Wideband spectral matrix filtering for multicomponent sensors array

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• 作者：Caroline Paulus ; Jé ; rô ; me Mars and Patrick Gounon
• 关键词：Multicomponent sensors array ; Subspace method ; Wavefield filter ; Polarized wave separation ; Wideband spectral matrix ; Eigenvalue decomposition (EVD)
• 刊名：Signal Processing
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：85
• 期：9
• 页码：1723-1743
• 全文大小：2738 K

文摘

As multicomponent (3C or 4C) seismic acquisitions are now commonly used, specific processings for multicomponent data sets are required. The aim of this paper is to present a new wavefield filter for multicomponent seismic data. The proposed method is derived from a recent technique used for single component data, which takes into account the wideband characteristics of the signal. The multicomponent extended method incorporates the polarization information and processes the various components in a global way instead of treating them independently. The proposed method is based on the computation of a global spectral matrix which gathers all the frequential and component interactions. We prove that the eigenvalue decomposition of a reduced matrix issued from this global matrix enables an efficient separation in two complementary spaces: one contains the signal and the other, the noise. The results obtained on synthetic and real data are presented and compared with others methods in order to assess the performances of our algorithm.