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Simulation of flow characteristics for leak detection in oil and gas pipeline network

Authors: B. Manshoor; A. Khalid; I. Zaman; D. Hissein Didane; N. F. F. Zulkefli;

Simulation of flow characteristics for leak detection in oil and gas pipeline network

Abstract

Pipelines are highly used in the oil and gas industry for the transportation of oil, natural gas and products from refineries. The efficiency and the reliability in distribution networks need to be considered to ensure that the fluid is transported perfectly. However, due to some leakages because of corrosion or poor maintenance, the quantities of fluid transported are affected. In this case, leakage gives a big impact on the industry. Thus, early leak detection of leakage needs to be conducted. A physical method in leak detection can sometimes lead to higher cost if the parameter used in certain equipment is not compatible and not suitable which resulted in vague leakage detection. Since the accuracy of a method to detect leakage is highly dependent on the flow and leak parameters in a given pipeline, a simulation-based method is proposed to study the most reliable and dependable parameter to detect a leak. This study has utilizes computational fluid dynamics (CFD) in 4m length of pipe with a diameter of 0.1m to have some insight into some parameters to study the flow characteristics surrounding virtual minor leaks. The parameter that is being considered in this study is pressure, velocity and turbulence kinetic energy. In all the parameters studied, the best possible leak detection parameter is identified. The CFD analysis is focused on a steady-state simulation of turbulent flow that was carried out in various setups in outlet pressure. Based on the CFD simulation, the pressure was found to be the most accurate and reliable parameter for detecting leakage due to the consistent trend in pressure data value in leakage and the graph plotted at the position along the pipe.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
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