Method for evaluating stability of heavy oil

Abstract

The invention relates to a method for evaluating the stability of heavy oil based on composition distribution of hydrocarbon, which comprises the following steps: detecting composition distribution data of hydrocarbon in a heavy oil sample by adopting high-resolution mass spectrometry equipment, and calculating the instability index of the heavy oil sample according to a specific formula. The sample amount and the solvent amount used for analysis are small, the test process is short in time consumption, the evaluation result is accurate, the reproducibility is good, and the discrimination degree is high; the method is especially suitable for analysis requirements of heavy oil stability in processes of heavy crude oil on-site modification, asphaltene deposition research, heavy oil separation and component refining, heavy ship fuel component blending, inferior residual oil fixed bed hydrogenation, slurry bed hydrogenation, fluidized bed hydrogenation and the like.

Description

Technical Field

[0001] This disclosure relates to a method for evaluating the stability of heavy oil. Background Technology

[0002] Converting a certain proportion of residual oil from heavy and low-quality crude oil into feedstocks or components suitable for producing chemical feedstocks, low-sulfur heavy marine fuel, low-sulfur coke, and high-grade road asphalt is a key research and development direction for current heavy oil processing technology. Currently, heavy oil processing technologies mainly include decarbonization and hydrotreating. Regardless of the route, the stability of heavy oil, its modified product oil, and unconverted oil are crucial property parameters for process technology. This is because they relate to the potential for heavy oil to aggregate and separate, leading to fouling and coking in reactors, pipelines, distillation towers, separators, heat exchangers, and catalysts, thus hindering the safe and stable operation of the process unit at its intended load.

[0003] Currently, the main methods for evaluating the stability of crude oil and heavy oil systems include spot test, microscopic observation, spectroscopy, refractive index method, conductivity method, precipitation method, viscosity method, and colloidal stability method. In their article "Crude Oil Compatibility and Its Influence on Distillation Process" (Acta Petrolei Sinica (Petroleum Processing), 2009, 25(2): 150-155), Guan Xiupeng et al. proposed an instability parameter for crude oil mixture systems using near-infrared light scattering analysis combined with the principle of multiple light scattering. This parameter can be used to characterize the compatibility of crude oil and crude oil mixture systems. The higher the instability parameter, the worse the compatibility of the system. In summary, most existing methods for evaluating the stability of crude oil or heavy oil rely on phenomena or physical characteristics observed in oil samples under the influence of external factors such as solvent, temperature, pressure, residence time, and gravity to assess the stability of heavy oil. They rarely evaluate intrinsic stability from the perspective of intrinsic factors such as the molecular composition and structure of crude oil and heavy oil. Moreover, existing methods generally suffer from drawbacks such as complex operation, long operation time, large sample and reagent quantities required, and limited adaptability to actual oil samples such as heavy oil and residue oil with high viscosity and dark color. Summary of the Invention

[0004] The purpose of this disclosure is to provide a method for evaluating the stability of heavy oil based on the hydrocarbon composition distribution.

[0005] To achieve the above objectives, this disclosure provides a method for evaluating the stability of heavy oil, the method comprising: High-resolution mass spectrometry was used to detect the test sample solution containing heavy oil, and spectral data were obtained. Molecular identification is performed on the spectral data to obtain the compositional distribution data of hydrocarbons, which includes the number of carbon atoms, the number of equivalent double bonds, and the abundance. Based on the compositional distribution data of the hydrocarbons, the instability index of the heavy oil sample is calculated according to formula (1). The instability index is used to characterize the tendency of the heavy oil sample to exhibit agglomeration, phase separation, and / or scaling and coking phenomena. (1) In equation (1), instab represents the instability index of the heavy oil sample, ∑ I CH(DBE≥p) This represents an equivalent number of double bonds greater than or equal to p The sum of the abundances of hydrocarbons, ∑ I CH(q×CN<DBE<p) This represents an equivalent double bond number greater than q The number of carbon atoms is twice that of the total number of carbon atoms, but less than that of the total number of carbon atoms. p The sum of the abundance of hydrocarbons, p and q These are preset constants, ∑ I CH Represents the sum of the abundance of all hydrocarbons. DBE CH(AVG) This represents the weighted average of the equivalent double bond numbers in all hydrocarbons. CN CH(AVG) This represents the weighted average number of carbon atoms in all hydrocarbons.

[0006] Optionally, the heavy oil sample includes one or more of the following: heavy crude oil, atmospheric residue, vacuum residue, petroleum asphalt, deasphalted oil, deoiled asphalt, oil slurry, circulating oil, heavy marine fuel oil, coal tar, waste plastic pyrolysis oil, and separated components, refining process materials, and products of the above oil products.

