Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data

A. Edrisi, S. I. Kam

Abstract


The use of pipelines is one of the most popular ways of delivering gas phases as shown by numerous examples in hydrocarbon transportation systems in Arctic regions, oil and gas production facilities in onshore and offshore wells, and municipal gas distribution systems in urban areas. A gas leak from pipelines can cause serious problems not only because of the financial losses associated but also its social and environmental impacts. Therefore, establishing an early leak detection model is vital to safe and secure operations of such pipeline systems.

A leak detection model for a single gas phase is presented in this study by using material balance and pressure traverse calculations. The comparison between two steady states, with and without leak, makes it possible to quantify the magnitude of disturbance in two leak detection indicators such as the change in inlet pressure (ΔPin) and the change in outlet flow rate (Δqout) in a broad range of leak locations (xleak) and leak opening sizes (dleak).

 The results from the fit to large-scale experimental data of Scott and Yi (1998) show that the value of leak coefficient (CD), which is shown to be the single-most important but largely unknown parameter, ranges from 0.55 to 4.11, and should be a function of Reynolds number (NRe) which is related to leak characteristics such as leak location (xleak), leak opening size (dleak), leak rate (qleak) and system pressure. Further investigations show that between the two leak detection indicators, the change in outlet flow rate (Δqout) is superior to the change in inlet pressure (ΔPin) because of larger disturbance, if the pressure drop along the pipeline is relatively small compared to the outlet pressure; otherwise, the change in inlet pressure (ΔPin) is superior to the change in outlet flow rate (Δqout).

Key words: Leak; Leak detection modeling; Pipeline; Leak coefficient; Gas flow in pipe


Keywords


Leak; Leak detection modeling; Pipeline; Leak coefficient; Gas flow in pipe

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References


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DOI: http://dx.doi.org/10.3968/j.aped.1925543820130501.1027

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