A method, device and storage medium for optimizing crude oil reaction kinetic parameters

Abstract

The present application discloses a method, device and storage medium for optimizing crude oil reaction kinetic parameters, the method comprising: performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve at a first heating rate; constructing an oil drop reaction model identical to the thermal analysis experiment; simulating the oil drop reaction model by a finite element method based on the working parameters of the TG / DSC instrument to obtain a second weight loss curve and a second reaction exothermic curve under an instantaneous state; adjusting the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model to make the second weight loss curve coincide with the first weight loss curve; adjusting the reaction enthalpy parameters of the oil drop reaction model to integrate the second reaction exothermic curve and the first reaction exothermic curve to make the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; thereby obtaining optimized reaction kinetic parameters. In this way, the accuracy and reliability of the kinetic parameters can be improved.

Description

Technical Field

[0001] The present application relates to the field of energy extraction technology, and in particular to a method, device, electronic device and storage medium for optimizing crude oil reaction kinetic parameters. Background Art

[0002] With the development of the petroleum industry, oil production technology has become increasingly mature, and the application of kinetic models in oil production software is particularly critical. The current kinetic models mainly provide technical support for traditional oil production industry software, and the kinetic parameters in these models are often obtained through a large number of experimental measurements. However, in practical applications, although the kinetic parameters determined by experiments can theoretically reflect the dynamic behavior of fluids in the reservoir, they have obvious limitations in the simulation reaction process, especially in the complex chemical reaction system involving coke formation. Specifically, the existing kinetic models often cannot accurately reflect the physical and chemical properties of the actual coke generated when simulating the coke pseudo-components in the reaction equation. This is because the coke formation process is affected by many factors, such as temperature, pressure, reaction time, and the interaction between reactants. The complexity of these factors makes it difficult to accurately describe the coke formation process through simple experimental parameters.

[0003] Therefore, the kinetic parameters simply determined by experiments often need to be calibrated and optimized when applied to actual reservoir simulation. This process aims to improve the accuracy and reliability of the simulation by adjusting the model parameters so that the simulated reservoir fluid dynamic behavior is closer to the actual reservoir characteristics. However, due to the complexity of coke formation, this process often takes a lot of time and resources, and it may be difficult to achieve the ideal simulation effect. Therefore, the current kinetic model has certain limitations when simulating complex chemical reaction systems involving coke formation, and its accuracy and reliability are poor. Summary of the invention

[0004] The embodiments of the present application solve the problem of poor accuracy and reliability of kinetic parameters obtained through existing kinetic models by providing a method, device, electronic device and storage medium for optimizing crude oil reaction kinetic parameters.

[0005] In order to achieve the above object, the technical solution of the embodiment of the present invention is:

[0006] In a first aspect, an embodiment of the present invention provides a method for optimizing crude oil reaction kinetic parameters, comprising: performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate; constructing an oil drop reaction model that is the same as the thermal analysis experiment; wherein the oil drop model in the oil drop reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil drop model is the same as the size of the TG / DSC instrument cavity; based on the working parameters of the TG / DSC instrument, simulating the oil drop reaction model by a finite element method to obtain a second weight loss curve and a second reaction exothermic curve under an instantaneous state; adjusting the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model so that the second weight loss curve coincides with the first weight loss curve; adjusting the reaction enthalpy parameters of the oil drop reaction model, integrating the second reaction exothermic curve and the first reaction exothermic curve so that the integrated amount of the second reaction exothermic curve is the same as that of the first reaction exothermic curve; and obtaining optimized reaction kinetic parameters according to the adjusted reaction activation energy, pre-exponential factor parameters and reaction enthalpy parameters.

[0007] In some possible implementations, after performing a thermal analysis experiment on the crude oil to be tested by using a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate, the method further includes: performing the same thermal analysis experiment on the crude oil to be tested at a second heating rate to obtain a third weight loss curve and a third reaction exothermic curve of the crude oil to be tested at the second heating rate.

[0008] In some possible implementations, after obtaining the optimized reaction kinetic parameters based on the adjusted reaction activation energy, pre-exponential factor parameters, and reaction enthalpy parameters, the method further includes: simulating the oil droplet reaction model at a second heating rate to obtain a fourth weight loss curve and a fourth reaction exothermic curve; determining whether the fitting effect of the fourth weight loss curve and the third weight loss curve meets a preset condition; when the fitting effect meets the preset condition, outputting the optimized reaction kinetic parameters; when the fitting effect does not meet the preset condition, re-adjusting the oil droplet reaction model.

[0009] In some possible implementations, the second weight loss curve is obtained by a mass normalization function, and the mass normalization function is expressed as:

[0010]

[0011] Among them, ρ oil is the real-time density of crude oil, is the real-time density of the incomplete combustion stage, is the real-time density at the complete combustion stage, ρ oil_init is the initial density of crude oil;

[0012] The second reaction exothermic curve is obtained by the exothermic function, which is expressed as:

[0013] DSC=(Q1+Q2+Q3) / ρ oil_init ;

[0014] Among them, Q1 is the real-time heat release in the oxygen addition reaction stage, Q2 is the real-time heat release in the incomplete combustion stage, and Q3 is the real-time heat release in the complete combustion stage.

