Numerical Comparison of Pressure Points Analysis and Transient Model Leak Detection and Location Systems

Document Type : Research Paper

Authors

Department of Mechanical Engineering, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria

Abstract

This study offers the basis and numerical application of the pressure points analysis (PPA) technique and transient model (TM) leak detection and location systems (DLS). The study numerically compared the PPA technique and the TM leak (DLS) method on a crude oil transmission pipeline. The PPA technique used pressure differentials derived from the pipeline’s upstream, midstream, and downstream pressure sensors to find and locate leaks. In contrast, the TM method used measurements of temperature, flow, and pressure at the pipeline’s inlet and outlet ends and differences in the continuity and law of conservation of momentum equations to derive equations that pilot the system to find and quantify leaks on the pipeline. The static parameters employed for both models were extracted from the pipeline (commercial steel) configuration and the Nigeria Bonny Light Crude Oil properties. The dynamics parameters applied in both models were obtained from SCADA (Supervisory Control and Data Acquisition) system. The models were used separately to detect and locate leak incidents on a straight horizontal pipeline of length 5km and diameter 0.3556m conveying Nigeria bonny light crude oil from Heritage Energy Operational Services Limited into the Trans-Forcados Pipeline (TFP). However, the Leak located by the PPA technique at 2781.2m from upstream is 30.07m after the actual Leak. In comparison, the same Leak located by the TM method is 15.10m behind the actual position, as discovered after excavation during pipeline leak remedial activities. Although both leaks (DLS)) are not accurate, the results show that the TM method is more précised regarding leak location than the PPA technique. On the other hand, the PPA technique can detect leaks faster than the TM method. Both methods are not expensive, and since they give an accurate narrow range of the section of the pipeline in which the Leak is found, they are complementary. Hence, it is recommended and advisable for an establishment to adopt both methods simultaneously for leak confirmation and to know the section of the pipeline to be excavated and replaced.

Keywords

References

  1. Chuka C E, Freedom I H, Anthony O U (2016) Transient model-based leak detection and localization technique for crude oil pipelines: a case of N.P.D.C, Olomoro, Saudi Journal of Engineering and Technology, 1, 2: 37–48, https://doi.org/10.21276/SJEAT.2016.1.2.2.##
  2. Chis T (2009) Pipeline leak detection techniques, Annual. University, Tibiscus Computer Science Series, 25–34, https://doi.org/10.48550/arXiv.0903.4283. ##
  3. Jang S P, Cho C Y, Nam J H, Lim S-H, Shin D, Chung T-Y (2010) Numerical study on leakage detection and location in a simple gas pipeline branch using an array of pressure sensors, Journal of Mechanical Science and Technology, 24:4, 24: 4, 983–990, https://doi.org/10.1007/S12206-010-0216-8. ##
  4. Adegboye M A, Fung W K, Karnik A (2019) Recent advances in pipeline monitoring and oil leakage detection technologies: Principles and Approaches, Sensors (Switzerland), 19, 11, https://doi.org/10.3390/S19112548. ##
  5. Yang Z, Liu M, Shao M, Ji Y (2011) Research on leakage detection and analysis of leakage point in the gas pipeline system, Open Journal of Safety Science and Technology, 1, 94–100, https://doi.org/10.4236/ojsst.2011.13010. ##
  6. Barradas I, Garza L E, Morales-Menendez R, Vargas-Martínez A (2009) Leaks detection in a pipeline using artificial neural networks, In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Guadalajara, Jalisco, Mexico, Proceedings 14, 637-644, Springer Berlin Heidelberg. ##
  7. Jasper A A, Ove G T, Torleiv B (2012) Experimental study of oil pipeline leak processes, Journal of Environmental Protection, 3, 597–604. https://doi.org/10.4236/jep.2012.37072. ##
  8. [8] Oyedeko K F K, Balogun H A (2015) Modeling and simulation of a leak detection for oil and gas pipelines via transient model: a case study of the Niger Delta, Journal of Energy Technologies and Policy, 5, 1, 16–27, https://iiste.org/Journals/index.php/JETP/article/view/19389. ##
  9. Ghazali M F (2012) Leak detection using instantaneous frequency analysis, PhD Thesis, University of Sheffield. United Kingdom,https://www.semanticscholar.org/paper/Leak-detection-using-instantaneous-frequency-Ghazali/7d3f44724916fdd84c5c23b2b79e8cc7c3d45619/figure/0. ##
  10. Golmohamadi M (2015) Pipeline leak detection, Masters Theses, https://scholarsmine.mst.edu/masters_theses/7397.
  11. Whaley R S, Nicholas R E, Van Reet J D (1992) Tutorial on software-based leak detection techniques, Pipeline Simulation Interest Group. ##
  12. Frank M white (2003) Fluid mechanics. McGraw-Hill. ##
  13. Robert H P, Green D W, Maloney J O (1999) Perry’s chemical engineers’ Handbook (7th Edition), McGraw Hill, 6-6 - 6-37. ##
  14. Tetzner P R (2003) Model-based pipeline leak detection and localization, Krohne Oil and Gas B.V. Dordrecht. 3R International (42) Heft/2003, 3R interna, 455–460. ##
  15. Abhulimen K E, Susu A A (2004) Liquid pipeline leak detection system: model development and numerical simulation, Chemical Engineering Journal, 97, 1: 47–67, https://doi.org/10.1016/S1385-8947(03)00098-6. ##
  16. Kam S I (2010) Mechanistic Modeling of pipeline leak detection at fixed inlet rate, Journal of Petroleum Science and Engineering, 70, 3–4: 145–156, doi.org/. doi: j. petrol.2009.09.008, doi.org/10.1016/j.petrol.2009.09.008. ##

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