Soft sensing for gas-lift wells

conference paper
2004
Bloemen, H.H.J.

Belfroid, S.P.C.

Sturm, W.L.

Verhelst, F.J.P.C.M.G.
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.
Topics
AlgorithmsApproximation theoryData acquisitionKalman filteringMathematical modelsMultiphase flowDrift flux parametersDrift-flux modelSoft sensingState-covariance matrixGas lifts
TNO Identifier
280197
Repository link
https://resolver.tno.nl/uuid:ce97a270-bcfb-4e92-9347-2d7f4999e253
Publisher
Society of Petroleum Engineers SPE
Source title
2004 SPE Annual Technical Conference and Exhibition, 26-29 September 2004, Houston, TX, USA
Collation
11 p.
Pages
2381-2391
Files
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