[0007] Optionally, the test sample solution is a mixture of the heavy oil sample and a solvent, wherein the solvent includes one or more of benzene, toluene, xylene, ethylbenzene, chlorobenzene, dichloromethane, chloroform, cyclohexane, methylcyclohexane, and quinoline.

[0008] Optionally, the amount of solvent used is 0.5 to 5 ml per milligram of the heavy oil sample.

[0009] Optionally, the high-resolution mass spectrometry device is a Fourier transform ion cyclotron resonance mass spectrometer and / or an ion trap mass spectrometer.

[0010] Optionally, the sample introduction device of the high-resolution mass spectrometer is an injection pump and / or liquid chromatography.

[0011] Optionally, the ionization source of the high-resolution mass spectrometer is an atmospheric pressure photoionization source.

[0012] Optionally, the detection conditions include: nebulizer pressure of 1~2 bar, drying gas flow rate of 2.0~4.0 L / min, drying gas temperature of 180~200℃, ion source temperature of 350~400℃, ion accumulation time of 0.1~0.5 s, nominal resolution of mass-to-charge ratio at 400 ≥ 480000, and mass-to-charge ratio detection range of 150~1500; and / or Before the step of using a high-resolution mass spectrometer to detect the test sample solution containing heavy oil and obtain spectral data, the method further includes: mass calibrating the high-resolution mass spectrometer using a known sample, wherein the known sample includes polystyrene standards and / or a mixed sample containing multiple alkylbenzene compounds.

[0013] Optionally, the step of performing molecular identification on the spectral data includes: The theoretical mass-to-charge ratio of the molecular ion is calculated according to equation (2): M = M C × CN + M H ×(2× CN -2× DBE +2 +n )+ M S × s + M N × n + M O × o (2) In equation (2), M C , M H , M S , M N , M O These represent the precise mass numbers of the elements carbon, hydrogen, sulfur, nitrogen, and oxygen, respectively. CN This represents the number of carbon atoms in a compound and ranges from 5 to 120. DBE This represents the number of equivalent double bonds in a compound and ranges from 0 to 60. s This represents the number of sulfur atoms in the compound and its value ranges from 0 to 5. n This represents the number of nitrogen atoms in the compound and its value ranges from 0 to 2. o It represents the number of O atoms in the compound and its value ranges from 0 to 4. The spectral data is matched and identified with the theoretical mass-to-charge ratio.

[0014] Optionally, in equation (1), p It is 30. q It is 0.75.

[0015] Optionally, the method further includes: When the instability index exceeds a preset threshold, the heavy oil sample is determined to have a potential unstable trend; wherein, the preset threshold is 2.

[0016] Through the above technical solution, this disclosure provides a method for evaluating the stability of heavy oil based on the compositional distribution of hydrocarbons. High-resolution mass spectrometry is used to detect the compositional distribution data of hydrocarbons in the heavy oil sample. The instability index of the heavy oil sample can then be calculated using a specific formula. This method overcomes the limitations of existing technologies that evaluate heavy oil stability based on external factors, observed phenomena, or physical characteristics. Furthermore, it requires small sample and solvent volumes, has a short experimental time, and provides accurate evaluation results with good reproducibility and high discrimination. It is particularly suitable for analyzing the stability of heavy oil in processes such as on-site upgrading of heavy crude oil, asphaltene deposition studies, heavy oil separation and component refining, blending of heavy marine fuel components, and fixed-bed, slurry-bed, and fluidized-bed hydrogenation of low-quality residue oil.

[0017] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating a method for evaluating the stability of heavy oil provided in one implementation.

[0019] Figure 2 This is a high-resolution mass spectrum of the vacuum residue oil from Example 1.

[0020] Figure 3 This is a compositional distribution diagram of hydrocarbons in vacuum residue as a function of DBE and carbon number in Example 1.

[0021] Figure 4 This is a linear correlation graph showing the instability index of the vacuum residue oil and its hydrogenated oil obtained in Example 2 and the total sediment content.

[0022] Figure 5 This is a linear correlation graph between the instability index of the vacuum residue oil and its hydrogenated oil obtained in Example 3 and the total sediment content.

[0023] Figure 6This is a linear correlation graph showing the instability index of the vacuum residue oil and its hydrogenated product obtained in Comparative Example 1 and the total sediment content.

