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

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...

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Main Authors: Edrisi, A., Kam, S. I.
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Research & Development Center of Sciences and Cultures 2013
Subjects:
Online Access:http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027
https://doi.org/10.3968/j.aped.1925543820130501.1027
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spelling ftjcsc:oai:ojs.cscanada.net:article/3321 2023-05-15T15:14:26+02:00 Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data Edrisi, A. Kam, S. I. 2013-03-31 application/pdf http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027 https://doi.org/10.3968/j.aped.1925543820130501.1027 eng eng Canadian Research & Development Center of Sciences and Cultures http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027/3642 http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027 doi:10.3968/j.aped.1925543820130501.1027 Advances in Petroleum Exploration and Development; Vol 5, No 1 (2013): Advances in Petroleum Exploration and Development; 22-36 1925-5438 1925-542X Leak Leak detection modeling Pipeline Leak coefficient Gas flow in pipe info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article 2013 ftjcsc https://doi.org/10.3968/j.aped.1925543820130501.1027 2022-02-13T08:20:40Z 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 Article in Journal/Newspaper Arctic CSCanada.net: E-Journals (Canadian Academy of Oriental and Occidental Culture, Canadian Research & Development Center of Sciences and Cultures) Arctic
institution Open Polar
collection CSCanada.net: E-Journals (Canadian Academy of Oriental and Occidental Culture, Canadian Research & Development Center of Sciences and Cultures)
op_collection_id ftjcsc
language English
topic Leak
Leak detection modeling
Pipeline
Leak coefficient
Gas flow in pipe
spellingShingle Leak
Leak detection modeling
Pipeline
Leak coefficient
Gas flow in pipe
Edrisi, A.
Kam, S. I.
Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
topic_facet Leak
Leak detection modeling
Pipeline
Leak coefficient
Gas flow in pipe
description 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
format Article in Journal/Newspaper
author Edrisi, A.
Kam, S. I.
author_facet Edrisi, A.
Kam, S. I.
author_sort Edrisi, A.
title Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
title_short Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
title_full Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
title_fullStr Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
title_full_unstemmed Mechanistic Leak-Detection Modeling for Single Gas-Phase Pipelines: Lessons Learned from Fit to Field-Scale Experimental Data
title_sort mechanistic leak-detection modeling for single gas-phase pipelines: lessons learned from fit to field-scale experimental data
publisher Canadian Research & Development Center of Sciences and Cultures
publishDate 2013
url http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027
https://doi.org/10.3968/j.aped.1925543820130501.1027
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Advances in Petroleum Exploration and Development; Vol 5, No 1 (2013): Advances in Petroleum Exploration and Development; 22-36
1925-5438
1925-542X
op_relation http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027/3642
http://cscanada.net/index.php/aped/article/view/j.aped.1925543820130501.1027
doi:10.3968/j.aped.1925543820130501.1027
op_doi https://doi.org/10.3968/j.aped.1925543820130501.1027
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