A method and system for determining hydrocarbon source rock hydrocarbon generation kinetics parameters

Abstract

The present application provides a kind of hydrocarbon source rock hydrocarbon generation kinetics parameter determination method and system.The method comprises: obtaining the discrete data points of the pyrolysis S2 peak spectrum of target hydrocarbon source rock sample;The discrete data points of the pyrolysis S2 peak spectrum of target hydrocarbon source rock sample are normalized to obtain normalized discrete data points;Determine the activation energy distribution range of organic matter;Based on the activation energy distribution range of organic matter, the normalized discrete data points of the pyrolysis S2 peak spectrum of target hydrocarbon source rock sample, determine the continuous initial solution of target hydrocarbon source rock sample hydrocarbon generation kinetics parameter;The continuous initial solution of target hydrocarbon source rock sample hydrocarbon generation kinetics parameter is discretized, and the discretization solution of the continuous initial solution of target hydrocarbon source rock sample hydrocarbon generation kinetics parameter is obtained;Based on the discretization solution of the continuous initial solution of target hydrocarbon source rock sample hydrocarbon generation kinetics parameter, the content of each organic matter component is optimized, and the final hydrocarbon generation kinetics parameter of target hydrocarbon source rock sample is obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of source rock evaluation, and particularly relates to a method and system for determining source rock hydrocarbon generation kinetics parameters. BACKGROUND

[0002] The hydrocarbon generation of source rock in a petroleum basin is a very complex geological and geochemical process, involving geological processes and hydrocarbon generation parent material properties. In order to study and reproduce the kerogen hydrocarbon generation, and achieve the purpose of scientific evaluation of source rock, the thermal simulation experiment and kinetics study of kerogen hydrocarbon generation are very useful means. Geologists have made a lot of fruitful work, reasonably solved the problems of hydrocarbon generation mechanism and evaluation, and laid a foundation for establishing modern kerogen oil generation theory. Because the chemical components of organic matter in source rock are extremely complex and it is difficult to accurately determine the complete chemical structure, it is necessary to make reasonable assumptions about the reaction process of source rock in the geological period in order to determine the hydrocarbon generation kinetics parameters of source rock. At present, a large number of studies have shown that the limited number of first-order parallel reaction models are closest to the actual reaction process under geological conditions. However, the solution of the limited number of first-order parallel reaction models is a very complex and time-consuming process. So far, the methods for optimizing the model mainly include the variable scale method and the regularization conjugate gradient descent method. However, the above two widely used methods have high requirements for the selection of key parameters and slow solution speed. This is mainly due to the following three shortcomings of the two methods:

[0003] 1. The penalty function is not properly constructed. In order to ensure that the obtained solution is positive, a penalty function is usually added inside the objective function to constrain the value range of the solution. The traditional penalty function is mainly a quadratic function type function. For the penalty function with a value range greater than zero, the specific form is as follows: γmin(0, x) 2 , x is the solution, and γ is the penalty coefficient. However, the gradient function of the penalty function is a linear function: 2γmin(0, x). This means that the constraint ability of the gradient function in the non-value range is poor, and multiple iterations are required to make the solution return to the vicinity of the value range, thereby causing the algorithm to run for a long time.

[0004] 2. The initial solution is not selected accurately. Whether it is the variable scale method or the regularization conjugate gradient descent method, the selection of the initial solution is very sensitive when solving the limited number of first-order parallel reaction models. Because this problem is a multi-solution problem with many local solutions, the algorithm can usually only find the local solution near the initial solution, so a good initial solution is the key to quickly obtaining the result of the algorithm. Some scholars use the solution of a sample with similar maturity as the initial solution of the algorithm iteration, and get good results. However, the effect of this initial solution for samples with different maturity is poor.

[0005] 3. The iterative accuracy requirement is difficult to select. The iterative accuracy is a key factor affecting the iteration time of the above two methods, and improper selection will make the solving algorithm not converge or the iteration time too long.

[0006] In short, the existing method for determining hydrocarbon source rock hydrocarbon generation kinetics parameters is complicated, time-consuming and low in accuracy. At present, a technical scheme for quickly and accurately determining the hydrocarbon source rock hydrocarbon generation kinetics parameters still needs to be researched. SUMMARY

[0007] The purpose of the present application is to provide a method and system capable of quickly and accurately determining hydrocarbon source rock hydrocarbon generation kinetics parameters.

[0008] In order to achieve the above-mentioned purpose, the present application provides the following two technical schemes.

[0009] In a first aspect, the present application provides a method for determining hydrocarbon source rock hydrocarbon generation kinetics parameters, wherein the method comprises:

[0010] obtaining discrete data points of a pyrolysis S2 peak spectrum of a target hydrocarbon source rock sample; wherein the pyrolysis S2 peak spectrum is a pyrolysis S2 peak temperature-reaction rate curve;

[0011] normalizing the discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample to obtain normalized discrete data points;

[0012] determining an organic matter activation energy distribution range;

[0013] based on the organic matter activation energy distribution range and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, determining a continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample; wherein the content of each organic matter component constituting the target hydrocarbon source rock sample and its activation energy obeys a normal distribution, and the hydrocarbon generation kinetics parameters include the activation energy of each organic matter component (different activation energies are different organic matter components), the content (i.e. the percentage content of each organic matter component in the total organic matter) and the frequency factor of the organic matter component;

[0014] discretizing the continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample to obtain a discretized solution of the continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample; wherein the discretized solution of the continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component and the frequency factor of the discrete organic matter component;

[0015] based on the discretized solution of the continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample, optimizing the content of each organic matter component to obtain the final hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample.

