Technology meets nature, A unique approach for optimized pipeline monitoring and leak detection

Proceedings Publication Date:

07 Sep 2017
Presenter
Cindy Verhoeven
Presenter
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Author
Cindy Verhoeven
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Abstract
Operators apply many tactics to manage pipeline integrity. This paper discusses limitations of modern techniques for finding small leaks and illegal tappings, as well as their exact location. Unneccessary environmental risks and high costs for soil remediation are inevitable when applied leak detection methods are unable to demonstrate the desired accuracy and reliability. Years of dedication and experience lead to a unique solution: leak detection dogs. A Dogs’ sniffing capabilities lie in the range of parts-per-billion, making it possible to identify the tyniest gas or oil leaks in a pipeline with the highest precision in a short period of time. A comparative study on a German Propylene pipeline, was evaluated by Tüv Nord confirming the effectiveness of leak detetction dogs. A Belgian comparative test again confirmed the added value of sniffing dogs. In two Belgian test cases the dogs showed superior results: Tracking down gas leaks in industrial environments and identifying simulated leaks of products (ethylene, propylene and butane) in different types of terrain with a depth of cover of +1 m. The accuracy of the dogs’ nose comes naturally. A special selection procedure and intensive training protocol, are critical to ensure efficiency, reliability, repeatability and therefore credibility for leak detection in various terrains and circumstances. The paper also discusses the suitability of the dogs to find illegal tappings. During the survey of 800km Ethylene pipeline with two dog teams, mobile PIMS software PERSEUS, was used to track the walking position and pipeline route and to communicate pipeline data back to the head office real time. To further increase the efficiency of surveying pipelines with dogs, other available layers of pipeline data such as CIP and DCVG data can be entered in the PIMS software. This method allows identification of pipeline sections with the highest risk for leaks.

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