An analytical model for performance prediction of miscible flooding methods

  • Omar Elkhatib
  • Mahmoud Abu El Ela Faculty of Engineering - Cairo University
  • Ahmed El-Banbi
  • El-Sayed El-Tayeb
  • Mohamed Helmy Sayyouh

Abstract

The main target of this study is to develop fast and efficient analytical model that can predict reservoir performance under the implementation of miscible flooding processes. The developed model uses upgraded fractional flow theories and several areal sweep efficiency models to predict several performance parameters with time including oil, water and solvent flow rates in conjunction with the cumulative production of the field.

Unlike previous attempts in this topic, the developed model accounts for reservoir instability factors such as reservoir heterogeneity, viscous fingering behavior and gravity segregation. Besides, the effects of loss of miscibility and dispersion on residual oil saturation to miscible flooding are considered. In addition, it accounts for different Enhanced Oil Recovery (EOR) injection strategies including: continuous solvent injection and simultaneous Water Alternate Gas (WAG) injection in both secondary and tertiary miscible displacement modes. Moreover, the model has been extended to account for different injection patterns including line drive and 5-spot.

The model was validated against two actual field applications: (1) the WAG injection pilot project of Slaughter field, and (2) the miscible flooding pilot project of Garber field (continuous solvent slug injection project). The study indicates that the results of the developed model are almost consistent with the actual performance of the two pilot applications. The results of the model deviate from the results of the field measurements with a range of 7.3 to 20.4%. This match demonstrated the ability and the strength of the developed model.

This model utilizes a limited set of input data that is available in the field at the early stages of the reservoir life. Therefore, it can be used as a pre-simulation tool to support the decision-making during the critical technology selection phase.

Published
2022-05-22
Section
Petroleum Engineering