Determination of Minimum Miscibility Pressure in Gas Injection Process by Mixing Rules

Miscible gas injection is one of the most effective enhanced oil recovery techniques and minimum miscibility pressure (MMP) is an importand parameter in miscible gas injection processes . Accurate determination of this parameter is critical to an adequate design of injection equipments project investment prospect the purpose of this paper is to develop anew universal artificial neural network (U-ANN) model to prekict the minimum miscibility pressure of CO2 and hydrocarbon gas flooding. different MMP correlations and models have been proposed regarding the type of injection gas and the mechanism of miscibility respectively based on mathematical and thermodynamic calculations. almost all the correlations proposed in the literature either represent condensing / vaporizing mechanisms or give reasonable results only in a limited range of data they based on. a new model is introduced by taking into consideration both condensing and vaporizing mechanisms and by using a wider range of data . experimental data from different crude oil reservoirs carried out by slim tube test have been applied in order to propose a new model in which the both mechanisms are included. mixing rules are used to decrease independent variables. the significance of this model is that MMP can be determined for any composition of oil and gas no matter which mechanism is dominant in achieving miscibility.

کلیدواژه ها:

minimum miscibility pressure (MMP) ، gas injection ، neural network ، mixing rules ، critical property ، slim tube