[0015] In some possible implementations, the evaluation indexes for determining whether the fitting effect meets preset conditions include at least: correlation coefficient, relative deviation, average relative deviation, average absolute relative deviation, maximum absolute relative deviation and root mean square error.

[0016] In some possible implementations, the correlation coefficient is expressed as:

[0017]

[0018] Among them, R 2 is the relative coefficient, n is the total number of data points, γ i,exp is the data measured by TS / DSC instrument, γ i,cal The data obtained from the simulation calculation is is the average value of the data measured by the TS / DSC instrument;

[0019] The relative deviation is expressed as:

[0020]

[0021] The average relative deviation is expressed as:

[0022]

[0023] The mean absolute relative deviation is expressed as:

[0024]

[0025] The maximum absolute relative deviation is expressed as:

[0026]

[0027] The root mean square error is expressed as:

[0028]

[0029] In some possible implementations, the parameters of the crude oil to be tested include at least the density, thermal conductivity, heat capacity, reaction equation and actual reference values ​​of kinetic parameters of the crude oil to be tested.

[0030] In a second aspect, an embodiment of the present invention provides a crude oil reaction kinetic parameter optimization device, comprising: an experimental test module, which performs a thermal analysis experiment on the crude oil to be tested through a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate; a model construction module, which constructs an oil droplet reaction model that is the same as the thermal analysis experiment; wherein the oil droplet model in the oil droplet reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil droplet model is the same as the size of the TG / DSC instrument cavity; a simulation module, which performs oil droplet reaction through a finite element method based on the working parameters of the TG / DSC instrument. The first calibration module is used to adjust the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model to make the second weight loss curve coincide with the first weight loss curve; the second calibration module is used to integrate the second reaction exothermic curve and the first reaction exothermic curve by adjusting the reaction enthalpy parameters of the oil drop reaction model to make the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; the parameter acquisition module is used to obtain the optimized reaction kinetic parameters according to the adjusted reaction activation energy, pre-exponential factor parameters and reaction enthalpy parameters.

[0031] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing the method provided in the first aspect of the present invention when executing the executable instructions or computer programs stored in the memory.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium storing executable instructions for causing a processor to execute the method provided in the first aspect of the present invention.

[0033] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0034] In the embodiment of the present invention, the first weight loss curve and the first reaction exothermic curve of the crude oil to be tested at the first heating rate are obtained by experiment, the oil drop reaction simulation of the same oil drop model is performed at the same heating rate, and the second weight loss curve and the second reaction exothermic curve of the oil drop reaction model are obtained. The reaction activation energy and the pre-exponential factor parameters of the oil drop reaction model are adjusted to make the second weight loss curve coincide with the first weight loss curve; the reaction enthalpy parameters of the oil drop reaction model are adjusted to integrate the second reaction exothermic curve and the first reaction exothermic curve, so that the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; according to the adjusted reaction activation energy, pre-exponential factor parameters and reaction enthalpy parameters, the optimized reaction kinetic parameters are obtained. In this way, by adjusting the reaction activation energy, pre-exponential factor and reaction enthalpy parameters of the oil drop reaction model, the simulated second weight loss curve and the second reaction exothermic curve are highly consistent with the experimentally measured first weight loss curve and the first reaction exothermic curve, thereby significantly improving the accuracy of the simulation, helping to more accurately predict the fluid dynamic behavior in the reservoir, and providing a more reliable basis for oil production decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention, the accompanying drawings required for use in the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0036] Figure 1 A schematic flow chart of an embodiment of a method for optimizing crude oil reaction kinetic parameters provided for the implementation of the present invention;

[0037] Figure 2a It is a structural schematic diagram of the first weight loss curve under different heating rate conditions in an embodiment of the present invention;

[0038] Figure 2b It is a schematic structural diagram of the first reaction exothermic curve under different heating rate conditions in an embodiment of the present invention;

[0039] Figure 3 It is a structural schematic diagram of an oil droplet model in an embodiment of the present invention;

[0040] Figure 4 A schematic diagram of a second weight loss curve normalized by mass provided in an embodiment of the present invention;

[0041] Figure 5a It is a structural schematic diagram of the first weight loss curve and the second weight loss curve before optimization;

[0042] Figure 5b It is a schematic diagram of the structure of the optimized first weight loss curve and the second weight loss curve;

[0043] Figure 6a It is a schematic diagram of the structure of the first reaction exothermic curve and the second reaction exothermic curve before optimization;

[0044] Figure 6b It is a schematic diagram of the structure of the optimized first reaction exothermic curve and the second reaction exothermic curve;

[0045] Figure 7 This is a schematic diagram of the structure of a crude oil reaction kinetic parameter optimization device in an embodiment of the present invention;

[0046] Figure 8 The figure is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] In the relevant description of this embodiment, the terms "including, containing, having" and the like are open terms and are generally understood to include but not be limited to; the term "at least one" is generally understood to mean one or more, where "plurality" refers to two or more; the term "at least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items, for example, "at least one of a, b or c", or "at least one of a, b and c", can all represent: a, b, c, ab (i.e., a and b), ac, bc, or abc, where a, b, c can be single or multiple, respectively; the symbol "A / B" is used to describe the selection relationship of associated objects, generally indicating an "or" relationship before and after.

