Soft sensing for gas-lift wells

Title

Soft sensing for gas-lift wells

 Author

Bloemen, H.H.J.
Belfroid, S.P.C.
Sturm, W.L.
Verhelst, F.J.P.C.M.G.
Technisch Physische Dienst TNO - TH

Publication year

2004

 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.

 Subject

Machines
Algorithms
Approximation theory
Data acquisition
Kalman filtering
Mathematical models
Multiphase flow
Drift flux parameters
Drift-flux model
Soft sensing
State-covariance matrix
Gas lifts

 To reference this document use:

http://resolver.tudelft.nl/uuid:ce97a270-bcfb-4e92-9347-2d7f4999e253

 TNO identifier

280197

 Publisher

Society of Petroleum Engineers SPE

 Source

2004 SPE Annual Technical Conference and Exhibition, 26-29 September 2004, Houston, TX, USA, 2381-2391

 Document type

conference paper
Files
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