To address the limitations of variational mode decomposition (VMD) in seismic denoising—namely, the necessity of presetting the number of modes and the disruption of event lateral continuity caused by trace-by-trace processing, a denoising method based on frequency-binned successive variational mode decomposition and multichannel singular spectrum analysis (SVMD-MSSA) is proposed. First, 1-D SVMD is utilized to adaptively extract intrinsic mode functions trace by trace, eliminating the need to preset the mode number based on prior knowledge. Furthermore, a frequency-binning spatial alignment strategy is formulated to route the decomposed modes of each trace into unified global wavefield sections according to their physical center frequencies, thereby resolving mode misalignment and lateral discontinuity. Finally, adaptive rank-reduction filtering is implemented via frequency-domain 2-D MSSA. In tests on a complex model with crossing and curved events under 0 dB noise, the reconstructed signal-to-noise ratio (SNR) of the proposed method outperforms both conventional MSSA and VMD-MSSA, with no leakage of valid wavefields in the difference residual profile.