EFFECT OF FLUID CHARACTERIZATION IN MINIMUM MISCIBLE PRESSURE PREDICTION USING MIXING CELL METHOD

Minimum miscibility pressure (MMP) is a key parameter in the design of gas flooding. The methods of predicting MMP include experimental approaches, correlations and equation of state (EOS) methods. This method relies on the EOS to represent the properties of components in reservoir fluid and injected gas over a wide range of conditions. One of the EOS methods to calculate MMP is the mixing cell method. This purpose of this work aims to understand the effect of fluid characterization of predicting MMP using mixing cell method. By accurate characterization of reservoir fluid, different selection of EOS and different tuning parameters may give different prediction in MMP values. In this work the factors are studied by looking at two aspects: 1) Selection of EOS, and 2) the tuning parameters of PVT properties that need to be match in order to predict MMP accurately. This work attempts to investigate the effect of fluid characterization in MMP prediction by the following approaches: 1) comparison of two EOS’s via software approach when calculating MMP and their performance also 2) tuning the EOS to match selected PVT data and observing the predicted MMP from the tuned EOS