New multicomponent filters for geophysical data processing

As multicomponent processing is a challenge in many fields such as geophysics, seismology, remote sensing, or electromagnetics, a method that could be used to filter multispectral, multicomponent, or multidimensional data is proposed. In this paper, the method, called multicomponent wideband spectral-matrix filtering (MC-WBSMF), is applied on geophysical data to separate interfering wavefields. The technique is based on the decomposition of a special multicomponent spectral matrix and could extract a given wavefield from a multicomponent dataset. MC-WBSMF is compared to two classical single-component seismic methods (the 2D-Fourier transform or f-k filter and the Radon transform) and to a fully multicomponent method based on singular value decomposition. Finally, MC-WBSMF is tested on a real geophysical subsurface dataset in order to remove surface waves and to enhance reflected waves