A Wavefield Separation Method Using Single-Station Six-Component Seismic Measurements

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ID: 314018
2026
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Abstract
Summary Six-component (6C) seismic observations offer a more comprehensive description of the wavefield than conventional three-component methods. However, current wavefield separation techniques are often constrained by their reliance on dense arrays. This study introduces a novel wavefield separation framework based on single-station 6C polarization analysis, which enables the simultaneous identification and improved separation of major seismic wave types: P-, SV-, Rayleigh, and transversely polarized horizontal waves (SH- and Love waves). Our proposed method models the observed wavefield as a weighted linear combination of theoretical wave models and optimizes the weighting coefficients via the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm, achieving reliable separation. A refined polarization-based filtering strategy incorporating likelihood estimation, degree of polarization, and energy distribution ratios enhances robustness under low signal-to-noise conditions. Furthermore, the inverse Short-Time Fourier Transform (iSTFT) is adopted to mitigate energy leakage issues associated with the inverse S-transform. Validation using synthetic and real teleseismic data suggests the method’s effectiveness and provides insight into its physical limitations. This study demonstrates a polarization-based framework for seismic phase identification and wavefield separation, which may support multi-phase joint inversion in selected seismic applications.
Reference Key
openalex_W7161551404 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hongbin Lu, Jie Shao, Qingfeng Xue, Yue Wang
Journal geophysical journal international
Year 2026
DOI
10.1093/gji/ggag185
URL
https://doi.org/10.1093/gji/ggag185
Keywords Keywords not found

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