[0024] Figure 7 Comparative Example 2: vacuum residue and its hydrogenated product oil w S + w As ) / ( w A + w R Linear correlation diagram between the ratio and the total sediment content. Detailed Implementation

[0025] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0026] This disclosure provides a method for evaluating the stability of heavy oil, with reference to... Figure 1 The method includes the following steps S101~S103: S101. High-resolution mass spectrometry is used to detect the test sample solution containing heavy oil to obtain spectral data; S102. Perform molecular identification on the spectral data to obtain the compositional distribution data of hydrocarbons, wherein the compositional distribution data includes the number of carbon atoms, the number of equivalent double bonds, and the abundance. S103. Based on the compositional distribution data of the hydrocarbons, calculate the instability index of the heavy oil sample according to formula (1). The instability index is used to characterize the tendency of the heavy oil sample to exhibit agglomeration, phase separation, and / or scaling and coking phenomena. (1) In equation (1), instab represents the instability index of the heavy oil sample, ∑ I CH(DBE≥p) This represents an equivalent number of double bonds greater than or equal to p The sum of the abundances of hydrocarbons, ∑ I CH(n×CN<DBE<q) This represents an equivalent double bond number greater than q The number of carbon atoms is twice that of the total number of carbon atoms, but less than that of the total number of carbon atoms. p The sum of the abundance of hydrocarbons, p and q These are preset constants, ∑ I CH Represents the sum of the abundance of all hydrocarbons. DBE CH(AVG) This represents the weighted average of the equivalent double bond numbers in all hydrocarbons. CNCH(AVG) This represents the weighted average number of carbon atoms in all hydrocarbons.

[0027] This disclosure provides a method for evaluating the stability of heavy oil based on the compositional distribution data of hydrocarbons. The method involves analyzing high-resolution mass spectrometry data of heavy oil samples to obtain compound composition data, extracting the number of carbon atoms, equivalent double bonds, and abundance information of characteristic hydrocarbons, and then calculating the instability index of the heavy oil sample according to a specific formula. This index reflects whether the heavy oil sample exhibits potential instability (i.e., agglomeration, phase separation, and / or scaling and coking). This disclosure constructs an instability index at the molecular composition and structural level, which can be used to evaluate and monitor the intrinsic stability of heavy oil. It eliminates the need for artificial operating conditions such as solvent treatment, aging treatment, isothermal treatment, pressurization treatment, and emulsification treatment commonly used in existing methods, overcoming the limitations of existing technologies that evaluate heavy oil stability based on external factors, observed phenomena, or physical characteristics. Furthermore, the method disclosed herein has the advantages of requiring small sample and solvent volumes, short experimental time, accurate evaluation results, good reproducibility, and high discrimination. It is particularly suitable for analyzing the stability of heavy oil in processes such as on-site upgrading of heavy crude oil, asphaltene deposition studies, heavy oil separation and component refining, blending of heavy marine fuel components, fixed-bed hydrogenation of inferior residue oil, slurry-bed hydrogenation, and fluidized-bed hydrogenation.

[0028] In step S101, the heavy oil sample may include oil products from various sources commonly found in the art with a distillation range from 350°C to the final boiling point (FBP). Specifically, the heavy oil sample may include one or more of the following: heavy crude oil, atmospheric residue, vacuum residue, petroleum asphalt, deasphalted oil, deoiled asphalt, oil slurry, circulating oil, heavy marine fuel oil, coal tar, waste plastic pyrolysis oil, and separated components, refining process materials, and products of the above oil products.

[0029] The sample solution to be tested is a mixture of the heavy oil sample and a solvent, wherein the solvent can be a common organic solvent. In one specific embodiment, the solvent may include one or more of benzene, toluene, xylene, ethylbenzene, chlorobenzene, dichloromethane, chloroform, cyclohexane, methylcyclohexane, and quinoline, preferably one or more of toluene, xylene, and chloroform, and most preferably toluene.

[0030] Furthermore, the amount of solvent can be adjusted within a certain range to ensure that the sample solution to be tested has a certain concentration. Specifically, the amount of solvent used relative to each milligram of the heavy oil sample can be 0.5 to 5 milliliters, preferably 1 to 2 milliliters. Using solvent within the above range is beneficial to further improve the accuracy of the evaluation results.

[0031] High-resolution mass spectrometry (HRMS) enables precise measurement of the mass-to-charge ratio of ions at extremely high mass resolution. In a preferred embodiment, the HRMS is a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) and / or an ion trap mass spectrometer (IT MS). These mass spectrometry devices are particularly suitable for the detection of heavy oil samples, which helps to improve the accuracy of evaluation results.

