Rising global energy demand and advancements in subsea engineering technology has made subsea oil and gas systems the dominant source for energy. The critical challenges in subsea systems included the associated external pressures and cold temperatures in ultra-deep water. Both of these challenges directly influence the safety and production of subsea oil and gas. Specifically, the design of a subsea pipeline must not only provide the structural integrity to withstand high external pressures but must be durable with respect to corrosion, and guarantee the flow of hydrocarbons. The latter two issues can only be investigated using temperature models that capture the heat transfer from the oil/gas mixture, through the pipeline and to the seawater. To predict temperatures along a pipeline during shutdown, software tools are available which provide numerical solutions based on the solution of mass, momentum and energy conservation equations. However, due to the complexity of these equations, it takes hours to generate results with no clear indication that the resulting simulations are correct. The objective of this project is to develop a low dimensional model that can accurately predict temperatures along pipelines during offshore oil production system shutdown. To develop the model, energy conservation of the fluid within the pipeline is considered. To solve this energy conservation equation, analytical and numerical methods, centered upon lumped capacitance method and finite difference method, are explored. These results are then compared with the developed low dimensional model. The low dimensional model is based on a modified finite difference method used for the energy conservation equation solution, which is integrated with a one dimensional heat conduction equation along a hollow composite cylinder. Steady state temperature profiles are also explored in order to generate the initial conditions for this modified finite difference method. Furthermore, the accuracy of this model is verified by comparing with the results generated by commercial software. The accuracy of this model could be further increased by using a finer mesh for which temperatures are to be determined. However, this would increase its computation time.


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