Method, medium and apparatus for determining the relationship between temperature and equilibrium distribution properties of solvent deasphalting

Abstract

The present disclosure relates to a method for determining the relationship between temperature and equilibrium distribution properties during solvent deasphalting. The method comprises: establishing molecular average structural models corresponding to each of the four residual oil components and C3-C5 light hydrocarbon solvent molecules; establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules based on each of the molecular average structural models; performing kinetic simulations on each of the stable amorphous unit cells at different temperatures to obtain kinetic models of oil phase-oil phase molecules and solvent-solvent molecules; calculating solubility parameters between the four residual oil components and between the solvent molecules based on each kinetic model; and determining the corresponding equilibrium distribution properties of the four components in the residual oil-light hydrocarbon mixture at different temperatures based on the respective solubility parameters and experimental data at a specific temperature. This solution can reduce tedious experimental trial and error, lower costs, improve efficiency, and thus guide the optimization of the solvent deasphalting process.

Description

Technical Field

[0001] The present disclosure relates to the field of petroleum processing, and in particular, to a method, medium, and apparatus for determining the relationship between solvent deasphalting temperature and equilibrium partition properties. Background Art

[0002] Currently, solvent deasphalting, a method for processing residual oil, is rapidly developing due to the widespread trend toward heavier crude oils and stringent quality requirements for petroleum products. Solvent deasphalting is a physical process involving liquid-liquid extraction, separating the components of residual oil using a solvent. Controlling the solvent's solubility is primarily achieved through changes in extraction temperature.

[0003] Currently, due to the extremely complex composition of residual oil and the significant differences in properties between different sources, the selection of extraction temperature for different sources and separation requirements relies primarily on extensive operational experience and experimental data. This approach is time-consuming, cumbersome, and subject to significant uncertainty, making it inconvenient in practical applications. Summary of the Invention

[0004] The purpose of the present disclosure is to provide a method, medium and equipment for determining the relationship between the temperature and equilibrium distribution properties of solvent deasphalting to solve the above technical problems.

[0005] To achieve the above objectives, the present disclosure provides, in a first aspect, a method for determining the relationship between solvent deasphalting temperature and equilibrium partition properties, comprising:

[0006] Establish the molecular average structure model corresponding to each molecule in the four components of residual oil and C3-C5 light hydrocarbon solvent molecules;

[0007] Establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules;

[0008] Performing dynamic simulation on each of the stable amorphous unit cells at different temperatures to obtain dynamic models of the oil phase-oil phase molecules and the solvent-solvent molecules;

[0009] Calculating the solubility parameters between the four components of the residual oil and between the solvent molecules according to each of the kinetic models;

[0010] Based on the solubility parameters and experimental data at specific temperatures, the equilibrium distribution properties of the four-component molecules in the residue oil-light hydrocarbon mixture system at different temperatures are determined.

[0011] Optionally, the establishing of the molecular average structure model corresponding to each molecule in the four components of the residual oil and the C3-C5 light hydrocarbon solvent molecules includes:

[0012] Establish the initial molecular average structure model corresponding to each molecule in the four components of residual oil and C3-C5 light hydrocarbon solvent molecules;

[0013] The initial molecular average structure model is geometrically optimized using an energy minimization method to obtain a molecular average structure model corresponding to each molecule.

[0014] Optionally, establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules comprises:

[0015] Establishing the initial amorphous unit cells of the oil phase-oil phase molecules and the solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules;

[0016] The initial amorphous unit cell is geometrically optimized using an energy minimization method to obtain the stable amorphous unit cell.

[0017] Optionally, the initial amorphous unit cell is established using an Amorphous Cell module with periodic boundary conditions.

[0018] Optionally, the number of molecules in the unit cell of the initial amorphous unit cell is 50, the initial density is 0.4 g / L, and annealing is performed using an NVT ensemble.

[0019] Optionally, performing dynamic simulation on each of the stable amorphous unit cells at different temperatures includes:

[0020] The dynamic simulation conditions are a temperature range of 323 to 463 K, a pressure range of 0.004 GPa, and a time step range of 2000 to 5000 ps, ​​and the dynamic simulation of the stable amorphous unit cell is performed.

