Gravity assistance is a critical factor influencing CO_(2)-Oil mixing and miscible flow during EOR and CO_(2)geological storage.Based on the Navier-Stokes equation,component mass conservation equation,and fluid proper...Gravity assistance is a critical factor influencing CO_(2)-Oil mixing and miscible flow during EOR and CO_(2)geological storage.Based on the Navier-Stokes equation,component mass conservation equation,and fluid property-composition relationship,a mathematical model for pore-scale CO_(2) injection in oilsaturated porous media was developed in this study.The model can reflect the effects of gravity assistance,component diffusion,fluid density variation,and velocity change on EOR and CO_(2) storage.For nonhomogeneous porous media,the gravity influence and large density difference help to minimize the velocity difference between the main flow path and the surrounding area,thus improving the oil recovery and CO_(2) storage.Large CO_(2) injection angles and oil-CO_(2) density differences can increase the oil recovery by 22.6% and 4.2%,respectively,and increase CO_(2) storage by 37.9% and 4.7%,respectively.Component diffusion facilitates the transportation of the oil components from the low-velocity region to the main flow path,thereby reducing the oil/CO_(2) concentration difference within the porous media.Component diffusion can increase oil recovery and CO_(2) storage by 5.7% and 6.9%,respectively.In addition,combined with the component diffusion,a low CO_(2) injection rate creates a more uniform spatial distribution of the oil/CO_(2) component,resulting in increases of 9.5% oil recovery and 15.7% CO_(2) storage,respectively.This study provides theoretical support for improving the geological CO_(2) storage and EOR processes.展开更多
The physical model is described by a seepage coupled system for simulating numerically three-dimensional chemical oil recovery, whose mathematical description includes three equations to interpret main concepts. The p...The physical model is described by a seepage coupled system for simulating numerically three-dimensional chemical oil recovery, whose mathematical description includes three equations to interpret main concepts. The pressure equation is a nonlinear parabolic equation, the concentration is defined by a convection-diffusion equation and the saturations of different components are stated by nonlinear convection-diffusion equations. The transport pressure appears in the concentration equation and saturation equations in the form of Darcy velocity, and controls their processes. The flow equation is solved by the conservative mixed volume element and the accuracy is improved one order for approximating Darcy velocity. The method of characteristic mixed volume element is applied to solve the concentration, where the diffusion is discretized by a mixed volume element method and the convection is treated by the method of characteristics. The characteristics can confirm strong computational stability at sharp fronts and it can avoid numerical dispersion and nonphysical oscillation. The scheme can adopt a large step while its numerical results have small time-truncation error and high order of accuracy. The mixed volume element method has the law of conservation on every element for the diffusion and it can obtain numerical solutions of the concentration and adjoint vectors. It is most important in numerical simulation to ensure the physical conservative nature. The saturation different components are obtained by the method of characteristic fractional step difference. The computational work is shortened greatly by decomposing a three-dimensional problem into three successive one-dimensional problems and it is completed easily by using the algorithm of speedup. Using the theory and technique of a priori estimates of differential equations, we derive an optimal second order estimates in 12 norm. Numerical examples are given to show the effectiveness and practicability and the method is testified as a powerful tool to solve the important problems.展开更多
以氢氧化铝干胶和六水合硝酸镍为原料,采用湿混捏法制备不同NiO含量的NiO/Al_(2)O_(3)催化剂,利用N_(2)吸附-脱附、XRD、NH_(3)-TPD、TPR和Py-IR等方法对所制备催化剂进行表征,以溴指数为4300 mg(100 g Br)的重整生成油为评价原料对所...以氢氧化铝干胶和六水合硝酸镍为原料,采用湿混捏法制备不同NiO含量的NiO/Al_(2)O_(3)催化剂,利用N_(2)吸附-脱附、XRD、NH_(3)-TPD、TPR和Py-IR等方法对所制备催化剂进行表征,以溴指数为4300 mg(100 g Br)的重整生成油为评价原料对所制备催化剂进行选择加氢脱烯烃活性评价。实验结果表明,在NiO含量30%~50%(w)的范围内,随着NiO含量的增加,NiO/Al_(2)O_(3)催化剂的比表面积和孔体积逐渐减小,平均孔径增大,总酸量增加,NiO的粒径逐渐增大;NiO/Al_(2)O_(3)催化剂只有L酸,没有B酸,NiO含量为30%(w)时,NiO晶粒较小,分散相对均匀,芳烃加氢率最高,烯烃选择加氢活性较低;NiO含量大于40%(w)时,NiO晶粒逐渐变大,出现镍铝尖晶石晶相,芳烃加氢活性降低,烯烃加氢选择性增加。展开更多
This article discusses the enhanced oil recovery numerical simulation of the chemical flooding(such as surfactants, alcohol, polymers) composed of two-dimensional multicomponent, ultiphase and incompressible mixed flu...This article discusses the enhanced oil recovery numerical simulation of the chemical flooding(such as surfactants, alcohol, polymers) composed of two-dimensional multicomponent, ultiphase and incompressible mixed fluids. After the oil field is waterflooded, there is still a large amount of crude oil left in the oil deposit. By adding certain chemical substances to the fluid injected, its driving capacity can be greatly increased. The mathematical model of two-dimensional enhanced oil recovery simulation can be described展开更多