[0016] In a second aspect, the present application provides a system for determining hydrocarbon generation kinetics parameters of a source rock, wherein the system comprises:

[0017] a sample data acquisition module 21 configured to acquire discrete data points of a pyrolysis S2 peak spectrum of a target source rock sample, wherein the pyrolysis S2 peak spectrum is a pyrolysis S2 peak temperature-reaction rate curve;

[0018] a sample data normalization processing module 22 configured to normalize the discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample to obtain normalized discrete data points;

[0019] an activation energy range determination module 23 configured to determine an activation energy distribution range of organic matter;

[0020] a continuous primary solution determination module 24 configured to determine a continuous primary solution of the hydrocarbon generation kinetics parameters of the target source rock sample based on the activation energy distribution range of the organic matter and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, wherein the content of each organic matter component constituting the target source rock sample and its activation energy obey a normal distribution, and the hydrocarbon generation kinetics parameters include the activation energy of each organic matter component constituting the target source rock sample (different activation energies are different organic matter components), the content (i.e., the percentage content of each organic matter component in the total organic matter), and the frequency factor of the organic matter component;

[0021] a continuous primary solution discretization module 25 configured to discretize the continuous primary solution of the hydrocarbon generation kinetics parameters of the target source rock sample to obtain a discretized solution of the continuous primary solution of the hydrocarbon generation kinetics parameters of the target source rock sample, wherein the discretized solution of the continuous primary solution of the hydrocarbon generation kinetics parameters of the target source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component, and the frequency factor of the discrete organic matter component;

[0022] a final hydrocarbon generation kinetics parameter determination module 26 configured to optimize the content of each organic matter component based on the discretized solution of the continuous primary solution of the hydrocarbon generation kinetics parameters of the target source rock sample to obtain the final hydrocarbon generation kinetics parameters of the target source rock sample.

[0023] The technical solution provided by the present application determines the continuous primary solution of the hydrocarbon generation kinetics parameters based on the fact that the content of each organic matter component and its activation energy obey a normal distribution, discretizes the determined continuous primary solution of the hydrocarbon generation kinetics parameters as a primary solution for solving the final solution, effectively ensures that a suitable primary solution can be found when solving the hydrocarbon generation kinetics parameters of any source sample, and thus realizes the rapid and accurate determination of the pyrolysis parameters of the source rock. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The flowchart of the method for determining the hydrocarbon generation kinetics parameters of a source rock according to a specific embodiment of the present application is shown.

[0025] Figure 2 A raw pyrolysis S2 temperature-reaction rate domain spectrum of the source rock sample S in the embodiment 1 of the present application.

[0026] Figure 3 A hydrocarbon generation kinetics parameter diagram of the source rock sample S determined according to the embodiment 1 of the present application.

[0027] Figure 4 A comparison diagram of the pyrolysis S2 temperature-reaction rate domain spectrum simulated by the hydrocarbon generation kinetics parameters of the source rock sample S determined according to the embodiment 1 of the present application and the raw pyrolysis S2 temperature-reaction rate domain. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to 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 the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0029] Reference Figure 1 , a hydrocarbon source rock hydrocarbon generation kinetics parameter determination method is provided in an embodiment of the present application, wherein the method comprises:

[0030] Step S1: obtaining discrete data points of a pyrolysis S2 peak spectrum of a target source rock sample; wherein the pyrolysis S2 peak spectrum is a pyrolysis S2 peak temperature-reaction rate curve;

[0031] Step S2: performing normalization processing on the discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample to obtain normalized discrete data points;

[0032] Step S3: determining an organic matter activation energy distribution range;

[0033] Step S4: determining a continuous type initial solution of the hydrocarbon generation kinetics parameters of the target source rock sample based on the organic matter activation energy distribution range and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample; wherein the content of each organic matter component constituting the target source rock sample and its activation energy obey a normal distribution, and the hydrocarbon generation kinetics parameters include the activation energy (different activation energies are different organic matter components), content (i.e. the percentage content of each organic matter component in the total organic matter) and frequency factor of the organic matter component of each organic matter component constituting the target source rock sample;

[0034] Step S5: discretize the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample to obtain a discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample; wherein the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component, and the frequency factor of the discrete organic matter component;

[0035] Step S6: based on the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample, optimizing the content of each organic matter component to obtain the final hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample.

[0036] In the above method for determining the hydrocarbon generation kinetic parameters of the hydrocarbon source rock, the continuous initial solution of the hydrocarbon generation kinetic parameters is determined based on the fact that the content of the organic matter component and its activation energy obey a normal distribution, and the discretized continuous initial solution of the determined hydrocarbon generation kinetic parameters is used as the initial solution for solving the final solution, which effectively ensures that a suitable initial solution can be found when solving the hydrocarbon generation kinetic parameters of any hydrocarbon source sample, thereby realizing the rapid and accurate determination of the pyrolysis parameters of the hydrocarbon source rock.

[0037] Further, in step S1, obtaining the discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample includes:

[0038] Step S11: obtaining the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample;

[0039] Step S12: uniformly obtaining original data points from the starting reaction temperature (T initial ) to the final reaction temperature (T end ) of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample as the discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample;

[0040] The more the number of selected original data points, the more accurate the subsequently determined hydrocarbon generation kinetic parameters, and the more computational effort is required. In a specific embodiment, the obtained original data points are arranged in order according to the reaction temperature, and the reaction temperature of the i-th data point is denoted as T i , the corresponding original reaction rate is V o (T i ), and the total number of obtained original data points is N.