[0021] Optionally, determining the equilibrium distribution properties of the four-component molecules in the residue oil-light hydrocarbon mixture system at different temperatures based on the solubility parameters and experimental data at a specific temperature includes:

[0022] Calculating the first equilibrium distribution coefficient of the four-component molecules in the solvent at the specific temperature based on the experimental data;

[0023] Calculating the first type activity coefficient between each of the four component molecules and the solvent at different temperatures based on each of the solubility parameters; and

[0024] Under the assumption that the activity coefficients between the four component molecules remain unchanged, calculating the second type activity coefficient between the four component molecules at the specific temperature by combining the first equilibrium partition coefficient and the first type activity coefficient;

[0025] By analyzing the second type activity coefficient at the specific temperature and the first type activity coefficient at different temperatures, the equilibrium partition coefficient and extraction rate of the four component molecules of the residual oil in the solvent at different temperatures are predicted, and the equilibrium partition properties include the extraction rate and the equilibrium partition coefficient.

[0026] Optionally, the equilibrium distribution properties further include one or more of the composition of four-component molecules in the deasphalted oil at different temperatures, the composition of four-component molecules in the deoiled asphalt, the mass yield of the deasphalted oil, and the mass yield of the deoiled asphalt.

[0027] Optionally, the oil phase molecules include one or more of asphaltenes, resins, aromatic components and saturates.

[0028] Optionally, the solvent molecules include one or more of propane, n-butane, isobutane, n-pentane, isopentane, and cyclopentane.

[0029] A second aspect of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when the program is executed by a processor.

[0030] A third aspect of the present disclosure provides an electronic device, including:

[0031] a memory having a computer program stored thereon;

[0032] A processor is used to execute the computer program in the memory to implement the steps of the method of the first aspect.

[0033] The above technical solution utilizes a molecular average structure model and kinetic simulations during the solvent deasphalting process to simulate the behavior between the four residue oil components and the solvent molecules, analyzing and calculating their solubility parameters. Using only a set of experimental data and solubility parameters, the equilibrium distribution properties of the four residue oil components can be calculated, thereby predicting the extraction yields of the four residue oil components at different temperatures and enabling rapid selection of extraction temperatures based on separation requirements. This solution reduces tedious trial-and-error experiments, lowers costs, and improves efficiency, thereby guiding the optimization of the solvent deasphalting process. This has practical implications for the stable operation of solvent deasphalting units and the optimization of deasphalting processes.

[0034] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0036] Figure 1 A flow chart illustrating the relationship between temperature and equilibrium partition properties for determining solvent deasphalting is provided by an exemplary embodiment;

[0037] Figure 2 A flowchart showing a specific implementation of step S110 provided by an exemplary embodiment is shown;

[0038] Figure 3 A schematic diagram showing a representative average structural model of the four-component molecules of residual oil;

[0039] Figure 4 A flowchart showing a specific implementation of step S120 provided by an exemplary embodiment is shown;

[0040] Figure 5 A flowchart showing a specific implementation of step S150 provided by an exemplary embodiment is shown;

[0041] Figure 6 A block diagram of an electronic device provided by an exemplary embodiment is shown.

[0042] Reference numerals:

[0043] S-saturates; A-aromatics; R-resin; Asp-asphaltene. DETAILED DESCRIPTION

[0044] The following describes the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure and are not intended to limit the present disclosure.

[0045] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0046] As previously mentioned, during the solvent deasphalting process, temperature directly affects the extraction rate of the solvent deasphalting process. However, existing solvent deasphalting devices do not consider the impact of temperature and, because they involve an oil-light hydrocarbon solvent mixture system, cannot simulate the equilibrium distribution properties of oil-phase molecules in the oil-light hydrocarbon solvent mixture system. Furthermore, the existing technology divides the oil product into several pseudo-components according to the distillation range and uses experimental data regression to calculate their interaction parameters for prediction. This method is not suitable for solvent deasphalting processes that achieve separation through component polarity differences.

[0047] In this regard, the disclosed embodiments provide a method for determining the relationship between solvent deasphalting temperature and equilibrium distribution properties. Based on an oil-light hydrocarbon solvent mixture system, an initial molecular average structure model is constructed through modeling. After constructing the initial molecular average structure model, the model is optimized to obtain a molecular average structure model. An amorphous unit cell is constructed based on the molecular average structure model. After optimizing the unit cell, a stable amorphous unit cell is obtained. Dynamic simulations are performed on the stable amorphous unit cell at different temperatures to obtain a kinetic model. Based on the kinetic model, solubility parameters are calculated. The equilibrium distribution properties corresponding to oil phase molecules at different temperatures in the oil-light hydrocarbon solvent mixture system can be predicted based on the solubility parameters and a set of experimental data at a specific temperature. The equilibrium distribution properties characterize the extraction rate and the equilibrium distribution coefficient.

