IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v262y2025ics0951832025004545.html

A DOOBN based approach for dynamic failure assessment of CO2 flooding injection string system

Author

Listed:
  • Li, Xinhong
  • Yu, Kai
  • Li, Sihan
  • Liu, Peihua
  • Chen, Guoming

Abstract

The failure of CO2 flooding injection string system including tubing, casing and packer, can lead to the malfunctions of oil well. This paper develops a structural model for dynamic failure assessment of CO2 flooding injection string system, which is implemented with dynamic object-oriented Bayesian network (DOOBN) and hidden Markov model (HMM). A DOOBN model is developed to present the failure scenario of CO2 flooding injection string system. It is quantified by HMM to estimate the state transition probabilities among a set of risk factors. Based on the developed model, dynamic failure probabilities of CO2 flooding injection string system are estimated throughout the service life, and the critical causes leading to string system failure are extracted to develop the risk mitigation strategies. A case study is implemented to illustrate the present study, and the outcomes of this study can support risk management of CO2 flooding injection string system.

Suggested Citation

  • Li, Xinhong & Yu, Kai & Li, Sihan & Liu, Peihua & Chen, Guoming, 2025. "A DOOBN based approach for dynamic failure assessment of CO2 flooding injection string system," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025004545
    DOI: 10.1016/j.ress.2025.111253
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832025004545
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2025.111253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Dao, Uyen & Sajid, Zaman & Khan, Faisal & Zhang, Yahui & Tran, Trung, 2023. "Modeling and analysis of internal corrosion induced failure of oil and gas pipelines," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Lee, Dooyoul & Kwon, Kybeom, 2023. "Dynamic Bayesian network model for comprehensive risk analysis of fatigue-critical structural details," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    3. Chang, Yuanjiang & Wu, Xiangfei & Zhang, Changshuai & Chen, Guoming & Liu, Xiuquan & Li, Jiayi & Cai, Baoping & Xu, Liangbin, 2019. "Dynamic Bayesian networks based approach for risk analysis of subsea wellhead fatigue failure during service life," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 454-462.
    4. Yanbin Qin & Yinping Cao & Yihua Dou & Wenwen Lin & Jiahao Cao & Luyao Wang, 2022. "Strength Failure of CO 2 Injection Tubular Strings Considering CO 2 Phase Transition," Energies, MDPI, vol. 15(23), pages 1-13, November.
    5. Shao, Xiaoyan & Cai, Baoping & Liu, Yonghong & Zhang, Junyan & Sui, Zhongfei & Feng, Qiang, 2023. "Remaining useful life prediction via a hybrid DBN-KF-based method: A case of subsea Christmas tree valves," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    6. Chen, Zhanfeng & Li, Xuyao & Wang, Wen & Li, Yan & Shi, Lei & Li, Yuxing, 2023. "Residual strength prediction of corroded pipelines using multilayer perceptron and modified feedforward neural network," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    7. Yuan, Shuaiqi & Reniers, Genserik & Yang, Ming, 2024. "Integrated management of safety and security barriers in chemical plants to cope with emerging cyber-physical attack risks under uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    8. Zhang, Tieyao & Shuai, Jian & Shuai, Yi & Hua, Luoyi & Xu, Kui & Xie, Dong & Mei, Yuan, 2023. "Efficient prediction method of triple failure pressure for corroded pipelines under complex loads based on a backpropagation neural network," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    9. Pan, Xing & Du, Hengte & Yu, Haofan, 2024. "A method for safety analysis of human-machine systems based on dynamic Bayesian simulation," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tao, Haohan & Jia, Peng & Wang, Xiangyu & Wang, Liquan, 2024. "Reliability analysis of subsea control module based on dynamic Bayesian network and digital twin," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Miao, Xingyuan & Ma, Yinghan & Sun, Xianglong & Zhao, Hong, 2025. "Residual strength prediction of hydrogen-blended natural gas pipelines based on incremental knowledge distillation," Energy, Elsevier, vol. 341(C).
