The majority of the world's offshore infrastructures are now showing the sign of aging and are approaching the end of their original design life. Their ability to withstand various operational and environmental changes have been the main concerns over the years. This is because the pipeline will still need to operate for a few more decades with increasing demand of oil and gas supply. To address the issues, an effective pipeline integrity management system is required to manage pipeline systems and to ensure the reliability and availability of the pipeline. The main goal is to identify, apply, and assess the applicability of the Bayesian network approach in evaluating the integrity of subsea pipelines that evolves with time. The study is aimed to specifically handle knowledge uncertainties and assist in the decision making of subsea pipeline integrity assessment. A static Bayesian network model was developed to compute the probability of pipeline condition and investigate the underlying factors that lead to pipeline damage. From the model, the most influential factors were identified and the sensitivity analysis demonstrated that the developed model was robust and accurate. The proposed model was then extended to develop a decision tool model using an Influence Diagram. The results from the proposed influence diagram were used to prioritize the maintenance scheme of the pipeline segments. Benefit to cost ratio was applied to determine the pipeline maintenance intervals. Dynamic Bayesian network was utilized to model timedependent deterioration of pipeline structural reliability. A good agreement with conventional structural reliability method is achieved. The present thesis has demonstrated the applicability and effectiveness of Bayesian network approach in the field of oil and gas. It is hoped that the proposed models can be applied by oil and gas pipeline practitioners to enhance the integrity and lifeltime of the oil and gas pipeline.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:720596 |
| Date | January 2017 |
| Creators | Sulaiman, Nurul Sa'aadah |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=232617 |
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