[0032] In one specific embodiment, the high-resolution mass spectrometer can be calibrated before detecting the sample solution to improve the accuracy of subsequent detection. Specifically, the method may further include: calibrating the high-resolution mass spectrometer using a known sample, wherein the known sample may include polystyrene standards and / or a mixed sample containing multiple alkylbenzene compounds. The specific operation of the mass calibration includes: (1) acquiring high-resolution mass spectra of known samples such as polystyrene standards and / or mixed samples containing multiple alkylbenzene compounds; (2) selecting the measured mass-to-charge ratio of polystyrene and / or alkylbenzene in the spectrum and fitting it with its theoretical mass-to-charge ratio using a quadratic polynomial curve, calibrating the mass axis of the mass spectrometer using the quadratic polynomial equation, and calculating the error between the calibrated mass-to-charge ratio of polystyrene and / or alkylbenzene and the theoretical mass-to-charge ratio; (3) repeating the above steps until the error between the calibrated mass-to-charge ratio of polystyrene and / or alkylbenzene and the theoretical mass-to-charge ratio is no greater than 1.0 × 10⁻⁶. -6 .

[0033] The high-resolution mass spectrometry (HMS) equipment can be appropriately equipped with a sample introduction device and an ionization source to improve the accuracy of the evaluation results. The sample introduction device is used to precisely introduce the sample into the HMS equipment, and the ionization source is used to convert the sample solution to be tested into gaseous ions (including molecular ions and / or addition ions). Thus, by injecting the sample solution to be tested into the ionization source through the sample introduction device, the mass-to-charge ratio and abundance information of the ions are analyzed using the HMS equipment to obtain the spectral data.

[0034] In one specific embodiment, the sample introduction device of the high-resolution mass spectrometer can be a syringe pump and / or a liquid chromatograph. Specifically, when the sample introduction device of the high-resolution mass spectrometer is a syringe pump, the injection rate of the syringe pump can be 120~360 μL / h; when the sample introduction device of the high-resolution mass spectrometer is a liquid chromatograph, the mobile phase flow rate of the liquid chromatograph can be 0.8~3.0 mL / min.

[0035] In one specific embodiment, the ionization source of the high-resolution mass spectrometer can be an atmospheric pressure photoionization source (APPI).

[0036] In one specific embodiment, the detection conditions may include: nebulizer pressure of 1~2 bar, drying gas flow rate of 2.0~4.0 L / min, drying gas temperature of 180~200℃, ion source temperature of 350~400℃, ion accumulation time of 0.1~0.5 s, nominal resolution of mass-to-charge ratio at 400 ≥480000, and mass-to-charge ratio detection range of 150~1500.

[0037] The spectral data includes the mass-to-charge ratio (m / z) of ions in the sample solution and their corresponding abundance. The m / z ratio is the ratio of the ion's mass to its charge. Abundance is the relative intensity or signal intensity of the ion in the mass spectrum, typically reflected as the peak height or peak area. The sample solution is prepared using a solvent that does not produce a signal in high-resolution mass spectrometry. The obtained spectral data can be used to evaluate the heavy oil sample. The precise mass number and corresponding abundance of each m / z ratio within the detection range can be determined by obtaining the data table corresponding to the high-resolution mass spectrometry spectrum. The source of the data table corresponding to the high-resolution mass spectrometry spectrum is known to those skilled in the art.

[0038] In step S102, molecular identification is performed on the spectral data to obtain the compositional distribution data of compounds in the heavy oil sample. These compounds include hydrocarbons and compounds containing heteroatoms (such as sulfur, nitrogen, and oxygen). This disclosure selects the compositional distribution data of hydrocarbons as the calculation parameter for the instability index of the heavy oil sample, including the number of carbon atoms in the hydrocarbon, the number of double bond equivalents (DBE), and the abundance of the hydrocarbon in the spectral data. The number of double bonds is the total number of double bonds, rings, and multiple bonds in the hydrocarbon, and can be used to characterize the degree of unsaturation of the hydrocarbon.

[0039] In one specific embodiment, the step of performing molecular identification on the spectral data may include: S1021. Calculate the theoretical mass-to-charge ratio of the molecular ion according to formula (2): M = M C × CN + M H ×(2× CN -2× DBE +2 +n )+ M S × s + M N × n + M O × o (2) In equation (2), M C , M H , M S , M N , M O These represent the precise mass numbers of carbon, hydrogen, sulfur, nitrogen, and oxygen, respectively, preferably retaining 5 or more precise mass numbers. CN Represents the number of C (carbon) atoms in a compound and ranges from 5 to 120. DBE Represents the equivalent number of double bonds in a compound and takes a value between 0 and 60. s This represents the number of sulfur atoms in the compound and ranges from 0 to 5. n This represents the number of N (nitrogen) atoms in the compound and its value ranges from 0 to 2. o It represents the number of O (oxygen) atoms in the compound and its value ranges from 0 to 4; S1022. Match the spectral data with the theoretical mass-to-charge ratio; specifically, compare the mass-to-charge ratio in the spectral data from smallest to largest with the theoretical mass-to-charge ratio, with an allowable error of (0.5~5)×10⁻⁶. -6 The preferred value is (0.5~2)×10 -6 For example, 1×10 -6 This allows us to determine the types of hydrocarbons and obtain compositional distribution data for them.

