This work is centered on the integration of different Leak Detection Technologies into a single platform for a better management of Pipeline Integrity Monitoring issues.
Leak detection methods covered in this paper belong to the family of Advanced Negative Pressure Wave, Mass-Balance, Acoustic Noise, and other predictive techniques based on data processing. Each detection technology relies on distinct physical principles, though independent, and could interact one another through cross-links data.
The integration of methods aims at solving a well-known problem in the Oil&Gas industry, which is the capability of detecting leaks and pipeline interferences originating from various threats (e.g., illegal tapping, third party interference, corrosion, and many other issues).
Such integrated approach has been named Advanced Leak Detection System and is developed over an already existing technological platform based on vibroacoustic sensing, which includes pressure sensors, accelerometers, temperature devices and flowmeters using acquisition units distributed along the pipeline, and processing servers.
The integration of different Leak Detection sub-systems can take place at distinct levels: cross-check of measurements; cross-link of computed fluid-dynamic quantities; merger of alarms associated to the same physical event.
The system is already deployed on several pipelines over Eni’s network and proved to be able to detect multiple leak-originating events and was widely tested with controlled spillages simulating several kinds of threats on pipeline with different characteristics (transported fluid, operating pressure, morphological features).
The Advanced Leak Detection system proved to be able to detect and localize every tested leakage with good sensitivity, specificity, and local accuracy.
In addition, Advanced Leak Detection alarms contain estimations of outflow rate and hole size, whose accuracy is assessed in the paper, as the alarm response time.
In conclusion, the Advanced Leak Detection System proved to be able to detect various events, leading to a complete and comprehensive Leak Detection Platform.