Seismic Time-Frequency Analysis via STFT-Based Concentration of Frequency and Time

• Published in: IEEE geoscience and remote sensing letters Vol. 14; no. 1; pp. 127 - 131
• Main Authors: Liu, Naihao, Gao, Jinghuai, Jiang, Xiudi, Zhang, Zhuosheng, Wang, Qian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Concentration in frequency and time (ConceFT); Continuous wavelet transform; Continuous wavelet transforms; Data interpretation; Data processing; Fourier transforms; Frequency analysis; Geological structures; Geology; Information processing; Resolution; Seismic activity; Seismic analysis; Seismic data processing; Seismological data; Signal analysis; Signal processing; Signal resolution; synchrosqueezing; TF resolution; Time dependence; Time-frequency analysis; time–frequency (TF) analysis; Wavelet transforms
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2016.2630734

Time-frequency (TF) analysis can reveal local variations in seismic data processing and interpretation, where seismic signals are nonstationary and time varying. High-quality TF representation (TFR) is important for revealing the local information about these nonstationary seismic signals and describing geological structures. Due to the Heisenberg uncertainty principle, traditional TF methods (e.g., short time Fourier transform and continuous wavelet transform) cannot get the finest time resolution and the best frequency resolution at the same time, which leads to ambiguous TFR with a negative effect on the seismic signal analysis. Concentration in frequency and time is proposed to distinguish the different TF contents of time-dependent signals with time-varying amplitude and instantaneous frequencies. We introduce this promising TF analysis tool to seismic data processing. Experiments on synthetic signals and seismic data show its validity and effectiveness, which is helpful for seismic data interpretation in the future.