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A new approach for predicting oil recovery factor during immiscible CO2 flooding in sandstones using dimensionless numbers

机译:一种利用无量纲数预测砂岩中不混溶CO2驱油期间石油采收率的新方法

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摘要

CO2 injection is one of the most promising techniques to enhance oil recovery.The most favorable properties of CO2 made this method popular and it has been widely used since 1950.Experimentally,the effect of CO2 injection on incremental oil recovery is widely measured by the core-flooding approach.An accurate estimation of the recovery factor is required to analyze the performance of the method to design the enhanced oil recovery method successfully.Hence,knowledge of the effects of different parameters on recovery is essential.Various reported experimental CO2 core-flooding data for the immiscible condition in sandstones were analyzed to develop the parametric relationships affecting ultimate oil recovery using data analytics.Selected data support a wide range of porosity(10.8-37.2),permeability(1-18000 mD),injection pressure(2.73-11.44 MPa),injection rate(0.1-1.0 cm3/min),and crude oil types,which enhance the methodology used to develop more comprehensive dimensionless numbers and correlations to predict the oil recovery.Series of new dimensionless numbers were defined and used for the study to develop a correlation for predicting oil recovery factor.Capillary number,relative radius,injection pressure ratio,and oil composition number are used as dimensionless numbers in our approach.The oil recovery prediction by the developed correlation was in agreement with the experimental data.The proposed correlation shows that capillary number is the most effective parameter when predicting oil recovery.
机译:CO2注入是提高石油采收率的最有前途的技术之一。CO2最有利的特性使该方法广受欢迎,自1950年以来被广泛使用,实验上,CO2注入对增量石油采收率的影响被广泛采用岩心驱法测量。需要准确估计采收率,以分析该方法的性能,以成功设计出提高采收率的方法。因此,了解不同参数对恢复的影响至关重要。分析了砂岩中不混溶条件的各种报告的CO2岩心堆场实验数据,以利用数据分析来开发影响最终石油采收率的参数关系。所选数据支持宽范围的孔隙度(10.8-37.2%)、渗透率(1-18000 mD)、注入压力(2.73-11.44 MPa)、注入速率(0.1-1.0 cm3/min)和原油类型,增强了用于开发更全面的无量纲数和相关性来预测石油采收率的方法。定义了一系列新的无量纲数,并用于研究,以建立预测石油采收率的相关性。在我们的方法中,毛细管数、相对半径、注射压力比和油成分数作为无量纲数。所开发的相关性预测的石油采收率与实验数据一致。所提出的相关性表明,毛细管数是预测石油采收率的最有效参数。

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