[0049] In the following description of the present embodiment, the terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0050] Those skilled in the art should understand that in the following description of the embodiments of the present application, the order of serial numbers does not mean the order of execution, some or all of the steps can be executed in parallel or sequentially, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0051] Those skilled in the art will appreciate that the numerical ranges in the embodiments of the present application are to be construed as also specifically disclosing each intermediate value between the upper and lower limits of the scope. Each smaller range between the intermediate value in any stated value or stated range and any other stated value or intermediate value in the range is also included in the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded in the scope.

[0052] Unless otherwise specified, the technical / scientific terms used herein have the same meanings as those generally understood by those skilled in the art to which this application belongs. Although this application only describes preferred methods and materials, any methods and materials similar or equivalent to these may also be used in the implementation or testing of this application. All documents mentioned in this specification are incorporated by reference to disclose and describe methods and / or materials related to the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0053] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0054] With the development of the petroleum industry, oil production technology has become increasingly mature, and the application of kinetic models in oil production software is particularly critical. The current kinetic models mainly provide technical support for traditional oil production industry software, and the kinetic parameters in these models are often obtained through a large number of experimental measurements. However, in practical applications, although the kinetic parameters determined by experiments can theoretically reflect the dynamic behavior of fluids in the reservoir, they have obvious limitations in the simulation reaction process, especially in the complex chemical reaction system involving coke formation. Specifically, the existing kinetic models often cannot accurately reflect the physical and chemical properties of the actual coke generated when simulating the coke pseudo-components in the reaction equation. This is because the coke formation process is affected by many factors, such as temperature, pressure, reaction time, and the interaction between reactants. The complexity of these factors makes it difficult to accurately describe the coke formation process through simple experimental parameters.

[0055] Therefore, the kinetic parameters simply determined by experiments often need to be calibrated and optimized when applied to actual reservoir simulation. This process aims to improve the accuracy and reliability of the simulation by adjusting the model parameters so that the simulated reservoir fluid dynamic behavior is closer to the actual reservoir characteristics. However, due to the complexity of coke formation, this process often takes a lot of time and resources, and it may be difficult to achieve the ideal simulation effect. Therefore, the current kinetic model has certain limitations when simulating complex chemical reaction systems involving coke formation, and its accuracy and reliability are poor.

[0056] Based on this, an embodiment of the present invention provides a method, device, electronic device and storage medium for optimizing crude oil reaction kinetic parameters, which solves the problem of poor accuracy and reliability of kinetic parameters obtained through existing kinetic models.

[0057] Figure 1 A schematic diagram of an embodiment of a crude oil reaction kinetic parameter optimization method provided for the implementation of the present invention is shown in FIG. Figure 1 As shown, the method may include:

[0058] S101, performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate;

[0059] Among them, the TG / DSC instrument, also known as a synchronous thermal analyzer (TG-DSC or STA), is an analytical instrument that combines thermogravimetric analysis (TG) and differential scanning calorimetry (DSC). Thermogravimetric analysis (TG) measures the relationship between the mass and temperature of a substance, and studies the thermal stability, redox, decomposition, adsorption and desorption of the substance. Differential scanning calorimetry (DSC) measures the relationship between the heat flow power difference and temperature of a substance, and studies the melting, crystallization, phase change, antioxidant properties and other information of the substance. A single TG or DSC technology is difficult to clearly reveal the thermal behavior of a substance, and the TG / DSC instrument combines the two into one to obtain more comprehensive information.

[0060] In some embodiments, during the thermal analysis experiment, the experiment can be conducted at different heating rates to obtain the first weight loss curve and the first reaction exothermic curve at the corresponding heating rates. In this way, after the optimized kinetic parameters are obtained according to the first heating rate, the optimized kinetic parameters can be verified at other heating rates by changing the heating rate to verify the effectiveness of the optimization results.

[0061] Based on this, in some embodiments, after step S101, the method may further include:

[0062] The same thermal analysis experiment is performed on the crude oil to be tested at the second heating rate to obtain a third weight loss curve and a third reaction exothermic curve of the crude oil to be tested at the second heating rate. The second heating rate may include multiple ones.

[0063] Exemplarily, the first heating rate may be 10°C / min, and the second heating rate may be 15°C / min and / or 20°C / min. After obtaining the first weight loss curve and the first reaction exothermic curve at a heating rate of 10°C / min, the same thermal analysis experiment is performed by a TG / DSC instrument at heating rates of 15°C / min and 20°C / min, respectively, to obtain a third weight loss curve and a third reaction exothermic curve at corresponding heating rates.

[0064] It should be noted that when the first heating rate can take different values, the second heating rate is actually equivalent to the first heating rate with different values, that is, the third weight loss curve and the third reaction exothermic curve are actually the first weight loss curve and the first reaction exothermic curve under different heating rates. For example, FIG2 is a graph showing the TG / DSC variation of the crude oil to be tested over time under different heating rates in an embodiment of the present invention. Figure 2a is a schematic diagram of the structure of the first weight loss curve under different heating rate conditions in an embodiment of the present invention, Figure 2b Schematic diagram of the structure of the first reaction exothermic curve under different heating rate conditions in an embodiment of the present invention.

