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A new methodology for online tuning of model parameters in a two-phase flow model by taking into account measured data is presented. Important model parameters are tuned using the ensemble Kalman filter. The present study is motivated by applications in underbalanced drilling, although the idea of using the ensemble Kalman filter in tuning of model parameters should be of interest in a wide area of applications. A description of modeling of the two-phase flow in the well is presented, as well as the implementation of the ensemble Kalman filter. The performance of the filter is studied, both using synthetic and experimental data.