[0048] This method, based on a set of data, can predict the equilibrium distribution properties of oil-phase molecules in advance, thereby identifying the optimal extraction temperature that meets production requirements. The solvent deasphalting unit can then be adjusted based on the predicted optimal extraction temperature. This provides practical guidance for the stable operation of solvent deasphalting units and the optimization of the deasphalting process.

[0049] Figure 1 A flow chart showing the relationship between the temperature and equilibrium partition properties of solvent deasphalting is provided in accordance with an exemplary embodiment. Figure 1 As shown, the method includes:

[0050] S110, establishing a molecular average structure model corresponding to each molecule in the four components of the residual oil and the C3-C5 light hydrocarbon solvent molecules.

[0051] Specifically, a molecular average structure model corresponding to each molecule of the four components of the residual oil is established; and a molecular average structure model corresponding to each molecule of the C3-C5 light hydrocarbon solvent is established.

[0052] It is worth noting that the four-component molecules of residual oil are the components obtained after the residual oil is eluted with different solvents in column chromatography, namely: saturates, aromatics, colloids and asphaltenes.

[0053] S120, establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each molecule.

[0054] Specifically, a stable amorphous unit cell of oil phase-oil phase molecules is established based on the molecular average structure model corresponding to each molecule of the four components of residual oil; a stable amorphous unit cell of solvent-solvent molecules is established based on the molecular average structure model corresponding to each molecule of C3-C5 light hydrocarbon solvent.

[0055] S130, performing dynamic simulation on each stable amorphous unit cell at different temperatures to obtain a dynamic model of oil phase-oil phase molecules and solvent-solvent molecules.

[0056] Specifically, the stable amorphous unit cells of oil phase-oil phase molecules are kinetically simulated at different temperatures to obtain the kinetic model of oil phase-oil phase molecules; the stable amorphous unit cells of solvent-solvent molecules are kinetically simulated at different temperatures to obtain the kinetic model of solvent-solvent molecules.

[0057] S140, calculating the solubility parameters between the molecules of the four components of the residual oil and between the molecules of the solvent according to various kinetic models.

[0058] Specifically, the solubility parameters between the four components of the residual oil are calculated based on the oil phase-oil phase molecule kinetic model; and the solubility parameters between the solvent molecules are calculated based on the solvent-solvent molecule kinetic model.

[0059] Based on the fully balanced stable amorphous unit cells corresponding to each molecule obtained after optimization in step S120, the Cohesive Energy Density (CED) in the Forcite module is used to calculate the solubility parameters δ corresponding to the different structural molecules of each molecule in the four components of the residual oil and the C3-C5 light hydrocarbon solvent molecules, and the calculated results are averaged.

[0060] In addition, MS software can also be used to calculate parameters such as density and molar volume of molecules with different structures. For example, Table 1 shows the change in density of vacuum residue molecules with temperature, Table 2 shows the change in solubility parameters of vacuum residue molecules with temperature, and Table 3 shows the change in density, molar volume, and solubility parameters of C3-C5 light hydrocarbon solvents with temperature.

[0061] Table 1

[0062]

[0063] Table 2

[0064]

[0065]

[0066] Table 3

[0067]

[0068] The suitable operating temperature is generally 5 to 40 K lower than the critical temperature of the solvent. As can be seen from Tables 1 and 2, the suitable operating temperature range of propane is 323 to 363 K, the suitable operating temperature range of n-butane is 373 to 413 K, and the suitable operating temperature range of n-pentane is 423 to 463 K.

[0069] The data in the table show that as the number of aromatic rings in the molecular structure increases and the number of alkyl side chains decreases, the density and solubility parameter of the model molecule increase. Cycloalkane molecules have higher density and solubility parameters than paraffin molecules. Notably, cycloalkane molecules also have higher density than alkyl aromatic molecules with very long side chains, but their solubility parameters are lower than those of alkyl aromatic molecules. Both the density and solubility parameters of the vacuum residue model molecule decrease with increasing temperature.