[0065] S102, constructing an oil drop reaction model identical to that of the thermal analysis experiment; wherein the oil drop model in the oil drop reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil drop model is identical to the size of the TG / DSC instrument cavity;

[0066] In some embodiments, the parameters of the crude oil to be tested include at least the density, thermal conductivity, heat capacity, reaction equation and actual reference values ​​of kinetic parameters of the crude oil to be tested.

[0067] The parameters of the crude oil to be tested can be obtained through literature research, or can also be determined through actual physical experiments.

[0068] Exemplarily, the parameters of the crude oil to be tested may be shown in the following Tables 1 and 2. Table 1 shows the molar masses of reactants and products in the crude oil to be tested in the embodiment of the present invention, and Table 2 shows the reaction heat transfer parameters of the crude oil to be tested in the embodiment of the present invention.

[0069] Table 1:

[0070]

[0071] Table 2:

[0072]

[0073] It should be noted that the above Tables 1 and 2 are only exemplary descriptions of the parameters of the crude oil to be tested in the embodiment of the present invention, and the specific parameter contents and the corresponding values ​​of the parameters may be different for different crude oils to be tested.

[0074] For example, taking the data in Table 1 and Table 2 as an example, the mass of the oil droplet model is determined to be 3-5 mg after the above numerical calculation. Figure 3 Schematic diagram of the structure of the oil droplet model in the embodiment of the present invention, wherein the oil droplet model is semicircular and the radius of the model is 1015 mm.

[0075] S103, based on the working parameters of the TG / DSC instrument, simulating the oil drop reaction model by a finite element method to obtain a second weight loss curve and a second reaction exothermic curve under a transient state;

[0076] Specifically, when simulating the oil drop reaction model, the inlet velocity, inlet temperature and other parameters in the simulation process can be set based on the gas injection parameters, heating rate and other contents of the TG / DSC instrument, so as to ensure the similarity between the simulation process and the experimental process.

[0077] Exemplarily, the model injection parameters and initial parameters may be as shown in Table 3 below:

[0078] Table 3:

[0079]

[0080] It should be noted that the model initial parameters (initial values) in Table 3 are only exemplary descriptions, and the specific model initial parameters in the embodiment of the present invention may have different values ​​based on the different samples to be tested in the actual application process. The inflow parameters of the model can be determined based on the working parameters of the actual TG / DSC instrument.

[0081] After determining the injection parameters and initial parameters of the oil droplet reaction model, simulation is performed under the corresponding parameters to obtain the corresponding second weight loss curve and second reaction exothermic curve. That is, the second weight loss curve and second reaction exothermic curve of the crude oil to be tested at the first heating rate are obtained through simulation.

[0082] In some embodiments, the reaction process of the crude oil to be tested may include an oxygen addition reaction stage (which is mainly a low-temperature oxidation stage), an incomplete combustion stage, and a complete combustion stage. Each reaction stage is respectively implemented by the following formulas (1) to (3).

[0083] R1 Oil+0.95O2=>22.72Coke1 (1)

[0084] R2 Coke1+1.72O2=>0.15CO+0.76CO2+1.58H2O+1.07Coke2 (2)

[0085] R3 Coke2+0.72O2=>0.07CO+0.35CO2+H2O (3)

[0086] Wherein, R1 is the oxygen addition reaction stage, R2 is the incomplete combustion stage, and R3 is the complete combustion stage. Oil is the crude oil to be tested, Coke1 is the coke in the incomplete combustion stage, and Coke2 is the coke in the complete combustion stage. Formulas (1) to (3) can be obtained through actual investigation or reference to existing literature.

[0087] In some embodiments, the second weight loss curve can be obtained by a mass normalization function, wherein the mass normalization function can be expressed by the following formula (4):

[0088]

[0089] Among them, ρ oil is the real-time density of crude oil, in kg / m 3 , is the real-time density during the incomplete combustion stage, in kg / m 3 , is the real-time density at the complete combustion stage, in kg / m 3 , ρ oil_init is the initial density of crude oil, in kg / m 3 ;

[0090] In some embodiments, the second reaction exothermic curve can be obtained by an exothermic function. The exothermic function can be expressed by the following formula (5):

[0091] DSC=(Q1+Q2+Q3) / ρ oil_init (5)

[0092] Among them, Q1 is the real-time heat release in the oxygen addition reaction stage, in W / m 3 , Q2 is the real-time heat release during the incomplete combustion stage, in W / m 3 , Q3 is the real-time heat release in the complete combustion stage, in W / m 3 .

[0093] It can be understood that in chemical engineering, petroleum industry or related materials science fields, the determination of weight loss curves and reaction exothermic curves is usually to understand the thermal decomposition or reaction characteristics of a certain material or mixture under specific conditions. For the purpose of thermal decomposition or reaction characteristics in specific industrial applications or research processes, coke, as a solid fuel mainly composed of carbon, has an important influence on the crude oil processing process due to its calorific value and stability. By measuring the mass loss and heat release of the crude oil and coke mixture during heating, important information about its thermal decomposition temperature, decomposition rate, final residue, reaction kinetics and thermodynamic properties can be obtained. Therefore, selecting "crude oil + coke" to determine the weight loss curve and reaction exothermic curve can provide important information about the stability of the raw materials, reaction kinetics and thermodynamics, which can help optimize the production process and ensure product quality in the subsequent production process. For example, under the model injection parameters and initial parameters shown in Table 3 above, the following can be obtained: Figure 4 The weight loss curve shown is Figure 4 A schematic diagram of a second mass-normalized weight loss curve provided in an embodiment of the present invention.

