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.
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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
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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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