Selection of Passive Inflow Control Devices Based on Dynamic Weight Fuzzy Evaluation

Abstract

In long horizontal wells, early water or gas may breakthrough into the wellbore due to the imbalanced production profile caused by the heel-toe effect, reservoir anisotropic, reservoir heterogeneity or fractureexisting. Once coning occurs, oil production may severely decrease due to the limited flow contribution from the non-coning regions. Inflow control devices (ICDs) are installed to maintain the flow across production zones uniformly by creating an additional pressure drop which cancels out the imbalanced production profile.Since a typical well with ICDs can be in production from 5 to more than 20 years, the long-term reliability of such a device is crucial to the well's overall success. Therefore, the ICDs must exhibit certain performance features during every phase of the well's life, however, the reality is that none of current ICDs alone meet the ideal requirements of an ICD designed, and current ICD selection for a specific reservoir mainly depends on the qualitative awareness of both the reservoir condition and the ICD performance.To make a better selection of the ICDs, dynamic weight theory is introduced into the fuzzy evaluation, and analytic hierarchy process is used for reference, which make the weight of each evaluation index change with the reservoir condition. The optimal membership degrees of these ICDs with varying flow rate, fluid density, and fluid viscosity are first calculated and then compared, which help to develop the ICD selection pattern. With the help of the pattern, we can select the optimal ICD simply and quickly once the reservoir condition is determined, which has the best corrosion resistance and the least viscosity sensitivity.