Chapter
Aug 6, 2020
Pipelines 2020

Emerging Technologies and Systems for Gas Pipeline Leak Detection

Publication: Pipelines 2020

ABSTRACT

Pipelines remain the primary means of transporting and delivering petroleum products, natural gas, liquid hydrocarbons, and water to consumers. Gas pipeline leaks which are the main threat to the reliability of the pipeline network can cause major incidents and environmental disasters resulting in both human injuries and financial losses. As technology is gaining traction for monitoring infrastructure, it is expected that the efficient application of emerging technologies will play a crucial role in the realization of real-time structural integrity and leak detection, monitoring, and repair systems for gas pipelines. The primary objective of this study is to conduct a state-of-the-art review and evaluation of emerging technologies and systems for pipeline leak detection. The capabilities of the identified technologies and systems are analyzed to elicit their advantages and disadvantages. Based on the findings of the study, recommendations are made on best practices for the application of these emerging technologies and systems.

Get full access to this article

View all available purchase options and get full access to this chapter.

REFERENCES

Adegboye, M. A., Fung, W. K., and Karnik, A. (2019). “Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches.” Sensors, 19(11), 2548.
Boaz, L., Kaijage, S., and Sinde, R. (2014). “An overview of pipeline leak detection and location systems.” In Proceedings of the 2nd Pan African International Conference on Science, Computing and Telecommunications (PACT 2014), IEEE, 133–137.
Chen, Q., Shen, G., Jiang, J., Diao, X., Wang, Z., Ni, L., and Dou, Z. (2018). “Effect of rubber washers on leak location for assembled pressurized liquid pipeline based on negative pressure wave method.” Process Safety and Environmental Protection, 119, 181–190.
Delgado, M. R., and Mendoza, O. B. (2017). “A comparison between leak location methods based on the negative pressure wave.” In 2017 14th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), IEEE, 1–6.
Gao, Y., Liu, Y., Ma, Y., Cheng, X., and Yang, J. (2018). “Application of the differentiation process into the correlation-based leak detection in urban pipeline networks.” Mechanical Systems and Signal Processing, 112, 251–264.
Garner, K. J., Busbee, L., Cornwell, P., Edmonds, J., Mullins, K., Rader, K., … and Williams, J. M. (2001). “Duty cycle of the detector dog: A baseline study.” Institute for Biological Detection Systems, Auburn University.
Geiger, G., Werner, T., and Matko, D. (2003). “Leak detection and locating-a survey.” In PSIG Annual Meeting.
He, G., Liang, Y., Li, Y., Wu, M., Sun, L., Xie, C., and Li, F. (2017). “A method for simulating the entire leaking process and calculating the liquid leakage volume of a damaged pressurized pipeline.” Journal of hazardous materials, 332, 19–32.
Hoarau, Q., Ginolhac, G., Atto, A. M., and Nicolas, J. M. (2017). “Robust adaptive detection of buried pipes using GPR.” Signal Processing, 132, 293–305.
Jia, Z., Ren, L., Li, H., and Sun, W. (2018). “Pipeline leak localization based on FBG hoop strain sensors combined with BP neural network.” Applied Sciences, 8(2), 146.
Jia, Z., Wang, Z., Sun, W., and Li, Z. (2019). “Pipeline leakage localization based on distributed FBG hoop strain measurements and support vector machine.” Optik, 176, 1–13.
Lim, K., Wong, L., Chiu, W. K., and Kodikara, J. (2016). “Distributed fiber optic sensors for monitoring pressure and stiffness changes in out-of-round pipes.” Structural Control and Health Monitoring, 23(2), 303–314.
Liu, J., Yao, J., Gallaher, M., Coburn, J., and Fernandez, R. (2008). “Study on Methane Emission Reduction Potential in Chinas Oil and Natural Gas Industry.”, April.
Mahmutoglu, Y., and Turk, K. (2018). “A passive acoustic based system to locate leak hole in underwater natural gas pipelines.” Digital Signal Processing, 76, 59–65.
Mandal, P. C. (2014). “Gas leak detection in pipelines & repairing system of titas gas.” Journal Of Applied Engineering, 2(2), 23–34.
Manekiya, M. H., and Arulmozhivarman, P. (2016). “Leakage detection and estimation using IR thermography.” In 2016 International Conference on Communication and Signal Processing (ICCSP), IEEE, 1516–1519.
Murvay, P. S. and Silea, I. (2012). “A survey on gas leak detection and localization techniques.” Journal of Loss Prevention in the Process Industries, 25(6), 966–973.
Png, W. H., Lin, H. S., Pua, C. H., and Rahman, F. A. (2018). “Pipeline monitoring and leak detection using Loop integrated Mach Zehnder Interferometer optical fiber sensor.” Optical Fiber Technology, 46, 221–225.
Quaife, L., and Acker, D. (1993). “Pipeline leak location technique using a novel test fluid and trained dogs”. In Pipeline Pigging and Integrity Monitoring Conference.
Rehman, K. and Nawaz, F. (2017). “Remote pipeline monitoring using wireless sensor networks.” In 2017 International Conference on Communication, Computing and Digital Systems (C-CODE), IEEE, 32–37.
Scott, S., and Barrufet, M. (2003). “Worldwide assessment of industry leak detection capabilities for single & multiphase pipelines.”. Dept. of Petroleum Engineering, Texas A&M University.
Shukla, A., and Karki, H. (2016). “Application of robotics in onshore oil and gas industry—A review Part I.” Robotics and Autonomous Systems, 75, 490-507.
Stafford, M., and Williams, N. (1996). “Pipeline leak detection study.” Health and Safety Executive – Offshore Technology Report, Bechtel Limited, HSE Books.
Tanimola, F., and Hill, D. (2009). “Distributed fibre optic sensors for pipeline protection.” Journal of Natural Gas Science and Engineering, 1(4–5), 134–143.
Tian, S., Du, J., Shao, S., Xu, H., and Tian, C. (2016). “A study on a real-time leak detection method for pressurized liquid refrigerant pipeline based on pressure and flow rate.” Applied Thermal Engineering, 95, 462–470.
Wang, L., Narasimman, S. C., Ravula, S. R., and Ukil, A. (2017). “Water ingress detection in low-pressure gas pipelines using distributed temperature sensing system.” IEEE Sensors Journal, 17(10), 3165–3173.
Xiao, Q., Li, J., Sun, J., Feng, H., and Jin, S. (2018). “Natural-gas pipeline leak location using variational mode decomposition analysis and cross-time–frequency spectrum.” Measurement, 124, 163–172.
Zhang, J. (1997). “Designing a cost-effective and reliable pipeline leak-detection system.” Pipes and Pipelines International, 42(1), 20–26.

Information & Authors

Information

Published In

Go to Pipelines 2020
Pipelines 2020
Pages: 64 - 73
Editors: J. Felipe Pulido, OBG, Part of Ramboll and Mark Poppe, Brown and Caldwell
ISBN (Online): 978-0-7844-8320-6

History

Published online: Aug 6, 2020
Published in print: Aug 6, 2020

Permissions

Request permissions for this article.

Authors

Affiliations

Ibukun G. Awolusi, Ph.D. [email protected]
Dept. of Construction Science, Univ. of Texas at San Antonio, San Antonio, TX. Email: [email protected]
Ayodeji K. Momoh [email protected]
Mears Group, Inc., Underground Utility Division, San Antonio, TX. Email: [email protected]
Aliu A. Soyingbe, Ph.D. [email protected]
Dept. of Building, Univ. of Lagos, Akoka, Yaba, Lagos, Nigeria. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$130.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$130.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share