[0041] Further, in step S2, the discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample are normalized to obtain normalized discrete data points, which includes:

[0042] Step S21: obtaining the area of the pyrolysis S2 peak of the target hydrocarbon source rock sample in the temperature-reaction rate domain;

[0043] Step S22: based on the area of the pyrolysis S2 peak of the target hydrocarbon source rock sample in the temperature-reaction rate domain, each discrete data point is normalized by using the following formula:

[0044]

[0045] In the formula, V(T i ) is the normalized reaction rate corresponding to the reaction temperature T i of the i-th discrete data point, mg / (g×K); V o (T i ) is the original reaction rate corresponding to the reaction temperature T i of the i-th discrete data point, mg / (g×K); T i is the reaction temperature of the i-th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K.

[0046] Further, step S3, determining the organic matter activation energy distribution range includes:

[0047] Step S31: determining the upper limit of the activation energy of organic matter;

[0048] Step S32: determining the lower limit of the activation energy of organic matter;

[0049] In a specific embodiment, the upper limit of the activation energy of the hydrocarbon source rock is determined as the upper limit of the activation energy of organic matter (Ea max ) according to the activation energy of each organic matter microcomponent constituting the hydrocarbon source rock, and the lower limit of the activation energy of the hydrocarbon source rock is determined as the lower limit of the activation energy of organic matter (Ea min ).

[0050] Further, step S4, based on the organic matter activation energy distribution range and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, determining the continuous type initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample includes:

[0051] Step S41: constructing an activation energy normal distribution model;

[0052] Step S42: based on the organic matter activation energy distribution range and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, using the activation energy normal distribution model, determining the continuous type initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample.

[0053] Further, step S41, constructing an activation energy normal distribution model includes:

[0054] Step S411: determining that the content of each organic matter component constituting the target hydrocarbon source rock sample and its activation energy obeys the expected value Ea -, a continuous normal distribution with a standard deviation of σ, and further determining the content of the organic matter component as a function of the activation energy, the expected value Ea - , the standard deviation σ of the normal distribution;

[0055] wherein the content of the organic matter component as a function of the activation energy, the expected value Ea - , the standard deviation σ of the normal distribution is preferably:

[0056]

[0057] wherein X c (Ea) is the content of the organic matter component with an activation energy of Ea in %, Ea is the activation energy in 4185.85 J / mol; Ea - is the expected value of the normal distribution in 4185.85 J / mol; and σ is the standard deviation of the normal distribution in 4185.85 J / mol;

[0058] Step S412: constructing an objective function of the optimized initial solution:

[0059] wherein,

[0060]

[0061] wherein ΔT is the difference (i.e. ΔT = T end -T initial ) between the final reaction temperature (T end ) and the initial reaction temperature (T initial ) in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in K; A0 is the frequency factor of the organic matter component, in min -1 ; N is the number of discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample; V(T i ) is the normalized reaction rate corresponding to the i-th discrete data point reaction temperature T i , in mg / (g·K); V(A0, Ea - , σ, T i ) is the reaction rate calculated under the condition of the frequency factor A0 of the organic matter component, the expected value Ea - , the standard deviation σ, and the reaction temperature T i , in mg / (g·K); T i is the reaction temperature of the i-th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in K; and Ea -Ea is the activation energy, unit 4185.85 J / mol; Ea is the expectation value of the normal distribution, unit 4185.85 J / mol; σ is the standard deviation of the normal distribution, unit 4185.85 J / mol; R is the ideal gas constant, unit 8.314 J / (mol·K); D is the heating rate of the thermal simulation experiment corresponding to the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K / min;

[0062] In the above embodiment, the activation energy normal distribution model includes a function of the content of the organic matter component about the activation energy, the expectation value Ea - , the standard deviation σ of the organic matter component and the objective function of the optimization initial solution; in a specific embodiment, the activation energy normal distribution model constructed is:

[0063]

[0064]

[0065]

[0066] In the formula, X c (Ea) is the content of the organic matter component with the activation energy Ea, unit %; Ea is the activation energy, unit 4185.85 J / mol; Ea - is the expectation value of the normal distribution, unit 4185.85 J / mol; σ is the standard deviation of the normal distribution, unit 4185.85 J / mol; V(A0, Ea - , σ, T i ) is the reaction rate calculated under the conditions of the frequency factor A0, the expectation value Ea - , the standard deviation σ, and the reaction temperature T i of the organic matter component, unit mg / (g·K); A0 is the frequency factor of the organic matter component, unit min -1 ; T i is the reaction temperature of the i th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K; R is the ideal gas constant, unit 8.314 J / (mol·K); D is the heating rate of the thermal simulation experiment corresponding to the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K / min; ΔT is the difference (i.e. ΔT=T end -T initial ) between the final reaction temperature (T end ) and the initial reaction temperature (T initial ) in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K; N is the number of discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample; V(T i ) is the normalized reaction rate corresponding to the i th discrete data point reaction temperature T i , unit mg / (g·K).

