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Corrosion risk assessment using adaptive bow-tie (ABT) analysis

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  • Taleb-Berrouane, Mohammed
  • Khan, Faisal
  • Hawboldt, Kelly

Abstract

Corrosion is a major threat to safety and asset integrity in oil and gas production and processing facilities. This paper proposes a simple, yet practical model for quantitative corrosion risk assessment from safety and economic perspectives. This includes an Adaptive Bow-Tie (ABT) model for the corrosion risk with a specific focus on microbiologically influenced corrosion, along with corrosion economic risk profile. The ABT model is logically tested using corrosion science and statistically verified using a pipeline corrosion database, including cases of corrosion-induced failures. The ABT model also provides opportunities to run root-cause contribution (RCC) analysis and to estimate the probability of corrosion, corrosion-induced failures, and highly probable sequences leading to failure. The model application is demonstrated using a crude oil transportation pipeline system. The study identifies and quantifies parameters that helps to prioritize the actions needed to prevent and control corrosion and avoid failures. The proposed model can serve as an important mechanism to identify, assess, and manage corrosion threat to an asset.

Suggested Citation

  • Taleb-Berrouane, Mohammed & Khan, Faisal & Hawboldt, Kelly, 2021. "Corrosion risk assessment using adaptive bow-tie (ABT) analysis," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:reensy:v:214:y:2021:i:c:s0951832021002659
    DOI: 10.1016/j.ress.2021.107731
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    References listed on IDEAS

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    Cited by:

    1. Amaya-Gómez, Rafael & Schoefs, Franck & Sánchez-Silva, Mauricio & Muñoz, Felipe & Bastidas-Arteaga, Emilio, 2022. "Matching of corroded defects in onshore pipelines based on In-Line Inspections and Voronoi partitions," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    2. Chen, Yinuo & Xie, Shuyi & Tian, Zhigang, 2022. "Risk assessment of buried gas pipelines based on improved cloud-variable weight theory," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Dao, Uyen & Sajid, Zaman & Khan, Faisal & Zhang, Yahui, 2023. "Dynamic Bayesian network model to study under-deposit corrosion," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Qing Deng & Kuo Wang & Jiahao Wu & Feng Yu & Huiling Jiang & Lida Huang, 2023. "An integrated model for evaluating the leakage risk of urban gas pipe: a case study based on Chinese real accident data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 319-340, March.
    5. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Na, Kyumin & Yoon, Heonjun & Kim, Jaedong & Kim, Sungjong & Youn, Byeng D., 2023. "PERL: Probabilistic energy-ratio-based localization for boiler tube leaks using descriptors of acoustic emission signals," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Ramadhani, Adhitya & Khan, Faisal & Colbourne, Bruce & Ahmed, Salim & Taleb-Berrouane, Mohammed, 2022. "Resilience assessment of offshore structures subjected to ice load considering complex dependencies," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Gholamizadeh, Kamran & Zarei, Esmaeil & Yazdi, Mohammad & Ramezanifar, Ehsan & Aliabadi, Mostafa Mirzaei, 2024. "A hybrid model for dynamic analysis of domino effects in chemical process industries," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Ruiz-Tagle, Andres & Lewis, Austin D. & Schell, Colin A. & Lever, Ernest & Groth, Katrina M., 2022. "BaNTERA: A Bayesian Network for Third-Party Excavation Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    10. Yazdi, Mohammad & Khan, Faisal & Abbassi, Rouzbeh & Quddus, Noor & Castaneda-Lopez, Homero, 2022. "A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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