Duran Sierra, Guillermo Fidel (2019-07). Towards an Integrated Probabilistic Risk Assessment and Management for Offshore Pipelines: From Site Characterization and Routing to Operation. Master's Thesis. Thesis uri icon

abstract

  • Offshore pipeline route selection is a multidisciplinary engineering task to determine the best alternative route by taking into account spatial project constraints, geohazards, safety procedures, environmental conditions, third-party activities, existing facilities, and construction and operation issues. Since the pipeline route selection operates with multiple threats and vulnerabilities, a Probabilistic Risk Assessment methodology for pipeline routing is introduced based on the integration of construction and operation constraints, and relevant serviceability and ultimate limit states from existing industry standard codes. The Probabilistic pipeline routing conceptual model was developed by adopting a Risk framework represented in a Bayesian Network for Risk Assessment and Management. Physically based-models for each limit state were employed by defining dependencies between serviceability and ultimate limit states by the identification of control parameters that are common to both of them when representing a single state of Risk for pipeline route selection. The Bayesian Network model is capable to quantify the uncertainties on the physically based model design parameters, and on the vulnerabilities regarding each pipeline failure mechanism considered in this research. The value of the consequences is qualitatively defined in three states (low, moderate, and high) for heuristic purposes, and can be easily modified by the user for other consequences such as economic, environmental, and life losses. The proposed approach is a useful tool for decision-makers such as pipeline engineers, pipeline operators, project managers, environmental, civil, mechanical, geotechnical, and structural engineers, to assess the Lowest-Risk Path for an offshore pipeline project.

publication date

  • July 2019