Feasibility of seismic time-lapse monitoring of CO2 with rock physics parametrized full waveform inversion

Carbon capture and storage is an important technology for greenhouse gas mitigation. Monitoring of CO2 storage should, in addition to locating the plume, provide quantitative information on CO2 saturation. We propose a full waveform inversion (FWI) algorithm for the prediction of the spatial distribution of CO2 saturation from time-lapse seismic data. The methodology is based on the application of a rock-physics parametrized FWI scheme that allows for direct updating of reservoir properties. We derive porosity and lithology parameters from baseline data and use them as input to predict CO2 saturation from monitor data. The method is tested on synthetic time-lapse data generated for the Johansen formation model. Practical issues associated with field data applications, such as acquisition limitations, construction of the initial model, noise and uncertainty in the rock physics model, are taken into account in the simulation. The results demonstrate the robustness of our approach for reconstructing baseline and monitor models. We also illustrate the potential of the approach as compared to conventional two-step inversion algorithms, in which an elastic FWI prediction of velocities and density is followed by rock physics inversion.