Comparison of Spectral Decomposition Algorithms for Channel Detection in 3D Seismic Data

The scope of the work was to chose the best spectral decomposition (SD) method for the channels detection in the Miocene strata of the Carpathian Fordeep, SE Poland in the 3D seismic data volume. For analysis three spectral decomposition algorithm were applied: based on Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT) and based on complete ensemble empirical mode decomposition (CEEMD). Because CWT results were considered rather poor the comparison was limited to FFT and CEEMD. Additionally the results of instantaneous frequency were compared with the results of peak frequency computed from CEEMD. Both algorithms of SD enabled to interpret channels, but the results are slightly different, i.e. FFT show more coarse, linear structures, that are straightforward for channel interpretation whereas CEEMD show more details and depicts where tuning effect occurs. So as to IF and PF we value more instantaneous frequency due to much better results: it shows nicely linear structures and is less noisy than PF. Moreover the computation of IF is much faster (‘on the fly’) than PF (couple of hours for the whole volume).