Minimum miscibility pressure(MMP)is a key parameter in the successful design of miscible gases injection such as CO2 flooding for enhanced oil recovery process(EOR).MMP is generally determined through experimental tes...Minimum miscibility pressure(MMP)is a key parameter in the successful design of miscible gases injection such as CO2 flooding for enhanced oil recovery process(EOR).MMP is generally determined through experimental tests such as slim tube and rising bubble apparatus(RBA).As these tests are time-consuming and their cost is very expensive,several correlations have been developed.However,and although the simplicity of these correlations,they suffer from inaccuracies and bad generalization due to the limitation of their ranges of application.This paper aims to establish a global model to predict MMP in both pure and impure CO2-crude oil in EOR process by combining support vector regression(SVR)with artificial bee colony(ABC).ABC is used to find best SVR hyper-parameters.201 data collected from authenticated published literature and covering a wide range of variables are considered to develop SVR-ABC pure/impure CO2-crude oil MMP model with following inputs:reservoir temperature(TR),critical temperature of the injection gas(Tc),molecular weight of pentane plus fraction of crude oil(MWC5+)and the ratio of volatile components to intermediate components in crude oil(xvol/xint).Statistical indicators and graphical error analyses show that SVR-ABC MMP model yields excellent results with a low mean absolute percentage error(3.24%)and root mean square error(0.79)and a high coefficient of determination(0.9868).Furthermore,the results reveal that SVR-ABC outperforms either ordinary SVR with trial and error approach or all existing methods considered in this work in the prediction of pure and impure CO2-crude oil MMP.Finally,the Leverage approach(Williams plot)is done to investigate the realm of prediction capability of the new model and to detect any probable erroneous data points.展开更多
An effective parameter in the miscible-CO_2 enhanced oil recovery procedure is the minimum miscibility pressure(MMP)defined as the lowest pressure that the oil in place and the injected gas into reservoir achieve misc...An effective parameter in the miscible-CO_2 enhanced oil recovery procedure is the minimum miscibility pressure(MMP)defined as the lowest pressure that the oil in place and the injected gas into reservoir achieve miscibility at a given temperature. Flue gases released from power plants can provide an available source of CO_2,which would otherwise be emitted to the atmosphere, for injection into a reservoir. However, the costs related to gas extraction from flue gases is potentially high. Hence, greater understanding the role of impurities in miscibility characteristics between CO_2 and reservoir fluids helps to establish which impurities are tolerable and which are not. In this study, we simulate the effects of the impurities nitrogen(N_2), methane(C_1), ethane(C_2) and propane(C_3) on CO_2 MMP. The simulation results reveal that,as an impurity, nitrogen increases CO_2–oil MMP more so than methane. On the other hand, increasing the propane(C_3)content can lead to a significant decrease in CO_2 MMP, whereas varying the concentrations of ethane(C_2) does not have a significant effect on the minimum miscibility pressure of reservoir crude oil and CO_2 gas. The novel relationships established are particularly valuable in circumstances where MMP experimental data are not available.展开更多
文摘Minimum miscibility pressure(MMP)is a key parameter in the successful design of miscible gases injection such as CO2 flooding for enhanced oil recovery process(EOR).MMP is generally determined through experimental tests such as slim tube and rising bubble apparatus(RBA).As these tests are time-consuming and their cost is very expensive,several correlations have been developed.However,and although the simplicity of these correlations,they suffer from inaccuracies and bad generalization due to the limitation of their ranges of application.This paper aims to establish a global model to predict MMP in both pure and impure CO2-crude oil in EOR process by combining support vector regression(SVR)with artificial bee colony(ABC).ABC is used to find best SVR hyper-parameters.201 data collected from authenticated published literature and covering a wide range of variables are considered to develop SVR-ABC pure/impure CO2-crude oil MMP model with following inputs:reservoir temperature(TR),critical temperature of the injection gas(Tc),molecular weight of pentane plus fraction of crude oil(MWC5+)and the ratio of volatile components to intermediate components in crude oil(xvol/xint).Statistical indicators and graphical error analyses show that SVR-ABC MMP model yields excellent results with a low mean absolute percentage error(3.24%)and root mean square error(0.79)and a high coefficient of determination(0.9868).Furthermore,the results reveal that SVR-ABC outperforms either ordinary SVR with trial and error approach or all existing methods considered in this work in the prediction of pure and impure CO2-crude oil MMP.Finally,the Leverage approach(Williams plot)is done to investigate the realm of prediction capability of the new model and to detect any probable erroneous data points.
文摘An effective parameter in the miscible-CO_2 enhanced oil recovery procedure is the minimum miscibility pressure(MMP)defined as the lowest pressure that the oil in place and the injected gas into reservoir achieve miscibility at a given temperature. Flue gases released from power plants can provide an available source of CO_2,which would otherwise be emitted to the atmosphere, for injection into a reservoir. However, the costs related to gas extraction from flue gases is potentially high. Hence, greater understanding the role of impurities in miscibility characteristics between CO_2 and reservoir fluids helps to establish which impurities are tolerable and which are not. In this study, we simulate the effects of the impurities nitrogen(N_2), methane(C_1), ethane(C_2) and propane(C_3) on CO_2 MMP. The simulation results reveal that,as an impurity, nitrogen increases CO_2–oil MMP more so than methane. On the other hand, increasing the propane(C_3)content can lead to a significant decrease in CO_2 MMP, whereas varying the concentrations of ethane(C_2) does not have a significant effect on the minimum miscibility pressure of reservoir crude oil and CO_2 gas. The novel relationships established are particularly valuable in circumstances where MMP experimental data are not available.
