Method and device for determining molecular composition of catalytic slurry oil by supercritical extraction

Abstract

This specification provides a method and apparatus for determining the molecular composition of catalytic slurry supercritical extraction. Based on the composition content, the compositional weight of each catalytic slurry molecule in its respective lumped component is determined, and molecular-lumped correspondence data is established. Based on molecular properties and compositional weights, the lumped physical property data of each lumped component is determined. Based on the lumped physical property data, the molecular structure descriptor of each lumped component is determined. Based on the molecular structure descriptor and supercritical extraction solvent information, the binary interaction parameters between the supercritical extraction solvent and each lumped component are determined. Phase equilibrium calculations are performed using the supercritical extraction solvent information, lumped physical property data, binary interaction parameters, and extraction operating conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and raffinate phase. Based on the molecular-lumped correspondence data and compositional weights, the molecular-level composition results of the extract phase and / or raffinate phase are obtained.

Description

Technical Field

[0001] This specification belongs to the field of petrochemical technology, and in particular relates to a method and apparatus for determining the molecular composition of catalytic oil slurry supercritical extraction. Background Technology

[0002] Catalytic slurry is a heavy byproduct of catalytic cracking units, with a complex molecular composition. Extraction using supercritical hydrocarbon solvents can separate the light, usable components from the heavy aromatic components. However, current techniques typically divide catalytic slurry into several pseudo-components for phase equilibrium calculations. During the lumping process, molecular composition and content relationships are easily lost, making it difficult to accurately obtain molecular-level composition information of the extract phase and raffinate phase.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This specification provides a method and apparatus for determining the molecular composition of supercritical catalytic oil slurry extraction, which solves the technical problem that existing technologies easily lose molecular composition and content relationships during the lumped calculation of catalytic oil slurry, making it difficult to accurately obtain molecular-level composition information of the extract phase and raffinate phase.

[0005] This specification provides a method for determining the molecular composition of catalytic supercritical oil extraction, including: Acquire catalytic oil slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic oil slurry molecular composition data includes the composition, content, and molecular properties of multiple catalytic oil slurry molecules; Based on the molecular properties, the plurality of catalytic slurry molecules are divided into multiple lumped components; based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecular-lumped correspondence data is established. Based on the molecular properties and the composition weights, determine the lumped property data of each lumped component; based on the lumped property data, determine the molecular structure descriptor of each lumped component; based on the molecular structure descriptor and the supercritical extraction solvent information, determine the binary interaction parameters between the supercritical extraction solvent and each lumped component. Phase equilibrium calculations are performed using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase. Based on the molecular-lumped correspondence data and the composition weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

[0006] In one embodiment, obtaining the molecular composition data of the catalytic oil slurry includes: Obtain gas chromatography-mass spectrometry analysis data, nuclear magnetic resonance analysis data, elemental analysis data, and simulated distillation analysis data of catalytic oil slurry samples; Based on the gas chromatography-mass spectrometry analysis data, the core molecules of the catalytic slurry were determined; Based on the nuclear magnetic resonance analysis data, the elemental analysis data, and the simulated distillation analysis data, the compositional distribution of the core molecule is constrained using a probability density function; The target physical property is determined based on the composition distribution, and the relative error between the predicted and experimental values ​​of the target physical property is used as the objective function. The parameters of the probability density function are optimized using a genetic algorithm to obtain the molecular composition data of the catalytic oil slurry.

[0007] In one embodiment, the step of dividing the plurality of catalytic slurry molecules into a plurality of lumped components based on the molecular properties includes: Based on at least one of the boiling point, molecular weight, aromatic carbon ratio, and structural family type of each catalytic oil slurry molecule, determine the lumped interval corresponding to each catalytic oil slurry molecule; Based on the lumped interval, each of the catalytic oil slurry molecules is divided into the corresponding lumped component.

[0008] In one embodiment, determining the compositional weight of each catalytic slurry molecule in its respective lumped component based on the compositional content, and establishing molecule-lumped component correspondence data, includes: Based on the composition content of each catalytic oil slurry molecule, the composition content of catalytic oil slurry molecules belonging to the same lumped component is normalized to determine the composition weight of each catalytic oil slurry molecule in its respective lumped component. Based on the lumped component to which each of the catalytic oil slurry molecules belongs and the composition weight, establish the molecule-lumped component correspondence data; The molecular-lumen correspondence data is stored in the form of a mapping matrix, mapping table, or index table, and the composition weights are normalized molar weights or normalized mass weights.

[0009] In one embodiment, determining the lumped property data of each lumped component based on the molecular properties and the compositional weights includes: Based on the molecular properties and corresponding compositional weights of the catalytic oil slurry molecules in each of the lumped components, the molecular properties are weighted according to composition to determine the equivalent physical properties of each of the lumped components; The equivalent physical properties are determined as the lumped physical property data of the corresponding lumped components; The equivalent physical properties include at least one of the following: equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio.

[0010] In one embodiment, determining the binary interaction parameters between the supercritical extraction solvent and each of the lumped components based on the molecular structure descriptor and the supercritical extraction solvent information includes: Based on the equivalent properties of each of the aggregated components, the corresponding molecular structure descriptor is determined; wherein, the molecular structure descriptor includes at least one of the following: equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, number of aromatic rings, and solubility parameter; Obtain experimental data on the yield of deasphalted oil under multiple experimental extraction conditions; Based on the experimental data of deasphalted oil yield, the model parameters of the binary interaction parameter correlation equation were determined; Based on the model parameters and the molecular structure descriptors of each lumped component, the binary interaction parameters between the supercritical extraction solvent and each lumped component are determined.

[0011] In one embodiment, the step of performing phase equilibrium calculations using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase includes: The supercritical extraction solvent and the feed composition of each of the aggregated components are determined based on the solvent-to-oil ratio in the extraction operation conditions. Using the lumped physical property data and the binary interaction parameters, the supercritical extraction solvent and the fugacity coefficients of each of the lumped components are determined by a preset equation of state. Phase stability analysis and flash evaporation calculations are performed based on the fugacity coefficients to determine the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase.

[0012] This specification provides an apparatus for determining the molecular composition of catalytic slurry supercritical extraction, comprising: The data acquisition module is used to acquire catalytic oil slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic oil slurry molecular composition data includes the composition content and molecular properties of multiple catalytic oil slurry molecules; The data determination module is used to divide the plurality of catalytic slurry molecules into multiple lumped components according to the molecular properties; determine the composition weight of each catalytic slurry molecule in its respective lumped component according to the composition content, and establish molecule-lumped component correspondence data; The parameter determination module is used to determine the lumped property data of each lumped component based on the molecular properties and the composition weights; determine the molecular structure descriptor of each lumped component based on the lumped property data; and determine the binary interaction parameters between the supercritical extraction solvent and each lumped component based on the molecular structure descriptor and the supercritical extraction solvent information. The allocation result determination module is used to perform phase equilibrium calculations using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operation conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase. The composition result determination module is used to allocate the lumped-level phase allocation result to the corresponding catalytic slurry molecules according to the molecular-lumped correspondence data and the composition weight, so as to obtain the molecular-level composition result of the extract phase and / or the raffinate phase.

[0013] This specification also provides an electronic device, including a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements a method for determining the molecular composition of catalytic oil slurry supercritical extraction.

[0014] This specification also provides a computer-readable storage medium storing computer instructions that, when executed, implement a method for determining the molecular composition of catalytic oil slurry supercritical extraction.

[0015] Based on the method for determining the molecular composition of catalytic slurry supercritical extraction provided in this specification, the following steps are taken: Molecular composition data of the catalytic slurry, supercritical extraction solvent information, and extraction operation conditions are obtained. The molecular composition data of the catalytic slurry includes the composition content and molecular properties of multiple catalytic slurry molecules. According to the molecular properties, the multiple catalytic slurry molecules are divided into multiple lumped components. Based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecule-lumped component correspondence data is established. Based on the molecular properties and the composition weight, the lumped property data of each lumped component is determined. Based on the lumped property data, the individual... The molecular structure descriptor of the lumped components is determined; based on the molecular structure descriptor and the supercritical extraction solvent information, the binary interaction parameters between the supercritical extraction solvent and each of the lumped components are determined; phase equilibrium calculations are performed using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase allocation results of each of the lumped components in the extract phase and the raffinate phase; based on the molecular-lumped correspondence data and the composition weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and / or the raffinate phase. In this way, by determining the lumped components and their weights based on the molecular properties and composition of the catalytic oil slurry molecules, and establishing molecular-lumped correspondence data, phase equilibrium calculations are performed based on the lumped physical property data and binary interaction parameters. Then, the lumped-level phase allocation results are distributed to the corresponding catalytic oil slurry molecules according to the molecular-lumped correspondence data and their weights. This allows the composition and content of the catalytic oil slurry molecules and their corresponding relationships to be retained during the lumping process, thereby accurately obtaining the molecular-level composition results of the extract phase and the raffinate phase. Attached Figure Description

[0016] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of a method for determining the molecular composition of catalytic oil slurry supercritical extraction, provided in one embodiment of this specification. Figure 2 This is a schematic diagram of the electronic device structure provided in one embodiment of this specification; Figure 3 This is a schematic diagram of the structural composition of a device for determining the molecular composition of catalytic oil slurry supercritical extraction, provided in one embodiment of this specification. Figure 4This is a schematic diagram illustrating the construction and experimental characterization verification of a catalytic oil slurry molecular composition model, provided in one embodiment of this specification. Figure 5 This is a schematic diagram illustrating the traceable aggregation of catalytic oil slurry molecules according to boiling point ranges, provided in one embodiment of this specification. Figure 6 This is a schematic diagram illustrating the composition and equivalent physical properties of a 22-component oil slurry aggregate provided in one embodiment of this specification; Figure 7 This is a schematic diagram illustrating the number of catalytic oil slurry molecules and their raw material composition weights within each oil slurry aggregate component, as provided in one embodiment of this specification. Figure 8 This is a schematic diagram illustrating an embodiment of this specification for determining the binary interaction parameters of solvent-oil slurry lumped components based on a lumped structure descriptor; Figure 9 This is a schematic diagram of a supercritical extraction phase equilibrium calculation route after lumped dimension reduction, provided in one embodiment of this specification; Figure 10 This is a schematic diagram showing experimental values, model calculation values, and calculation errors of deasphalted oil yield under different temperature and pressure conditions, provided as an embodiment of this specification. Figure 11 This is a schematic diagram of the composition of each aggregated component of the oil slurry in the extract phase and raffinate phase under typical operating conditions, and the enrichment coefficient of the extract phase relative to the composition of the feedstock, provided by an embodiment of this specification. Figure 12 This is a schematic diagram of the molecular-level DBE (density-carbon molar content) bubble distribution of a feedstock catalytic slurry, extract phase, and raffinate phase, provided in one embodiment of this specification. Figure 13 This is a schematic diagram of the functional structure of a molecular-level modeling device suitable for supercritical extraction and separation of catalytic oil slurry, provided as an embodiment of this specification. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0019] See Figure 1As shown in the embodiments of this specification, a method for determining the molecular composition of catalytic oil slurry supercritical extraction is provided, wherein the method is specifically applied on the server side. In specific implementation, the method may include the following: S101: Obtain catalytic oil slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic oil slurry molecular composition data includes the composition content and molecular properties of multiple catalytic oil slurry molecules; S102: Based on the molecular properties, the plurality of catalytic slurry molecules are divided into a plurality of lumped components; based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecular-lumped component correspondence data is established; S103: Determine the lumped property data of each lumped component based on the molecular properties and the composition weights; determine the molecular structure descriptor of each lumped component based on the lumped property data; determine the binary interaction parameters between the supercritical extraction solvent and each lumped component based on the molecular structure descriptor and the supercritical extraction solvent information. S104: Using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters and the extraction operation conditions, phase equilibrium calculations are performed to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase; S105: Based on the molecular-lumped correspondence data and the composition weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

[0020] The aforementioned catalytic slurry molecular composition data can be used to characterize the composition and properties of each catalytic slurry molecule. It can be obtained based on experimental analysis data such as gas chromatography-mass spectrometry, nuclear magnetic resonance, elemental analysis, and simulated distillation of the catalytic slurry sample. It includes the composition content and molecular properties of each catalytic slurry molecule, and is used for subsequent lumped component division, composition weight determination, and lumped property data determination.