[0094] S104, adjusting the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model so that the second weight loss curve coincides with the first weight loss curve;

[0095] In some embodiments, the first weight loss curve measured experimentally can be plotted in correspondence with the second weight loss curve obtained above, and then the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model can be continuously adjusted and optimized to make the second weight loss curve gradually overlap with the first weight loss curve, so that the overlap degree of the two curves meets the preset overlap condition.

[0096] Exemplarily, FIG5 is a schematic diagram of the optimization of the second weight loss curve in an embodiment of the present invention, wherein: Figure 5a It is a schematic diagram of the structure of the first weight loss curve and the second weight loss curve before optimization. Figure 5b The diagram is a schematic diagram of the structure of the first weight loss curve and the second weight loss curve after optimization. There are obvious differences between the first weight loss curve (obtained by TG / DSC instrument experiment, with dots representing specific multiple values) and the second weight loss curve (obtained by oil drop reaction model simulation, displayed as a continuous curve). By optimizing the reaction activation energy and pre-exponential factor in the oil drop reaction model, the structure of the second weight loss curve gradually approaches the curve structure corresponding to the experimental result value, realizing the optimization of these two parameters. In this way, not only the accuracy of the oil drop reaction model is improved, but also more reliable data support is provided for subsequent experimental and theoretical research.

[0097] In some embodiments, the optimization process may include: first, setting the initial reaction activation energy and pre-exponential factor values ​​for the oil drop reaction model. These initial values ​​can be set based on previous experimental data, literature values ​​or empirical values. Then, using the set initial parameter values, the oil drop reaction model is simulated and calculated to generate a second weight loss curve. The simulated second weight loss curve is then compared with the experimentally obtained first weight loss curve. If there is a large difference between the two, the reaction activation energy and the pre-exponential factor need to be adjusted. Generally, this adjustment can be done by trial and error or an optimization algorithm, such as the least squares method, the genetic algorithm, etc. Then, using the adjusted parameter values, the oil drop reaction model is simulated and calculated again to generate a new second weight loss curve. After generating the new second weight loss curve, the newly generated second weight loss curve can also be compared with the first weight loss curve to evaluate the degree of fit between the two. If the degree of fit is good (i.e., the difference is within an acceptable range), the optimization process is considered to be completed; otherwise, the optimization process needs to be repeated to continue adjusting the parameters and re-simulating. Through multiple iterations and adjustments, the difference between the simulation curve and the experimental curve is gradually reduced until the expected optimization effect is achieved.

[0098] S105, integrating the second reaction exothermic curve and the first reaction exothermic curve by adjusting the reaction enthalpy parameter of the oil drop reaction model, so that the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount;

[0099] Exemplarily, FIG6 is a schematic diagram of the optimization of the second reaction exothermic curve in an embodiment of the present invention, wherein: Figure 6a This is a schematic diagram of the structure of the first reaction exothermic curve and the second reaction exothermic curve before optimization. Figure 6bThe schematic diagram of the structure of the first reaction exothermic curve and the second reaction exothermic curve after optimization. The above step S105 may specifically include: first, obtain the first reaction exothermic curve from the experimental data, draw the first reaction exothermic curve in the second reaction exothermic curve, and set the initial reaction enthalpy parameter value. The initial value can be set based on previous experimental data, literature value or empirical value. Then use the initial reaction enthalpy parameter value to simulate and calculate the second reaction exothermic curve through the oil drop reaction model. This simulation process usually involves solving the reaction rate equation and the thermodynamic equation to obtain heat flow data at different temperatures or times. After that, the first reaction exothermic curve and the second reaction exothermic curve are integrated to calculate the respective integral amount, that is, the total heat release. The integration is usually carried out over the entire temperature or time range to obtain the total thermal effect of the entire reaction process. Then compare the integral amounts of the two curves, if different, adjust the reaction enthalpy parameter. It is realized by an iterative algorithm, and each iteration will fine-tune the reaction enthalpy parameter according to the difference in the current integral amount. Then, the simulation calculation is re-performed using the adjusted parameters, and the integral comparison is performed again until the integrals of the two curves are the same or within the preset error range. Finally, when the integrals of the two curves are the same or meet the error requirements, the optimization process is considered to be completed. At this point, the optimized reaction enthalpy parameter value and the corresponding second reaction exothermic curve can be output.

[0100] In some embodiments, the specification of the optimization process of the above step S104 and step S105 may include:

[0101] (1) The volume of the reactants does not change during the reaction, and their weight loss is determined by ρ oil , and Change representation;

[0102] (2) The curve will turn at the junction of the low-temperature oxidation stage and the high-temperature oxidation stage;

[0103] (3) The conventional heavy oil mass loss curve contains three peaks, which correspond to the consumption of crude oil and two coke reactions. Therefore, when dividing the reaction interval of the three-reaction equation, the TG curve Oil and Coke1 need to participate in the mass loss before the turning point, and Coke2 is mainly responsible for the mass loss curve after the turning point;

[0104] (4) Due to the influence of the stoichiometric coefficient of the equation, the software only contains one exothermic peak. The exothermic start temperature corresponds to the start temperature of the low-temperature oxidation stage, and the end temperature corresponds to the temperature of the high-temperature oxidation stage;

[0105] (5) The overall heat release of the exothermic peak should be similar to the experimental results;

[0106] (6) Reaction process R1 is an oxygen addition reaction, the reaction of Oil to form Coke1 is a mass increase process, and the other two reactions are mass reduction reactions.