[0067] Further, step S42: Based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, using the activation energy normal distribution model, the continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample is determined, including:

[0068] Step S421: Based on the range of activation energy distribution of organic matter, determine the expected value Ea in the normal distribution model of activation energy. - The maximum value (Ea) - max ) and minimum value (Ea) - min This allows us to determine the expected value Ea in the activation energy normal distribution model. - The range of values ​​for ;

[0069] Among them, the expected value Ea in the activation energy normal distribution model - The maximum value (Ea) - max ) and minimum value (Ea) - min The preferred method is determined by the following formula:

[0070]

[0071]

[0072] In the formula, Ea - max The expected value Ea in the activation energy normal distribution model - The maximum value, in units of 4185.85 J / mol; Ea - min The expected value Ea in the activation energy normal distribution model - The minimum value, in units of 4185.85 J / mol; Ea max Ea represents the upper limit of the activation energy distribution range of organic matter, expressed in units of 4185.85 J / mol. min The lower limit of the activation energy of organic matter is the range of activation energy distribution for organic matter, expressed in units of 4185.85 J / mol.

[0073] Step S422: Determine the minimum value of the standard deviation σ in the activation energy normal distribution model (σ min Based on the range of activation energy distribution of organic matter, the maximum value of the standard deviation σ in the normal distribution model of activation energy is determined. max This allows us to determine the range of values ​​for the standard deviation σ in the activation energy normal distribution model.

[0074] Among them, the minimum standard deviation σ in the activation energy normal distribution model (σ min The preferred value is 0;

[0075] wherein the maximum value of the standard deviation σ in the normal distribution model of activation energy is preferably determined by the following formula:

[0076]

[0077] wherein σ max is the maximum value of the standard deviation σ in the normal distribution model of activation energy, with the unit of 4185.85 J / mol; Ea max is the upper limit of the activation energy of organic matter in the distribution range of the activation energy of organic matter, with the unit of 4185.85 J / mol; Ea min is the lower limit of the activation energy of organic matter in the distribution range of the activation energy of organic matter, with the unit of 4185.85 J / mol;

[0078] Step S423: determining the value range of the frequency factor of the organic matter component in the normal distribution model of activation energy;

[0079] wherein the determination of the value range of the frequency factor of the organic matter component in the normal distribution model of activation energy preferably comprises the determination of the value range of the parameters a and b; wherein the value range of a is preferably in the interval (0, 1), and the value range of b is preferably determined according to the order of magnitude of the frequency factor of each organic matter maceral in the decimal system (for example, [10, 20]), and the relationship between the frequency factor and the parameters a and b is shown in the following formula: A0 = a x 10 b , A0 is the frequency factor of the organic matter component, with the unit of min -1 ;

[0080] Step S424: based on the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, solving the normal distribution model of activation energy within the value range of the expected value Ea - , the standard deviation σ and the frequency factor of the organic matter component, to determine the optimal expected value Ea - , the standard deviation σ and the frequency factor of the organic matter component, and further determine the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample.

[0081] wherein the solving of the normal distribution model of activation energy is preferably performed by using a genetic algorithm.

[0082] Further, step S5, the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample is discretized to obtain the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample, which comprises:

[0083] Step S51: obtaining the activation energy discrete interval (ΔEa);

[0084] The smaller the discrete activation energy interval is, the smaller the difference between the obtained discrete activation energy spectrum and the original continuous activation energy distribution is, and the larger the calculation amount paid in subsequent solving is. In an embodiment, an integer interval is used as the discrete activation energy interval;

[0085] Step S52: determining a discrete organic matter component activation energy set (Ea d ) based on the organic matter activation energy distribution range and in combination with the discrete activation energy interval;

[0086] Preferably, the activation energy of the discrete organic matter component in the discrete organic matter component activation energy set is:

[0087] Ea dj =Ea min +(j-1)ΔEa

[0088] In the formula, Ea min is the lower limit of the organic matter activation energy in the organic matter activation energy distribution range, and has a unit of 4185.85 J / mol; ΔEa is the discrete activation energy interval, and has a unit of 4185.85 J / mol; Ea dj is the activation energy of the jth discrete organic matter component in the discrete organic matter component activation energy set, j is a positive integer and ∈[1, n], and has a unit of 4185.85 J / mol; n is the number of the discrete organic matter components in the discrete organic matter component activation energy set, and is preferably determined by the following formula:

[0089]

[0090] In the formula, ceil(…) is a rounding function to positive infinity; Ea max is the upper limit of the organic matter activation energy in the organic matter activation energy distribution range, and has a unit of 4185.85 J / mol; Ea min is the lower limit of the organic matter activation energy in the organic matter activation energy distribution range, and has a unit of 4185.85 J / mol; ΔEa is the discrete activation energy interval, and has a unit of 4185.85 J / mol;

[0091] Step S53: determining the content of each discrete organic matter component based on the continuous initial solution of the target hydrocarbon source rock sample hydrocarbon generation kinetics parameters and in combination with the discrete organic matter component activation energy set;

[0092] In the formula, the content of each discrete organic matter component is preferably determined by the following formula:

[0093]

[0094]

[0095] In the formula, X d_o (Ea dj ) is the activation energy of the jth discrete organic matter component.dj initial content of the discrete organic matter component with activation energy of Ea, unit %; Ea dj activation energy of the jth discrete organic matter component in the set of activation energies of discrete organic matter, positive integer j∈[1, n], unit 4185.85 J / mol; n is the number of discrete organic matter components in the set of activation energies of discrete organic matter; ΔEa is the activation energy discrete interval, unit 4185.85 J / mol; X c (Ea) is the content of the organic matter component with activation energy of Ea, unit %; Ea is the activation energy, unit 4185.85 J / mol; X d (Ea dj ) is the content of the discrete organic matter component with activation energy of Ea dj ;

[0096] In a specific embodiment, the content of each discrete organic matter component is preferably determined by the following formula:

[0097]

[0098]

[0099] In the formula, X d_o (Ea dj ) is the initial content of the discrete organic matter component with activation energy of Ea dj , unit %; Ea dj activation energy of the jth discrete organic matter component in the set of activation energies of discrete organic matter, positive integer j∈[1, n], unit 4185.85 J / mol; n is the number of discrete organic matter components in the set of activation energies of discrete organic matter; ΔEa is the activation energy discrete interval, unit 4185.85 J / mol; Ea is the activation energy, unit 4185.85 J / mol; Ea - is the expected value of the normal distribution, unit 4185.85 J / mol; σ is the standard deviation of the normal distribution, unit 4185.85 J / mol; X d (Ea dj ) is the content of the discrete organic matter component with activation energy of Ea dj .