[0070] Among them, the decreases in the S-alk, AO, and A-2B molecules were significant. These three molecules share a common structural characteristic: they have no or very few aromatic rings and possess very long alkyl chains. The changes in the S-cyl and AN molecules were minimal. Both molecules contain multiple cycloalkane rings and very short alkyl side chains. This demonstrates the significant influence of the molecular model of the alkyl side chain structure on the thermal sensitivity of the molecular solubility parameters. The changes in the RS, R-lsc, R-ssc, and Asp molecules decreased with increasing aromatic ring count and decreasing alkyl side chains. It can be concluded that in vacuum residue, the effect of temperature on resins and asphaltenes is weaker than on saturates and aromatics, which is consistent with experimental observations.

[0071] Table 3 shows that the solubility parameters of propane, n-butane, and n-pentane are primarily contributed by van der Waals interactions. As temperature increases, the density and solubility parameters of small alkane solvents decrease. This is primarily due to the intensified molecular thermal motion and increased intermolecular distances caused by increasing temperature. Van der Waals forces, which decrease with increasing distance, are the primary forces acting between small alkanes. Consequently, intermolecular interactions in alkane solvents decrease with increasing temperature. Given the same temperature fluctuation, the solubility parameters of light hydrocarbons vary much more than those of residual oil molecules.

[0072] S150, based on the solubility parameters and experimental data at specific temperatures, determine the equilibrium distribution properties of the four-component molecules in the residue oil-light hydrocarbon mixture at different temperatures.

[0073] Specifically, based on the solubility parameters between the four components of the residual oil, the solubility parameters between the solvent molecules, and the experimental data at a specific temperature, the different equilibrium distribution properties of the four components of the residual oil-light hydrocarbon mixture at different temperatures can be determined.

[0074] In the above scheme, first, based on the molecular average structure model corresponding to each molecule, a stable amorphous unit cell corresponding to each molecule is established, and at different temperatures, the stable amorphous unit cell corresponding to each molecule is subjected to dynamic simulation to obtain a kinetic model of the oil phase molecules and the oil phase molecular structure, as well as a kinetic model of the solvent molecules and the solvent molecular structure. According to the kinetic model, the solubility parameters between each oil phase molecule and between each solvent molecule are calculated. Based on the solubility parameters and the experimental data at a specific temperature, the equilibrium distribution properties corresponding to the oil phase molecules at different temperatures in the oil-light hydrocarbon solvent mixture system are calculated.

[0075] Therefore, this scheme can not only take into account the influence of temperature in the oil-light hydrocarbon solvent mixture system, but also obtain the equilibrium distribution properties corresponding to the oil phase molecules at different temperatures through only one set of experimental data and kinetic models, which has practical guiding significance for the optimization of the solvent deasphalting process.

[0076] Figure 2 FIG. 1 is a flowchart showing a specific implementation of step S110 provided by an exemplary embodiment. Figure 2 As shown, step S110 includes:

[0077] S111, establishing an initial molecular average structure model corresponding to each molecule in the four-component residue oil molecules and the C3-C5 light hydrocarbon solvent molecules.

[0078] Specifically, an initial molecular average structural model corresponding to each molecule in the four components of the residual oil is established; an initial molecular average structural model corresponding to each molecule in the C3-C5 light hydrocarbon solvent is established. The initial molecular average structural model represents an unoptimized average structural model.

[0079] For example, the initial molecular average structure model corresponding to each molecule in the four-component residual oil molecules and the C3-C5 light hydrocarbon solvent molecules can be established using Material Studio (MS) software, that is, the structures of each molecule in the four-component residual oil molecules and the C3-C5 light hydrocarbon solvent molecules are drawn separately in the MS software, and the initial molecular average structure model of each molecule is formed by the MS software.

[0080] Illustratively, the MS software may be the MS software developed by BIOVIA Corporation of the United States.

[0081] like Figure 3 Shown is a schematic diagram showing a representative average structural model of the four-component molecules of residual oil.

[0082] There are 10 representative average structural models of the four components of residue oil. Among them, S1-S2, A1-A4, and R1-R3 molecules are the average molecular structures of the G&D model, and asphaltene molecules are the average molecular structure of Tahe asphaltene.

[0083] S112, using an energy minimization method to perform geometric optimization on the initial molecular average structure model to obtain a molecular average structure model corresponding to each molecule.

[0084] Specifically, the energy minimization method is used to geometrically optimize the initial molecular average structural model corresponding to each molecule in the four components of residual oil, and the molecular average structural model corresponding to each molecule in the four components of residual oil is obtained; the energy minimization method is used to geometrically optimize the initial molecular average structural model corresponding to each molecule in the C3~C5 light hydrocarbon solvent molecules, and the molecular average structural model corresponding to each molecule in the C3~C5 light hydrocarbon solvent molecules is obtained.

