Risk-Based Inspection for Offshore Structures
Keywords:
Risk-Based Inspection, Offshore Structures, Structural Integrity, Reliability, SafetyAbstract
Offshore structures operate in a demanding marine environment where waves, wind, currents, corrosion, fatigue, and repeated loading can gradually affect structural condition. Regular inspection is necessary to identify damage and maintain the safety and reliability of offshore facilities. However, inspecting every component with the same frequency may require considerable time, cost, and resources. Risk-Based Inspection (RBI) provides an approach for determining inspection priorities by considering the likelihood of failure and the consequences that may result from it. This article discusses the application of RBI in offshore structures and its role in supporting structural integrity and safety. A literature review method was used by examining studies related to offshore structural inspection, failure mechanisms, risk assessment, and maintenance planning. The reviewed studies indicate that RBI can help identify components with higher levels of risk and allocate inspection resources according to their condition and potential consequences. The approach can also support maintenance decisions and reduce the possibility of unexpected structural failure. Effective RBI implementation requires reliable inspection data, appropriate risk assessment, continuous monitoring, and regular reassessment of structural conditions.
References
[1] T. Dai, W. Jiang, and Z. Jia, “A review on environmental load identification and structural health monitoring of offshore structures,” Adv. Struct. Eng., vol. 0, no. 0, p. 13694332261420440, 2026, doi: 10.1177/13694332261420440.
[2] E. G. Veruz, R. Favarão da Silva, G. F. Martha de Souza, and F. A. Rodrigues, “Risk-based inspection framework for outer hull of floating units based on the integration of inspection programs,” Ocean Eng., vol. 350, p. 124249, 2026, doi: https://doi.org/10.1016/j.oceaneng.2026.124249.
[3] B. Asgarian, M. J. B. Bilandi, P. Rezadoost, and H. Gholami, “Integrated system-level framework for inspection and cost-effective maintenance of jacket type offshore platforms using dynamic Bayesian networks,” Appl. Ocean Res., vol. 168, p. 104979, 2026, doi: https://doi.org/10.1016/j.apor.2026.104979.
[4] Arianta, R. Budiana, and R. Negara, “Quantitative risk-based inspection analysis for assessing offshore structure,” IOP Conf. Ser. Earth Environ. Sci., vol. 1464, p. 12036, 2025, doi: 10.1088/1755-1315/1464/1/012036.
[5] R. Xia, C. Jia, and Y. Garbatov, “Deterioration of marine offshore structures and subsea installations subjected to severely corrosive environment: A review,” Mater. Corros., vol. 76, no. 6, pp. 758–775, 2025, doi: https://doi.org/10.1002/maco.202314050.
[6] Y. Yang, C. Chen, Y. Zhuang, and Z. Suo, “Reviewing the progress of corrosion fatigue research on marine structures,” Front. Mater., vol. Volume 11-2024, 2024, doi: 10.3389/fmats.2024.1399292.
[7] S. Rouse, N. C. Lacey, P. Hayes, and T. A. Wilding, “Benthic Conservation Features and Species Associated With Subsea Pipelines: Considerations for Decommissioning,” Front. Mar. Sci., vol. Volume 6-2019, 2019, doi: 10.3389/fmars.2019.00200.
[8] M. Xie and Z. Tian, “A review on pipeline integrity management utilizing in-line inspection data,” Eng. Fail. Anal., vol. 92, pp. 222–239, 2018, doi: https://doi.org/10.1016/j.engfailanal.2018.05.010.
[9] J. S. Baioco, M. H. A. de Lima Jr., C. H. Albrecht, B. S. L. P. de Lima, B. P. Jacob, and D. M. Rocha, “Optimal Design of Submarine Pipelines by a Genetic Algorithm with Embedded On-Bottom Stability Criteria,” Math. Probl. Eng., vol. 2018, no. 1, p. 1781758, 2018, doi: https://doi.org/10.1155/2018/1781758.
[10] D. Straub and M. H. Faber, “Risk based inspection planning for structural systems,” Struct. Saf., vol. 27, no. 4, pp. 335–355, 2005, doi: https://doi.org/10.1016/j.strusafe.2005.04.001.
[11] T. Gao and Y. Liu, “Bayesian optimal experimental design of risk-based inspection policy through deep reinforcement learning,” Ocean Eng., vol. 365, p. 127263, 2026, doi: https://doi.org/10.1016/j.oceaneng.2026.127263.
[12] T. Bull et al., “Probabilistic digital-twin-informed risk-based inspection planning for offshore wind turbine structures,” Struct. Heal. Monit., vol. 25, no. 4, pp. 2383–2402, 2026, doi: 10.1177/14759217251316199.
[13] A. Fjeldstad and F. Bratbak, “Probabilistic inspection planning for fatigue cracks in floating production, storage, and offloading units,” Procedia Struct. Integr., vol. 57, pp. 692–700, 2024, doi: https://doi.org/10.1016/j.prostr.2024.03.075.
[14] R. He, Z. Tian, Y. Wang, Y. Chen, and M. J. Zuo, “Predictive maintenance for offshore wind farms with incomplete and biased prognostic information,” Ocean Eng., vol. 322, p. 120541, 2025, doi: https://doi.org/10.1016/j.oceaneng.2025.120541.
