Multi-point Acoustic Sensing (MAS) technology makes use of hydrophone sensors placed at discrete distances along pipelines in order to detect third party interference (TPI) and leaks. Leak transients are associated to “rarefaction waves”, and any interaction with the pipe generates pressure (acoustic) waves that are guided within the fluid for long distances, carrying information on the source event. Pressure propagation is mainly governed by the absorption coefficient and the sound speed. These parameters are in turn complicated functions of the signal frequency, the geometrical and elastic parameters of the pipe shell, the elastic parameters of the surrounding medium, and the acoustic and thermodynamic properties of the transported fluid. We have analyzed this last aspect while processing acoustic data collected on crude oil and natural gas transportation pipelines, in different operational and flow conditions. In this paper we describe advanced procedures for the identification and classification of operational situations of the pipeline/fluid system, and the elaboration steps for the experimental derivation of fluid properties.
Advanced pipeline monitoring using multipoint acoustic data
BERNASCONI, GIANCARLO;DEL GIUDICE, SILVIO;
2013-01-01
Abstract
Multi-point Acoustic Sensing (MAS) technology makes use of hydrophone sensors placed at discrete distances along pipelines in order to detect third party interference (TPI) and leaks. Leak transients are associated to “rarefaction waves”, and any interaction with the pipe generates pressure (acoustic) waves that are guided within the fluid for long distances, carrying information on the source event. Pressure propagation is mainly governed by the absorption coefficient and the sound speed. These parameters are in turn complicated functions of the signal frequency, the geometrical and elastic parameters of the pipe shell, the elastic parameters of the surrounding medium, and the acoustic and thermodynamic properties of the transported fluid. We have analyzed this last aspect while processing acoustic data collected on crude oil and natural gas transportation pipelines, in different operational and flow conditions. In this paper we describe advanced procedures for the identification and classification of operational situations of the pipeline/fluid system, and the elaboration steps for the experimental derivation of fluid properties.File | Dimensione | Formato | |
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