Soft sensing for two-phase flow using an ensemble Kalman filter

A new approach for real-time monitoring of horizontal wells, which is based on data assimilation concepts, is presented. Such methodology can be used when the direct measurement of multiphase flow rates is unfeasible or even unavailable. The real-time estimator proposed is an ensemble Kalman filter employing a dynamic model of the pipe flow and information from several downhole pressure sensors with a single measurement of the flow velocity and composition. By means of simulation examples it is shown that the proposed algorithm operates quite accurately both for noisy synthetic measurements and artificial data generated by the OLGA simulator