[0085] For example, MS software can also be used to optimize the initial molecular average structural model corresponding to each of the four residual oil components and the C3-C5 light hydrocarbon solvent molecules. The initial molecular average structural model is geometrically optimized using an energy minimization method to obtain a molecular structural model with the lowest energy conformation, i.e., the molecular average structural model.

[0086] Specifically, for the optimization process of the initial molecular average structure model, the Forcite module in the MS software was used, the calculation accuracy was fine, the force field was COMPASSⅡ, the electrostatic interaction adopted the Ewald summation method, the van der Waals interaction adopted the Groupbased summation method, the temperature control function adopted the Nose method, and the pressure control function adopted the Berendsen method.

[0087] In addition, the operations of steps S120 to S140 can all be performed in the MS software.

[0088] In this scheme, the initial molecular average structural model corresponding to each molecule is then geometrically optimized using energy minimization to obtain the molecular average structural model. Therefore, this scheme can produce a stable molecular average structural model, which has practical guiding significance for optimizing the solvent deasphalting process.

[0089] Figure 4 FIG. 4 is a flowchart showing a specific implementation of step S120 provided by an exemplary embodiment. Figure 4 As shown, step S120 includes:

[0090] S121, establishing initial amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each molecule.

[0091] Specifically, based on the molecular average structure model corresponding to each molecule in the optimized four-component residual oil molecules obtained above, the initial amorphous unit cell of oil phase-oil phase molecules is established; based on the molecular average structure model corresponding to each molecule in the optimized C3~C5 light hydrocarbon solvent molecules obtained above, the initial amorphous unit cell of solvent-solvent molecules is established.

[0092] S122, the energy minimization method is used to perform geometric optimization on the initial amorphous unit cell to obtain a stable amorphous unit cell.

[0093] Specifically, the energy minimization method is used to geometrically optimize the initial amorphous unit cell corresponding to each molecule in the four-component residual oil molecules, and the stable amorphous unit cell corresponding to each molecule in the four-component residual oil molecules is obtained; the energy minimization method is used to geometrically optimize the initial amorphous unit cell corresponding to each molecule in the C3~C5 light hydrocarbon solvent molecules, and the stable amorphous unit cell corresponding to each molecule in the C3~C5 light hydrocarbon solvent molecules is obtained.

[0094] Optionally, in step S121 and step S122, the initial amorphous unit cell is established using the Amorphous Cell module with periodic boundary conditions; the number of molecules in the unit cell of the initial amorphous unit cell is set to 50, the initial density is set to 0.4 g / mL, and annealing is performed using a canonical ensemble.

[0095] For example, based on the average structure models of 50 optimized molecules, the Amorphous Cell module is used to establish an initial amorphous unit cell model with an initial density of 0.4 g / mL; then the initial amorphous unit cell model is geometrically optimized, and the optimized unit cell model is annealed using a canonical ensemble at a temperature of 300-700K. Among the conformations obtained after annealing, the model with the lowest energy conformation is selected, which is the stable amorphous unit cell model.

[0096] In this scheme, the initial amorphous unit cell corresponding to each molecule is established based on the obtained average molecular structure model. Then, the geometry is optimized through energy minimization to obtain a stable amorphous unit cell. Therefore, this scheme can produce a stable unit cell model structure, which has practical guiding significance for optimizing the solvent deasphalting process.

[0097] In an exemplary embodiment, step S130 includes performing a dynamic simulation on the stable amorphous unit cell with a temperature ranging from 323 to 463 K, a pressure ranging from 0.004 GPa, and a time step ranging from 2000 to 5000 ps as dynamic simulation conditions.

[0098] For example, the stable amorphous unit cell obtained in step S120 is subjected to a 5000 ps molecular dynamics simulation using an isothermal and isobaric ensemble at a temperature in the range of 323 to 463 K and a pressure of 0.004 GPa.

[0099] Among them, the applicable temperature range of propane in the solvent deasphalting process is 323~363K, the applicable temperature range of butane in the solvent deasphalting process is 373~413K, and the applicable temperature range of pentane in the solvent deasphalting process is 323~463K; the commonly used pressure in the solvent deasphalting process is 0.004GPa.

[0100] For example, in the temperature range of 323-463K and the pressure of 0.004GPa, an isothermal and isobaric ensemble is used to perform a 2000ps dynamic simulation on the model of the last frame in the previous step, and a 2000ps dynamic simulation is performed again with the last frame as the structural model to examine whether the average density of two consecutive trajectory files is the same; if the same, it means that the model is fully balanced; if different, repeat this step until the average density of two consecutive trajectory files is the same.