[0021] The supercritical extraction solvent information mentioned above can be information used to characterize the extraction solvent used in the supercritical extraction process of catalytic oil slurry. The supercritical extraction solvent can be isobutane, propane, n-butane, pentane or a mixture thereof, used to determine the binary interaction parameters between the supercritical extraction solvent and each lumped component, and as input for phase equilibrium calculation.

[0022] The above-mentioned extraction operating conditions can be process conditions used to characterize the operating state of the supercritical extraction process of catalytic oil slurry, including at least one of temperature, pressure and catalyst-to-oil ratio in the supercritical extraction process, used to define the extraction conditions corresponding to the phase equilibrium calculation.

[0023] The aforementioned composition content can be data used to characterize the relative content of each catalytic slurry molecule in the composition of the catalytic slurry molecule, and can be expressed as mole fraction or mass fraction; the composition content is used to further determine the composition weight of each catalytic slurry molecule in its respective lumped component, thereby preserving the compositional contribution of each catalytic slurry molecule to the corresponding lumped component.

[0024] The aforementioned molecular properties can be data used to characterize the physical properties and compositional structure of each catalytic slurry molecule, including at least one of boiling point, molecular weight, critical temperature, critical pressure, eccentricity factor, number of carbon atoms, number of hydrogen atoms, number of aromatic carbon atoms, hydrogen-carbon ratio, and aromatic carbon ratio, used to classify lumped components and determine the lumped physical properties of each lumped component.

[0025] The lumped components mentioned above can be formed by grouping multiple catalytic oil slurry molecules with corresponding property ranges based on their molecular properties; specifically, they can be divided according to boiling point range, molecular weight range, aromatic carbon ratio range, structural family type, or a combination thereof. The lumped components serve as component inputs in phase equilibrium calculations, reducing the component dimension required for direct calculations on a large number of catalytic oil slurry molecules.

[0026] The aforementioned composition weights can be data used to characterize the proportion of a catalytic slurry molecule in its lumped component, and can be normalized molar weights or normalized mass weights. For catalytic slurry molecules belonging to the same lumped component, the corresponding composition weights are determined by normalizing their composition content, which are used to determine the lumped property data and to redistribute the lumped-level phase allocation results to specific catalytic slurry molecules.

[0027] The aforementioned molecule-lumped group correspondence data can be used to record the attribution relationship between each catalytic slurry molecule and each lumped group component, as well as the corresponding compositional weights. This data can be stored in the form of a mapping matrix, mapping table, or index table. Through this molecule-lumped group correspondence data, the catalytic slurry molecules contained in each lumped group component and the compositional contribution of each catalytic slurry molecule can be determined. This data is then used to subsequently back-allocate the lumped group phase allocation results to the corresponding catalytic slurry molecules.

[0028] The aforementioned lumped property data can be data used to characterize the equivalent properties of a lumped component, determined based on the molecular properties and corresponding compositional weights of each catalytic slurry molecule in the lumped component. This data may include at least one of equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio, and serve as the data basis for subsequent determination of molecular structure descriptors and phase equilibrium calculations.

[0029] The aforementioned molecular structure descriptor may be data determined based on the lumped property data of the lumped components, used to characterize the molecular structure characteristics of the corresponding lumped components, including at least one of equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, number of aromatic rings, and solubility parameters; the molecular structure descriptor is used to characterize the structural differences between different lumped components and to determine the binary interaction parameters between the supercritical extraction solvent and the corresponding lumped components.

[0030] The aforementioned binary interaction parameters can be used to characterize the interaction relationship between the supercritical extraction solvent and the corresponding lumped component. They are determined based on the molecular structure descriptor of the lumped component and the information of the supercritical extraction solvent, and are used for phase equilibrium calculations.

[0031] The above-mentioned lumped-level phase distribution results can be obtained by performing phase equilibrium calculations using supercritical extraction solvent information, lumped property data, binary interaction parameters and extraction operating conditions. These results are used to characterize the distribution of each lumped component in the extract phase and raffinate phase, including the composition and content of each lumped component in the extract phase and raffinate phase, and serve as input for subsequent inverse lumping to obtain molecular-level composition results.

[0032] The molecular-level composition results of the above-mentioned extract phase and / or raffinate phase can be obtained by redistributing the lumped-level phase allocation results of each lumped component in the extract phase and / or raffinate phase to the corresponding catalytic slurry molecules based on the molecular-lumped correspondence data and composition weights. This result is used to characterize the composition content of each catalytic slurry molecule in the extract phase and / or raffinate phase. Based on this result, the single-molecule extraction rate, molecular weight, aromatic carbon ratio, boiling point, and structural family distribution can also be further determined.

[0033] In some embodiments, obtaining supercritical extraction solvent information and extraction operation conditions may specifically include: Obtain the type of supercritical extraction solvent, as well as the temperature, pressure, and solvent-to-oil ratio corresponding to the target extraction conditions; The supercritical extraction solvent information is determined based on the solvent type. The extraction operating conditions are determined based on the temperature, the pressure, and the agent-to-oil ratio; The supercritical extraction solvent includes isobutane, propane, n-butane, pentane, or a mixture thereof.

[0034] By obtaining the type of supercritical extraction solvent and the temperature, pressure, and solvent-to-oil ratio corresponding to the target extraction conditions, the supercritical extraction solvent information and extraction operation conditions corresponding to the target extraction conditions can be determined. This provides corresponding inputs for the subsequent determination of binary interaction parameters and phase equilibrium calculations, so that the obtained lumped-level phase distribution results correspond to the specific extraction conditions.

[0035] In some embodiments, determining the molecular structure descriptor of each lumped component based on the lumped property data may specifically include: From the lumped property data of each of the lumped components, determine at least one of the following: equivalent molecular weight, equivalent aromatic carbon ratio, and equivalent hydrogen-to-carbon ratio. At least one of the determined equivalent molecular weight, equivalent aromatic carbon ratio, and equivalent hydrogen-carbon ratio is used as the molecular structure descriptor for the corresponding lumped component.

[0036] By determining at least one of the equivalent molecular weight, equivalent aromatic carbon ratio, and equivalent hydrogen-carbon ratio from the lumped property data as a molecular structure descriptor, the molecular structure differences between different lumped components can be characterized using the equivalent properties of the lumped components. This provides a data basis for subsequently determining the binary interaction parameters between the supercritical extraction solvent and each lumped component based on the molecular structure descriptor.

[0037] In some embodiments, the step of allocating the lumped-level phase allocation result to the corresponding catalytic slurry molecules according to the molecular-lumped correspondence data and the composition weights to obtain the molecular-level composition result of the extract phase and / or the raffinate phase may specifically include: Based on the lumped-level phase distribution results, determine the phase content of each lumped component in the extract phase and / or the raffinate phase; Based on the molecular-lumped group correspondence data, determine the catalytic slurry molecules corresponding to each of the lumped group components; Based on the compositional weights of each catalytic slurry molecule and the phase content of the corresponding lumped component, the molecular phase content of each catalytic slurry molecule in the extract phase and / or the raffinate phase is determined. The molecular-level composition of the extract phase and / or the raffinate phase is determined based on the molecular phase content of each of the catalytic oil slurry molecules.

[0038] In practice, after completing the phase equilibrium calculation of the catalytic oil slurry and the supercritical extraction solvent, the lumped-level phase distribution results of each lumped component in the extract phase and raffinate phase are obtained. Taking the extraction conditions of 421 Kelvin, 5.0 MPa, and a catalyst-to-oil mass ratio of 4 as an example, the phase equilibrium calculation yields the normalized molar composition of 22 lumped components in the extract phase and raffinate phase, and based on this, the phase content of each lumped component in the extract phase and the phase content in the raffinate phase are determined respectively.

[0039] Based on pre-established molecule-lumped group correspondence data, each lumped group is queried to determine all catalytic slurry molecules belonging to that lumped group and the compositional weight of each catalytic slurry molecule. In this embodiment, each catalytic slurry molecule belongs to a corresponding lumped group. The compositional weight of each catalytic slurry molecule within the same lumped group is determined by normalization based on its molar content, and the sum of the compositional weights within the same lumped group is one. Thus, each lumped group can be mapped to specific catalytic slurry molecules within it and the compositional contribution of each catalytic slurry molecule.

[0040] For any lumped component, based on its phase content in the extract phase and the compositional weights of each catalytic slurry molecule within it, the phase content of the lumped component in the extract phase is allocated to the corresponding catalytic slurry molecules according to the stated compositional weights, thereby determining the molecular phase content of each catalytic slurry molecule in the extract phase. Following the same processing method, based on the phase content of the lumped component in the raffinate phase and its corresponding compositional weights, the molecular phase content of each catalytic slurry molecule in the raffinate phase is determined.

[0041] The above allocation process was performed on each of the 22 lumped components. The molecular phase content of the catalytic oil slurry molecules corresponding to each lumped component in the extract phase was summarized to obtain the molecular-level composition of the extract phase. Similarly, the molecular phase content of the catalytic oil slurry molecules corresponding to each lumped component in the raffinate phase was summarized to obtain the molecular-level composition of the raffinate phase. Thus, the phase equilibrium calculation results originally expressed as lumped components were restored to the specific catalytic oil slurry molecular level, allowing for further statistical analysis of the molecular composition of the extract and raffinate phases based on the carbon number, molecular weight, aromatic carbon ratio, boiling point, and structural family of each catalytic oil slurry molecule.

[0042] By utilizing molecular-lumped correspondence data to determine the specific catalytic slurry molecules corresponding to each lumped component, and allocating the phase content of the lumped components in the extract and raffinate phases according to the composition weight of each catalytic slurry molecule, the lumped-level phase allocation results can be restored to the molecular-level composition results of the extract and raffinate phases. While using lumped components for phase equilibrium calculations, the composition and content relationships of specific molecules are preserved, thereby improving the availability and traceability of the molecular-level composition results of the extract and raffinate phases.

[0043] In some embodiments, the method for obtaining the molecular composition data of the catalytic oil slurry may further include the following: S1: Obtain gas chromatography-mass spectrometry analysis data, nuclear magnetic resonance analysis data, elemental analysis data, and simulated distillation analysis data of the catalytic oil slurry sample; S2: Based on the gas chromatography-mass spectrometry analysis data, determine the core molecules of the catalytic slurry; S3: Based on the nuclear magnetic resonance analysis data, the elemental analysis data, and the simulated distillation analysis data, the compositional distribution of the core molecule is constrained using a probability density function; S4: Determine the target physical property based on the composition distribution, and use the relative error between the predicted and experimental values ​​of the target physical property as the objective function. Optimize the parameters of the probability density function using a genetic algorithm to obtain the molecular composition data of the catalytic oil slurry.

[0044] In practice, gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), elemental analysis, and simulated distillation analysis data of the catalytic slurry sample to be analyzed are acquired. Representative molecular structures in the catalytic slurry are identified based on the GC-MS data, and core molecules are determined by combining the double bond equivalent-carbon number distribution. This embodiment identifies 179 core molecules, covering alkanes, cycloalkanes, and aromatic structures with varying degrees of fusion, enabling the identified core molecules to characterize the main molecular structure types in the catalytic slurry.

