ArticleScientific reports2025
STFT-based multisynchrosqueezing transform using a second-order signal model for seismic data analysis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- A self-supervised GNN-Transformer framework for weak microseismic signal identification.Scientific reports · 2026Article
- High-Precision Waveform Stacking Location Method for Microseismic Events Based on S-Transform.Sensors (Basel, Switzerland) · 2025Article
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5 authors.
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Abstract
Since time-frequency analysis (TFA) technique can reveal the local properties of seismic signals, it has been widely applied in seismic data analysis. Short-time Fourier transform (STFT) is a valuable tool for analyzing non-stationary signals in geophysics, and researchers have utilized it to solve various geophysical problems including spectral decomposition, seismic data interpolation and signal filtering. In this paper, a novel time-frequency method named short-time Fourier transform based multisynchrosqueezing transform using a second-order signal model (FMSST2) is introduced to analyze seismic data. The FMSST2 combines the multisynchrosqueezing framework using an iterative reassignment procedure and a second-order signal model to concentrate the energy in the time-frequency map. Moreover, The FMSST2 allows for signal reconstruction with a high accuracy. Two synthetic examples are employed to validate the effectiveness of the FMSST2 method, and the results show that the FMSST2 method does a good job in terms of energy-concentration and noise robustness compared to some classic TFA methods such as the STFT, STFT-Based synchrosqueezing transform (FSST) and multisynchrosqueezing transform (MSST). Applications on field data further demonstrate the potential of the FMSST2 method in characterizing hydrocarbon reservoir, making it a promising time-frequency resolution enhancement tool in seismic data analysis.
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