[0101] Figure 5 FIG. 4 is a flowchart showing a specific implementation of step S150 provided by an exemplary embodiment. Figure 5 As shown, step S150 includes:

[0102] S151, calculating the first equilibrium distribution coefficient of the four-component molecules in the solvent at a specific temperature based on experimental data.

[0103] It should be noted that for each molecule in the four-component system, the residual oil-light hydrocarbon mixture is defined as the equilibrium partition system consisting of the molecule of that component, the set of molecules of all other components except that component, and the solvent. When the actual system is a multi-component liquid-liquid equilibrium partition system, to simplify the calculation, the multi-component system is divided into four independent ternary systems (ABS) based on the four components. For each ternary system, one of the four components is designated as A, the set of the other components is designated as B, and the solvent used is designated as S.

[0104] For example, in the residue oil-light hydrocarbon mixed system, saturated hydrocarbons are set as solute A, the collection of aromatic hydrocarbons, colloids and asphaltenes is set as solute B, and the solvent used is set as S.

[0105] For example, for a ternary liquid-liquid equilibrium distribution system of an ABS, the two-phase distribution of the liquid-liquid equilibrium can be expressed by the first equilibrium distribution coefficient m, which is calculated as follows:

[0106]

[0107] Among them, γ A,S represents the activity coefficient of solute A in solvent S, γ A,B It represents the activity coefficient of solute A in solute B, and X is the mass fraction.

[0108] S152, calculating the first type activity coefficients between each of the four component molecules and the solvent at different temperatures based on the solubility parameters.

[0109] S153, assuming that the activity coefficients between the four component molecules remain unchanged, the second type activity coefficients between the four component molecules at a specific temperature are calculated by combining the first equilibrium partition coefficient and the first type activity coefficient.

[0110] Among them, the first type of activity coefficient represents the activity coefficient of the four-component molecules in the solvent, that is, the activity coefficient γ of the solute A in the solvent S mentioned above A,S The second type of activity coefficient represents the activity coefficient between the four component molecules, that is, the activity coefficient of solute A in solute B is γ A,B .

[0111] According to formula (1), it can be concluded that the change of the first equilibrium distribution coefficient mainly depends on the first type activity coefficient γ A,S and the second kind activity coefficient γ A,B According to the formal solution theory, the first-type activity coefficient γ A,S The calculation formula is as follows:

[0112]

[0113] Among them, V A represents the molar volume of solute A, Φ S represents the volume fraction of solvent S in the system, δ A represents the solubility parameter of solute A, δ S represents the solubility parameter of solvent S, R represents the thermodynamic constant 8.314, and T represents the thermodynamic temperature.

[0114] Among them, V A It can be calculated by the model molecular weight and the molecular density in Table 1, Φ S The first-class activity coefficient γ can be calculated based on the agent-oil ratio used in the experiment. A,S .

[0115] According to formula (2), the first type activity coefficient γ A,S The value of is easy to calculate. The second type activity coefficient γ A,B The value of is difficult to calculate because in the set residue oil-light hydrocarbon mixture system, solute B contains many components. In order to accurately calculate the second type activity coefficient γ A,BThe process is very complicated.

[0116] As mentioned above, the effect of temperature on the intermolecular forces of the four components is much smaller than that on the solvent molecules. As can be seen from Table 3, with the exception of the saturated fraction, the solubility parameters of most of the four components of the residual oil vary very little with temperature.

[0117] Therefore, it is assumed that in the same system, the second type activity coefficient γ A,B is a constant that does not change with temperature, ignoring the effect of temperature on the intermolecular forces of the four components of the residual oil. This means that the change of the first equilibrium distribution coefficient is only affected by the first type activity coefficient γ A,S impact.

[0118] By performing weighted average calculation on the model molecules of the four components of the residual oil, the first-class activity coefficients γ of the four components at different temperatures in C3-C5 light hydrocarbon solvents can be obtained. A,S As shown in Table 4, the γ values ​​of the four-component molecules in the solvent at different temperatures are shown. A,S value.

[0119] Table 4

[0120]

[0121] S154, by analyzing the second-type activity coefficient at a specific temperature and the first-type activity coefficient at different temperatures, the equilibrium distribution coefficient and extraction rate of the four-component molecules of the residual oil in the solvent at different temperatures are predicted. The equilibrium distribution properties include the extraction rate and the equilibrium distribution coefficient.

