Dynamic Time Warping-Based Seislet Transform and Its Application in Seismic Discontinuity Characterization

The characterization of seismic discontinuities is crucial for interpreting the geological structures they represent, such as faults and channels, which are fundamental to reservoir characterization. Transform-based methods, such as the Seislet transform, leverage sparse representations to highlight such features. However, the Seislet transform relies on local slope estimation for trace prediction within its lifting scheme framework. This approach can be suboptimal for complex seismic events involving interfering events or rapid dip changes where a single slope assumption fails. This limitation can lead to energy leakage into detail coefficients, potentially obscuring subtle discontinuities or creating artifacts. To address this, we propose the Dynamic Time Warping Seislet (DTW-Seislet) transform, a novel modification that replaces the slope-based prediction operator with one based on Dynamic Time Warping (DTW). DTW finds an optimal non-linear alignment between adjacent traces, inherently adapting to complex waveform variations without assuming a single slope trend. We further enhance the prediction accuracy by incorporating a resampling strategy into the DTW process, allowing for sub-sample alignment precision. We demonstrate how analyzing the detail coefficients of the DTW-Seislet transform effectively characterizes seismic discontinuities. Validation using synthetic data and 3-D field data demonstrates that the proposed DTW-Seislet approach yields discontinuity maps with improved clarity and accuracy, better delineation of both major and subtle features, and potentially reduced noise artifacts compared to the Seislet transform and conventional C3 coherence attributes. The DTW-Seislet transform offers a promising tool for detailed seismic structural interpretation.