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The transport of hydrocarbons by offshore pipeline is threatened by the rapid expansion of pipe networks and the increasing frequency of maritime activities. Risk management is thus necessary to manage and to prevent ship-related hazardous events that may damage offshore pipelines. Probability analysis is key to assessing the risk associated with ship operations on offshore pipelines and to decision making in managing that risk. Bayesian network (BN) models are proposed in this paper to determine the probability of anchor and trawling damage to subsea pipelines. The BN models are developed by integrating directed acyclic graphs and three computational methods (Boolean operation, standard and historical statistical analyses, and fuzzy set theory) to elicit both marginal and conditional probability tables. A case study illustrates the use of two BN-related functions—probability prediction and probability updating—to determine final probabilities of damage to a subsea pipeline. The results of the analysis support risk-ranking and risk-reducing decisions associated with maritime operations in the area of offshore pipelines.
Liu et al. (2013) studied this question.