We investigate the feasibility of using the dynamic time warping (DTW) technique as an alternative to windowed cross correlation (WCC) for an indirect measure to quantify both the similarity and relationship between two seismic time series. We first examine the sensitivity and performance of the DTW technique by analyzing both synthetic and real seismic time series in geophysical applications. Results show that DTW efficiently retrieves useful information from seismic data and has a high sensitivity to minor variations in time series that WCC fails to detect. We further propose four potential applications of DTW to routine seismic data interpretation—earthquake detection, template matching, clustering of waveforms, and full‐waveform inversion for 1D velocity models. The earthquake detection scheme employing DTW is proposed in this study as an alternative to traditional methods. The accuracy of DTW in estimating similarity is explored for template matching and clustering of seismic traces. Finally, we discuss a realistic example of 1D Earth velocity model inversion using DTW and explore its feasibility in full‐waveform inversion.

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