Real time monitoring of a fluid transportation system is still a challenging matter, due to the complexity of the asset and a continuous demand of sustainability. The current frontier is a re-design of the information management during the asset lifecycle, with the digitalization and collection of large datasets which are used to infer “data driven” solutions. This paper presents a monitoring strategy based on the medium/long term detection and tracking of “smart indicators” of the oil & gas transportation system operations. The indicators exploit the digital vibroacoustic signals recorded by proprietary stations located on the conduit at an inter-distance of around 20 km. The collected data are analysed on a long-term basis, together with the measurements coming from other instruments (i.e. temperature, density, flow rate), in order to highlight small variations in the pipeline, which move the operational parameters to new states. As an example, sound speed, and attenuation are inverted for the fluid composition and the inner pipe condition. The correlation analysis of the signals recorded in consecutive pipeline segments, interpreted as an equivalent acoustic channel, reveals pipe deformations and/or flow anomalies. We show a case history of an oil trunkline in Nigeria, conveying a variable ratio water-oil mixture, with an inter-distance between the stations along the pipeline at about 17 km. We derive from the long-term and medium-term database some key parameters, which are the actual input for automatic digital monitoring algorithms.

Pipeline digital monitoring based on vibroacoustic measurements

Bernasconi G.;Bondi L.
2019

Abstract

Real time monitoring of a fluid transportation system is still a challenging matter, due to the complexity of the asset and a continuous demand of sustainability. The current frontier is a re-design of the information management during the asset lifecycle, with the digitalization and collection of large datasets which are used to infer “data driven” solutions. This paper presents a monitoring strategy based on the medium/long term detection and tracking of “smart indicators” of the oil & gas transportation system operations. The indicators exploit the digital vibroacoustic signals recorded by proprietary stations located on the conduit at an inter-distance of around 20 km. The collected data are analysed on a long-term basis, together with the measurements coming from other instruments (i.e. temperature, density, flow rate), in order to highlight small variations in the pipeline, which move the operational parameters to new states. As an example, sound speed, and attenuation are inverted for the fluid composition and the inner pipe condition. The correlation analysis of the signals recorded in consecutive pipeline segments, interpreted as an equivalent acoustic channel, reveals pipe deformations and/or flow anomalies. We show a case history of an oil trunkline in Nigeria, conveying a variable ratio water-oil mixture, with an inter-distance between the stations along the pipeline at about 17 km. We derive from the long-term and medium-term database some key parameters, which are the actual input for automatic digital monitoring algorithms.
Offshore Mediterranean Conference and Exhibition 2019, OMC 2019
9788894043679
vibroacoustic monitoring, pipeline, digital, machine leraning, data driven relations
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1120343
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