[0100] Further, in step S6, based on the discretized solution of the continuous solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample, the content of each organic matter component is optimized to obtain the final hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample, including:

[0101] Step S61: constructing a final optimization target function:

[0102] wherein,

[0103]

[0104] wherein ΔT is the difference (i.e. ΔT = T end -T initial ) between the final reaction temperature (T end ) and the initial reaction temperature (T initial ) in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in K; A0 is a frequency factor of the discrete organic matter components (same as the frequency factor in the continuous primary solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample), in min -1 -1 ; Ea d is a list of activation energies obtained from the discrete primary solution; Ea dj is the activation energy of the jth discrete organic matter component, where j is a positive integer in [1, n], in 4185.85 J / mol; n is the number of the discrete organic matter components; X fd (Ea d ) is the content of each final discrete organic matter component to be optimized; X fd (Ea dj ) is the content of the jth discrete organic matter component; T i is the reaction temperature of the ith data point in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in K; N is the number of the discrete data points in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample; V(T i ) is the normalized reaction rate corresponding to the ith discrete data point reaction temperature T i , in mg / (g·K); γ is a penalty function coefficient, and the penalty coefficient is selected from one of [1000, 5000, 10000, 50000, 100000];

[0105] Step S62: selecting the smallest penalty function;

[0106] Step S63: determining the content of each discrete organic matter component in the discrete solution of the continuous primary solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample as the primary solution, setting an iteration stop condition based on the variance of the objective function in the latest iteration number, and solving the final optimization objective function constructed based on the selected penalty function, the determined primary solution and the set iteration stop condition to determine the optimal content of each discrete organic matter component and obtain the optimal hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample;

[0107] wherein the iteration stop condition is preferably that the variance of the objective function values in the latest m iterations is less than 10 -2 , where the value range of the positive integer m is [1000, 10000]; the variance of the objective function values in the latest m iterations is less than 10 -2 , indicating that the objective function has reached a local minimum point and the iteration can be stopped;

[0108] Preferably, the final optimization objective function is solved by using a quasi-Newton method, and the Hessen matrix used in the quasi-Newton method is a positive definite matrix.

[0109] The variance of the objective function in the latest iteration is used as the termination condition of the algorithm iteration. With the increase of the number of iterations, the value of the objective function gradually decreases, but sometimes increases, which is caused by the iteration solution being in the non-value domain triggering the penalty function. In the vicinity of the local solution, the penalty function will not be triggered and the change of the value of the objective function will be very small, that is, the variance of the value of the objective function in the vicinity of the local solution is very small. Therefore, using the variance of the value of the objective function in the latest iteration as the termination condition of the algorithm iteration can effectively and quickly end the algorithm.

[0110] Step S64: determining the final optimization objective function error limit, and then determining the final hydrocarbon generation kinetic parameters based on the optimal content of each discrete organic matter component obtained in step S63:

[0111] 1. If for non-negative integer j, the following condition is met: and the final optimization objective function value is less than ∈, the optimal hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample obtained in step S63 are the final hydrocarbon generation kinetic parameters; wherein n is the number of discrete organic matter components, X fd ′(Ea dj ) is the optimal content of the jth discrete organic matter component.

[0112] 2. If for non-negative integer j, the following condition is met: then the optimal content of each discrete organic matter component is non-negative, and if the final optimization objective function value after non-negative processing is less than ∈, the non-negative processed hydrocarbon generation kinetic parameters are the final hydrocarbon generation kinetic parameters; wherein n is the number of discrete organic matter components, X d ′(Ea dj ) is the optimal content of the jth discrete organic matter component; wherein the non-negative processing is preferably performed by the following method:

[0113]

[0114] In the formula, Xfd + ′(Ea dk ) is the content of the discrete organic matter component with the kth content being positive in the optimal content of all discrete organic matter components, the positive integer k ∈ [1, n-z], n is the number of discrete organic matter components in the discrete organic matter activation energy set, and z is the number of negative contents in the optimal content of all discrete organic matter components; X fd -′(Ea dp ) is the content of the discrete organic matter component with the pth content being negative in the optimal content of all discrete organic matter components, X fd+ ″(Eadk ) is the non-negative processed content of the kth content of all discrete organic matter components with positive content in the optimal content of all discrete organic matter components, Xf d - "(Ea dp ) is the non-negative processed content of the pth content of all discrete organic matter components with negative content in the optimal content of all discrete organic matter components;

[0115] ③ If the conditions of ① and ② are not met, the penalty coefficient is increased, and steps S63 and S64 are repeated until the final hydrocarbon generation kinetic parameters are determined.

[0116] The embodiment of the present application also provides a specific implementation of a hydrocarbon source rock hydrocarbon generation kinetic parameter determination system, which is used to implement the hydrocarbon source rock hydrocarbon generation kinetic parameter determination method embodiment described above, and the system comprises:

[0117] A sample data acquisition module 21 is configured to acquire discrete data points of a pyrolysis S2 peak spectrum of a target hydrocarbon source rock sample, wherein the pyrolysis S2 peak spectrum is a pyrolysis S2 peak temperature-reaction rate curve.