[0040] In step S103, based on the compositional distribution data of the hydrocarbons, hydrocarbons exhibiting unstable characteristics are selected for use in formula (1) to calculate the instability index of the heavy oil sample. Hydrocarbons exhibiting unstable characteristics include those with an equivalent double bond number greater than or equal to... p Hydrocarbons, denoted as CH (DBE≥p), and having an equivalent number of double bonds greater than [value missing]. q The number of carbon atoms is twice that of the total number of carbon atoms, but less than that of the total number of carbon atoms. p Hydrocarbons, denoted as CH (q×CN<DBE<p), typically have complex polycyclic aromatic structures or other unsaturated properties. They tend to aggregate and form deposits or coke during heavy oil processing. By using these compounds as the characteristic compounds most likely to affect the stability of heavy oil, the instability index of heavy oil samples can be accurately calculated.

[0041] Specifically, p and q These are preset constants and can be set according to stability evaluation criteria, for example, p It can be 20~35. qIt can be 0.67~0.8. In a preferred embodiment, in formula (1), p It is 30. q With a value of 0.75, by screening hydrocarbons with an equivalent double bond number greater than or equal to 30 and / or an equivalent double bond number greater than 0.75 times their carbon atom number, molecules that play a key role in the stability of heavy oil can be precisely identified, thereby better predicting and evaluating the performance of heavy oil under different processing conditions.

[0042] Furthermore, in equation (1), DBE CH(AVG) It can be calculated according to the following formula (3), CN CH(AVG) It can be calculated according to the following formula (4): (3) (4) In equation (3), DBE CH(i) Represents hydrocarbons i The equivalent number of double bonds, I CH(i) Represents hydrocarbons i The abundance; in equation (4), CN CH(i) Represents hydrocarbons i The number of carbon atoms, I CH(i) Represents hydrocarbons i The abundance of.

[0043] By obtaining the instability index of heavy oil samples instab The instability index can be used to evaluate the stability of the heavy oil sample. The larger the instability index, the stronger the tendency of the heavy oil sample to exhibit agglomeration, phase separation, and / or scaling and coking.

[0044] Furthermore, by determining the magnitude of the instability index, it is beneficial to monitor the trend of heavy oil agglomeration and / or scaling and coking during separation and refining. Specifically, the method may further include the following step S104: S104. When the instability index exceeds a preset threshold, it is determined that the heavy oil sample has a potential unstable trend; wherein, the preset threshold can be adjusted within a certain range according to the type of oil, and in one specific embodiment, the preset threshold is 2.

[0045] This disclosed method enables rapid evaluation of heavy oil stability, with accurate and reliable results. In practical applications, by calculating the instability index of multiple heavy oil samples, the stability trends of these samples can be compared according to their order of magnitude. For heavy oil samples from similar processing processes or technological units with different instability indices, further auxiliary optimization can be achieved. This provides a scientific basis for optimizing process conditions in heavy oil separation, refining, and blending processes, helps to achieve refined control of the process, improves production efficiency and product quality, and has significant industrial application value.

[0046] The present disclosure is further described in detail below through examples. All raw materials used in the examples are commercially available.

[0047] Example 1 In this embodiment, vacuum residue with a distillation range >540℃ from Shijiazhuang Refinery and its separated four components (i.e., SARA), saturated fraction, aromatic fraction, gum and asphaltenes, were used as heavy oil samples.

[0048] (1) Preparation of the test sample solution for heavy oil samples Prepare mixed solutions of vacuum residue (VR1) and its separated saturated fraction (VR-S), aromatic fraction (VR-A), gum (VR-R), and asphaltenes (VR-As) with solvent toluene in 2 mL chromatographic bottles. The amount of solvent used is 2 mL per milligram of vacuum residue, saturated fraction, aromatic fraction, and gum, and 1 mL per milligram of asphaltenes.

[0049] (2) Acquire high-resolution mass spectrometry data of the sample solution to be tested, and analyze and identify the composition and distribution of hydrocarbons. High-resolution mass spectra of the above-mentioned sample solutions were acquired using a Bruker solariX XR Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS). An atmospheric pressure photoionization source (APPI) in positive ion mode was used, with sample injection via a syringe pump. The high-resolution mass spectrometer was calibrated using alkylbenzene homologues before sample injection.

