Time-lapse rock physics CO₂ monitoring with FWI

Qi Hu, Kristopher A. Innanen

Carbon capture and storage is a viable greenhouse gas mitigation technology. Monitoring of the injected CO₂ 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 parameterized 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. The results with realistic initial models and noisy data demonstrate the robustness of our approach for reconstructing baseline models. For the inversion of monitor data, we show that both the errors in baseline model estimates and the random noise could compromise the reconstructed CO₂ saturation model. We propose to improve the result using a regularization technique that consists of two penalty terms: the Tikhonov term to ensure smoothness and the prior model term to help the convergence towards expected models.