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
基金The project supported by National Natural Science Foundation of China(No.51991364,51974347)the Major Scientific and Technological Projects of CNPC under Grant ZD2019-184-002。
文摘Gravity assistance is a critical factor influencing CO_(2)-Oil mixing and miscible flow during EOR and CO_(2)geological storage.Based on the Navier-Stokes equation,component mass conservation equation,and fluid property-composition relationship,a mathematical model for pore-scale CO_(2) injection in oilsaturated porous media was developed in this study.The model can reflect the effects of gravity assistance,component diffusion,fluid density variation,and velocity change on EOR and CO_(2) storage.For nonhomogeneous porous media,the gravity influence and large density difference help to minimize the velocity difference between the main flow path and the surrounding area,thus improving the oil recovery and CO_(2) storage.Large CO_(2) injection angles and oil-CO_(2) density differences can increase the oil recovery by 22.6% and 4.2%,respectively,and increase CO_(2) storage by 37.9% and 4.7%,respectively.Component diffusion facilitates the transportation of the oil components from the low-velocity region to the main flow path,thereby reducing the oil/CO_(2) concentration difference within the porous media.Component diffusion can increase oil recovery and CO_(2) storage by 5.7% and 6.9%,respectively.In addition,combined with the component diffusion,a low CO_(2) injection rate creates a more uniform spatial distribution of the oil/CO_(2) component,resulting in increases of 9.5% oil recovery and 15.7% CO_(2) storage,respectively.This study provides theoretical support for improving the geological CO_(2) storage and EOR processes.
基金Supported by the National Natural Science Foundation of China(11101124 and 11271231)Natural Science Foundation of Shandong Province(ZR2016AM08)National Tackling Key Problems Program(2011ZX05052,2011ZX05011-004)
文摘The physical model is described by a seepage coupled system for simulating numerically three-dimensional chemical oil recovery, whose mathematical description includes three equations to interpret main concepts. The pressure equation is a nonlinear parabolic equation, the concentration is defined by a convection-diffusion equation and the saturations of different components are stated by nonlinear convection-diffusion equations. The transport pressure appears in the concentration equation and saturation equations in the form of Darcy velocity, and controls their processes. The flow equation is solved by the conservative mixed volume element and the accuracy is improved one order for approximating Darcy velocity. The method of characteristic mixed volume element is applied to solve the concentration, where the diffusion is discretized by a mixed volume element method and the convection is treated by the method of characteristics. The characteristics can confirm strong computational stability at sharp fronts and it can avoid numerical dispersion and nonphysical oscillation. The scheme can adopt a large step while its numerical results have small time-truncation error and high order of accuracy. The mixed volume element method has the law of conservation on every element for the diffusion and it can obtain numerical solutions of the concentration and adjoint vectors. It is most important in numerical simulation to ensure the physical conservative nature. The saturation different components are obtained by the method of characteristic fractional step difference. The computational work is shortened greatly by decomposing a three-dimensional problem into three successive one-dimensional problems and it is completed easily by using the algorithm of speedup. Using the theory and technique of a priori estimates of differential equations, we derive an optimal second order estimates in 12 norm. Numerical examples are given to show the effectiveness and practicability and the method is testified as a powerful tool to solve the important problems.
文摘以氢氧化铝干胶和六水合硝酸镍为原料,采用湿混捏法制备不同NiO含量的NiO/Al_(2)O_(3)催化剂,利用N_(2)吸附-脱附、XRD、NH_(3)-TPD、TPR和Py-IR等方法对所制备催化剂进行表征,以溴指数为4300 mg(100 g Br)的重整生成油为评价原料对所制备催化剂进行选择加氢脱烯烃活性评价。实验结果表明,在NiO含量30%~50%(w)的范围内,随着NiO含量的增加,NiO/Al_(2)O_(3)催化剂的比表面积和孔体积逐渐减小,平均孔径增大,总酸量增加,NiO的粒径逐渐增大;NiO/Al_(2)O_(3)催化剂只有L酸,没有B酸,NiO含量为30%(w)时,NiO晶粒较小,分散相对均匀,芳烃加氢率最高,烯烃选择加氢活性较低;NiO含量大于40%(w)时,NiO晶粒逐渐变大,出现镍铝尖晶石晶相,芳烃加氢活性降低,烯烃加氢选择性增加。
基金This project is sponsored by the National Scaling Programthe National Eighth-Five-Year Tackling Key Problems Program
文摘This article discusses the enhanced oil recovery numerical simulation of the chemical flooding(such as surfactants, alcohol, polymers) composed of two-dimensional multicomponent, ultiphase and incompressible mixed fluids. After the oil field is waterflooded, there is still a large amount of crude oil left in the oil deposit. By adding certain chemical substances to the fluid injected, its driving capacity can be greatly increased. The mathematical model of two-dimensional enhanced oil recovery simulation can be described
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.
