The paper will present a system, jointly developed by ENEA, ENI-AGIP E&P Division, GAMMATOM and University of Rome in the frame of an EU project, aimed at providing enhanced monitoring and diagnostics functionality for multiphase transportation flowlines. The system has been installed and tested in the Trecate Multiphase Test Loop. In the first section the paper will present a Data Fusion approach to improve the performance capability of multiphase flowmeters, exploiting techniques such as neural networks and fuzzy logic. In the second part, it will describe the application of the Data Fusion approach within the MEF (Multiphase Expert Flowmeter) system. The third section will present an approach for multiphase flowline diagnostics, based on fluid dynamic simulation and tuning.

ENHANCING MULTIPHASE FLOWLINE MONITORING AND DIAGNOSTICS USING DATA FUSION AND SIMULATION TECHNIQUES / M., Annunziato; I., Bertini; R., Bruschi; S., Lopez; S., Pizzuti; Alimonti, Claudio; A., Mazzoni; M., Piantanida; R., Busnelli. - STAMPA. - (1999). ((Intervento presentato al convegno 9th Int. Conf. Multiphase ‘99 tenutosi a Cannes (F) nel 16-19 Giugno.

ENHANCING MULTIPHASE FLOWLINE MONITORING AND DIAGNOSTICS USING DATA FUSION AND SIMULATION TECHNIQUES

ALIMONTI, Claudio;
1999

Abstract

The paper will present a system, jointly developed by ENEA, ENI-AGIP E&P Division, GAMMATOM and University of Rome in the frame of an EU project, aimed at providing enhanced monitoring and diagnostics functionality for multiphase transportation flowlines. The system has been installed and tested in the Trecate Multiphase Test Loop. In the first section the paper will present a Data Fusion approach to improve the performance capability of multiphase flowmeters, exploiting techniques such as neural networks and fuzzy logic. In the second part, it will describe the application of the Data Fusion approach within the MEF (Multiphase Expert Flowmeter) system. The third section will present an approach for multiphase flowline diagnostics, based on fluid dynamic simulation and tuning.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/203815
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