[0045] Based on the identified core molecule, the core molecule was structurally expanded according to the number of side chains, side chain length, and substitution positions to construct a set of candidate molecules for catalytic slurry. In this embodiment, 6136 catalytic slurry molecules were obtained through structural expansion. For each catalytic slurry molecule, its molecular structure and corresponding molecular properties were determined, including the number of carbon atoms, molecular weight, boiling point, and number of aromatic carbon atoms. The composition to be determined was assigned to each catalytic slurry molecule, thereby forming a candidate data set for determining the composition of the catalytic slurry molecules.

[0046] Based on nuclear magnetic resonance analysis data, elemental analysis data, and simulated distillation analysis data, the compositional distribution of each catalytic slurry molecule in the candidate data set is constrained. Specifically, a probability density function is used to describe the compositional distribution of different catalytic slurry molecules. The probability density function used includes at least one of the Gamma function and the Histogram function. The compositional content of different catalytic slurry molecules in the candidate data set is changed by adjusting the function parameters of the probability density function, and the corresponding combination of probability density functions is determined according to the compositional characteristics of the catalytic slurry.

[0047] Based on the composition distribution, the corresponding distillation curve, composition content, elemental content, and aromatic ring number are calculated, and these are used as target properties. The calculated values ​​of each target property are compared with the corresponding experimental values ​​of the catalytic oil slurry sample to determine the relative error of each target property. An objective function is then constructed based on the relative error of each target property to characterize the deviation between the current composition distribution and the experimental analysis results of the catalytic oil slurry sample.

[0048] A genetic algorithm is used to optimize the parameters of the probability density function. For different combinations of function parameters generated by the genetic algorithm, the compositional distribution of each catalytic oil slurry molecule is re-determined based on the corresponding function parameters. The predicted value of the target property is calculated, and the corresponding objective function value is determined based on the relative error between the predicted and experimental values. The combination of function parameters is optimized based on the objective function value, so that the predicted results of the target property gradually approach the experimental analysis results. By adjusting the function parameters of the probability density function and the number of iterations of the genetic algorithm, the relative error of the target property is controlled within 5%, and the compositional content of each catalytic oil slurry molecule is determined.

[0049] Based on the optimized composition and molecular properties of each catalytic slurry molecule, catalytic slurry molecular composition data was generated. In this example, the 6136 catalytic slurry molecules obtained mainly concentrated between C20 and C40 in terms of carbon number mass fraction, forming a long tail towards higher carbon numbers. The molar contents of catalytic slurry molecules with the same carbon number and double bond equivalent were summed to obtain the corresponding double bond equivalent-carbon number distribution. Verification showed that the root mean square error between the simulated distillation temperature and the experimental value corresponding to the obtained molecular composition was 20.3 Kelvin, and the average absolute error of the mass fraction of the 13 hydrocarbon groups was 0.84 percentage points, indicating that the obtained catalytic slurry molecular composition data can simultaneously characterize the distillation range characteristics and the main structural group composition of the catalytic slurry.

[0050] The core molecules were identified by gas chromatography-mass spectrometry analysis, and the expanded molecular composition distribution of the catalytic slurry was constrained by nuclear magnetic resonance analysis, elemental analysis, and simulated distillation analysis. Then, an objective function was constructed by the relative errors between the predicted and experimental values ​​of multiple target properties, and the composition distribution was optimized by a genetic algorithm. This method can simultaneously match the determined molecular composition data of the catalytic slurry with the composition characteristics, elemental characteristics, and distillation range characteristics of the sample, providing a relatively accurate molecular composition data basis for the lumped partitioning, composition weight determination, and phase equilibrium calculation of the catalytic slurry molecules.

[0051] In some embodiments, the method of dividing the plurality of catalytic slurry molecules into a plurality of lumped components according to the molecular properties may further include the following: S1: Determine the lumped interval corresponding to each of the catalyst slurry molecules based on at least one of the boiling point, molecular weight, aromatic carbon ratio and structural family type of each of the catalyst slurry molecules; S2: Based on the lumped interval, each of the catalyst oil slurry molecules is divided into the corresponding lumped component.

[0052] In practice, the molecular properties of each catalytic oil slurry molecule were obtained, and the atmospheric boiling point was selected as the basis for lumping. Lumping was performed on 6136 catalytic oil slurry molecules, with the atmospheric boiling point range of 423.789 K to 1072.846 K. Based on this atmospheric boiling point range, 22 consecutive boiling point intervals were established, each with a width of approximately 29.503 K, and each boiling point interval was assigned as a lumped component. All the above specific parameters are from documented records.

[0053] For any given catalytic oil slurry molecule, its atmospheric boiling point is read. This atmospheric boiling point is then matched with various boiling point intervals to determine the interval in which it falls. The catalytic oil slurry molecule is then assigned to the lumped component corresponding to that boiling point interval. This interval matching process is repeated for each catalytic oil slurry molecule to ensure that each molecule is assigned to only one corresponding lumped component, preventing the same catalytic oil slurry molecule from being counted repeatedly in different lumped components or not at all.

[0054] After the lumped grouping is completed, the catalytic oil slurry molecules contained in each lumped component are determined according to the lumped grouping relationship of each catalytic oil slurry molecule. For the same lumped component, the atmospheric boiling point of the catalytic oil slurry molecules within it all falls within the boiling point range corresponding to that lumped component. For each lumped component, its composition content is not directly determined based on the number of catalytic oil slurry molecules it contains, but rather based on the composition content of each catalytic oil slurry molecule, the compositional weight of each catalytic oil slurry molecule in its respective lumped component is further determined, thereby distinguishing between the number of molecules within the lumped component and the actual contribution of each catalytic oil slurry molecule to the composition of the feedstock.

[0055] In one specific embodiment, the lumped component can also be divided based on the molecular weight, aromatic carbon ratio, structural family type, or a combination of at least two of these molecular properties of the catalytic slurry molecules. When dividing by molecular weight or aromatic carbon ratio, multiple lumped intervals are set according to the value range of the corresponding molecular properties, and the corresponding lumped interval is determined according to the molecular weight or aromatic carbon ratio of each catalytic slurry molecule. When dividing by structural family type, the corresponding lumped component is determined according to the structural family type of each catalytic slurry molecule.

[0056] After obtaining multiple lumped components through the above method, molecular-lumped correspondence data is established based on the lumped affiliation and composition weight of each catalytic slurry molecule. Furthermore, lumped property data is determined based on the molecular properties and corresponding composition weights of the catalytic slurry molecules contained in each lumped component, so that each lumped component can maintain the correspondence with its internal catalytic slurry molecules and their compositional contributions.

[0057] By determining the corresponding lumped intervals based on the molecular properties of catalytic oil slurry molecules and classifying each catalytic oil slurry molecule into its corresponding lumped component, a large number of catalytic oil slurry molecules can be lumped according to their molecular properties, while retaining the lumped affiliation relationship of each catalytic oil slurry molecule. This provides a data foundation for determining composition weights, establishing molecular-lumped correspondence, and determining lumped property data.

[0058] In some embodiments, the method of determining the compositional weight of each catalytic oil slurry molecule in its respective lumped component based on the compositional content and establishing molecule-lumped component correspondence data may further include the following: S1: Based on the composition content of each catalytic oil slurry molecule, normalize the composition content of catalytic oil slurry molecules belonging to the same lumped component, and determine the composition weight of each catalytic oil slurry molecule in its respective lumped component. S2: Establish the molecule-lumped group correspondence data based on the lumped group composition to which each catalytic oil slurry molecule belongs and the composition weight; The molecular-lumen correspondence data is stored in the form of a mapping matrix, mapping table, or index table, and the composition weights are normalized molar weights or normalized mass weights.

[0059] In practice, based on the established lumped-off relationships of each catalytic slurry molecule, the composition of each lumped-off component is normalized. When molar content is used as the composition content, for any lumped-off component, the molar content of all catalytic slurry molecules belonging to that component is obtained, the sum of the molar contents of all catalytic slurry molecules is calculated, and the normalized molar weight of each catalytic slurry molecule in its respective lumped-off component is determined based on the ratio of its molar content to the sum of the molar contents, ensuring that the sum of the composition weights of all catalytic slurry molecules within the same lumped-off component is one.

[0060] When characterizing the molecular composition of catalytic slurry using mass content, the mass content of each catalytic slurry molecule within the same lumped component can be normalized in the same way to obtain the corresponding normalized mass weight. Therefore, the composition weight reflects the compositional contribution of a catalytic slurry molecule within its respective lumped component, rather than the number of catalytic slurry molecules contained in that lumped component, thus avoiding confusion between the number of molecules within the lumped component and their actual compositional contribution.

[0061] A molecule-lump correspondence data is established based on the lumped affiliation of each catalytic slurry molecule and its corresponding composition weight. When using a mapping matrix for storage, the catalytic slurry molecule is considered as one dimension, and the lumped components as another. When a catalytic slurry molecule belongs to a corresponding lumped component, its composition weight is recorded at the position corresponding to that catalytic slurry molecule and the lumped component. When the catalytic slurry molecule does not belong to a corresponding lumped component, the corresponding position is recorded as zero. Since each catalytic slurry molecule belongs to only one lumped component, the lumped affiliation of each catalytic slurry molecule and its composition weight within its respective lumped component can be directly determined based on the mapping matrix.

[0062] For example, when establishing molecular-lumped group correspondence data for 22 lumped groups divided according to atmospheric boiling point, the lumped group to which each of the 6136 catalytic slurry molecules belongs and its normalized composition weight are recorded one by one. For any lumped group, the catalytic slurry molecules contained in the lumped group can be extracted based on the molecular-lumped group correspondence data, and the composition weight corresponding to each catalytic slurry molecule can be obtained, so that the lumped group can be traced back to the specific catalytic slurry molecules inside it and the raw material composition contribution of each catalytic slurry molecule.

[0063] In other specific embodiments, the molecular-lumped group correspondence data can also be stored using a mapping table or an index table. When using a mapping table, the identifier of the catalytic slurry molecule, its associated lumped group component, and its corresponding composition weight are stored together. When using an index table, an index is established based on the attribution relationship between the catalytic slurry molecule and the lumped group component, and the corresponding composition weight is recorded. Regardless of whether a mapping matrix, mapping table, or index table is used, the correspondence between the catalytic slurry molecule, its associated lumped group component, and its composition weight is maintained. The document explicitly states that the correspondence data can be stored using a mapping matrix, mapping table, or index table, and that the composition weight can be a normalized molar weight or a normalized mass weight.

[0064] Based on the established molecular-lumped correspondence data, the lumped physical property data of each lumped component can be determined by using the molecular properties and corresponding composition weights of each catalytic slurry molecule. After obtaining the lumped-level phase allocation results, the phase content of each lumped component can be allocated to the corresponding catalytic slurry molecule according to the same molecular-lumped correspondence and composition weights, so that the lumping process and the molecular-level composition recovery process adopt a corresponding data relationship.

[0065] By normalizing the composition content of each catalytic slurry molecule within the same lumped component and linking the lumped component attribution relationship with the composition weight to form molecule-lumped component correspondence data, the specific attribution and composition contribution of each catalytic slurry molecule can be preserved during the molecular lumping process. This allows each lumped component to be traced back to its internal catalytic slurry molecules and provides a clear data correspondence for determining lumped property data and allocating lumped-level phase distribution results to molecular-level composition results.

[0066] In some embodiments, the method for determining the lumped property data of each lumped component based on the molecular properties and the compositional weights may further include the following: S1: Based on the molecular properties and corresponding compositional weights of the catalytic oil slurry molecules in each of the lumped components, the molecular properties are weighted according to their composition to determine the equivalent physical properties of each of the lumped components; S2: Determine the equivalent physical properties as the lumped physical property data of the corresponding lumped components; The equivalent physical properties include at least one of the following: equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio.

