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Multicomponent Seismic Data Vector Reconstruction Via Quaternionic Matrix Factorization

Third International Meeting for Applied Geoscience &amp Energy Expanded Abstracts(2023)

China University of Geosciences (Beijing) | CNOOC Research Institute Ltd.

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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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要点】:本文提出了一种新的多分量地震数据向量重建方法——四元数矩阵分解(QMF),可以同时重建所有分量,有效保持波场的向量结构及各分量间的极化特性和相对幅度关系。

方法】:通过四元数矩阵分解方法,将多分量数据作为一个整体进行重建,而不是传统方法中的独立分量重建。

实验】:使用合成3D-3C数据集和实际3D-3C数据集进行实验,结果表明QMF方法在恢复缺失道时能更好地保持波场的向量结构。