[0118] A sample data normalization processing module 22 is configured to perform normalization processing on the discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample to obtain normalized discrete data points.

[0119] An activation energy range determination module 23 is configured to determine an organic matter activation energy distribution range.

[0120] A continuous type initial solution determination module 24 is configured to determine a continuous type initial solution of hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample based on the organic matter activation energy distribution range and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, wherein the content of each organic matter component constituting the target hydrocarbon source rock sample and the activation energy thereof obey a normal distribution, and the hydrocarbon generation kinetic parameters include the activation energy of each organic matter component constituting the target hydrocarbon source rock sample (different activation energies are different organic matter components), the content (i.e., the percentage content of each organic matter component in the total organic matter), and the frequency factor of the organic matter component.

[0121] A continuous type initial solution discretization module 25 is configured to discretize the continuous type initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample to obtain a discretized solution of the continuous type initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample, wherein the discretized solution of the continuous type initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component, and the frequency factor of the discrete organic matter component.

[0122] A final hydrocarbon generation kinetic parameter determination module 26 is configured to optimize the content of each organic matter component based on the discretized solution of the continuous type initial solution of the hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample to obtain the final hydrocarbon generation kinetic parameters of the target hydrocarbon source rock sample.

[0123] Further, the sample data acquisition module 21 comprises:

[0124] a sample pyrolysis S2 peak spectrum acquisition submodule 211, configured to acquire a pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample;

[0125] a sample data point acquisition submodule 212, configured to acquire, from the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, original data points as discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, from a starting reaction temperature (T initial ) to a final reaction temperature (T end ) of the pyrolysis S2 peak spectrum;

[0126] The more the number of selected original data points, the more accurate the subsequent determined hydrocarbon generation kinetic parameters, and the more computational effort is paid. In a specific embodiment, the acquired original data points are sequentially arranged according to the reaction temperature, and the reaction temperature of the i-th data point is denoted as T i , the corresponding original reaction rate is denoted as V o (T i ), and the total number of acquired original data points is denoted as N.

[0127] Further, the sample data normalization processing module 22 comprises:

[0128] an area determination submodule 221, configured to acquire an area of the pyrolysis S2 peak of the target hydrocarbon source rock sample in the temperature-reaction rate domain;

[0129] a normalization processing submodule 222, configured to perform normalization processing on each discrete data point based on the area of the pyrolysis S2 peak of the target hydrocarbon source rock sample in the temperature-reaction rate domain, using the following formula:

[0130]

[0131] In the formula, V(T i ) is the normalized reaction rate corresponding to the reaction temperature T i of the i-th discrete data point, mg / (g×K); V o (T i ) is the original reaction rate corresponding to the reaction temperature T i of the i-th discrete data point, mg / (g×K); and T i is the reaction temperature of the i-th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K.

[0132] Further, the activation energy range determination module 23 comprises:

[0133] an upper limit of activation energy determination submodule 231, configured to determine an upper limit of activation energy of organic matter;

[0134] Activation energy lower limit determining sub-module 232: configured to determine the lower limit of activation energy of the organic matter.

[0135] Further, the continuous primary solution determining module 24 comprises:

[0136] Activation energy normal distribution model constructing sub-module 241: configured to construct an activation energy normal distribution model.

[0137] Continuous primary solution determining sub-module 242: configured to determine the continuous primary solution of the kinetic parameters of the target hydrocarbon source rock sample based on the activation energy distribution range of the organic matter, the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, and the activation energy normal distribution model.

[0138] Further, the activation energy normal distribution model constructing sub-module 241 comprises:

[0139] First function constructing unit 2411: configured to determine that the content of each organic matter component constituting the target hydrocarbon source rock sample and the activation energy thereof are subject to a continuous normal distribution with an expected value of Ea - and a standard deviation of σ, and further determine a function of the content of the organic matter component with respect to the activation energy of the organic matter component, the expected value Ea - and the standard deviation σ;

[0140] The function of the content of the organic matter component with respect to the activation energy of the organic matter component, the expected value Ea - and the standard deviation σ is preferably:

[0141]

[0142] In the formula, X c (Ea) is the content of the organic matter component with the activation energy of Ea, in unit of %; Ea is the activation energy, in unit of 4185.85 J / mol; Ea - is the expected value of the normal distribution, in unit of 4185.85 J / mol; σ is the standard deviation of the normal distribution, in unit of 4185.85 J / mol;

[0143] Second function constructing unit 2412: configured to construct a target function of the optimized primary solution:

[0144]

[0145] In the formula, ΔT is the difference between the final reaction temperature (T end ) and the initial reaction temperature (T initial ) in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample (i.e. ΔT = T end -T initial ), in unit of K; A0 is the frequency factor of the organic matter component, in unit of min -1; N is the number of discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample; V(T i ) is the reaction rate of the i th discrete data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit: mg / (g·K); V(A0, Ea i , σ, T - ) is the corresponding normalized reaction rate, unit: mg / (g·K); V(A0, Ea i , σ, T - ) is the reaction rate calculated under the frequency factor A0, expectation value Ea i , standard deviation σ, and reaction temperature T i of the organic matter component, unit: mg / (g·K); T - is the reaction temperature of the i th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit: K; Ea c is the expectation value of the normal distribution, unit: 4185.85 J / mol; σ is the standard deviation of the normal distribution, unit: 4185.85 J / mol; R is the ideal gas constant, unit: 8.314 J / (mol·K); D is the heating rate of the corresponding thermal simulation experiment of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit: K / min.

