Thesis (Ph. D.)--Ohio University, 2001. / Title from PDF t.p.

Thesis (Ph.D.)--University of Tulsa, 1994. / Includes bibliographical references ( leaves 168-174).

Thesis (Ph.D.)--University of Tulsa, 1984. / Bibliography: leaves 73-75.

Thesis (Ph.D.)--University of Tulsa, 1990. / Bibliography: leaves 88-89.

Thesis (Ph.D.)--University of Tulsa, 1991. / Bibliography: leaves 80-82.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 186-202).

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 169-172). Available also in a digital version from Dissertation Abstracts.

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.

Call number: LD2668 .T4 1965 R649 / Master of Science

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering, 2016 / Wax deposition in sub-sea pipelines is a major concern in the oil industry. Wax precipitates in a pipeline when the temperature falls below a certain temperature called the Wax Appearance Temperature. As wax precipitates and deposits in a pipeline, the wax deposit can cause oil flow problems and reduce production efficiency. At critical conditions wax deposits in pipelines may damage production equipment or cause a production stoppage. In the past two or three decades, the challenge has been to develop and apply high-fidelity models for wax deposition. In this context, two promising models have recently been developed: that of Eskin et al. (2014) and that of Haj-Shafiei et al. (2014). This research report tries to solve and elucidate some of the key assumptions of these wax deposition models, through implementing them in the Python Programming Language. In investigating the significance of the shape of the Solubility Curve on wax deposition, a concave shaped solubility curve was found to exhibit the highest average deposition and the convex shaped solubility curve the lowest average deposition. The shape of the solubility curve also drastically affects the peak wax height with a concave shaped solubility curve forming the greatest wax peak. The results have shown that the description of the phenomenon of Wax deposition in undersea pipelines is difficult to grasp for anyone not familiar with the topic because of the complexity of the mechanisms involved. Often, the models are difficult to visualise owing to their multi-dimensional solution procedure and the interdependence of parameters. The resultant programs could be utilised to help illustrate the process of Wax deposition to Engineering students or professionals who do not have access to expensive proprietary software or who are less proficient with programming but interested in the field. / GS2016