<p>To address the challenges of inadequate resolution and mode aliasing in the time–frequency analysis of complex non-stationary seismic signals, this paper proposes a novel method termed the Variational mode Synchrosqueezing Generalized S-Transform (VSGST). The core contributions of this work are threefold: first, the establishment of a deep coupling mechanism between Variational Mode Decomposition (VMD) and the Synchrosqueezing Generalized S-Transform (SGST) within a unified “decomposition–analysis–fusion” iterative framework, which fundamentally differs from simple sequential combinations; second, the introduction of an adaptive modal energy-weighted fusion strategy that synthesizes component time–frequency representations based on physical significance rather than simple summation; third, the development of parameter optimization guidelines specifically tailored for the characteristics of seismic data. In contrast to recent advanced methods such as high-order synchrosqueezing transforms—which often incur significantly higher computational cost for marginal gain—or deep learning-based time–frequency analysis—which suffers from poor physical interpretability and requires extensive training data—the proposed VSGST achieves an optimal balance, offering superior resolution and noise robustness while preserving computational efficiency and full physical transparency. The proposed approach first adaptively decomposes a multi-component signal into intrinsic mode functions (IMFs) via VMD to mitigate mode mixing. Each IMF is then processed using SGST to sharpen its time–frequency energy distribution. Finally, a high-resolution time–frequency representation is constructed by fusing the results from all components using the adaptive weighting strategy. Simulation results demonstrate that VSGST significantly outperforms traditional methods such as the Synchrosqueezing Short-Time Fourier Transform (SSTFT) and the Synchrosqueezing S-Transform (SST) in both resolution and noise robustness. Applications to field seismic data confirm its ability to produce time–frequency profiles with enhanced lateral continuity and improved correlation with well-log impedance, underscoring its practical value for high-resolution seismic interpretation..</p>