[0067] In practice, based on the catalytic slurry molecules contained in each lumped component and the corresponding compositional weights of each catalytic slurry molecule, the lumped property calculations are performed on each lumped component. For any lumped component, the boiling point, molecular weight, critical temperature, critical pressure, eccentricity factor, hydrogen-to-carbon ratio, number of aromatic carbon atoms, and total number of carbon atoms of each catalytic slurry molecule within that lumped component are obtained. The compositional weights of each catalytic slurry molecule in that lumped component are then read, and these weights characterize the compositional contribution of different catalytic slurry molecules to the equivalent properties of the lumped component. The document explicitly states that the properties of the catalytic slurry molecules within each lumped component are weighted by composition to calculate the corresponding equivalent properties.

[0068] For equivalent molecular weight, the molecular weights of each catalytic slurry molecule within the same lumped component are weighted according to their molecular weights and corresponding compositional weights, and the resulting weighted value is determined as the equivalent molecular weight of the lumped component. For equivalent boiling point, the boiling points of each catalytic slurry molecule are weighted according to their corresponding compositional weights, and the resulting weighted value is determined as the equivalent boiling point of the lumped component. Following the corresponding compositional weighting method, the equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, and equivalent hydrogen-carbon ratio of the corresponding lumped component can be determined based on the critical temperature, critical pressure, eccentricity factor, and hydrogen-carbon ratio of each catalytic slurry molecule.

[0069] For the equivalent aromatic carbon ratio, the weighted total number of aromatic carbon atoms is determined based on the number of aromatic carbon atoms and their corresponding compositional weights of each catalytic slurry molecule within the same lumped component; the weighted total number of total carbon atoms is determined based on the total number of carbon atoms and their corresponding compositional weights of each catalytic slurry molecule; and the equivalent aromatic carbon ratio of the lumped component is determined based on the ratio between the weighted total number of aromatic carbon atoms and the weighted total number of total carbon atoms. This ensures that the determined equivalent aromatic carbon ratio reflects the aromatic carbon composition contribution of each catalytic slurry molecule within the lumped component, rather than simply using the average value of molecular properties within the lumped component.

[0070] In the specific method of dividing the lumped components according to their boiling points at atmospheric pressure into 22 lumped components, the above-mentioned compositional weighting process is performed on each lumped component to obtain the equivalent boiling point, equivalent molecular weight, and equivalent aromatic carbon ratio of each lumped component. The equivalent boiling points of the 22 lumped components range from 433.5 Kelvin to 1049.7 Kelvin, and the equivalent molecular weights range from 130.8 g / mol to 1571.0 g / mol. For example, the first lumped component contains 10 catalytic oil slurry molecules, with an equivalent boiling point of 433.5 Kelvin and an equivalent molecular weight of 130.8 g / mol; the twenty-second lumped component contains 426 catalytic oil slurry molecules, with an equivalent boiling point of 1049.7 Kelvin and an equivalent molecular weight of 1571.0 g / mol.

[0071] At least one of the following parameters, determined as described above: equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio, is used as the lumped property data for the corresponding lumped component, and the correlation between the lumped property data and the corresponding lumped component is maintained. This lumped property data can be used as input for the lumped component properties in subsequent phase equilibrium calculations. Furthermore, the equivalent molecular weight, equivalent aromatic carbon ratio, and equivalent hydrogen-to-carbon ratio can also be used to determine the molecular structure descriptor of the corresponding lumped component. The document explicitly states that the above lumped properties are determined based on the molecular properties and compositional weights of the catalytic slurry molecules within the lumped component.

[0072] By using the compositional weights of each catalytic slurry molecule to weight the molecular properties within its lumped component, the determined lumped property data can simultaneously reflect the molecular properties of the catalytic slurry molecules within the lumped component and their actual compositional contributions. This avoids characterizing the lumped component solely based on the number of molecules or simple average properties, thus providing property data corresponding to the actual composition of each lumped component for determining molecular structure descriptors and subsequent phase equilibrium calculations.

[0073] In some embodiments, the method for determining the binary interaction parameters between the supercritical extraction solvent and each of the lumped components based on the molecular structure descriptor and the supercritical extraction solvent information may further include the following: S1: Determine the corresponding molecular structure descriptor based on the equivalent physical properties of each of the aggregated components; wherein, the molecular structure descriptor includes at least one of the following: equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, number of aromatic rings, and solubility parameter; S2: Obtain experimental data on the yield of deasphalted oil corresponding to multiple experimental extraction operation conditions; S3: Determine the model parameters of the binary interaction parameter correlation equation based on the experimental data of the deasphalted oil yield; S4: Determine the binary interaction parameters between the supercritical extraction solvent and each of the lumped components based on the model parameters and the molecular structure descriptors of each of the lumped components.

[0074] In practice, isobutane is selected as the supercritical extraction solvent, and corresponding lumped property data are obtained for each lumped component. Based on the lumped property data of each lumped component, equivalent properties that characterize the differences in molecular structure of the lumped components are selected as molecular structure descriptors. In one specific approach, equivalent molecular weight and equivalent aromatic carbon ratio are selected as molecular structure descriptors, wherein both equivalent molecular weight and equivalent aromatic carbon ratio are determined based on the molecular properties and compositional weights of the catalytic oil slurry molecules within the lumped component, thereby ensuring that the molecular structure descriptors correspond to the actual molecular composition of each lumped component. The document explicitly uses equivalent molecular weight and equivalent aromatic carbon ratio to establish the binary interaction parameter correlation between isobutane and each lumped component.

[0075] Experimental data on deasphalted oil yield were obtained under different experimental extraction conditions, including at least temperature, pressure, and agent-to-oil ratio. A correspondence was established between each experimental extraction condition and the corresponding deasphalted oil yield data, ensuring that each set of deasphalted oil yield data had corresponding temperature, pressure, and agent-to-oil ratio conditions. This provides an experimental data basis for determining the model parameters in the binary interaction parameter correlation equation. The document explicitly states that the model parameters in the correlation equation are determined through regression analysis based on the deasphalted oil yield measured under different temperatures, pressures, and agent-to-oil ratios.

[0076] Based on the equivalent molecular weight and equivalent aromatic carbon ratio of each lumped component, a unified binary interaction parameter correlation is established between the supercritical extraction solvent and the lumped components. Specifically, the correlation can be expressed as:

[0077] in, Indicates supercritical extraction solvent and the first Binary interaction parameters between lumped components Indicates the first The equivalent molecular weight of each lumped component Indicates the first The equivalent aromatic carbon fraction of each lumped component Indicates the reference molecular weight. Indicates the reference aromatic carbon ratio. , , and This represents the model parameters that need to be determined.

[0078] Based on experimental data of deasphalted oil yield under multiple experimental extraction conditions, regression analysis was performed on the model parameters in the correlation equation for the binary interaction parameters. Specifically, under each experimental extraction condition, the corresponding binary interaction parameters were determined based on the candidate model parameters and the equivalent molecular weight and equivalent aromatic carbon ratio of each lumped component. Phase equilibrium calculations were then performed based on the determined binary interaction parameters to obtain the calculated deasphalted oil yield under the corresponding experimental extraction conditions. The model parameters were adjusted based on the deviation between the calculated deasphalted oil yield and the corresponding experimental deasphalted oil yield data. The model parameters were determined by jointly constraining the model parameters using data from multiple experimental extraction conditions.

[0079] Based on the determined model parameters and the equivalent molecular weight and equivalent aromatic carbon ratio of each lumped component, the binary interaction parameters between the supercritical extraction solvent and each lumped component are calculated. For the 22 lumped components obtained according to boiling point, the same binary interaction parameter correlation is used for calculation of each lumped component. Different binary interaction parameters are obtained only based on their respective equivalent molecular weight and equivalent aromatic carbon ratio, without the need to establish independent parameter relationships for each of the 22 lumped components. Thus, each binary interaction parameter maintains a clear correlation with the molecular structure descriptor of the corresponding lumped component and serves as input for subsequent phase equilibrium calculations.

[0080] In other specific embodiments, molecular structure descriptors for the corresponding lumped components can be determined based on at least one of the equivalent hydrogen-to-carbon ratio, aromatic ring number, and solubility parameters, and binary interaction parameters between the supercritical extraction solvent and each lumped component can be determined based on the selected molecular structure descriptors. The specific type of the molecular structure descriptor can be determined based on the lumped property data used to establish the correlation between the binary interaction parameters.

[0081] By establishing a unified relationship between binary interaction parameters using the molecular structure descriptors of lumped components, and determining model parameters based on experimental data of deasphalted oil yield under different extraction conditions, the binary interaction parameters corresponding to each lumped component can be correlated with its molecular structure characteristics such as equivalent molecular weight and equivalent aromatic carbon ratio. This avoids determining independent binary interaction parameters for each lumped component, reduces the number of independent parameters that need to be determined, and provides binary interaction parameters with clear data sources for subsequent phase equilibrium calculations.

[0082] In some embodiments, the phase equilibrium calculation using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase may further include the following in specific implementations: S1: Determine the supercritical extraction solvent and the feed composition of each of the aggregated components based on the solvent-to-oil ratio in the extraction operation conditions; S2: Using the lumped physical property data and the binary interaction parameters, determine the supercritical extraction solvent and the fugacity coefficients of each lumped component through a preset equation of state; S3: Based on the fugacity coefficient, perform phase stability analysis and flash evaporation calculations to determine the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase.

[0083] In practice, information on the supercritical extraction solvent and the extraction operating conditions, including temperature, pressure, and solvent-to-oil ratio, is obtained. The lumped physical properties and binary interaction parameters of each lumped component are also read. When isobutane is used as the supercritical extraction solvent, the feed mass of isobutane and the feed mass of the catalytic slurry are determined based on the given solvent-to-oil mass ratio. Based on the composition of each lumped component in the catalytic slurry, the feed mass of the catalytic slurry is allocated to the corresponding lumped components. Combining the molecular weights of isobutane and each lumped component, the feed mass is converted into molar composition, thereby determining the feed composition consisting of isobutane and each lumped component.

[0084] The equation of state is calculated based on the feed composition, temperature and pressure during the extraction operation, lumped property data of each lumped component, and binary interaction parameters between isobutane and each lumped component.

[0085] In one specific implementation, the Peng-Robinson equation of state is used to calculate the fugacity coefficients of isobutane and each lumped component under the current temperature and pressure conditions, based on the lumped property data such as the equivalent critical temperature, equivalent critical pressure, and equivalent eccentricity factor of each lumped component, as well as the corresponding binary interaction parameters. The equation of state can also be the Soave-Redlich-Kwong equation of state or other cubic equations of state suitable for supercritical fluid systems.

[0086] Based on the determined fugacity coefficient, a phase stability analysis is performed on the mixture corresponding to the feed composition. Specifically, a tangential distance function is used to determine the phase state under the current temperature, pressure, and feed composition. The phase stability analysis results determine whether the mixture can maintain single-phase stability. When the phase stability analysis indicates that the mixture exhibits two-phase separation conditions, the feed composition, fugacity coefficient, and extraction operating conditions are used as inputs for flash evaporation calculations to solve for the distribution of isobutane and each lumped component in different phases. The document explicitly uses a tangential distance function for phase stability analysis.

[0087] During flash evaporation calculations, multiple sets of initial values ​​are set for the same extraction operating conditions, and candidate phase equilibrium results are obtained based on each set of initial values. For each candidate phase equilibrium result, selection is based on calculation convergence residuals, phase stability, and physical rationality to determine the valid results that meet the requirements of phase equilibrium calculations, thereby reducing the influence of a single initial value on the phase equilibrium solution. Based on the determined valid results, the composition and content of each lumped component in the extract phase and the raffinate phase are obtained, and the corresponding phase fractions are determined to form the lumped-level phase distribution results of each lumped component in the extract and raffinate phases.