    3. Xie, Mingjiang & Wang, Yifei & Zhao, Jianli & Pei, Xianjun & Zhang, Tairui, 2024. "Prediction of pipeline fatigue crack propagation under rockfall impact based on multilayer perceptron," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    4. Li, Shulin & Yang, Yan & Huang, Bensheng & Jia, Yanlin, 2025. "Residual strength hybrid prediction of hydrogen-blended natural gas pipelines based on FEM-FC-BP model," Energy, Elsevier, vol. 321(C).
    5. Zerouali, Bilal & Sahraoui, Yacine & Nahal, Mourad & Chateauneuf, Alaa, 2024. "Reliability-based maintenance optimization of long-distance oil and gas transmission pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    6. Xiao, Rui & Sushama, Laxmi & Meguid, Mohamed A. & Zayed, Tarek, 2026. "Evaluating the influence of climate change on the deterioration and bearing capacity of corroded gas pipelines," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).
    7. Miao, Xingyuan & Zhao, Hong, 2023. "Novel method for residual strength prediction of defective pipelines based on HTLBO-DELM model," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    8. Peng, Xiangzhen & Zheng, Chengliang & Wang, Yidi & Cui, Xiaohui & Shen, Zhidong, 2025. "Double layer blockchain-assisted trusted data flow model for industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    9. Zhiqiang Liu & Wenbo Zhu & Hongzhou Zhang & Shengjin Wang & Lu Fang & Weijun Hong & Hua Shao & Guopeng Wang, 2020. "Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network," International Journal of Distributed Sensor Networks, , vol. 16(3), pages 15501477209, March.
    10. Jing, Qi & Yu, Lin & Lan, Fengyi & Li, Yuntao, 2024. "Quantitative assessment rules and models for dynamic disaster risk in high-density gas gathering stations: Practical application in a largest CBM gathering station," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    11. Xu, Yingchun & Yao, Wen & Zheng, Xiaohu & Gong, Zhiqiang & Yan, Lei & Xu, Na, 2025. "A generic quality and accuracy driven uncertainty quantification framework for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    12. Shao, Xiaoyan & Cai, Baoping & Gao, Lei & Zhang, Yanping & Yang, Chao & Gao, Chuntan, 2024. "Data-model-linked remaining useful life prediction method with small sample data: A case of subsea valve," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    13. Adumene, Sidum & Khan, Faisal & Adedigba, Sunday & Zendehboudi, Sohrab & Shiri, Hodjat, 2021. "Dynamic risk analysis of marine and offshore systems suffering microbial induced stochastic degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    14. Zhou, Jun & Zhu, Jiaxing & Liang, Guangchuan & Ma, Junjie & He, Jiayi & Du, Penghua & Ye, Zhanpeng, 2024. "Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    15. Yao, Zhenghong & Hao, Jin & Li, Changyou & Jiang, Zhiyuan & Zhao, Jinsong, 2025. "Reliability-based design optimization of fluid-conveying pipeline structure subjected to in-service loadings," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    16. Wang, Zheng & Wang, Jinjiang & Wei, Zhenqiang & Ye, Wencong & Zhang, Laibin, 2026. "Safety integrity level assessment for safety instrumented system in oil and gas station with cyber threat," Reliability Engineering and System Safety, Elsevier, vol. 265(PB).
    17. Yang, Ruochen & Schell, Colin A. & Rayasam, Dhruva & Groth, Katrina M., 2025. "Hydrogen impact on transmission pipeline risk: Probabilistic analysis of failure causes," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
    18. Dongshi Sun & Di Guo & Danlan Xie, 2023. "Using Multicriteria Decision Making to Evaluate the Risk of Hydrogen Energy Storage and Transportation in Cities," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    19. Li, Xinhong & Liu, Yabei & Zhang, Renren & Zhang, Nan, 2025. "Probabilistic failure assessment of oil and gas gathering pipelines using machine learning approach," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    20. Ye, Yumei & Yang, Qiang & Zhang, Jingang & Meng, Songhe & Wang, Jun, 2023. "A dynamic data driven reliability prognosis method for structural digital twin and experimental validation," Reliability Engineering and System Safety, Elsevier, vol. 240(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025004545. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.