[0107] S106, obtaining optimized reaction kinetic parameters according to the adjusted reaction activation energy, pre-exponential factor parameter and reaction enthalpy parameter.

[0108] It can be understood that through the optimization process of the above steps S104 to S105, the activation energy, pre-exponential factor and reaction enthalpy value that make the model prediction most consistent with the experimental data can be found, thereby obtaining the optimized reaction kinetic parameters, which can more accurately reflect the kinetic characteristics and thermodynamic effects of the chemical reaction.

[0109] In some embodiments, after obtaining the optimized reaction kinetic parameters, it is necessary to verify the effectiveness of the optimization results. Based on this, after the above step S106, the above method may further include:

[0110] S1061, simulating the oil drop reaction model at a second heating rate to obtain a fourth weight loss curve and a fourth reaction exothermic curve;

[0111] S1062, determining whether the fitting effect of the fourth weight loss curve and the third weight loss curve meets a preset condition;

[0112] S1063, when the fitting effect meets the preset conditions, outputting the optimized reaction kinetic parameters;

[0113] S1064: when the fitting effect does not meet the preset conditions, readjust the oil drop reaction model.

[0114] In some embodiments, since the temperature of the model at different heating rates varies within the same time, in order to adapt the model to different heating rates, the temperature corresponding to the model needs to be adaptively adjusted.

[0115] In some embodiments, the temperature of the model at different heating rates may be expressed as follows:

[0116] T=β·t+298.15 (6)

[0117] Among them, T is the real-time temperature of the model, β is the heating rate, the unit is ℃ / min, and t is time. By modifying the β value, the weight loss and heat release curve of the crude oil to be tested is simulated under the required heating rate conditions so that the simulated crude oil parameters to be tested are consistent with the actual crude oil characteristics.

[0118] In some embodiments, evaluation indicators for determining whether the fitting effect meets preset conditions include but are not limited to: correlation coefficient, relative deviation, average relative deviation, average absolute relative deviation, maximum absolute relative deviation and root mean square error.

[0119] In some embodiments, the correlation coefficient may be expressed by the following formula (7):

[0120]

[0121] Among them, R 2 is the relative coefficient, n is the total number of data points, γ i,exp is the data measured by TS / DSC instrument, γ i,cal The data obtained from the simulation calculation is is the average value of the data measured by the TS / DSC instrument;

[0122] The relative deviation can be expressed by the following formula (8):

[0123]

[0124] The average relative deviation can be expressed by the following formula (9):

[0125]

[0126] The average absolute relative deviation can be expressed by the following formula (10):

[0127]

[0128] The maximum absolute relative deviation can be expressed by the following formula (11):

[0129]

[0130] The root mean square error can be expressed by the following formula (12):

[0131]

[0132] Exemplarily, the validity verification result of the optimization result may be shown in the following Table 4:

[0133] Table 4:

[0134]

[0135] Table 4 shows the calculation results of evaluation indexes, total heat release (including heat absorption) and actual heat release under different heating conditions of the simulation results of fitting kinetic parameters. When the heating rates are 15 and 20, the data within 0-35 and 0-25 minutes are intercepted for calculation. As can be seen from Table 4, the R2 under the three heating rate conditions are 0.996, 0.987 and 0.980, respectively, indicating that the overall fitting degree of the two sets of data is high. It can be seen from the relative deviation (RD) curve that within the interception interval, the corresponding numerical difference is not large, which shows that the kinetic parameters are relatively reasonable and can be used as the basic parameters of the subsequent model. At the same time, the absolute values ​​of the relative deviation (RD) of heat release are 4.0%, 6.98% and 4.45%, respectively, which are within an acceptable range. In summary, the model describes the changing trend of temperature and solid mass well, especially at the intermediate temperature.

[0136] The reaction kinetic parameters before and after optimization in the embodiment of the present invention can be shown in the following Table 5.

[0137] Table 5:

[0138]

[0139] In the embodiment of the present invention, the first weight loss curve and the first reaction exothermic curve of the crude oil to be tested at the first heating rate are obtained by experiment, the oil drop reaction simulation of the same oil drop model is performed at the same heating rate, and the second weight loss curve and the second reaction exothermic curve of the oil drop reaction model are obtained. The reaction activation energy and the pre-exponential factor parameters of the oil drop reaction model are adjusted to make the second weight loss curve coincide with the first weight loss curve; the reaction enthalpy parameters of the oil drop reaction model are adjusted to integrate the second reaction exothermic curve and the first reaction exothermic curve, so that the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; according to the adjusted reaction activation energy, pre-exponential factor parameters and reaction enthalpy parameters, the optimized reaction kinetic parameters are obtained. In this way, by adjusting the reaction activation energy, pre-exponential factor and reaction enthalpy parameters of the oil drop reaction model, the simulated second weight loss curve and the second reaction exothermic curve are highly consistent with the experimentally measured first weight loss curve and the first reaction exothermic curve, thereby significantly improving the accuracy of the simulation, helping to more accurately predict the fluid dynamic behavior in the reservoir, and providing a more reliable basis for oil production decisions.

