Multicomponent Seismic Data Vector Reconstruction Via Quaternionic Matrix Factorization
Third International Meeting for Applied Geoscience & Energy Expanded Abstracts(2023)
China University of Geosciences (Beijing) | CNOOC Research Institute Ltd.
Abstract
For multicomponent seismic data reconstruction, the conventional scalar reconstruction methods treat multicomponent data as independent components and recover each component separately. These component-wise approaches may destroy the polarization characteristics and relative amplitude relationship between different components. In this paper, we propose a vector reconstruction method named quaternion matrix factorization (QMF) to recover all components simultaneously, which is also the vectorization development of the traditional scalar matrix factorization (MF) method used for component-wise reconstruction. We compare the proposed QMF method with the traditional MF method through experiments with a synthetic 3D-3C dataset and a field 3D-3C volume. Both experiments indicate the proposed method can better maintain the vector structure of the wavefield during the recovery of missing traces.
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