[0088] In a specific operating condition, the extraction temperature is 421 Kelvin, the pressure is 5.0 MPa, and the catalyst-to-oil mass ratio is 4. After performing phase stability analysis and flash evaporation calculations as described above, the normalized molar composition of 22 lumped components in the extract and raffinate phases can be obtained. Thus, each lumped component has a corresponding extract phase composition and raffinate phase composition. The lumped-level phase allocation results can be further combined with molecule-lumped correspondence data and the compositional weights of each catalyst slurry molecule to allocate the phase content of each lumped component to the corresponding catalyst slurry molecule.

[0089] By determining the supercritical extraction solvent and the feed composition of each lumped component based on the solvent-to-oil ratio, and combining the lumped physical property data, binary interaction parameters, and temperature and pressure to determine the fugacity coefficient of each component, and then using the fugacity coefficient to perform phase stability analysis and flash evaporation calculations, the distribution of each lumped component in the extract phase and raffinate phase can be determined at the lumped component level. Furthermore, by screening effective results using multiple initial values, convergence residuals, phase stability, and physical rationality, the stability and reliability of the lumped-level phase distribution results can be improved.

[0090] In some embodiments, after obtaining the lumped-level phase distribution results of each of the lumped components in the extract phase and the raffinate phase, the implementation may further include: Obtain the normalized molar content of each lumped component in the feed and the normalized molar content in the extract phase; determine the enrichment degree of the corresponding lumped component in the extract phase based on the normalized molar content of the same lumped component in the feed and its normalized molar content in the feed.

[0091] When the normalized molar content of a corresponding lumped component in the extract phase increases relative to its normalized molar content in the feed, the lumped component is considered enriched in the extract phase; conversely, when the normalized molar content of a corresponding lumped component in the extract phase decreases relative to its normalized molar content in the feed, the lumped component is considered depleted in the extract phase. Based on the boiling point range and enrichment degree of each lumped component in the extract phase, the distribution differences between the extract phase and the raffinate phase are determined.

[0092] For example, under extraction conditions of 421 Kelvin, 5.0 MPa, and an oil-to-solvent mass ratio of 4, 22 lumped components were analyzed. The low-boiling-point lumped components were generally enriched in the extract phase, the high-boiling-point lumped components were generally enriched in the raffinate phase, and the lumped components in the intermediate boiling point range formed a transitional region of two-phase distribution.

[0093] In some embodiments, after obtaining the molecular-level composition results of the extract phase and / or the raffinate phase, the specific implementation may further include: The catalytic oil slurry molecules are classified according to the number of carbon atoms and the equivalent of double bonds in each catalytic oil slurry molecule; the molar contents of catalytic oil slurry molecules with the same number of carbon atoms and the equivalent of double bonds are accumulated to determine the molar contents of the number of carbon atoms and the equivalent of double bonds in the feed, extract phase and raffinate respectively.

[0094] Based on the composition and content of each catalytic oil slurry molecule in the feed, extract phase, and raffinate phase, the extract phase content, raffinate phase content, and single-molecule extraction rate of each catalytic oil slurry molecule are determined. Based on the molecular weight, aromatic carbon ratio, boiling point, or structural family type of each catalytic oil slurry molecule, the molecular-level composition results are statistically analyzed to obtain at least one of the molecular weight distribution, aromatic carbon ratio distribution, boiling point distribution, and structural family distribution corresponding to the extract phase and raffinate.

[0095] The molecular composition distribution of the feed, extract phase, and raffinate phase was compared using the same statistical caliber to determine the differences in the distribution of catalytic oil slurry molecules with different carbon numbers, different double bond equivalents, and different structural groups during the extraction process.

[0096] In some embodiments, after obtaining the molecular-level composition results corresponding to different extraction operation conditions, the specific implementation may further include: Obtain experimental values ​​of deasphalted oil yield corresponding to multiple experimental extraction conditions; perform phase equilibrium calculations based on the same raw material composition, supercritical extraction solvent information, temperature, pressure, and solvent-to-oil ratio as each experimental extraction condition to determine the calculated value of deasphalted oil yield corresponding to each experimental extraction condition.

[0097] Based on the calculated yield of each deasphalted oil and the corresponding experimental yield, the coefficient of determination, root mean square error, and mean absolute error of the calculated results are determined. Based on the error between the calculated and experimental values ​​under each experimental extraction operation condition, the extraction operation conditions with relatively large errors are determined.

[0098] Specifically, 21 sets of supercritical isobutane extraction experimental data were selected. The pressure corresponding to sets 1 to 17 was 5.0 MPa, and the pressure corresponding to sets 18 to 21 was 4.5 MPa. The agent-to-oil mass ratio was 4 in each set of experiments, and the temperature range was 348 Kelvin to 473 Kelvin. Based on the 21 sets of experimental data, the coefficient of determination between the calculated and experimental values ​​of the deasphalted oil yield was 0.986, the root mean square error was 0.038, and the mean absolute error was 0.028. For operating conditions with relatively large errors near the phase transition, relevant parameters can be further corrected based on the corresponding experimental data.

[0099] In some embodiments, after obtaining the molecular-level composition results of the extract phase and / or the raffinate phase, the specific implementation may further include: Multiple sets of extraction operating conditions are set up for comparison, wherein different extraction operating conditions correspond to at least one of different temperatures, pressures, agent-to-oil ratios, and solvent types; phase equilibrium calculations are performed for each set of extraction operating conditions to determine the corresponding deasphalted oil yield, lumped-level phase distribution results, and molecular-level composition results.

[0100] Based on the molecular-level composition results corresponding to different extraction operation conditions, at least one of the following is determined: extract phase content, raffinate content, single-molecule extraction rate, molecular weight distribution, aromatic carbon ratio distribution, boiling point distribution, and structural family distribution of the catalytic oil slurry molecules; the yield of deasphalted oil corresponding to each extraction operation condition is compared with the molecular-level composition results to determine the separation differences under different extraction operation conditions.

[0101] Based on the separation differences, candidate extraction operating conditions are determined from multiple sets of extraction operating conditions, so that the comparison of extraction operating conditions is not only based on the deasphalted oil yield, but also on the specific catalytic oil slurry molecular composition and molecular property distribution in the extract phase and raffinate phase.

[0102] Based on the above embodiments, this specification establishes a molecular-lumped mapping relationship simultaneously during the lumping process, preserving the chemical, structural, and compositional information of the catalytic oil slurry molecules. While controlling the scale of the phase equilibrium calculation model, the lumped-level calculation results can be restored to the molecular-level composition based on the mapping relationship, thus balancing computational efficiency and result traceability. Based on the molecular-level composition results, not only can the total yield of deasphalted oil be obtained, but also molecular-scale results such as the content of single molecules and the distribution of structural families in the extract and raffinate phases can be obtained. At the same time, by utilizing structural characteristics such as molecular weight and aromatic carbon ratio to determine binary interaction parameters, the parameters have a clear data source and improve the applicability under different raw materials and operating conditions. In addition, it can compare the separation results under different temperature, pressure, agent-to-oil ratio, and solvent conditions, providing a basis for product composition prediction and extraction operation condition screening, reducing repeated experiments and corresponding material and testing consumption.

[0103] In some embodiments, the molecular composition and experimental characterization data of the catalytic slurry are used as the basis for determining the molecular composition data of the catalytic slurry. The experimental characterization data may include gas chromatography-mass spectrometry analysis data, nuclear magnetic resonance analysis data, elemental analysis data, and simulated distillation analysis data. Based on the experimental characterization data, 179 core molecules are identified, and side chain extensions are performed on these core molecules to obtain 6136 catalytic slurry molecules. For each catalytic slurry molecule, information such as the structure guiding string, SMILES, molecular formula, carbon number, DBE, molecular weight, boiling point, aromatic carbon number, and composition content are recorded to form the molecular composition data of the catalytic slurry.

[0104] In practice, based on the molecular properties of each catalytic slurry molecule, multiple catalytic slurry molecules are divided into multiple lumped components, and molecular-lumped component correspondence data is established simultaneously. This molecular-lumped component correspondence data can be stored in the form of a mapping matrix, used to record the lumped component to which each catalytic slurry molecule belongs and the compositional weight of each catalytic slurry molecule within its respective lumped component, enabling each lumped component to correspond to its internal catalytic slurry molecules and their corresponding compositional sources.

[0105] Let the catalytic oil slurry molecular system be Furthermore, the lumped component system is The molecular-lumn correspondence data adopts a mapping matrix. This indicates that when the i-th catalytic slurry molecule belongs to the j-th lumped component, This indicates the compositional weight of the catalytic oil slurry molecule in the j-th lumped component; when the i-th catalytic oil slurry molecule does not belong to the j-th lumped component... It is 0.

[0106] In one specific embodiment, based on the molar content of each catalytic slurry molecule, the molar content of catalytic slurry molecules belonging to the same lumped component is normalized to determine the composition weight of each catalytic slurry molecule in its respective lumped component. The composition weight is a normalized molar weight, which can be expressed as:

[0107] in, Let represent the molar content of the i-th catalytic slurry molecule in the catalytic slurry, and the summation range is all catalytic slurry molecules within the j-th lumped component.

[0108] In practice, based on the molecular properties and corresponding compositional weights of the catalytic oil slurry molecules in each lumped component, the molecular properties are weighted according to their composition to determine the equivalent physical properties of each lumped component, and these equivalent physical properties are then defined as the lumped property data of the corresponding lumped component. For example, the equivalent molecular weight of the j-th lumped component... It can be represented as: .

[0109] Equivalent boiling point of the j-th lumped component It can be represented as: .

[0110] Equivalent aromatic carbon ratio of the j-th lumped component Determined based on the weighted total number of aromatic carbon atoms and the weighted total number of total carbon atoms, it can be expressed as:

[0111] in, Let be the molecular weight of the i-th catalytic oil slurry molecule. Let be the boiling point of the i-th catalytic oil slurry molecule. Let i be the number of aromatic carbon atoms in the i-th catalytic oil slurry molecule. Let be the total number of carbon atoms in the i-th catalytic oil slurry molecule. According to the corresponding compositional weighting method, the equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, and equivalent hydrogen-to-carbon ratio can also be determined, and at least one of the above equivalent properties can be used as the lumped property data of the corresponding lumped component.

[0112] In practice, information on the supercritical extraction solvent and extraction operating conditions is obtained, and the supercritical extraction solvent is combined with each lumped component to form a multi-component system for phase equilibrium calculations. The supercritical extraction solvent can be isobutane, propane, n-butane, pentane, or mixtures thereof; the extraction operating conditions can include temperature, pressure, and solvent-to-oil ratio. The preset equation of state used for phase equilibrium calculations can be the Peng-Robinson equation of state, the Soave-Redlich-Kwong equation of state, or other cubic equations of state suitable for supercritical fluid systems.

[0113] In one specific implementation, the Peng-Robinson equation of state is used to determine the supercritical extraction solvent and the fugacity coefficients of each lumped component based on the lumped physical property data, binary interaction parameters, and extraction operating conditions. Phase stability analysis is performed using the tangential plane distance function based on the fugacity coefficients. When it is determined that two-phase separation conditions exist for the corresponding multi-component system, flash evaporation calculations are performed using multiple sets of initial values. The candidate calculation results are then screened based on the convergence residuals, phase stability, and physical rationality to determine the lumped-level phase distribution results of each lumped component in the extract phase and raffinate phase.

