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

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.