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Accurate metering of flow rates and prediction of water breakthrough are important issues in offshore oil production. The multiphase flow rates can be found for instance from frequent well testing, from multiphase flow meters, or from software simulations. Multiphase flow meters are very expensive and so are single-well tests, especially in cases with long tiebacks. On the contrary, software simulations are cheap, they can be made accurate, and simulations can usually be based on existing sensors. Also, software is easy to install, operate, and maintain compared to hardware multiphase meters.In this article we describe the main components needed in a flexible software system for flow metering that can handle sparsely instrumented production facilities. Several sources of implicit information are pointed out, and a tuning strategy that avoids single-well tests is described. We also present examples that show the power of advanced simulations in situations that are not well handled by multiphase flow meters and standard software because of very low flow rates. What makes the situation in the examples even harder is that: There is no available information about the choke, the bottom hole sensors fail, and the temperature measurements are influenced by the seawater temperature. Despite this, good results are obtained.

In this note we formulate the Kalman-YakuboviE-Popov Lemma for generalized first-order systems, both in continuous-and discrete-time.

The classical Kalman-Yakubovich-Popov lemma provides a link between dissipativity of a system in state-space form and the solution to a linear matrix inequality. In this paper we derive the KYP lemma for linear systems described by higher-order differential equations. The result is an LMI in terms of the original coefficients in which the dissipativity problem is posed. Subsequently we study the connection between dissipativity and spectral factorization of polynomial matrices. This enables us to derive a new algorithm for polynomial spectral factorization in terms of an LMI in the coefficients of the polynomial matrix.

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