[0050] The sampling method was as follows: injection rate 360 ​​μL / h, capillary voltage 2000 V, nebulizer 1 bar, drying gas flow rate 2.0 L / min, dryer temperature 200 °C, and ion source temperature 400 °C. For vacuum residue, saturated fractions, and aromatic fractions, the ion accumulation time was 0.1 s; for resins, 0.2 s; and for asphaltenes, 0.5 s. The time-of-flight (TOF) was 1.0 ms, the mass filter Q1 mass was 200 μm, the radio frequency (RF) voltage was 350 Vpp, the front and rear baffle voltages were 2.5 V, the sweep excitation power (SEP) was 20, and the mass-to-charge ratio (MTBF) was... m / z The detection range is 150~1500, the nominal resolution at a mass-to-charge ratio of 400 is 800000, and the cumulative number of scans is 128.

[0051] Spectrum identification process: For mass spectrum peaks with a signal-to-noise ratio greater than 5.5, the theoretical mass-to-charge ratio of the molecular ion is calculated using equation (2) and matched with the spectrum data for identification. M = M C × CN + M H ×(2× CN -2× DBE +2 +n )+ M S × s + M N × n + M O × o (2) In equation (2), M C , M H , M S , M N , M O These represent the precise mass numbers of carbon, hydrogen, sulfur, nitrogen, and oxygen, retaining at least five digits. CN The value ranges from 5 to 120. DBE The value ranges from 0 to 60. s The value ranges from 0 to 5. n The value ranges from 0 to 2. o The value ranges from 0 to 4.

[0052] The mass-to-charge ratios in the spectral data of the sample solution to be tested are compared with the calculated theoretical mass-to-charge ratios in ascending order. The allowable error for matching and identification is 1 ppm, thereby obtaining the compositional distribution data of hydrocarbons.

[0053] The high-resolution mass spectra of the collected vacuum residue are as follows: Figure 2 As shown in the figure, the compositional distribution of hydrocarbons with varying numbers of equivalent double bonds and carbon atoms is as follows: Figure 3 As shown.

[0054] (3) Calculate the instability index of the heavy oil sample. The sum of the abundances of all hydrocarbons and the weighted average of the equivalent double bond number and carbon atom number were calculated. The results are listed in Table 1 below, where the weights represent the proportion of the abundance of each hydrocarbon in the total abundance of all hydrocarbons. The abundances of compounds with an equivalent double bond number greater than or equal to 30 and compounds with an equivalent double bond number greater than 0.75 times the carbon atom number were extracted. The results of characteristic compounds that meet the extraction criteria are listed in Table 2 below.

[0055] The instability index of each heavy oil sample is calculated according to formula (1): (1) In equation (1), instab represents the instability index of the heavy oil sample, ∑ I CH(DBE≥p) This represents an equivalent number of double bonds greater than or equal to p The sum of the abundances of hydrocarbons, ∑ I CH(q×CN<DBE<p) This represents an equivalent double bond number greater than q The number of carbon atoms is twice that of the total number of carbon atoms, but less than that of the total number of carbon atoms. p The sum of the abundance of hydrocarbons, p It is 30. q It is 0.75, ∑ I CH Represents the sum of the abundance of all hydrocarbons. DBE CH(AVG) This represents the weighted average of the equivalent double bond numbers in all hydrocarbons. CN CH(AVG) This represents the weighted average number of carbon atoms in all hydrocarbons.

[0056] The calculated instability indices of vacuum residue and its four SARA components are listed in Table 3 below in ascending order of instability index.

[0057] Table 1

[0058] Table 2

[0059] Among them, the matching error = 1000000×(theoretical value - measured value) / measured value Table 3

[0060] As can be seen from Table 3, the relative order of the instability indices of the vacuum residue and its SARA four components evaluated by the method of the present disclosure conforms to the trend judgment of the vacuum residue and its SARA four components in terms of aggregation and instability known to those skilled in the art. Moreover, it can be seen that the instability indices of the stable vacuum residue, its saturates, and aromatics are all small (both less than 2), while the instability indices of the unstable resins and asphaltenes are all large (far greater than 2), indicating that the method provided by the present disclosure can qualitatively evaluate the instability trend of heavy oil and its separated components.

[0061] Example 2 According to the method of Example 1, the stability evaluation was carried out on the vacuum residue (VR2) with a distillation range > 540 °C from the Middle East and three hydrocracked oils with different hydrocracking conversion depths (vacuum residue hydrocracked oil A, vacuum residue hydrocracked oil B, vacuum residue hydrocracked oil C, and the distillation range is 350 °C - 720 °C). At the same time, the total sediment content in the above oils was detected by the standard hot filtration method of SH / T 0701. The calculation results of the instability index and the data of the total sediment content are listed in Table 4 below.

