Minimum miscibility pressure (MMP) is one of the key parameters that affects the microscopic and macroscopic effectiveness (displacement performance) of gas injection for enhanced oil recovery. Numerous research efforts have been made to measure and predict the MMP, including experimental, analytical, numerical, and empirical methodologies. Despite these efforts, a comprehensive, user-friendly, and accurate model does not exist yet. In this study, we introduce ‘‘Gene Expression Programming (GEP)” as a novel connectionist tool to determine the MMP parameter. This new model is developed and tested using a large databank available in the literature for theMMPmeasurements. The accuracy of the proposed model is validated and compared with the outcomes from the commercial simulators. The performance of the proposed model is also examined through a systematic parametric sensitivity analysis where various input variables such as temperature and volatile-to-intermediate ratio are considered. The new GEP model outperforms all the published correlations in term of accuracy and reliability.
کلید واژگان :CO2 injection; Minimum miscible pressure (MMP); Gene Expression Programming ;Miscible displacement ;Oil production
ارزش ریالی : 600000 ریال
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