Estimation of long term gas condensate well productivity using pressure transient data

Conventional composite models can be used to calculate gas condensate well skin values including that due to condensate banking.However, the calculated skin varies in time as the fluid properties and gas and condensate fractional flow change, hence, making estimation of long term performance of a well unreliable. The dependency of gas and condensate mobility on the flow rate at near well bore conditions makes the problem more challenging.We have addressed this issue by developing an analytical method to use transient well test data to determine gas-condensate relative permeability, accounting for the rate effect, which makes future performance prediction a more reliable task.

Synthetic well test data have been generated by a commercial compositional numerical simulator with and without the rate effect. The impact of including the rate effect in the simulated cases on well test analysis results has been evaluated.The results show that for the cases analysed that the derivative of pressure responses does not necessarily always exhibit a three-radial composite behaviour due to condensate banking, when the rate effect is present, though such behaviour could be exhibited in some cases.

Our developed analytical methodology is based on a technique that allows estimating the reservoir pressure as a function of distance from the well, at the end of the drawdown period, using the bottom-hole pressure value before the shut-in. Once this reservoir pressure profile is available, the actual reservoir pressure gradient as a function of distance is determined, which can be used to calculate the values of gas and condensate relative permeability. Therefore, we show for the first time that it is possible to calculate from pressure transient data the near well gas and oil relative permeability values accounting for the rate effect. The well must be shut in at the bottom of the hole to avoid any wellbore storage effect on pressure build-up. We also show that the size of the two-phase region can be predicted with excellent accuracy using an analytical approach.