[0062] Table 4

[0063] According to the instability index and the total sediment content in Table 4, a linear correlation diagram of the two was drawn, as Figure 4 shown. As can be seen from Table 4 and Figure 4 that the relative order of the instability indices of the vacuum residue VR2 and its three hydrocracked oils and the sediment content in their actual systems due to instability is VR2 < A < B < C. The method provided by the present disclosure can evaluate and judge the instability trend of the residue oil raw material and the vacuum residue hydrocracked oils with different conversion depths, and there is a good linear correlation between the instability index and the total sediment content in their actual systems due to instability ( R 2 > 0.98), indicating that the method provided by the present disclosure can be used for the quantitative evaluation of the instability trend of heavy oil and the auxiliary regulation of the hydrocracking conversion depth of residue oil.

[0064] Example 3 The stability of vacuum residue (VR2) and three hydrotreated oils (residue hydrotreated oil A, residue hydrotreated oil B, and residue hydrotreated oil C) with different hydrocracking conversion depths were evaluated according to the method in Example 2. The difference is that in formula (1), p It is 20. q The value is 0.67. The results of the instability index calculation and the total sediment content data are listed in Table 5 below.

[0065] Table 5

[0066] A linear correlation diagram between the instability index and total sediment content in Table 5 was plotted, as shown below. Figure 5 As shown in Table 5 and Figure 5 As can be seen, the order of the instability index calculated in this embodiment is consistent with the relative order of the total sediment content of the sample, but the linear correlation between the instability index and the total sediment content of the sample is slightly worse than that in Example 2.

[0067] Example 4 The stability of deoiled bitumen DOA-1 and DOA-2 with a distillation range >540°C from Saudi heavy oil was evaluated according to the method in Example 1. At the same time, the asphaltenes content in the above oil products was determined by the four-component petroleum bitumen assay. The results are listed in Table 6 below.

[0068] Table 6

[0069] As shown in Table 6, the instability index of deoiled asphalt DOA-2 is greater than that of deoiled asphalt DOA-1, reflecting that the intrinsic stability of deoiled asphalt DOA-2 in terms of composition and structure is worse than that of deoiled asphalt DOA-1. In addition, the content of asphaltenes actually separated from deoiled asphalt DOA-2 is also higher than that of deoiled asphalt DOA-1. This indicates that the method disclosed in this paper can provide an evaluation reference for the instability and precipitation trend of heavy oil.

[0070] Comparative Example 1 The stability of vacuum residue (VR2) and three hydrotreated oils (hydrotreated oil A, hydrotreated oil B, and hydrotreated oil C) with different hydrocracking conversion depths were evaluated according to the method in Example 2. The difference was that the input of hydrocarbons with an equivalent double bond number greater than or equal to 30 and their abundance as the input of the instability index calculation formula was replaced with sulfur-containing compounds with an equivalent double bond number greater than or equal to 30 and their abundance as the input. That is, the instability index of each heavy oil sample was calculated according to the following formula (5): (5) In equation (5), ∑ IS1(DBE≥30) The sum of abundances of sulfur-containing compounds with an equivalent double bond number greater than or equal to 30 in heavy oil samples, ∑ I S1(0.75×CN<DBE<30) The sum of abundances corresponding to sulfur-containing compounds with an equivalent double bond number greater than 0.75 times but less than 30 carbon atoms, ∑ I S1 This represents the sum of the abundances of all sulfur-containing compounds (S1). DBE S1(AVG) The weighted average of the equivalent double bond numbers for all sulfur-containing compounds (S1) CN S1(AVG) This represents the weighted average number of carbon atoms in all sulfur-containing compounds (S1).

[0071] The results of the instability index calculation and the total sediment content data are listed in Table 7 below, and the linear correlation between the two is shown in the figure below. Figure 6 As shown.

[0072] Table 7

[0073] From Table 7 and Figure 6 As can be seen, the order of the instability index calculated in this comparative example is still consistent with the relative order of the total sediment content of the sample, but the linear correlation between the two is significantly worse.

[0074] Comparative Example 2 This comparative example employs a commonly used method in the art for predicting the stability of heavy oil, namely, based on a specific ratio of the mass fractions of the four components of heavy oil: saturated fraction, aromatic fraction, resin, and asphaltenes. w S + w As ) / ( w A + w R The instability of vacuum residue feedstock (VR2) and three hydrotreated product oils (residue hydrotreated product oil A, residue hydrotreated product oil B, and residue hydrotreated product oil C) with different hydrocracking conversion depths was evaluated, specifically as follows: The specific ratios of the four components of the vacuum residue VR2 and its three hydrotreated oils were analyzed and calculated. w S + w As ) / ( w A + w R The relative trends of the sediment content and its occurrence are compared in Table 8 below, and the linear correlation between the two is shown in the figure below. Figure 7 As shown.