[0114] In practice, the corresponding molecular structure descriptors are determined based on the lumped physical property data of each lumped component, and the binary interaction parameters are determined based on the molecular structure descriptors and the supercritical extraction solvent information. To reduce the number of parameters required to determine independent binary interaction parameters for each lumped component, the equivalent molecular weight and equivalent aromatic carbon ratio of each lumped component can be selected as the molecular structure descriptors, and a correlation equation for the binary interaction parameters between the supercritical extraction solvent and each lumped component can be established. This correlation equation can be expressed as:

[0115] in, Indicates supercritical extraction solvent and the first Binary interaction parameters between lumped components Indicates the first The equivalent molecular weight of each lumped component Indicates the first The equivalent aromatic carbon fraction of each lumped component Indicates the reference molecular weight. Indicates the reference aromatic carbon ratio. , , and This represents the model parameters that need to be determined.

[0116] Experimental data on deasphalted oil yield corresponding to different temperatures, pressures, and solvent-to-oil ratios were obtained. The model parameters were determined by regression based on the experimental data on deasphalted oil yield. Based on the determined model parameters and the molecular structure descriptors of each lumped component, the binary interaction parameters between the supercritical extraction solvent and each lumped component were determined.

[0117] In specific implementation, after obtaining the lumped-level phase distribution results of each lumped component in the extract phase and raffinate phase, the phase content of each lumped component is allocated to the corresponding catalytic slurry molecules according to the molecule-lumped correspondence data and the composition weight of each catalytic slurry molecule. If the j-th lumped component is in phase... The phase content in is Then, the i-th catalytic slurry molecule belonging to the j-th lumped component is in the phase Molecular phase content It can be represented as: .

[0118] Based on the molecular phase content of each catalytic oil slurry molecule in the extract phase, the molecular-level composition of the extract phase can be determined; based on the molecular phase content of each catalytic oil slurry molecule in the raffinate phase, the molecular-level composition of the raffinate phase can be determined. Based on the molecular-level composition, the extract phase content, raffinate phase content, and molecular property content of each catalytic oil slurry molecule in both phases can be statistically analyzed, and the carbon number distribution, DBE distribution, molecular weight distribution, aromatic carbon ratio distribution, boiling point distribution, and structural family distribution corresponding to the deasphalted oil and raffinate can be determined.

[0119] As can be seen from the above, the embodiments of this specification provide a method for determining the molecular composition of catalytic slurry supercritical extraction, which acquires catalytic slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic slurry molecular composition data includes the composition content and molecular properties of multiple catalytic slurry molecules; based on the molecular properties, the multiple catalytic slurry molecules are divided into multiple lumped components; based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecule-lumped component correspondence data is established; based on the molecular properties and the composition weight, the lumped property data of each lumped component is determined; based on the lumped property data, The molecular structure descriptors of each lumped component are determined; based on the molecular structure descriptors and the supercritical extraction solvent information, the binary interaction parameters between the supercritical extraction solvent and each lumped component are determined; phase equilibrium calculations are performed using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase; based on the molecular-lumped correspondence data and the composition weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and / or the raffinate phase. In this way, by determining the lumped components and their weights based on the molecular properties and composition of the catalytic oil slurry molecules, and establishing molecular-lumped correspondence data, phase equilibrium calculations are performed based on the lumped physical property data and binary interaction parameters. Then, the lumped-level phase allocation results are distributed to the corresponding catalytic oil slurry molecules according to the molecular-lumped correspondence data and their weights. This allows the composition and content of the catalytic oil slurry molecules and their corresponding relationships to be retained during the lumping process, thereby accurately obtaining the molecular-level composition results of the extract phase and the raffinate phase.

[0120] See Figure 2 As shown in the embodiments of this specification, a specific electronic device is also provided, wherein the electronic device includes a network communication port 201, a processor 202 and a memory 203, and the above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0121] Specifically, the network communication port 201 can be used to acquire catalytic oil slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic oil slurry molecular composition data includes the composition content and molecular properties of multiple catalytic oil slurry molecules.

[0122] The processor 202 can be specifically configured to: divide the plurality of catalytic slurry molecules into multiple lumped components based on the molecular properties; determine the composition weight of each catalytic slurry molecule in its respective lumped component based on the composition content, and establish molecule-lumped component correspondence data; determine the lumped property data of each lumped component based on the molecular properties and the composition weight; determine the molecular structure descriptor of each lumped component based on the lumped property data; determine the binary interaction parameters between the supercritical extraction solvent and each lumped component based on the molecular structure descriptor and the supercritical extraction solvent information; perform phase equilibrium calculations using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operation conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase; and allocate the lumped-level phase allocation results to the corresponding catalytic slurry molecules based on the molecule-lumped component correspondence data and the composition weight to obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

[0123] The memory 203 can be used to store the corresponding instruction program.

[0124] Based on the above method, the relevant structural performance of electronic devices can be effectively utilized to improve the data processing speed of electronic devices and efficiently realize a method for determining the molecular composition of catalytic oil slurry supercritical extraction.

[0125] In this embodiment, the network communication port 201 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0126] In this embodiment, the processor 202 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0127] In this embodiment, the memory 203 may include a hierarchy. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0128] This specification also provides a computer-readable storage medium based on the above-described method for determining the molecular composition of catalytic slurry supercritical extraction, which acquires catalytic slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic slurry molecular composition data includes the composition content and molecular properties of multiple catalytic slurry molecules; based on the molecular properties, the multiple catalytic slurry molecules are divided into multiple lumped components; based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecule-lumped correspondence data is established; based on the molecular properties and the composition weight, the lumped physical property data of each lumped component is determined; based on the lumped... Based on the physical property data, determine the molecular structure descriptors of each lumped component; based on the molecular structure descriptors and the supercritical extraction solvent information, determine the binary interaction parameters between the supercritical extraction solvent and each lumped component; use the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operating conditions to perform phase equilibrium calculations, obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase; based on the molecular-lumped correspondence data and the composition weights, allocate the lumped-level phase allocation results to the corresponding catalytic slurry molecules, obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

[0129] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0130] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments, and will not be repeated here.

[0131] See Figure 3 At the software level, this specification also provides an apparatus for determining the molecular composition of catalytic oil slurry supercritical extraction, which may specifically include the following structural modules: The data acquisition module 301 is used to acquire catalytic oil slurry molecular composition data, supercritical extraction solvent information, and extraction operation conditions; the catalytic oil slurry molecular composition data includes the composition content and molecular properties of multiple catalytic oil slurry molecules; The data determination module 302 is used to divide the plurality of catalytic oil slurry molecules into a plurality of lumped components according to the molecular properties; to determine the composition weight of each catalytic oil slurry molecule in its respective lumped component according to the composition content; and to establish molecule-lumped component correspondence data. The parameter determination module 303 is used to determine the lumped property data of each lumped component based on the molecular properties and the composition weights; determine the molecular structure descriptor of each lumped component based on the lumped property data; and determine the binary interaction parameters between the supercritical extraction solvent and each lumped component based on the molecular structure descriptor and the supercritical extraction solvent information. The allocation result determination module 304 is used to perform phase equilibrium calculations using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters and the extraction operation conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase. The composition result determination module 305 is used to allocate the lumped-level phase allocation result to the corresponding catalytic slurry molecules according to the molecular-lumped correspondence data and the composition weight, so as to obtain the molecular-level composition result of the extract phase and / or the raffinate phase.

[0132] In some embodiments, the data acquisition module 301 specifically acquires gas chromatography-mass spectrometry (GC-MS) analysis data, nuclear magnetic resonance (NMR) analysis data, elemental analysis data, and simulated distillation analysis data of the catalytic oil slurry sample; determines the core molecules of the catalytic oil slurry based on the GC-MS analysis data; constrains the compositional distribution of the core molecules using a probability density function based on the NMR analysis data, the elemental analysis data, and the simulated distillation analysis data; determines the target physical property based on the compositional distribution, and optimizes the parameters of the probability density function using a genetic algorithm with the relative error between the predicted and experimental values ​​of the target physical property as the objective function, thereby obtaining the molecular composition data of the catalytic oil slurry.

[0133] In some embodiments, the data determination module 302, in specific implementation, determines the lumped interval corresponding to each of the catalytic slurry molecules based on at least one of the boiling point, molecular weight, aromatic carbon ratio, and structural family type of each catalytic slurry molecule; and classifies each catalytic slurry molecule into its corresponding lumped component based on the lumped interval. Based on the composition content of each catalytic slurry molecule, the composition content of catalytic slurry molecules belonging to the same lumped component is normalized to determine the composition weight of each catalytic slurry molecule in its respective lumped component; and a molecule-lumped correspondence data is established based on the lumped component to which each catalytic slurry molecule belongs and the composition weight; wherein the molecule-lumped correspondence data is stored in the form of a mapping matrix, mapping table, or index table, and the composition weight is a normalized molar weight or a normalized mass weight.

[0134] In some embodiments, the parameter determination module 303, in specific implementation, performs compositional weighting on the molecular properties of the catalytic slurry molecules in each lumped component based on their molecular properties and corresponding compositional weights, to determine the equivalent physical properties of each lumped component; the equivalent physical properties are determined as the lumped physical property data of the corresponding lumped component; wherein, the equivalent physical properties include at least one of equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio. Based on the equivalent physical properties of each lumped component, a corresponding molecular structure descriptor is determined; wherein, the molecular structure descriptor includes at least one of equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, number of aromatic rings, and solubility parameter; experimental data on deasphalted oil yield corresponding to multiple experimental extraction operating conditions are obtained; based on the deasphalted oil yield experimental data, model parameters of the binary interaction parameter correlation formula are determined; based on the model parameters and the molecular structure descriptors of each lumped component, binary interaction parameters between the supercritical extraction solvent and each lumped component are determined.

[0135] In some embodiments, the above-mentioned allocation result determination module 304, in specific implementation, determines the supercritical extraction solvent and the feed composition of each of the lumped components based on the solvent-to-oil ratio in the extraction operation conditions; uses the lumped physical property data and the binary interaction parameters to determine the fugacity coefficients of the supercritical extraction solvent and each of the lumped components through a preset equation of state; and performs phase stability analysis and flash evaporation calculations based on the fugacity coefficients to determine the lumped-level phase allocation result of each of the lumped components in the extract phase and the raffinate phase.

[0136] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in the same software and / or hardware, or modules that implement the same function can be implemented by a combination of sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0137] As can be seen from the above, based on the embodiments of this specification, a device for determining the molecular composition of supercritical fluid extraction of catalytic oil slurry includes a data acquisition module for acquiring molecular composition data of catalytic oil slurry, supercritical extraction solvent information, and extraction operation conditions; the molecular composition data of the catalytic oil slurry includes the composition content and molecular properties of multiple catalytic oil slurry molecules; the data determination module is used to divide the multiple catalytic oil slurry molecules into multiple lumped components according to the molecular properties; determine the composition weight of each catalytic oil slurry molecule in its respective lumped component according to the composition content, and establish molecule-lumped component correspondence data; the parameter determination module is used to determine the lumped physical property data of each lumped component according to the molecular properties and the composition weight; and determine the lumped physical property data according to the lumped physical properties. The system uses data to determine the molecular structure descriptors of each lumped component; based on the molecular structure descriptors and the supercritical extraction solvent information, it determines the binary interaction parameters between the supercritical extraction solvent and each lumped component; a distribution result determination module is used to perform phase equilibrium calculations using the supercritical extraction solvent information, the lumped property data, the binary interaction parameters, and the extraction operation conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase; a composition result determination module is used to allocate the lumped-level phase distribution results to the corresponding catalytic slurry molecules according to the molecular-lumped correspondence data and the composition weights to obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

[0138] In a specific scenario example, the method and apparatus for determining the molecular composition of supercritical catalytic oil slurry extraction provided in this specification can be applied. This solves the technical problem that existing technologies easily lose molecular composition and content relationships during the lumped calculation of catalytic oil slurry, leading to difficulties in accurately obtaining molecular-level composition information of the extract phase and raffinate phase. The specific implementation process may include the following:

[0139] In some embodiments, 179 core molecules are identified based on mass spectrometry data of the catalytic slurry. These core molecules cover alkanes, cycloalkanes, and aromatic structures with varying degrees of cohesion. Based on these core molecules, molecular expansion is performed according to the number of side chains, side chain length, and substitution position, resulting in 6136 catalytic slurry molecules. The compositional distribution of these catalytic slurry molecules is constrained using probability density functions based on nuclear magnetic resonance analysis data, elemental composition data, and simulated distillation experimental data. These probability density functions include a Gamma function and a Histogram function, with the corresponding compositional distribution controlled by adjusting the function parameters. The combination of probability density functions is determined based on the experimental data. Distillation curves, compositional content, elemental content, and number of aromatic rings are used as target properties. An objective function is constructed using the relative error between the predicted and experimental values ​​of each target property. The parameters of the probability density function are then optimized using a genetic algorithm. By adjusting the function parameters and the number of iterations of the genetic algorithm, the relative error is controlled within 5%, and the mole fraction of each catalytic oil slurry molecule is determined, thereby obtaining the catalytic oil slurry molecule composition data, so that the determined catalytic oil slurry molecule set matches the experimental results in terms of distillation range and hydrocarbon structure group composition.

