Ehsan Jalilian, HiFi Engineering, Canada, presents distributed fibre optic sensing use cases for pipeline integrity management, with some case studies from North America.
Distributed fibre optic sensing (DFOS) is best known for its traditional role in leak detection, with first-generation, backscatter-based technologies like distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) having their roots in external leak detection almost two decades ago. While the ubiquitous nature of telecom fibre made early versions of DAS and DTS logical candidates for pipeline monitoring projects, the inherent limitations of the host telecom fibre itself act to restrict the utility and breadth of application of these systems.
In recent years, the continuous evolution of sensor design and system architecture has dramatically improved fidelity and enabled integrated measurement of acoustics, temperature, and strain/vibration over long distances with minimal performance degradation, resulting in next-generation, high-fidelity DFOS systems, such as Hifi’s High Fidelity Distributed Sensing (HDS™), with enhanced performance in leak detection and expanded operational applicability. High-fidelity DFOS systems play an expanded role in pipeline leak detection with the ability to not only better detect, but also better differentiate event characteristics allowing for greater precision (i.e. the ability to detect pinhole leaks at low pressures) as well as superior accuracy (specifically the virtual elimination of false positives). Moreover, high-fidelity DFOS systems such as HDS leverage next-generation fibre optics and advanced machine learning (ML) tools to provide a pipeline monitoring platform that transcends traditional leak detection.
Specifically engineered for sensing, Hifi’s next-generation HDS fibre optic sensors continuously capture acoustic, strain and vibration, and thermal data generated by a wide range of activities occurring on, in or near the pipeline while leveraging the power of ML tools such as sequential neural networks to dive deep into the data to identify events of interest. The result is a comprehensive monitoring solution with capabilities that extend well beyond the traditional role in advanced leak detection. Combining these powerful technologies in a single system provides operators with unparalleled real-time monitoring capabilities while also delivering a host of predictive insights to support proactive integrity management. Among its transformative applications, pig tracking and accurate estimations of flow, pressure, and density are of high value to pipeline operators.
The high sensitivity and light-speed transmission capabilities of Hifi’s HDS, when combined with advanced ML strategies, offer a wide range of applications. These include advanced leak detection to pinhole levels, pipeline insulation mapping, ground disturbance and intrusion detection, pig detection, tracking, and analysis, and distributed strain analysis for preventative integrity management. The technology can also be used for geotechnical investigations, including the analysis of the impacts of earthquakes, landslides and other ground movements.
Pigging applications
Operators have been quick to seize on the recent rapid advancements in high fidelity DFOS capabilities, to detect, track and analyse pipeline inspection gauges (pigs), which has continued to push the technology into new applications to expand its operational utility and value-in-use.
One primary application of DFOS that appears to have considerable direct financial value for pipeline operators is the tracking of inline inspection (ILI) pigging tools. Pigs generate vibrations and acoustics when travelling through the pipe (for instance, when contacting weld joints – Figure 1), and these signatures are generally quite pronounced in the context of fibre optic sensitivity, allowing advanced systems to detect pigs from thousands of metres away. High fidelity DFOS systems such as Hifi’s HDS are well-suited to do double-duty as pig tracking and analysis platforms, enabling operators to efficiently monitor pig location, speed, status (i.e. stopped vs. moving) without the need for costly third party services. Most importantly, applications like pig tracking and analysis are enabled by customised algorithms that can be initialised remotely (i.e. via software updates) without any need for new equipment or system hardware. The result is a highly versatile tool that brings considerable real value at minimal cost...
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