Carbon capture and storage (CCS) is forecast to play a significant role towards CO2 emissions reduction. Cost-effective and simplified monitoring will be essential for rapid adoption and growth of CCS. Seismic imaging methods are regularly utilized to monitor low-velocity anomalies generated by injection of CO2 in the subsurface. In this study we generate active and passive synthetic seismic datasets at different stages of CO2 injection in the subsurface based on geologically constrained subsurface models of the Pelican storage site in the Gippsland Basin, Australia. We apply full waveform inversion (FWI) and wave-equation dispersion (WD) inversion to seafloor deployed distributed acoustic sensing (DAS) data to reconstruct the low-velocity anomalies. We model both strain (DAS) and displacement datasets for the active data component of the study and show that they
result in similar reconstruction of the CO2 anomaly. FWI based time-lapse imaging of active data yields the most accurate results. However, this approach is expensive and also suffers from complex issues because of the near-onshore location of the storage site. Alternatively inverting passive data results in only minor differences, but can still effectively monitor changes in the subsurface, and assist in monitoring the CO2 plume at the reservoir depth. Furthermore, we demonstrate the capability of WD for inverting Scholte-waves derived from ambient noise for shallow detection of CO2 in the unlikely event of a leakage. Therefore, we propose a mixed mode monitoring strategy where passive data is utilised for routine monitoring while active surveys are deployed only when further investigation is required.