A Robust Qualification of Fiber-Sensing for Leak Detection, based on Hyper-Scan Technology
Proceedings Publication Date
Dr. Eran Inbar
Eran Inbar
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Distributed fiber-optic sensing is well-suited for fluid leak detection in oil and gas pipelines. One can detect and locate, with a resolution of meters, not only leaks, but also dangerous digging activity along the pipeline. This is extremely appealing in cases where an optical cable is already deployed along the pipeline for communication uses.

However, the sensitivity of external leak detection system depends on many parameters. In the case of monitoring an existing pipeline with pre-deployed cables, there is a broad, and sometimes unknown, range of parameters such as the type and installation process of the optical cable that has been deployed, the distance and orientation between the optical cable and the pipeline. These parameters have a strong influence on the measured leak signal, and therefore influence leak detection performance of the system.

Moreover, real leaks are extremely rare. This could lead to a situation in which systems are deployed without verification of the exact system performance.

Therefore, we created an extensive test field for leak simulation comprised of a broad range of different optical cable types, deployed in various ways, at varying distances from pipelines of different cross-sections, in order to simulate an exhaustive range of pre-existing optical cables deployed along existing pipelines.

By varying the pressure in the pipes, and using different orifice diameters, we controlled the leak discharge rates.

Using this versatile test field, we demonstrate the superior leak detection sensitivity of PrismaFlow, detecting gas leaks as small as 200 SLPM using our proprietary Hyper-Scan technology, without relying on momentary effects such as a negative pressure pulse. We also demonstrate the detection capability in different real-life optical cable layouts, at a range of distances from the pipeline and in the presence of strong acoustic background signals.

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