Saudi Arabian non associate gas reservoirs produce various amounts of condensate depending upon field and reservoir. In most cases, these wells are hydraulically fractured and at the initial stage after such stimulation treatment, each well needs to unload high quantity of the pumped fluid to ensure full potential. If the liquid starts accumulating in the wellbore during production, the well productivity will gradually decrease and eventually may stop producing. If the gas flow velocity in the production string is high enough, the gas will continue flowing and will carry the liquid droplets up the wellbore to the surface. The minimum velocity and critical gas rate (Qcrit) are therefore the determining factors while producing a well or several wells from a condensate-rich field so as to ensure the stable field production rate and maintain production plateau.

An analytical model has been developed to iteratively compute the critical velocity (Vcrit) and Qcrit, for given flowing wellhead pressure (FWHP), tubing diameter, and many other reservoir and completion properties. If the FWHP is set and a certain production rate is expected of a well, the program automatically computes the pressure drop due to friction, dynamic hydrostatic head, and the bottomhole pressure. Simultaneously, both Vcrit and Qcrit to unload the fluids are calculated. If the Qcrit is above the expected production rate, a different wellbore completion is automatically selected and computation is continued until Qcrit is lower than the expected rate of the well. If this is not possible, the program will display appropriate message.

Several wells from a condensate gas reservoir are analyzed from a field that has to maintain certain production potential for a given number of years. The analyses show that the wells that are producing without intervention are those that are confirmed by this model to be flowing above the Qcrit. For wells that were intermittently producing and ultimately could not sustain production were producing at rates below the critical values. Using this iterative model, those rates are automatically adjusted or new completion string is suggested to bring them back into production.

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