[0140] like Figure 4 The molecular composition model and experimental characterization of the catalytic slurry show that the carbon number mass fraction of the 6136 catalytic slurry molecules is mainly concentrated in the C20–C40 range, exhibiting a long tail distribution towards higher carbon numbers. In the DBE-carbon number distribution, the molar content of catalytic slurry molecules with the same carbon number and DBE is accumulated, and the cumulative molar content at corresponding grid points is characterized by bubble area; a larger bubble area indicates a higher cumulative molar content corresponding to that carbon number and DBE. The root mean square error between the simulated distillation temperature and the experimental value is 20.3 K; when comparing the composition of 13 hydrocarbon groups using mass fraction, the average absolute error is 0.84 percentage points. Therefore, the determined molecular composition data of the catalytic slurry can simultaneously characterize the experimental distillation range characteristics and the compositional characteristics of the main hydrocarbon structural groups, and can serve as the basis for subsequent lumped partitioning and phase equilibrium calculations.

[0141] In some embodiments, 6136 catalytic slurry molecules are divided into equal-width lumped groups based on their atmospheric boiling points. The atmospheric boiling point range of each catalytic slurry molecule is 423.789 K to 1072.846 K. Within this range, 22 consecutive boiling point intervals are defined, each corresponding to a lumped group. The width of each boiling point interval is approximately 29.503 K. The corresponding boiling point interval is determined based on the atmospheric boiling point of each catalytic slurry molecule, and each catalytic slurry molecule is assigned to its corresponding lumped group. Each catalytic slurry molecule belongs to only one lumped group to avoid the same catalytic slurry molecule being counted repeatedly in different lumped groups or not counted at all. Figure 5 The traceable boiling point lumped array of catalytic oil slurry molecules is shown, and the division relationship between each catalytic oil slurry molecule and the lumped array components is characterized by molecular points, boiling point interval boundaries, and corresponding composition weights.

[0142] During the lumped component partitioning process, a molecule-lumped component correspondence data is established based on the lumped component to which each catalytic slurry molecule belongs and its corresponding composition weight. This molecule-lumped component correspondence data is generated using a mapping matrix. This indicates that when the i-th catalytic oil slurry molecule belongs to the j-th lumped component, This represents the normalized molar weight of the catalytic oil slurry molecule in the j-th lumped component; when the i-th catalytic oil slurry molecule does not belong to the j-th lumped component... The weight is set to 0. The sum of the compositional weights of each catalytic slurry molecule within the same lumped component is 1. The mole fraction and mass fraction corresponding to the 22 lumped components are normalized respectively. Based on the mapping matrix, the catalytic slurry molecules contained in any lumped component and the corresponding raw material composition weights of each catalytic slurry molecule can be determined, thereby maintaining a traceable correspondence between the lumped components and their internal catalytic slurry molecules. Figure 7 As shown in the relationship between the number of molecules and the contribution of raw material composition, the number of molecules contained in each lumped component and its contribution to the composition of the raw material are characterized respectively, thereby distinguishing the number of molecules and the actual composition content within the lumped component.

[0143] In some embodiments, based on the molecular-lumped correspondence data and the compositional weights of each catalytic slurry molecule, the molecular properties of the catalytic slurry molecules within each lumped component are weighted according to their composition to determine the lumped property data of the corresponding lumped component. The lumped property data includes at least one of equivalent boiling point, equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, equivalent critical temperature, equivalent critical pressure, and equivalent eccentricity factor. The equivalent aromatic carbon ratio is determined based on the ratio between the weighted total number of aromatic carbon atoms and the weighted total number of carbon atoms in the catalytic slurry molecules within the same lumped component. Through compositional weighting, the lumped property data of each lumped component can reflect the molecular properties and corresponding compositional contributions of different catalytic slurry molecules within it. Figure 6 The composition and equivalent properties of the 22 oil slurry aggregate components shown can be used to obtain the boiling point range, equivalent boiling point, equivalent molecular weight, raw material aggregate composition, and equivalent aromatic carbon ratio of each aggregate component as a function of the aggregate component number.

[0144] Specifically, the equivalent boiling point range for the 22 lumped components is 433.5 K to 1049.7 K, and the equivalent molecular weight range is 130.8 g·mol⁻¹. -1 ~1571.0 g·mol -1 For example, lumped component L1 contains 10 catalytic oil slurry molecules with an equivalent boiling point of 433.5 K and an equivalent molecular weight of 130.8 g·mol⁻¹; lumped component L22 contains 426 catalytic oil slurry molecules with an equivalent boiling point of 1049.7 K and an equivalent molecular weight of 1571.0 g·mol⁻¹. 1 Table 1 records the boiling point range, number of molecules, equivalent boiling point, equivalent molecular weight, equivalent aromatic carbon ratio, and mole fraction of each of the 22 lumped components. The determined lumped property data are used as the property inputs for each lumped component when performing phase equilibrium calculations using the equation of state.

[0145] Table 1

[0146] In some embodiments, isobutane is selected as the supercritical extraction solvent, and a binary interaction parameter correlation between the supercritical extraction solvent and the lumped components is established based on the molecular structure descriptors corresponding to each lumped component. To avoid regressing independent binary interaction parameters for each of the 22 lumped components, the equivalent molecular weight and equivalent aromatic carbon ratio of each lumped component are selected as molecular structure descriptors. The binary interaction parameter between isobutane and the j-th lumped component can be determined according to the following formula:

[0147] in, Indicates supercritical extraction solvent and the first Binary interaction parameters between lumped components Indicates the first The equivalent molecular weight of each lumped component Indicates the first The equivalent aromatic carbon fraction of each lumped component Indicates the reference molecular weight. Indicates the reference aromatic carbon ratio. , , and This represents the model parameters that need to be determined.

[0148] The equivalent molecular weight and equivalent aromatic carbon ratio are determined based on the molecular composition data of the catalytic slurry and the molecular-lumped mapping matrix; the model parameters are determined by regression analysis of deasphalted oil yield experimental data measured under different temperature, pressure, and catalyst-to-oil ratio conditions. Therefore, different lumped components adopt a unified binary interaction parameter correlation formula, and the corresponding binary interaction parameters are determined based on their respective molecular structure descriptors. For example... Figure 8 The binary interaction parameters of the solvent-oil slurry lumped components are determined by the lumped structure descriptor. A correspondence is formed between the molecular structure descriptor of the lumped components, the binary interaction parameter correlation, and the binary interaction parameters corresponding to each lumped component. This allows the binary interaction parameters to be determined based on the calculable lumped structure characteristics without the need to set independent empirical parameters for each lumped component.

[0149] In some embodiments, the feed masses corresponding to isobutane and each lumped component are determined based on the agent-to-oil mass ratio in the extraction operating conditions, and the feed masses are converted into molar composition based on the molecular weight of each component to determine the feed composition used for phase equilibrium calculations. Based on the feed composition, the lumped property data of each lumped component, the binary interaction parameters between isobutane and each lumped component, and the temperature and pressure in the extraction operating conditions, the Peng-Robinson equation of state is used to calculate the fugacity coefficients of isobutane and each lumped component. Figure 9 As shown in the supercritical extraction phase equilibrium calculation route after lumped dimension reduction, the molecular composition data of the catalytic oil slurry is entered into the phase equilibrium calculation after lumped partitioning, lumped property determination and binary interaction parameter determination, and the extract phase composition, raffinate phase composition, phase fraction, material balance results and deasphalted oil yield are obtained.

[0150] In the specific phase equilibrium calculation, based on the fugacity coefficient, a phase stability analysis is performed on the mixture under the current feed composition, temperature, and pressure conditions using the tangential plane distance function. When the phase stability analysis results indicate that the mixture can form two phases, flash evaporation calculations are performed using multiple sets of different initial values ​​to obtain multiple candidate phase equilibrium results. Based on the convergence residuals, phase stability, and physical rationality corresponding to each candidate phase equilibrium result, a selection is made to determine the effective phase equilibrium result that meets the calculation requirements. Based on this, the composition, phase fraction, and deasphalted oil yield of each lumped component in the extract phase and raffinate phase under each extraction operation condition are obtained. The phase stability analysis and multi-initial-value flash evaporation solution are used to improve the effectiveness and stability of the phase equilibrium results; the specific numerical solution method can be selected according to the actual calculation conditions.

[0151] In some embodiments, after obtaining the lumped-level phase allocation results of each lumped component in the extract phase and raffinate phase, the lumped-level phase allocation results are distributed to the corresponding catalytic slurry molecules according to the molecular-lumped mapping matrix and the composition weights corresponding to each catalytic slurry molecule, so as to obtain the molecular-level composition results of the extract phase and raffinate phase. Taking operating condition 11 as an example, the extraction temperature is 421K, the pressure is 5.0MPa, and the catalyst-to-oil mass ratio is 4. Figure 11 As shown in (a), the normalized molar composition of 22 lumped components in the feed, extract phase and raffinate phase were determined respectively.

[0152] The enrichment factor of the corresponding lumped component in the extractant phase is determined based on the normalized mole fraction of each lumped component in the extractant phase and in the feed. The enrichment factor of the extractant phase can be expressed as:

[0153] in, This represents the enrichment coefficient of the extractable phase for the j-th lumped component. This represents the normalized mole fraction of the j-th lumped component in the extractant phase. This represents the normalized mole fraction of the j-th lumped component in the raw material.

[0154] when When >1, it indicates that the corresponding lumped component is enriched in the extract phase relative to the feedstock; when A value less than 1 indicates that the corresponding lumped component is depleted in the extract phase relative to the feedstock. For example... Figure 11 As shown in (b), the low-boiling-point lumped components are generally enriched in the extractable phase, while the high-boiling-point lumped components are generally enriched in the raffinate phase, forming a transitional region of two-phase distribution near lumped component 10. The enrichment coefficient of the extractable phase is based on the feed composition, rather than on the raffinate phase composition or the total yield of deasphalted oil.

[0155] In some embodiments, let the phase contents of the j-th lumped component in the extract phase E and the raffinate phase R be respectively... and The molecular phase content of the i-th catalytic slurry molecule belonging to the j-th lumped component in the extract phase and raffinate phase is determined according to the following formulas:

[0156] in, This represents the compositional weight of the i-th catalytic slurry molecule in the j-th lumped component. Based on the above allocation relationship, the phase content of each lumped component in the extract phase and raffinate phase is allocated to the corresponding catalytic slurry molecules, thereby restoring the molecular-level composition results of the extract phase and raffinate phase. Based on the molecular-level composition results, the extract phase content, raffinate phase content, single-molecule extraction rate, and compositional distribution corresponding to different molecular properties of each catalytic slurry molecule are determined.