[0122] For the real system, the equilibrium distribution coefficient m of the four components of the residual oil i It can be calculated by the following formula:

[0123]

[0124] Among them, m i represents the equilibrium distribution coefficient of the four components of residual oil, i represents the components in the oil (i.e., saturates, aromatics, resins, and asphaltenes), X represents the mass fraction, E represents deasphalted oil, R represents deoiled asphalt, and Yield represents the relevant yield.

[0125] Combining formula (1) and formula (3), we can get the following formula:

[0126]

[0127] Among them, m i Represents the equilibrium distribution coefficient of the four components of residual oil, EP i It represents the extraction rate of the four components of residual oil.

[0128] Based on formula (4), the extraction rate and equilibrium distribution coefficient of the four component molecules in the residue oil-light hydrocarbon mixture system can be converted to each other.

[0129] Based on the above scheme, the first equilibrium distribution coefficient of the four components at a specific temperature can be obtained through a set of experimental data, and the first equilibrium distribution coefficient and the first type activity coefficient γ A,S Calculate the second-type activity coefficient γ A,B Assuming the second type activity coefficient γ A,B Once the equilibrium distribution coefficient and extraction rate at different temperatures are calculated, the optimal temperature can be determined based on the separation requirements by calculating the extraction rates of the four components in the residue oil-light hydrocarbon mixture at different temperatures.

[0130] For example, as shown in Table 5, different properties of different residual oils from Fujian and Binzhou are shown.

[0131] Table 5

[0132]

[0133] For example, the residual oil of Fujian reduced residue was selected for kinetic simulation, the solvent used was selected as n-butane, the temperature of the kinetic simulation was set to 393K, the pressure of the kinetic simulation was set to 4MPa, and the solvent-oil volume ratio used in the kinetic simulation was 6:1. The simulation experimental results are shown in Table 6.

[0134] Table 6

[0135]

[0136] For example, under the above conditions, the equilibrium distribution coefficient and extraction rate of the four-component molecules in n-butane solvent under these conditions can be calculated according to formula (3) and formula (4); the activity coefficient γ between the four-component molecules under the experimental conditions can be calculated according to formula (1) and formula (2). A,B , that is, the second type activity coefficient, and can be calculated to predict the extraction rate of the four-component molecules in n-butane solvent under the temperature of 373~413K, as shown in Table 7, which shows the extraction rate of Fujian residual oil in deasphalting in n-butane solvent.

[0137] Table 7

[0138]

[0139]

[0140] For example, an experiment was conducted on a solvent deasphalting unit using residual oil from Wuhan residue. The solvent used was n-butane. The experimental temperatures were 380K and 412K, respectively. The experimental pressure was 4 MPa. The solvent-to-oil volume ratio used in the experiment was 6:1. The experimental results were compared with the calculated results in the embodiment, as shown in Table 8, which shows a comparison table of experimental and simulated values ​​of the extraction rates of the four-component molecules in the deasphalting process in n-butane solvent at different temperatures.

[0141] Table 8

[0142]

[0143] In addition, the sources of the data used in this disclosure are shown in Table 9.

[0144] Table 9

[0145]

[0146] In the above scheme, the solubility parameters calculated in step S140 are first used, using the activity coefficient method based on regular solution theory and a first equilibrium partition coefficient calculated from experimental data at a specific temperature, to calculate the equilibrium partition coefficients and extraction yields of the four components at different temperatures in a residual oil-light hydrocarbon mixture. Therefore, this scheme can account for the effects of temperature in an oil-light hydrocarbon solvent system and has practical guiding significance for optimizing the solvent deasphalting process.

[0147] Figure 6 FIG. 6 is a block diagram of an electronic device 600 according to an exemplary embodiment. Figure 6 As shown, the electronic device 600 may include: a processor 601 , a memory 602 , and may further include one or more of a multimedia component 603 , an input / output (I / O) interface 604 , and a communication component 605 .

[0148] The processor 601 is used to control the overall operation of the electronic device 600 to complete all or part of the steps in the above-mentioned method for determining the relationship between the temperature and the equilibrium partition property of solvent deasphalting. The memory 602 is used to store various types of data to support the operation of the electronic device 600. Such data may include, for example, instructions for any application or method operating on the electronic device 600, as well as application-related data, such as contact information, sent and received messages, images, audio, video, etc. The memory 602 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 603 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 602 or transmitted via the communication component 605. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more thereof, is not limited here. Therefore, the corresponding communication component 605 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0149] In an exemplary embodiment, the electronic device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-mentioned method for determining the relationship between the temperature and equilibrium distribution properties of solvent deasphalting.

