A new empirical model for predicting flue gas miscibility for light oils

Abstract

It is typical to observe a decline in production rate and a decrease in reservoir pressure after oil reservoirs have been allowed to produce for a long time. Miscible flooding is a tertiary recovery method for enhancing the reservoirs’ sweep efficiency. During miscible injection, gasses such as carbon dioxide, natural gas, and nitrogen are employed to increase production levels. Carbon dioxide is commonly used as a miscible gas, but less abundant and more expensive than nitrogen. Flue gas, a mixture of carbon dioxide and nitrogen gas, is often used to replace pure carbon dioxide. For this study, flue gasses with the compositions, 15% of carbon dioxide, 85% of nitrogen gas and 30% of carbon dioxide,70% of nitrogen gas, are used as the injection gas to develop an empirical correlation for minimum miscibility pressure (MMP) for candidate light oil reservoirs that have been previously waterflooded. In data analysis and data analytics, the dataset was separated into two groups at random: the training set, which consists of 80% of the entire dataset, and the testing set, which made up 20% of the total dataset. The independent variables employed for model development include temperature, oil sample oil gravity, molecular percentage of carbon dioxide in the injection gas, the molecular weight of hexane plus in the oil, and the molecular percentage of intermediates. The findings reveal that the newly built model is more accurate and delivers better predictions than the existing correlations. For the testing dataset, the new model predicts flue gas MMP with an average absolute percentage error of 5.5519% and a correlation coefficient of 0.92.