Soft Sensing for Gas-Lift Wells

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Conference object 26 Sep 2004 Netherlands Publisher:SPEJournal:SPE Annual Technical Conference and Exhibition

Authors: Bloemen, H.H.J.; Belfroid, S.P.C.; Sturm, W.L.; Verhelst, F.J.P.C.M.G.;

doi: 10.2118/90370-ms , 10.2118/90370-pa

Soft Sensing for Gas-Lift Wells

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Abstract

Abstract This paper considers the use of extended Kalman Filtering as a soft-sensing technique for gas-lift wells. This technique is deployed for the estimation of dynamic variables that are not directly measured. Possible applications are the estimation of flow rates from pressure measurements or the estimation of parameters of a drift-flux model. By means of simulation examples different configurations of sensor systems are analyzed. The estimation of drift-flux model parameters is demonstrated on real data from a laboratory set-up.

Country

Netherlands

Related Organizations

Delft University of Technology
Netherlands

Keywords

Sensor data fusion, Mathematical models, Drift flux parameters, Approximation theory, Data acquisition, Computer simulation, Oil wells, Flow rates, Drift-flux model, Gas lifts, Soft sensing, State-covariance matrix, Multiphase flow, Pressure measurement, Drift-flux, Kalman filtering, Algorithms

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