[0140] Based on the same inventive concept, an embodiment of the present application also provides a crude oil reaction kinetic parameter optimization device. Figure 7 FIG. 1 is a schematic diagram of a crude oil reaction kinetic parameter optimization device according to an embodiment of the present invention. Figure 7As shown, the crude oil reaction kinetic parameter optimization device 700 may include: an experimental test module 701, which performs a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate; a model construction module 702, which constructs an oil drop reaction model that is the same as the thermal analysis experiment; wherein the oil drop model in the oil drop reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil drop model is the same as the size of the TG / DSC instrument cavity; a simulation module 703, which performs a simulation of the oil drop reaction model by a finite element method based on the working parameters of the TG / DSC instrument Simulation, to obtain the second weight loss curve and the second reaction exothermic curve under the instantaneous state; the first calibration module 704, by adjusting the reaction activation energy and the pre-exponential factor parameters of the oil drop reaction model, so that the second weight loss curve coincides with the first weight loss curve; the second calibration module 705, for integrating the second reaction exothermic curve and the first reaction exothermic curve by adjusting the reaction enthalpy parameters of the oil drop reaction model, so that the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; the parameter acquisition module 706, for obtaining the optimized reaction kinetic parameters according to the adjusted reaction activation energy, pre-exponential factor parameters and reaction enthalpy parameters.

[0141] In some possible implementations, the experimental testing module 701 is further used to perform the same thermal analysis experiment on the crude oil to be tested at a second heating rate to obtain a third weight loss curve and a third reaction exothermic curve of the crude oil to be tested at the second heating rate.

[0142] In some possible implementations, the device also includes: a verification module, which is used to simulate the oil droplet reaction model at a second heating rate to obtain a fourth weight loss curve and a fourth reaction exothermic curve; determine whether the fitting effect of the fourth weight loss curve and the third weight loss curve meets a preset condition; when the fitting effect meets the preset condition, output the optimized reaction kinetic parameters; when the fitting effect does not meet the preset condition, readjust the oil droplet reaction model.

[0143] In some possible implementations, the second weight loss curve is obtained by a mass normalization function, and the mass normalization function is expressed as:

[0144]

[0145] Among them, ρ oil is the real-time density of crude oil, is the real-time density of the incomplete combustion stage, is the real-time density at the complete combustion stage, ρ oil_init is the initial density of crude oil;

[0146] The second reaction exothermic curve is obtained by the exothermic function, which is expressed as:

[0147] DSC=(Q1+Q2+Q3) / ρ oil_init ;

[0148] Among them, Q1 is the real-time heat release in the oxygen addition reaction stage, Q2 is the real-time heat release in the incomplete combustion stage, and Q3 is the real-time heat release in the complete combustion stage.

[0149] In some possible implementations, the evaluation indexes for determining whether the fitting effect meets preset conditions include at least: correlation coefficient, relative deviation, average relative deviation, average absolute relative deviation, maximum absolute relative deviation and root mean square error.

[0150] In some possible implementations, the correlation coefficient is expressed as:

[0151]

[0152] Among them, R 2 is the relative coefficient, n is the total number of data points, γ i,exp is the data measured by TS / DSC instrument, γ i,cal The data obtained from the simulation calculation are: is the average value of the data measured by the TS / DSC instrument;

[0153] The relative deviation is expressed as:

[0154]

[0155] The average relative deviation is expressed as:

[0156]

[0157] The mean absolute relative deviation is expressed as:

[0158]

[0159] The maximum absolute relative deviation is expressed as:

[0160]

[0161] The root mean square error is expressed as:

[0162]

[0163] In some possible implementations, the parameters of the crude oil to be tested include at least the density, thermal conductivity, heat capacity, reaction equation and actual reference values ​​of kinetic parameters of the crude oil to be tested.

[0164] Based on the same inventive concept, an embodiment of the present application provides an electronic device, which may be consistent with the crude oil reaction kinetic parameter optimization method in one or more of the above embodiments. Figure 8 FIG. 1 is a schematic diagram of the structure of an electronic device in an embodiment of the present invention, see Figure 8 As shown, the electronic device 800 may adopt general computer hardware, including a processor 801 and a memory 802 .

[0165] In some possible implementations, at least one processor may constitute any physical device having a circuit that performs a logical operation on one or more inputs. For example, at least one processor may include one or more integrated circuits, including application specific integrated circuits, microchips, microcontrollers, microprocessors, all or part of a central processing unit, a graphics processing unit, a digital signal processor, a field programmable gate array, or other circuits suitable for executing instructions or performing logical operations. The instructions executed by at least one processor may be preloaded, for example, into a memory integrated with or embedded in a controller, or may be stored in a separate memory. The memory may include a random access memory, a read-only memory, a hard disk, an optical disk, a magnetic medium, a flash memory, other permanent, fixed or volatile memory, or any other mechanism capable of storing instructions. In some embodiments, at least one processor may include more than one processor. Each processor may have a similar structure, or the processors may have different configurations that are electrically connected or disconnected from each other. For example, the processor may be a separate circuit or integrated in a single circuit. When more than one processor is used, the processor may be configured to operate independently or collaboratively. The processors may be coupled electrically, magnetically, optically, acoustically, mechanically, or by other means that allow them to interact.

