利用交替条件变换确定二氧化碳与地层原油体系最小混相压力

Accurate Determination of Minimum Miscibility Pressure( MMP) of CO_2-Oil System Using Graphical Alternating Conditional Expectation

在对国内外29个典型油田的油藏温度、原油组分(C1-N2、C2-C6、M(C7+))进行数理统计的基础上,通过编制交替条件期望变换(ACE)程序,建立了新的MMP(最小混相压力)预测模型。结果表明:基于ACE方法建立的MMP预测关联式与实验测试值吻合程度较高,且能够高效处理大批量数据。与现有经验公式对比表明:改进模型比其他模型具有更高的计算精度和稳定性,平均相对误差(ARE)为5.22%,标准差(SD)为7.87%。另外,基于斯皮尔曼等级相关系数对各影响因素进行敏感性分析,表明C1-N2的摩尔分数和温度是影响MMP的主要因素。

A new MMP prediction model for CO2 miscibility flooding is established using preparing alternative conditional expectation transform（ ACE） program based on the statistical data of the reservoir temperature and the crude oil components such as x（ C1- N2）,x（ C2- C6） and M（ C7 ＋） of 29 oilfields at home and abroad. The predicted MMP values using the model are highly consistent to experimental test values,and to use it can finish the efficient processing of large quantities of data. Compared with the existing empirical formulas,the improved model has higher accuracy and stability,the average relative error（ ARE） is 5. 22%,and the standard deviation（ SD） is 7. 87%. The sensitivity of the influencing factors of MMP of CO2 miscibility flooding is analyzed based on Spielman rank correlation coefficient,and it is shown that the mole fraction of C1- N2 and the reservoir temperature are the main influencing factors of MMP.