[0150] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When executed by a processor, the program instructions implement the steps of the aforementioned method for determining the relationship between the solvent deasphalting temperature and the equilibrium partition property. For example, the computer-readable storage medium may be the aforementioned memory 602 including the program instructions. The program instructions may be executed by the processor 601 of the electronic device 600 to perform the aforementioned method for determining the relationship between the solvent deasphalting temperature and the equilibrium partition property.

[0151] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the scope of protection of the present disclosure.

[0152] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0153] In addition, the various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for determining the relationship between solvent deasphalting temperature and equilibrium partition properties, characterized in that: include: Establish the molecular average structure model corresponding to each molecule in the four components of residual oil and C3~C5 light hydrocarbon solvent molecules; Establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules; Performing dynamic simulation on each of the stable amorphous unit cells at different temperatures to obtain dynamic models of the oil phase-oil phase molecules and the solvent-solvent molecules; Calculating the solubility parameters between the four components of the residual oil and between the solvent molecules according to each of the kinetic models; Determining the equilibrium distribution properties of the four-component molecules in the residue oil-light hydrocarbon mixture at different temperatures based on the solubility parameters and experimental data at specific temperatures; The determination of the equilibrium distribution properties of the four-component molecules in the residue oil-light hydrocarbon mixture system at different temperatures based on the solubility parameters and experimental data at specific temperatures includes: Calculating the first equilibrium distribution coefficient of the four-component molecules in the solvent at the specific temperature based on the experimental data; Calculating the first type activity coefficient between each of the four component molecules and the solvent at different temperatures based on each of the solubility parameters; and Under the assumption that the activity coefficients between the four component molecules remain unchanged, calculating the second type activity coefficient between the four component molecules at the specific temperature by combining the first equilibrium partition coefficient and the first type activity coefficient; By analyzing the second type activity coefficient at the specific temperature and the first type activity coefficient at different temperatures, the equilibrium partition coefficient and extraction rate of the four component molecules of the residual oil in the solvent at different temperatures are predicted, and the equilibrium partition properties include the extraction rate and the equilibrium partition coefficient.

2. The method according to claim 1, characterized in that The establishment of the molecular average structure model corresponding to each molecule in the four components of the residual oil and the C3-C5 light hydrocarbon solvent molecules includes: Establish the initial molecular average structure model corresponding to each molecule in the four components of residual oil and C3~C5 light hydrocarbon solvent molecules; The initial molecular average structure model is geometrically optimized using an energy minimization method to obtain a molecular average structure model corresponding to each molecule.

3. The method according to claim 1, characterized in that The step of establishing stable amorphous unit cells of oil phase-oil phase molecules and solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules comprises: Establishing the initial amorphous unit cells of the oil phase-oil phase molecules and the solvent-solvent molecules according to the molecular average structure model corresponding to each of the molecules; The energy minimization method is used to perform geometric optimization on the initial amorphous unit cell to obtain the stable amorphous unit cell.

4. The method according to claim 3, characterized in that The initial amorphous unit cell is established using the AmorphousCell module with periodic boundary conditions.

5. The method according to claim 4, characterized in that The number of molecules in the unit cell of the initial amorphous unit cell is 50, the initial density is 0.4 g / L, and annealing is performed using an NVT ensemble.

6. The method according to claim 1, characterized in that The performing dynamic simulation on each of the stable amorphous unit cells at different temperatures comprises: The dynamic simulation of the stable amorphous unit cell is performed under the dynamic simulation conditions of a temperature range of 323-463 K, a pressure range of 0.004 GPa, and a time step range of 2000-5000 ps.

7. The method according to claim 1, characterized in that The equilibrium distribution properties also include one or more of the composition of the four-component molecules in the deasphalted oil at different temperatures, the composition of the four-component molecules in the deoiled asphalt, the mass yield of the deasphalted oil, and the mass yield of the deoiled asphalt.

8. The method according to any one of claims 1 to 7, characterized in that The oil phase molecules include one or more of asphaltenes, colloids, aromatic components and saturates.

9. The method according to any one of claims 1 to 7, characterized in that The solvent molecules include one or more of propane, n-butane, isobutane, n-pentane, isopentane, and cyclopentane.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 7.

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