Efficient data‐worth analysis for the selection of surveillance operation in a geologic CO2 sequestration system. Issue 5 (23rd April 2015)

• Record Type: Journal Article
• Authors: Dai, Cheng; Li, Heng; Zhang, Dongxiao; Xue, Liang
• Is Part Of: Greenhouse gases. Volume 5:Issue 5(2015)
• Page Start: 513
• Page End: 529
• Publication Date: 2015-04-23
• Subjects: CO2 sequestration -- data‐worth analysis -- probabilistic collocation‐based Kalman filter -- uncertainty reduction; Greenhouse gases -- Periodicals; Greenhouse gas mitigation -- Periodicals; 363.7387405
• DOI: 10.1002/ghg.1492
• Languages: English
• ISSNs: 2152-3878

Abstract

Abstract: In this study, we propose an approach to selecting an appropriate surveillance operation in a geologic CO2 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 CO2 leakage from abandoned wells during geologic CO2 sequestration. Our results reveal that the proposed approach of data‐worth analysis can be utilized to select an appropriate surveillance operation in a geologic CO2 system, with a small computational effort.© 2015 Society of Chemical Industry and John Wiley & Sons, Ltd