An Accurate and Reliable Correlation to Determine CO2/Crude Oil MMP for High-Temperature Reservoirs in Abu Dhabi

Abstract

Abstract Minimum miscibility pressure (MMP) is an important parameter in the design of a successful miscible gas injection project. It is common industry-practice to infer MMP from a series of carefully designed slimtube tests, but there are cases where a quick and rough estimate of MMP is required to screen for potential application of miscible gas injection. Mathematical correlations are attractive because they require few input parameters, little information about the fluids, and are quick and easy to use. Whereas MMP using hydrocarbon gas or nitrogen can be predicted with relative confidence using standard correlations, the same level of accuracy is not found for correlations predicting CO2 MMP, in part because of a more complicated temperature-dependent mass transfer. This study is part of an ongoing effort to evaluate miscibility conditions using a variety of injection gases across the ADNOC reservoir fluid portfolio. We have tested the most common existing CO2 MMP correlations against measured MMP data from slimtube tests for a large number of Abu Dhabi reservoir fluids. The results show that none of the existing correlations can accurately predict MMP for these crude oils and we believe that this is attributed to the fact that most available correlations were established based on reservoir temperatures much lower than the typical temperature conditions of 250 °F found in many Abu Dhabi reservoirs. We therefore propose a new correlation for estimating CO2 MMP with particular emphasis on high-temperature fluid systems. The new formulation has been developed based on multiple-parameter regression of measured data as a function of temperature, saturation pressure and reservoir fluids composition. In addition to the existing data sets available in the literature, we performed 17 additional slimtube experiments on different Abu Dhabi reservoir fluids to enlarge the parameter envelope and increase robustness of the model. The proposed new correlation predicts CO2 MMP within 6.4%. To constrain the correlation, we performed a series of EOS-based MMP calculations for several fluids in the temperature range of 100 to 350 °F. These calculations confirm that MMP attains a maximum value around 320 °F.