Seismic Denoising Based on Time-Varying Filtering and Empirical Mode Decomposition in the fx Domain

Abstract

Ground roll is a type of coherent noise with low velocity, low frequency and high energy, which negatively affects the quality of the seismic data. The contamination of the ground roll is a persistent problem in the seismic processing field. For this reason, we considered the predictability of useful signals in the fx domain, introduced the time-varying filtering based on the empirical mode decomposition (TVFEMD) into the fx domain, and therefore proposed a novel algorithm (Ada-fx-TVFEMD). Similar to the Variational Mode Decomposition (VMD), the TVFEMD algorithm consists in adaptive decomposition of multi-component signals. The TVFEMD algorithm is more suitable for nonstationary signals because of its time-varying characteristic. The proposed Ada-fx-TVFEMD algorithm performs decomposition of each frequency slice and reconstruction of partial Intrinsic Mode Functions (IMFs). Moreover, it allows to accurately select the IMFs that contain ground roll based on automatic ground roll identification. A presented synthetic example illustrates the superiority of the Ada-fx-TVFEMD algorithm in ground roll attenuation. Applying the proposed method on field data further demonstrates its potential in industrial applications, compared with frequency-wavenumber (FK) filtering and fx-VMD.