[0166] Based on the same inventive concept, the present application provides a computer storage medium, which stores computer executable instructions. After the computer executable instructions are executed by a processor, a method for optimizing crude oil reaction kinetic parameters as described in one or more of the above embodiments can be implemented.

[0167] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments.

[0168] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A method for optimizing crude oil reaction kinetic parameters, characterized in that: include: Performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate; Constructing an oil drop reaction model identical to that of the thermal analysis experiment; wherein the oil drop model in the oil drop reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil drop model is identical to the size of the TG / DSC instrument cavity; Based on the working parameters of the TG / DSC instrument, the oil drop reaction model is simulated by a finite element method to obtain a second weight loss curve and a second reaction exothermic curve under a transient state; By adjusting the reaction activation energy and the pre-exponential factor parameters of the oil drop reaction model, the second weight loss curve is made to coincide with the first weight loss curve; By adjusting the reaction enthalpy parameter of the oil drop reaction model, integrating the second reaction exothermic curve and the first reaction exothermic curve, the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; The optimized reaction kinetic parameters are obtained according to the adjusted reaction activation energy, the pre-exponential factor parameter and the reaction enthalpy parameter.

2. The method according to claim 1, characterized in that After performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument to obtain a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate, the method further comprises: The same thermal analysis experiment is performed on the crude oil to be tested at a second heating rate to obtain a third weight loss curve and a third reaction exothermic curve of the crude oil to be tested at the second heating rate.

3. The method according to claim 2, characterized in that After obtaining the optimized reaction kinetic parameters according to the adjusted reaction activation energy, the pre-exponential factor parameter and the reaction enthalpy parameter, the method further includes: Simulating the oil drop reaction model at the second heating rate to obtain a fourth weight loss curve and a fourth reaction exothermic curve; Determining whether a fitting effect of the fourth weight loss curve and the third weight loss curve meets a preset condition; When the fitting effect meets the preset conditions, outputting the optimized reaction kinetic parameters; When the fitting effect does not meet the preset condition, the oil drop reaction model is readjusted.

4. The method according to claim 3, characterized in that The second weight loss curve is obtained by a mass normalization function, and the mass normalization function is expressed as: Among them, ρ oil is the real-time density of crude oil, is the real-time density of the incomplete combustion stage, is the real-time density at the complete combustion stage, ρ oil_init is the initial density of crude oil; The second reaction exothermic curve is obtained by an exothermic function, and the exothermic function is expressed as: DSC=(Q1+Q2+Q3) / ρ oil_init ; Among them, Q1 is the real-time heat release in the oxygen addition reaction stage, Q2 is the real-time heat release in the incomplete combustion stage, and Q3 is the real-time heat release in the complete combustion stage.

5. The method according to claim 3, characterized in that: The evaluation indexes for determining whether the fitting effect meets the preset conditions include at least: correlation coefficient, relative deviation, average relative deviation, average absolute relative deviation, maximum absolute relative deviation and root mean square error.

6. The method according to claim 5, characterized in that The correlation coefficient is expressed as: Among them, R 2 is the relative coefficient, n is the total number of data points, γ i,exp is the data measured by TS / DSC instrument, γ i,cal The data obtained from the simulation calculation is is the average value of the data measured by the TS / DSC instrument; The relative deviation is expressed as: The average relative deviation is expressed as: The mean absolute relative deviation is expressed as: The maximum absolute relative deviation is expressed as: The root mean square error is expressed as:

7. The method according to claim 1, characterized in that The parameters of the crude oil to be tested at least include the density, thermal conductivity, heat capacity, reaction equation and actual reference values ​​of kinetic parameters of the crude oil to be tested.

8. A crude oil reaction kinetic parameter optimization device, characterized in that: include: An experimental test module, performing a thermal analysis experiment on the crude oil to be tested by a TG / DSC instrument, and obtaining a first weight loss curve and a first reaction exothermic curve of the crude oil to be tested at a first heating rate; A model building module, constructing an oil drop reaction model identical to that of the thermal analysis experiment; wherein the oil drop model in the oil drop reaction model is determined according to the parameters of the crude oil to be tested, and the size of the oil drop model is identical to the size of the TG / DSC instrument cavity; A simulation module, based on the working parameters of the TG / DSC instrument, simulates the oil drop reaction model by a finite element method to obtain a second weight loss curve and a second reaction exothermic curve under a transient state; a first calibration module, which adjusts the reaction activation energy and pre-exponential factor parameters of the oil drop reaction model so that the second weight loss curve coincides with the first weight loss curve; a second calibration module, configured to integrate the second reaction exothermic curve and the first reaction exothermic curve by adjusting the reaction enthalpy parameter of the oil drop reaction model, so that the second reaction exothermic curve and the first reaction exothermic curve have the same integral amount; The parameter acquisition module is used to obtain the optimized reaction kinetic parameters according to the adjusted reaction activation energy, the pre-exponential factor parameter and the reaction enthalpy parameter.

9. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable instructions; A processor, configured to implement the method according to any one of claims 1 to 7 when executing the executable instructions or computer programs stored in the memory.

10. A computer-readable storage medium storing executable instructions or a computer program, characterized in that: When the executable instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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