays a vital role in seismic reservoir prediction and interpretation to reveal the time-varying frequency characteristics of seismic data. Usually, we use spectral decomposition methods based on 1D CWT. This paper introduces a spectral decomposition method based on 3D CWT and presents an efficient implementation of the for spectral decomposition. By leveraging spatial correlations in 3D seismic data, the proposed method overcomes the limitations of traditional 1D CWT, enabling extracting spectral variations across spatial dimensions rather than confining to the temporal dimension. Furthermore, the implementation of the 3D CWT in the wave-number domain significantly reduces computational complexity, thereby facilitating practical applications. To demonstrate the effectiveness of our method, it is applied to the real seismic data. Moreover, we show the spectral decomposition results through slices at different frequencies. By comparing with the 1D CWT, we find that the 3D CWT can accurately characterize detailed geological structures.