Summary: | Distributed optical fiber sensors (OFS) are very promising candidates for remote online-monitoring of pipelines, above or below ground as well as underwater. Usage of OFS is a very interesting way for environmental monitoring of this kind, owing to advantages including resistance to electromagnetic interference, durability under extreme temperatures and pressures, high sensing speed, light weight, small size, and flexibility. In particular, phase-sensitive Optical Time Domain Reflectometry (F-OTDR) can provide for sensitive and prompt detection of vibro-acoustic signals. It can be useful for leakage or other malfunctioning detection along the pipeline or also for monitoring of processes in wells. Leakage of hydrocarbon products from a pipeline not only represents loss of natural resources, but it also poses a serious and dangerous environmental pollution, in addition to the risk of fire disaster. Suitable diagnostic systems need to be used to monitor gas and oil pipelines in order to early detect and precisely locate leakage problems. Furthermore, by specific analysis of the backscattered signals, ϕ-OTDR sensors can detect unwanted activities (intrusion or drilling or others) in proximity of the pipeline. To achieve such detection capability, a single-mode optical fiber is laid along the pipeline and it is continuously interrogated by a narrow-linewidth 1.55 µm laser in order to detect vibrations and acoustic perturbations in proximity of the fiber and pipeline itself. Sensing with ϕ-OTDR in wells makes it possible to raise the quantity and quality of information from well seismic observations, for monitoring the hydraulic fracturing and extracting of hydrocarbons. Also this technology allows cost reduction of the operations. In this paper, a real-time distributed oil and gas pipeline security pre-warning system based on the ϕ-OTDR technology is proposed. The experimental platform is established in the laboratory and some trials have been performed in the field over a pipeline length of 180 km in Yakutia (RU) ...
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