[0075] Table 8

[0076] From Table 8 and Figure 7 It can be seen that using a group composition with specific ratios for four components ( w S + w As ) / ( w A + w R The obtained instability evaluation results are inconsistent with the relative order of total sediment content in the actual system due to instability, and the linear correlation is poor.

[0077] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0078] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0079] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for evaluating the stability of heavy oil, characterized in that, The method includes: High-resolution mass spectrometry was used to detect the test sample solution containing heavy oil, and spectral data were obtained. Molecular identification is performed on the spectral data to obtain the compositional distribution data of hydrocarbons, which includes the number of carbon atoms, the number of equivalent double bonds, and the abundance. Based on the compositional distribution data of the hydrocarbons, the instability index of the heavy oil sample is calculated according to formula (1). The instability index is used to characterize the tendency of the heavy oil sample to exhibit agglomeration, phase separation, and / or scaling and coking phenomena. （1） In equation (1), instab represents the instability index of the heavy oil sample, ∑ I CH(DBE≥p) This represents an equivalent number of double bonds greater than or equal to p The sum of the abundances of hydrocarbons, ∑ I CH(q×CN<DBE<p) This represents an equivalent double bond number greater than q The number of carbon atoms is twice that of the total number of carbon atoms, but less than that of the total number of carbon atoms. p The sum of the abundance of hydrocarbons, p and q These are preset constants, ∑ I CH Represents the sum of the abundance of all hydrocarbons. DBE CH(AVG) This represents the weighted average of the equivalent double bond numbers in all hydrocarbons. CN CH(AVG) This represents the weighted average number of carbon atoms in all hydrocarbons.

2. The method according to claim 1, wherein, The heavy oil samples include one or more of the following: heavy crude oil, atmospheric residue, vacuum residue, petroleum asphalt, deasphalted oil, deoiled asphalt, oil slurry, circulating oil, heavy marine fuel oil, coal tar, waste plastic pyrolysis oil, and separated components, refining process materials, and products of the above oils.

3. The method according to claim 1, wherein, The test sample solution is a mixture of the heavy oil sample and a solvent, wherein the solvent includes one or more of benzene, toluene, xylene, ethylbenzene, chlorobenzene, dichloromethane, chloroform, cyclohexane, methylcyclohexane, and quinoline.

4. The method according to claim 3, wherein, The amount of solvent used is 0.5 to 5 ml per milligram of the heavy oil sample.

5. The method according to claim 1, wherein, The high-resolution mass spectrometry equipment is a Fourier transform ion cyclotron resonance mass spectrometer and / or an ion trap mass spectrometer.

6. The method according to claim 1, wherein, The sample introduction device of the high-resolution mass spectrometer is an injection pump and / or liquid chromatography.

7. The method according to claim 1, wherein, The ionization source of the high-resolution mass spectrometer is an atmospheric pressure photoionization source.

8. The method according to claim 1, wherein, The detection conditions include: nebulizer pressure of 1-2 bar, drying gas flow rate of 2.0-4.0 L / min, drying gas temperature of 180-200℃, ion source temperature of 350-400℃, ion accumulation time of 0.1-0.5 s, nominal resolution of mass-to-charge ratio at 400 ≥ 480000, and mass-to-charge ratio detection range of 150-1500; and / or Before the step of using a high-resolution mass spectrometer to detect the test sample solution containing heavy oil and obtain spectral data, the method further includes: mass calibrating the high-resolution mass spectrometer using a known sample, wherein the known sample includes polystyrene standards and / or a mixed sample containing multiple alkylbenzene compounds.

9. The method according to claim 1, wherein, The molecular identification of the spectral data includes: The theoretical mass-to-charge ratio of the molecular ion is calculated according to equation (2): M = M C × CN + M H ×(2× CN -2× DBE +2 +n )+ M S × s + M N × n + M O × o （2） In equation (2), M C , M H , M S , M N , M O These represent the precise mass numbers of the elements carbon, hydrogen, sulfur, nitrogen, and oxygen, respectively. CN This represents the number of carbon atoms in a compound and ranges from 5 to 120. DBE This represents the number of equivalent double bonds in a compound and ranges from 0 to 60. s This represents the number of sulfur atoms in the compound and its value ranges from 0 to 5. n This represents the number of nitrogen atoms in the compound and its value ranges from 0 to 2. o It represents the number of O atoms in the compound and its value ranges from 0 to 4. The spectral data is matched and identified with the theoretical mass-to-charge ratio.

10. The method according to claim 1, wherein, In equation (1), p It is 30. q It is 0.

75.

11. The method according to claim 1, wherein, The method also includes: When the instability index exceeds a preset threshold, the heavy oil sample is determined to have a potential unstable trend; wherein, the preset threshold is 2.

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