Uncertainty Analysis of the Storage Efficiency Factor for CO 2 Saline Resource Estimation

Zan Wang (), Shengwen Qi and Bowen Zheng ()
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Zan Wang: Institute of Geology and Geophysics, Chinese Academy of Sciences, No. 19, Beitucheng Western Road, Chaoyang District, Beijing 100029, China
Shengwen Qi: Institute of Geology and Geophysics, Chinese Academy of Sciences, No. 19, Beitucheng Western Road, Chaoyang District, Beijing 100029, China
Bowen Zheng: Institute of Geology and Geophysics, Chinese Academy of Sciences, No. 19, Beitucheng Western Road, Chaoyang District, Beijing 100029, China

Energies, 2024, vol. 17, issue 6, 1-17

Abstract: Carbon capture and sequestration (CCS) is a promising technology for reducing CO 2 emissions to the atmosphere. It is critical to estimate the CO 2 storage resource before deploying the CCS projects. The CO 2 storage resource is limited by both the formation pore volume available to store CO 2 and the maximum allowable pressure buildup for safe injection. In this study, we present a workflow for estimating the volume- and pressure-limited storage efficiency factor and quantifying the uncertainty in the estimates. Thirteen independent uncertain physical parameters characterizing the storage formation are considered in the Monte Carlo uncertainty analysis. The uncertain inputs contributing most to the overall uncertainty in the storage efficiency factor are identified. The estimation and uncertainty quantification workflow is demonstrated using a publicly available dataset developed for a prospective CO 2 storage site. The statistical distributions of the storage efficiency factor for the primary storage formation and the secondary storage formation located in deeper depth are derived using the proposed workflow. The effective-to-total porosity contributes most to the overall uncertainty in the estimated storage efficiency factor at the study site, followed by the maximum allowable pressure buildup, the net-to-gross thickness ratio, the irreducible water saturation, and the permeability. While the significant uncertain input variables identified are tailored to the characteristics of the study site, the statistical methodology proposed can be generalized and applied to other storage sites. The influential uncertain inputs identified from the workflow can provide guidance on future data collection needs for uncertainty reduction, improving the confidence in the CO 2 saline storage resource estimates.

Keywords: carbon sequestration; saline formation; storage resource; storage efficiency factor; Monte Carlo uncertainty analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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