[0146] Further, the activation energy normal distribution model constructed by the activation energy normal distribution model construction submodule 241 is.

[0147]

[0148]

[0149]

[0150] In the formula, X c (Ea) is the content of the organic matter component with activation energy Ea, unit: %; Ea is the activation energy, unit: 4185.85 J / mol; Ea - is the expectation value of the normal distribution, unit: 4185.85 J / mol; σ is the standard deviation of the normal distribution, unit: 4185.85 J / mol; V(A0, Ea - , σ, T i ) is the reaction rate calculated under the frequency factor A0, expectation value Ea - , standard deviation σ, and reaction temperature T i of the organic matter component, unit: mg / (g·K); A0 is the frequency factor of the organic matter component, unit: min -1 ; T iΔT represents the reaction temperature of the i-th data point in the pyrolysis S2 peak spectrum of the target source rock sample, in K; R is the ideal gas constant, in 8.314 J / (mol·K); D is the heating rate of the thermal simulation experiment corresponding to the pyrolysis S2 peak spectrum of the target source rock sample, in K / min; ΔT is the final reaction temperature (Ti) in the pyrolysis S2 peak spectrum of the target source rock sample. end ) and initial reaction temperature (T) initial The difference between (i.e., ΔT = T) end -T initial ), unit K; N is the number of discrete data points in the pyrolysis S2 peak spectrum of the target source rock sample; V(T i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate, in mg / (g·K).

[0151] Furthermore, the continuous initial solution determination submodule 242 includes:

[0152] Expected value range determination unit 2421: Used to determine the expected value Ea in the normal distribution model of activation energy based on the distribution range of activation energy of organic matter. - The maximum value (Ea) - max ) and minimum value (Ea) - min This allows us to determine the expected value Ea in the activation energy normal distribution model. - The range of values ​​for ;

[0153] Among them, the expected value Ea in the activation energy normal distribution model - The maximum value (Ea) - max ) and minimum value (Ea) - min The optimal wash is determined by the following formula:

[0154]

[0155]

[0156] In the formula, Ea - max The expected value Ea in the activation energy normal distribution model - The maximum value, in units of 4185.85 J / mol; Ea - min The expected value Ea in the activation energy normal distribution model - The minimum value, in units of 4185.85 J / mol; Ea max Ea represents the upper limit of the activation energy distribution range of organic matter, expressed in units of 4185.85 J / mol. minThe lower limit of the activation energy distribution range of organic matter is 4185.85 J / mol;

[0157] The standard deviation range determination unit 2422 is configured to determine the minimum value (σ min ) of the standard deviation σ in the activation energy normal distribution model based on the lower limit of the activation energy distribution range of organic matter, which is 4185.85 J / mol; max , and determine the value range of the standard deviation σ in the activation energy normal distribution model.

[0158] Preferably, the minimum value (σ min ) of the standard deviation σ in the activation energy normal distribution model is 0.

[0159] Preferably, the maximum value of the standard deviation σ in the activation energy normal distribution model is determined by the following formula:

[0160]

[0161] In the formula, σ max is the maximum value of the standard deviation σ in the activation energy normal distribution model, which is 4185.85 J / mol; Ea max is the upper limit of the activation energy distribution range of organic matter, which is 4185.85 J / mol; and Ea min is the lower limit of the activation energy distribution range of organic matter, which is 4185.85 J / mol.

[0162] The frequency factor range determination unit 2423 is configured to determine the value range of the frequency factor of the organic matter component in the activation energy normal distribution model.

[0163] Preferably, the determination of the value range of the frequency factor of the organic matter component in the activation energy normal distribution model includes the determination of the value range of the parameters a and b. Preferably, the value range of a belongs to the interval (0, 1), and the value range of b is determined according to the order of magnitude of the frequency factor of each organic matter macromolecular component in the decimal system (for example, [10, 20]). The relationship between the frequency factor and the parameters a and b is shown in the following formula: A0=a×10 b , where A0 is the frequency factor of the organic matter component, and the unit is min -1 .

[0164] The continuous initial solution determination unit 2424 is configured to determine the optimal expected value Ea - , the standard deviation σ, and the frequency factor of the organic matter component in the activation energy normal distribution model based on the normalized discrete data points of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample. -a continuous initial solution of the target hydrocarbon source rock sample hydrocarbon generation kinetics parameters is determined by using the standard deviation σ, the frequency factor of the organic matter component and the continuous initial solution;

[0165] Wherein, the genetic algorithm is preferably used to solve the normal distribution model of activation energy.

[0166] Further, the continuous initial solution discretization module 25 comprises:

[0167] The discrete interval acquisition unit 251 is configured to acquire the activation energy discrete interval (ΔEa).

[0168] Wherein, the smaller the activation energy discrete interval, the smaller the difference between the obtained activation energy discrete spectrum and the original continuous activation energy distribution, and the greater the amount of calculation paid in subsequent solving. In a specific embodiment, an integer interval is used as the activation energy discrete interval.

[0169] The discrete activation energy determination unit 252 is configured to determine the discrete organic matter component activation energy set (Ea d ) based on the organic matter activation energy distribution range and the activation energy discrete interval.

