This paper examines the feasibility of Real Time Transient Model (RTTM) based methods for gas pipeline leak detection, elucidates the factors that must be managed for effective gas pipeline leak detection, and examines factors that impact leak detection and location sensitivity.


A growing regulatory focus on minimizing the impacts of ruptures in natural gas commodity pipelines is increasing the pressure on the operators of such systems to provide means of rapidly detecting and locating such leaks. Leak detection systems have become standardized components of liquid commodity pipelines over the last few decades, but have not been emphasized for natural gas systems.

Although many methods have been used to detect leaks in liquid systems, the most commonly used approach uses real time transient models and a mass-balance approach to detect commodity losses. The approach is extensible to gas systems in a fairly straightforward manner, and this paper will discuss such implementation. However, it is worth nothing that gas systems have certain differences that make them distinct from liquid pipeline systems. One difference is that gas pipelines, especially if they are part of or support gas distribution, have the potential to be far more highly networked, branched and looped than liquid transportation systems. Gas is a far more highly compressible commodity than most liquids are, and this has ramification for desired levels of instrumentation and speed of response. Finally, gas pipelines are more highly typified by maintenance requirements that can interfere with or degrade the performance of RTTM systems.

Another significant different between liquid and gas pipeline leak detection requirements is that generally, in a liquid line, a very large leak may be quickly identified by rate of change alarms. In contrast, a large leak in a gas pipeline, because of the compressibility of the gas, will cause much slower changes in the pipeline pressure. A gas pipeline therefore, may need to rely on an RTTM based leak detection system even for the reliable and timely detection of very large leaks.

This paper attempts to illuminate these issues and equip the reader to understand and deal with them.

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