Improvement of CO2 MMP Correlations by Incorporating Paraffinicity Factor

• Main Author: Muhammad Syahmi Azri Md Zanil, Muhammad Syahmi Azri
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2012
• Online Access: http://utpedia.utp.edu.my/5791/1/DISSERTATIONsyahmi.pdf; http://utpedia.utp.edu.my/5791/

Enhanced Oil Recovery (EOR) implies oil recovery technique beyond the conventional recovery stages of primary or secondary recovery. Out of several extensive methods, miscible gas displacement has been widely used in some of the field in Malaysia. Due to the location at the offshore, CO2 gas injection was chose to be employed as the EOR technique. The key to successful gas displacement efficiency is to have a reservoir pressure greater than a minimum miscibility pressure (MMP). The MMP has been defined as the minimum pressure at which the injected gas and the oil become miscible with each other. A high degree of accuracy is needed for predicting the outcome of the gas injection process for it is known as a very costly operation. Empirical correlations were often used to predict the MMP during the preliminary study. The aim of this study is to reduce the error of the prediction by correlation. To alleviate the error of prediction, parafinicty factor is incorporated into the correlation. In order to develop accurate predictive compositional models, it is necessary to have at one's disposal many experimental data. This study suggests incorporating the parafinicity factor into the correlation to further characterize the oil composition and reduce the error. A total of 72 MMP measurements from the literature were used to assess the Maklavani (2001), Sebastian (1985), Cronquist (1977) and Yellig (1980) correlations. Parafinicity factor was used to further characterize the correlation which will increase accuracy.. It was demonstrated in this study that some correlations predictions would give huge error of predictions. Several correlations are eliminated from improvement and Yellig et Metcalfe is finally chosen for improvement.