[0157] like Figure 12 As shown, the molar contents of catalytic slurry molecules with the same carbon number and DBE are summed, and the cumulative molar contents of corresponding carbon number and DBE grid points are represented by bubble area. The distributions of the feed, extract, and raffinate phases are characterized using the same bubble area scale, allowing for direct comparison of their molecular composition distributions. The molecular composition of the extract phase is mainly concentrated in the lower carbon number region, while the raffinate phase retains a wider range of high carbon number and high DBE compositions. Since the molecular-level composition results of the feed, extract, and raffinate phases are all determined based on the same molecular-lumped mapping relationship, the lumped-level phase distribution results can be traced back to specific catalytic slurry molecules.

[0158] In some embodiments, to determine representative specific catalytic slurry molecules within each lumped component, the molar fraction of each catalytic slurry molecule in its respective lumped component can be compared to identify the catalytic slurry molecule with the largest molar fraction of raw material in each lumped component. Information such as the molecular formula, carbon number, DBE, molecular weight, boiling point, and molar fraction of the corresponding catalytic slurry molecule is recorded. Table 2 lists the catalytic slurry molecules with the largest molar fraction of raw material corresponding to each of the 22 lumped components. The identified catalytic slurry molecules are used to characterize specific molecular entries that contribute significantly to the composition of the raw material in the corresponding lumped component and do not replace other catalytic slurry molecules contained in the same lumped component.

[0159] Table 2

[0160] In some embodiments, to verify the calculation results of the method for determining the molecular composition of the supercritical catalytic oil slurry extraction and to compare different extraction operating conditions, 21 sets of isobutane supercritical extraction experimental data were selected for verification. The pressure corresponding to conditions 1-17 was 5.0 MPa, and the pressure corresponding to conditions 18-21 was 4.5 MPa. The agent-to-oil mass ratio was 4 for all conditions, and the temperature range was 348-473 K. Based on the measured deasphalted oil yield corresponding to each condition, and while maintaining consistency in raw material composition, supercritical extraction solvent type, and extraction operating conditions, the deasphalted oil yield for each condition was calculated. Based on the calculated and experimental values ​​of the deasphalted oil yield for all 21 conditions, the coefficient of determination, root mean square error, and mean absolute error were uniformly determined. Figure 7The relationship between the yield of deasphalted oil and temperature under different pressure conditions and the signed error corresponding to each working condition are shown.

[0161] like Figure 10 Experimental verification of DAO yield under different temperatures and pressures shows that the calculated deasphalted oil yield is generally consistent with the experimental values, with a coefficient of determination R² of 0.986, a root mean square error of 0.038, and a mean absolute error of 0.028. Under a pressure of 5.0 MPa, the calculation results can characterize the rapid change in deasphalted oil yield from a high yield region of approximately 0.75 to a low yield region. Under a low yield condition of 4.5 MPa, some calculated values ​​show relative deviations from experimental values, but the corresponding absolute errors remain at a low level. Based on the signed errors corresponding to each condition, extraction operating conditions with relatively large errors near phase transitions can be identified. Further corrections to relevant model parameters or increasing experimental data near these operating conditions can improve the calculation accuracy of the corresponding operating regions. Therefore, the changing trends of extraction effects can be compared based on the calculated deasphalted oil yield under different temperature and pressure conditions, and specific operating conditions with relatively large calculation errors can be identified, providing a basis for comparing and selecting extraction operating conditions.

[0162] In some embodiments, such as Figure 13 As shown, an apparatus for determining the molecular composition of catalytic slurry supercritical extraction is also provided. The apparatus includes a processor, a memory, a data input interface, and a result output interface. The memory stores computer programs, molecular-lumped correlation data, and data generated during calculations. The processor executes the computer program to acquire catalytic slurry molecular composition data, partition lumped components, establish molecular-lumped correlation data, determine lumped property data, determine binary interaction parameters, perform phase equilibrium calculations, determine molecular-level composition results, and screen extraction operation conditions. The apparatus can be deployed on servers, workstations, industrial process simulation platforms, enterprise R&D platforms, or process package development platforms.

[0163] During operation, the data input interface acquires data on the molecular composition of the catalytic slurry, information on the supercritical extraction solvent, extraction operating conditions, and experimental data on the deasphalted oil yield. The processor determines multiple lumped components and their corresponding weights based on the molecular properties and compositional content of the catalytic slurry molecules, establishes molecular-lumped correspondence data, determines the lumped physical properties of each lumped component based on the molecular properties and weights, determines binary interaction parameters based on the lumped physical properties, and performs phase equilibrium calculations in conjunction with the supercritical extraction solvent information and extraction operating conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and raffinate phase. Based on the stored molecular-lumped correspondence data and weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and raffinate phase. The result output interface outputs the deasphalted oil yield, the molecular composition and molecular property distribution of the catalytic slurry in the extract phase and raffinate phase, and the corresponding extraction operating condition screening results. Figure 13 The connection relationships in the code are used to represent the data or calculation result transfer relationships between the components.

[0164] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0165] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0166] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0167] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations and modifications are possible without departing from the spirit of this specification, and it is intended that the appended claims cover such variations and modifications without departing from the spirit of this specification.

Claims

1. A method for determining the molecular composition of catalytic oil slurry supercritical extraction, characterized in that, include: Acquire data on the molecular composition of the catalytic oil slurry, information on the supercritical extraction solvent, and extraction operating conditions; The molecular composition data of the catalytic slurry includes the composition, content, and molecular properties of multiple catalytic slurry molecules; Based on the molecular properties, the plurality of catalytic slurry molecules are divided into multiple lumped components; based on the composition content, the composition weight of each catalytic slurry molecule in its respective lumped component is determined, and molecular-lumped correspondence data is established. Based on the molecular properties and the compositional weights, determine the lumped property data of each lumped component; Based on the lumped physical property data, determine the molecular structure descriptor of each lumped component; based on the molecular structure descriptor and the supercritical extraction solvent information, determine the binary interaction parameters between the supercritical extraction solvent and each lumped component; Phase equilibrium calculations are performed using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operating conditions to obtain the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase. Based on the molecular-lumped correspondence data and the composition weights, the lumped-level phase allocation results are assigned to the corresponding catalytic slurry molecules to obtain the molecular-level composition results of the extract phase and / or the raffinate phase.

2. The method according to claim 1, characterized in that, The acquisition of catalytic oil slurry molecular composition data includes: Obtain gas chromatography-mass spectrometry analysis data, nuclear magnetic resonance analysis data, elemental analysis data, and simulated distillation analysis data of catalytic oil slurry samples; Based on the gas chromatography-mass spectrometry analysis data, the core molecules of the catalytic slurry were determined; Based on the nuclear magnetic resonance analysis data, the elemental analysis data, and the simulated distillation analysis data, the compositional distribution of the core molecule is constrained using a probability density function; The target physical property is determined based on the composition distribution, and the relative error between the predicted and experimental values ​​of the target physical property is used as the objective function. The parameters of the probability density function are optimized using a genetic algorithm to obtain the molecular composition data of the catalytic oil slurry.

3. The method according to claim 1, characterized in that, The process of dividing the plurality of catalytic slurry molecules into a plurality of lumped components based on the molecular properties includes: Based on at least one of the boiling point, molecular weight, aromatic carbon ratio, and structural family type of each catalytic oil slurry molecule, determine the lumped interval corresponding to each catalytic oil slurry molecule; Based on the lumped interval, each of the catalytic oil slurry molecules is divided into the corresponding lumped component.

4. The method according to claim 1, characterized in that, The step of determining the compositional weight of each catalytic oil slurry molecule in its respective lumped group based on the compositional content, and establishing molecule-lumped group correspondence data, includes: Based on the composition content of each catalytic oil slurry molecule, the composition content of catalytic oil slurry molecules belonging to the same lumped component is normalized to determine the composition weight of each catalytic oil slurry molecule in its respective lumped component. Based on the lumped component to which each of the catalytic oil slurry molecules belongs and the composition weight, establish the molecule-lumped component correspondence data; The molecular-lumen correspondence data is stored in the form of a mapping matrix, mapping table, or index table, and the composition weights are normalized molar weights or normalized mass weights.

5. The method according to claim 1, characterized in that, The determination of the lumped property data of each lumped component based on the molecular properties and the composition weights includes: Based on the molecular properties and corresponding compositional weights of the catalytic oil slurry molecules in each of the lumped components, the molecular properties are weighted according to composition to determine the equivalent physical properties of each of the lumped components; The equivalent physical properties are defined as the lumped physical property data of the corresponding lumped components; The equivalent physical properties include at least one of the following: equivalent boiling point, equivalent molecular weight, equivalent critical temperature, equivalent critical pressure, equivalent eccentricity factor, equivalent hydrogen-to-carbon ratio, and equivalent aromatic carbon ratio.

6. The method according to claim 5, characterized in that, The step of determining the binary interaction parameters between the supercritical extraction solvent and each of the lumped components based on the molecular structure descriptor and the supercritical extraction solvent information includes: Based on the equivalent properties of each of the aggregated components, the corresponding molecular structure descriptor is determined; wherein, the molecular structure descriptor includes at least one of the following: equivalent molecular weight, equivalent aromatic carbon ratio, equivalent hydrogen-to-carbon ratio, number of aromatic rings, and solubility parameter; Obtain experimental data on the yield of deasphalted oil under multiple experimental extraction conditions; Based on the experimental data of deasphalted oil yield, the model parameters of the binary interaction parameter correlation equation were determined; Based on the model parameters and the molecular structure descriptors of each lumped component, the binary interaction parameters between the supercritical extraction solvent and each lumped component are determined.

7. The method according to claim 1, characterized in that, The phase equilibrium calculation, performed using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operating conditions, yields the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase, including: The supercritical extraction solvent and the feed composition of each of the aggregated components are determined based on the solvent-to-oil ratio in the extraction operation conditions. Using the lumped physical property data and the binary interaction parameters, the supercritical extraction solvent and the fugacity coefficients of each of the lumped components are determined by a preset equation of state; Phase stability analysis and flash evaporation calculations are performed based on the fugacity coefficients to determine the lumped-level phase distribution results of each lumped component in the extract phase and the raffinate phase.

8. A device for determining the molecular composition of catalytic oil slurry supercritical extraction, characterized in that, include: The data acquisition module is used to acquire data on the molecular composition of catalytic oil slurry, information on supercritical extraction solvents, and extraction operating conditions. The molecular composition data of the catalytic slurry includes the composition, content, and molecular properties of multiple catalytic slurry molecules; The data determination module is used to divide the plurality of catalytic slurry molecules into multiple lumped components according to the molecular properties; determine the composition weight of each catalytic slurry molecule in its respective lumped component according to the composition content, and establish molecule-lumped component correspondence data; The parameter determination module is used to determine the lumped property data of each of the lumped components based on the molecular properties and the composition weights. Based on the lumped physical property data, determine the molecular structure descriptor of each lumped component; based on the molecular structure descriptor and the supercritical extraction solvent information, determine the binary interaction parameters between the supercritical extraction solvent and each lumped component; The allocation result determination module is used to perform phase equilibrium calculations using the supercritical extraction solvent information, the lumped physical property data, the binary interaction parameters, and the extraction operation conditions to obtain the lumped-level phase allocation results of each lumped component in the extract phase and the raffinate phase. The composition result determination module is used to allocate the lumped-level phase allocation result to the corresponding catalytic slurry molecules according to the molecular-lumped correspondence data and the composition weight, so as to obtain the molecular-level composition result of the extract phase and / or the raffinate phase.

9. An electronic device, characterized in that, It includes a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.

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