Progress on empirical mode decomposition-based techniques and its impacts on seismic attribute analysis

Abstract

Spectral decomposition plays a significant role in seismic data processing and is commonly used to generate seismic attributes that are useful for interpretation and reservoir characterization. Among several techniques that are applied to this finality, complete ensemble empirical mode decomposition (CEEMD) is an alternative procedure that has proven higher spectral-spatial resolution than the short-time Fourier transform or wavelet transform, thus offering potential in highlighting subtle geologic structures that might otherwise be overlooked. We have analyzed a recent development in CEEMD, which we call improved CEEMD (ICEEMD), and its impacts on seismic attribute analysis commonly used in the empirical mode decomposition framework. By replacing the estimation of modes by the estimation of local means, the mode mixing and the presence of noise in the modes are reduced. Application on a synthetic and real data reveals that ICEEMD improves the signal decomposition and the energy concentration in the time-frequency domain, producing a better understanding of the analyzed signal and, consequently, of the geology under investigation.