Leak Detection in Subsea Pipeline: A Mechanistic Modeling Approach With Fixed Pressure Boundaries
- Rahul N. Gajbhiye (Louisiana State University) | Seung I. Kam (Louisiana State University)
- Document ID
- Society of Petroleum Engineers
- SPE Projects, Facilities & Construction
- Publication Date
- December 2008
- Document Type
- Journal Paper
- 1 - 10
- 2008. Society of Petroleum Engineers
- 5.3.2 Multiphase Flow, 4.3.4 Scale, 4.1.2 Separation and Treating, 4.2 Pipelines, Flowlines and Risers, 4.1.5 Processing Equipment, 4.1.4 Gas Processing, 6.5.5 Oil and Chemical Spills, 5.4.2 Gas Injection Methods, 5.2.1 Phase Behavior and PVT Measurements, 2 Well Completion, 4.2.5 Offshore Pipelines
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This study shows how a subsea pipeline leak can be modeled in a mechanistic way. Special attention is paid to the implication of fixed-pressure boundary conditions at both upstream and downstream locations, which is relevant to the way the majority of field operations are actually performed. The use of fixed-pressure boundary conditions leaves the change in inlet total flow rate (?qt in) and the change in outlet total flow rate (?qt out) as two possible leak-detection indicators that can be monitored on a real-time basis. The two-phase flow of gas and oil mixtures in subsea pipelines is analyzed by using Beggs and Brill's correlations. The effect of different parameters on the mechanistic leak-detection modeling is also investigated, accounting for gas compressibility, backpressure of the system, pressure drop across the system, and gas/oil fraction at the leak.
Also presented in this study is a new method to predict the change in inlet or outlet total flow rates (?qt in or ?qt out) in a form of contours with dimensionless leak opening size (d leak/D) and dimensionless leak position (x leak/L) in x and y axes. This new style of reporting leak-detection indicators is believed to provide a convenient means to improve data interpretation in actual field practice and laboratory tests.
A safe and proper operation of complex deepwater infrastructure has been a serious issue for the oil industry (Teal 2003; Tubb 2006; Carlsen and Mjaaland 2006; French et al. 2006). Even small oil-spill incidents may create a considerable technical and financial adversity, facing a delay in oil and gas production, a loss of hydrocarbon products, an additional expense for repair and remediation, and a negative impact on the operating company's reputation (Don 2004). In fact, pipeline leaks have already become a frequent problem. It is not only the environment, but also companies, including producers and transporters, that suffer from leak accidents. Leaks from subsea pipelines are just as common as those from inland pipelines. Earlier experience shows that small leaks leading to spills of 1-5 gallons per hour is very difficult to detect by using existing leak-detection methods, compared to leaks with relatively large opening sizes (Mastandrea et al. 1990; Cranswick 2001; Teal 2003).
Pipeline operators use various types of detection approaches including both hardware- and software-based methods (Jolly et al. 1992; Barlas 2001; Theakston and Larnaes 2002; Bloom 2004; Liu et al. 2005). Scott and Barrufet (2003) provide a thorough summary about recent developments in this area. Acoustics, fiber optics, ultrasonics, and cable sensors are examples of hardware-based methods, while mass balance, transient modeling, and pressure analysis are examples of software-based methods. A software-based leak-detection method identifies a pipeline leak which occasionally causes several immediate detectable effects in terms of fluctuations in the monitoring pressures and/or flow rates (Mastandrea et al. 1990; Bonn 1998). Earlier studies usually focused on the drastic change in flow conditions resulting from the blowdown and rupture of subsea vessels or pipelines (Norris and Puls 1993; Norris and Hissong 1994). It is clear that such a relatively large leak can predict the failure of multiphase flowlines reasonably well.
Looking into the impact of relatively small-size leaks in subsea pipelines, Dinis et al. (1999) developed the concept of leak-detection modeling for a single-phase incompressible flow. They claimed that a leak which is larger in its size and located further downstream can be more easily detected by comparing their modeling results with laboratory flow experiments in 9,460-ft-long horizontal flow loops. Their analysis was based on the flow rate measured only at the outlet, ignoring the pressure and flow rate at the inlet. The same concept was tested with a single-phase compressible gas line (Scott and Yi 1998) by comparing the responses before and after the leak. Scott et al. (1999) and Smith and Griffin (2001) further extended these leak-detection procedures by utilizing an empirical two-phase flow-friction factor.
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Barlas, S. 2001. Pipeline inspection officials say no method is 100%fool-proof. Pipeline & Gas Journal (January 2001).
Beggs, H.D. 1972. An Experimental Study of Two-Phase Flow in Inclined Pipes.PhD dissertation. University of Tulsa, Tulsa, Oklahoma.
Beggs, H.D. and Brill, J.P. 1973. Study of Two-Phase Flow in Inclined Pipes.Journal of Petroleum Technology (May 1973).
Bloom, D. 2004. Non-intrusive systems detects leaks using mass measurement.Pipeline & Gas Journal (July 2004).
Bonn, R.J.C. 1998. OperationalLessons From the UKCS Hydrocarbon Leaks Database . Paper SPE 46641presented at the SPE International Conference on Health, Safety, andEnvironment in Oil and Gas Exploration and Production, Caracas, 7-10 June. doi:10.2118/46641-MS.
