Spectral decomposition is an innovative way of utilizing seismic data and the Discrete Fourier Transform (DFT) for imaging and mapping bed thickness and geological discontinuities over large 3D seismic surveys.

Seismic data is rarely dominated by simple blocky and resolved reflections. Also, it is rare that true geological boundaries fall along fully resolved seismic peaks and troughs.  By transforming seismic data into the frequency domain with the Discrete Fourier Transform, short-window amplitude and phase spectra localize thin bed reflections and define bed thickness variability within complex rock strata.

Fourier analysis is based on the assumption that the frequency content of the seismic trace is not changing with time. However, we know that the spectral content of the trace varies with time through the earth; higher frequencies getting preferentially lost. It is desirable to have a frequency spectrum that adjusts its resolution depending on the frequency content of the signal. The Continuous Wavelet Transform method directly extracts the frequency content at each time location, eliminating windowing problems and results in high-resolution spectral analysis.

Besides the traditional Fourier transform, TGS offers the CWT (Continuous Wavelet Transform), and Matching Pursuit Decomposition (MPD) for transformation of data to frequency domain. The latter technique offers more accurate analysis.