Efficient data‐worth analysis for the selection of surveillance operation in a geologic CO 2 sequestration system

In this study, we propose an approach to selecting an appropriate surveillance operation in a geologic CO 2 sequestration, through efficient data‐worth analysis with the probabilistic collocation‐based Kalman Filter (PCKF). A surrogate model with polynomial chaos expansion is constructed by performing a small number of flow simulations, based on which history‐matching is implemented with the observations from the surveillance operations. The proposed approach is demonstrated numerically for selecting a surveillance operation and assessing the reduction of uncertainties in predicting CO 2 leakage from abandoned wells during geologic CO 2 sequestration. Our results reveal that the proposed approach of data‐worth analysis can be utilized to select an appropriate surveillance operation in a geologic CO 2 system, with a small computational effort.© 2015 Society of Chemical Industry and John Wiley & Sons, Ltd

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