How to specify and measure sensitivity  in Distributed Acoustic Sensing (DAS)?

Haniel Gabai; Avishay Eyal

doi:10.1117/12.2265527

23 April 2017 How to specify and measure sensitivity in Distributed Acoustic Sensing (DAS)?

Haniel Gabai, Avishay Eyal

Proceedings Volume 10323, 25th International Conference on Optical Fiber Sensors; 103238A (2017) https://doi.org/10.1117/12.2265527
Event: 25th International Conference on Optical Fiber Sensors, 2017, Jeju, Korea, Republic of

Abstract

In Rayleigh-scattering-based Distributed Acoustic Sensing (DAS) an optical fiber is transformed into an array of thousands of 'virtual microphones'. This approach has gained tremendous popularity in recent years and is one of the most successful examples of a fiber-optic sensing method which made its way from the academia to the market. Despite the great amount of work done in this field, sensitivity, which is ones of the most critical parameters of any sensing technique, was rarely investigated in this context. In particular, little attention was given to its random characteristics. Without careful consideration of the random aspects of DAS, any attempt to specify its sensitivity or to compare between different DAS modalities is of limited value. Recently we introduced a new statistical parameter which defines DAS sensitivity and enables comparison between the performances of different DAS systems. In this paper we generalize the previous parameter and give a broader, simple and intuitive definition to DAS sensitivity. An important attribute of these parameters is that they can be easily extracted from the static backscatter profile of the sensing fiber. In the paper we derive the relation between DAS sensitivity and the static backscatter profile and present an experimental verification of this relation.

Citation Download Citation

Haniel Gabai and Avishay Eyal "How to specify and measure sensitivity in Distributed Acoustic Sensing (DAS)?", Proc. SPIE 10323, 25th International Conference on Optical Fiber Sensors, 103238A (23 April 2017); https://doi.org/10.1117/12.2265527

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