Reliability Analysis of Carbon Capture and Storage Systems

Bayan Hamdan, Pingfeng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


While offshore salt caverns, as part of the carbon capture and storage (CCS) systems, could offer significant advantages in storage carbon dioxide, they are still not widely implemented, partially due the challenges in maintaining the safe operation of such systems with a long-projected storage time. The presented study provided a Fault Tree (FT) analysis for the causal relationships of storage system failures with respect to the root causes, and further the potential integration of the FT with the dynamic Bayesian network (DBN) in order to monitor offshore salt caverns in the long-term operations. The presented study can incorporate both physics-of-failure models and sensory data to update the failure probabilities of the components in the offshore salt cavern storage system. The fault tree considers unintentional flow as the main failure mode and divides the system into three subsystems: the wellhead, the well and the cavern itself. Then, each individual subsystem is studied based on the components in the subsystem and the NORSOK standards for safe well design. The fault tree presented in this study also outlines the relationship between the failure modes and the effect they have on the system failure. Th fault tree analysis tool can then be converted into a DBN to provide a long-term monitoring framework for offshore CCS systems with limited observability, where real-time data can be utilized in order to update the probabilities of failure of components over time.

Original languageEnglish (US)
Title of host publication68th Annual Reliability and Maintainability Symposium, RAMS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665424325
StatePublished - 2022
Event68th Annual Reliability and Maintainability Symposium, RAMS 2022 - Tucson, United States
Duration: Jan 24 2022Jan 27 2022

Publication series

NameProceedings - Annual Reliability and Maintainability Symposium
ISSN (Print)0149-144X


Conference68th Annual Reliability and Maintainability Symposium, RAMS 2022
Country/TerritoryUnited States


  • Bayesian Networks
  • Carbon Capture
  • Fault Tree Analysis
  • Multi-fidelity

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • General Mathematics
  • Computer Science Applications


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