Bourgoyne, A.T., Chenevert, M.E., and Milheim, K.K. 1986. AppliedDrilling Engineering. Textbook Series, SPE, Richardson, Texas 2:128-130.
Carlsen, I.M. and Mjaaland, S. 2006. Subsea Leak Detection—Screening ofSystems. Final report, IK 29.6215.00 SINTEF Petroleumsforskning AS, Trondheim,Norway (24 November 2006).
Cranswick, D. 2001. Brief Overview of Gulf of Mexico OCS Oil and GasPipelines: Installation, Potential Impacts, and Mitigation Measures. OCS ReportMMS 2001-067, MMS, Gulf of Mexico OCS Region, New Orleans (August 2001).
Dinis, J.M., Wojtanowicz, A.K., and Scott, S.L. 1999. Leak detection in liquid subseaflowlines with no recorded feed rate. Journal of Energy ResourceTechnology 121 (3): 161-166. doi:10.1115/1.2795976.
Don B. 2004. Non-Intrusive Systems Detects Leaks Using Mass Measurement.Pipeline & Gas Journal (July 2004).
Economides, M.J., Hill, A.D., and Ehlig-Economides, C. 1993. PetroleumProduction Systems. Englewood Cliffs, New Jersey: Petroleum EngineeringSeries, Prentice Hall.
French, L.S, Richardson, G., Ed, Kazanis, E.G., Montgomery, T.M., Bohannon,C.M., Gravois, M.P. 2006. Deepwater Gulf of Mexico 2006: America's ExpandingFrontier. OCS Report MMS 2006-022, MMS, Gulf of Mexico OCS Region, New Orleans(May 2006).
Jolly, W.D., Morrow, T.B., O'Brien, J.F., Spence, H.F., and Svedeman, S.J.1992. New Methods for Rapid Leak Detection in Offshore Pipelines. Final Report,SWRI Project No. 04-4558, MMS, Southwest Research Institute, San Antonio, Texas(April 1992).
Kam, S.I. Submitted. Mechanistic modeling of leak detection in horizontalsubsea pipelines. Journal of Petroleum Science and Engineering(submitted 2008).
Kam, S.I. 2008. Complication of boundary conditions in mechanistic modelingof subsea pipeline leak detection. Exploration & Production: The Oil andGas Review 6 (1): 114-117.
Lee, W.J. and Wattenbarger, R.A. 1996. Gas Reservoir Engineering.Textbook Series, SPE, Richardson, Texas 5.
Liu, M., Zang, S., and Zhou, D. 2005. Fast leak detection and location ofgas pipelines based on an adaptive particle filter. Int. J. AppliedMathematics and Computer Sci. 15 (4): 541-550.
Mastandrea, J.R., Miller, J.W, and Clare, D.M. 1990. Rapid Leak DetectionFor Sea Floor Pipelines: Development of Practical New Methods. NDE TechnicalReport No. E-90R0081601, MMS, Herndon, Virginia (August 16, 1990).
Norris, H.L. and Hissong, D.W. 1994. Consequence Analysis in theProduction and Transportation of Oil and Gas. Paper SPE 27962 presented atthe University of Tulsa Centennial Petroleum Engineering Symposium, Tulsa,29-31 August. doi: 10.2118/27962-MS.
Norris, H.L. III and Puls, R.C. 1993. Single-Phase or Multiphase Blowdownof Vessels or Pipelines. Paper SPE 26565 presented at the SPE AnnualTechnical Conference and Exhibition, Houston, 3-6 October. doi:10.2118/26565-MS.
Scott, S.L. and Barrufet, M.A. 2003. Worldwide Assessment of Industry LeakDetection Capabilities for Single & Multiphase Pipeline. Project Report,MMS/OTRC 1435-01 -99-CA-3, Task Order 18133, MMS, Gulf of Mexico OCS Region,College Station, Texas (August 6, 2003).
Scott, S.L., Liu, L., and Yi, J. 1999. Modeling the Effects of a DeepwaterLeak on Behavior of a Multi-phase Production Flowlines. Paper SPE 52760presented at the SPE/EPA Exploration and Production Environmental Conference,Austin, Texas, USA, 1-3 March. DOI: 10.2118/52760-MS.
Scott, S.L. and Yi, J. 1998. Detection of Critical Flow Leaks inDeepwater Gas Flowlines. Paper SPE 49310 presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans, 27-30 September. DOI:10.2118/49310-MS.
Smith, J.R. and Griffin, J.M. 2001. Investigation of Hybrid Deep WaterProduction Systems. Final report No. 1435-01-97-CA-30879, MMS, Herndon,Virginia (29 November 2001).
Teal, C. 2003. Subsea pipeline and installations leak detection. BusinessBriefing: Exploration & Production: The Oil and Gas Review 2:1-4.
Theakston, J. and Larnaes, G. 2002. Selecting and installing asoftware-based leak detection system. Pipeline & Gas Journal(October 2002): 52-53.
Tubb, R. 2006. Growing U.S. gas demand continues to drive new pipelineconstruction. Pipeline & Gas Journal (July 2006): 45-46.