Time-Lapse Full-Waveform Inversion Using Cross-Correlation-Based Dynamic Time Warping

Abstract

Offshore carbon capture, utilization, and storage (OCCUS) is regarded as a crucial technology for mitigating greenhouse gas emissions. Quantitative monitoring maps of sealed carbon dioxide are necessary in a comprehensive OCCUS project. A potential high-resolution method for the aforementioned purpose lies in the full-waveform inversion (FWI) of time-lapse seismic data. However, practical applications of FWI are severely restricted by the well-known cycle-skipping problem. A new time-lapse FWI method using cross-correlation-based dynamic time warping (CDTW) is proposed to detect changes in the subsurface property due to carbon dioxide (CO₂) injection and address the aforementioned issue. The proposed method, namely CDTW, which combines the advantages of cross-correlation and dynamic time warping, is employed in the automatic estimation of the discrepancy between the seismic signals simulated using the baseline/initial model and those acquired. The proposed FWI method can then back-project the estimated discrepancy to the subsurface space domain, thereby facilitating retrieval of the induced subsurface property change by taking the difference between the inverted baseline and monitor models. Numerical results on pairs of signals prove that CDTW can obtain reliable shifts under amplitude modulation and noise contamination conditions. The performance of CDTW substantially outperforms that of the conventional dynamic time warping method. The proposed time-lapse full-waveform inversion (FWI) method is applied to the Frio-2 CO₂ storage model. The baseline and monitor models are inverted from the corresponding time-lapse seismic data. The changes in velocity due to CO₂ injection are reconstructed by the difference between the baseline and the monitor models.

Keywords

Full-waveform inversion / Dynamic time warping / Ocean carbon dioxide storage monitoring / Discrepancy estimation / Model test

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