[0170] Wherein, the discrete organic matter component activation energy in the discrete organic matter component activation energy set is preferably:

[0171] Ea dj =Ea min +(j-1)ΔEa

[0172] In the formula, Ea min is the lower limit of the organic matter activation energy in the organic matter activation energy distribution range, and the unit is 4185.85 J / mol; ΔEa is the activation energy discrete interval, and the unit is 4185.85 J / mol; Ea dj is the activation energy of the jth discrete organic matter component in the discrete organic matter component activation energy set, and the positive integer j ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components in the discrete organic matter component activation energy set, which is preferably determined by the following formula:

[0173]

[0174] In the formula, ceil(…) is the rounding function to positive infinity; Ea max is the upper limit of the organic matter activation energy in the organic matter activation energy distribution range, and the unit is 4185.85 J / mol; Ea min is the lower limit of the organic matter activation energy in the organic matter activation energy distribution range, and the unit is 4185.85 J / mol; ΔEa is the activation energy discrete interval, and the unit is 4185.85 J / mol;

[0175] The discrete content determination unit 253 is configured to determine the content of each discrete organic matter component based on the continuous solution of the target hydrocarbon source rock sample hydrocarbon generation kinetics parameters and the set of discrete organic matter component activation energies.

[0176] The content of each discrete organic matter component is preferably determined by the following formula:

[0177]

[0178]

[0179] wherein X d_o (Ea dj ) is the initial content of the discrete organic matter component with activation energy Ea dj , in percentage; Ea dj is the activation energy of the jth discrete organic matter component in the set of discrete organic matter activation energies, where j is a positive integer and j ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components in the set of discrete organic matter activation energies; ΔEa is the activation energy interval, and the unit is 4185.85 J / mol; Ea c (Ea) is the content of the organic matter component with activation energy Ea d , in percentage; Ea is the activation energy, and the unit is 4185.85 J / mol; and X dj (Ea dj ) is the content of the discrete organic matter component with activation energy Ea d_o .

[0180] In an embodiment, the content of each discrete organic matter component is preferably determined by the following formula:

[0181]

[0182]

[0183] wherein X d_o (Ea dj ) is the initial content of the discrete organic matter component with activation energy Ea dj , in percentage; Ea dj is the activation energy of the jth discrete organic matter component in the set of discrete organic matter activation energies, where j is a positive integer and j ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components in the set of discrete organic matter activation energies; ΔEa is the activation energy interval, and the unit is 4185.85 J / mol; Ea is the activation energy, and the unit is 4185.85 J / mol; Ea - is the mean value of the normal distribution, and the unit is 4185.85 J / mol; and σ is the standard deviation of the normal distribution, and the unit is 4185.85 J / mol; and X d (Eadj ) is the activation energy of the discrete organic matter component dj .

[0184] Further, the final hydrocarbon generation kinetics parameter determination module 26 is specifically used for:

[0185] (1) constructing a final optimization objective function:

[0186] wherein,

[0187]

[0188] In the formula, ΔT is the difference (i.e., ΔT = T end - T initial ) between the final reaction temperature (T end ) and the initial reaction temperature (T initial ) in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in units of K; A0 is the frequency factor of the discrete organic matter component, in units of min -1 ; Ea d is the list of activation energies obtained by the discrete initial solution; Ea dj is the activation energy of the jth discrete organic matter component, where j is a positive integer and j ∈ [1, n], in units of 4185.85 J / mol; n is the number of discrete organic matter components; X fd (Ea d ) is the content of the final each discrete organic matter component to be optimized; X fd (Ea dj ) is the content of the jth discrete organic matter component; T i is the reaction temperature of the ith data point in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in units of K; N is the number of discrete data points in the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample; V(T i ) is the normalized reaction rate corresponding to the ith discrete data point reaction temperature T i , in units of mg / (g·K); γ is a penalty function coefficient, and the selection principle of the penalty coefficient is one of [1000, 5000, 10000, 50000, 100000];

[0189] (2) selecting the smallest penalty function;

[0190] (3) determining the content of each discrete organic matter component in the discrete solution of the continuous initial solution of the hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample as the initial solution, setting an iteration stop condition based on the variance of the objective function in the latest iteration number, and solving the final optimization objective function constructed based on the selected penalty function, the determined initial solution, and the set iteration stop condition to determine the optimal content of each discrete organic matter component and obtain the optimal hydrocarbon generation kinetics parameters of the target hydrocarbon source rock sample;

[0191] wherein the iteration stopping condition is preferably that the variance of the objective function values in the latest m iterations is less than 10 -2 wherein the positive integer m is in the range of [1000, 10000]; the variance of the objective function values in the latest m iterations is less than 10 -2 indicating that the objective function has reached a local minimum point, and the iteration can be stopped;

[0192] wherein the final optimization objective function is preferably solved by using a quasi-Newton method, and the Hessen matrix used in the quasi-Newton method is a positive definite matrix;

[0193] (4) determining the final optimization objective function allowable error limit, and then determining the final hydrocarbon generation kinetic parameters based on the optimal content of each discrete organic matter component obtained in step S63:

[0194] ① if for a non-negative integer j, the following condition is satisfied: and the final optimization objective function value is less than ∈, then the optimal hydrocarbon generation kinetic parameters of the target source rock sample obtained in step S63 are the final hydrocarbon generation kinetic parameters; wherein n is the number of discrete organic matter components in the discrete organic matter activation energy set, X fd ′(Ea dj ) is the optimal content of the jth discrete organic matter component;

[0195] ② if for a non-negative integer j, the following condition is satisfied: then the optimal content of each discrete organic matter component is non-negative processed, and if the final optimization objective function value after the non-negative processing is less than ∈, then the hydrocarbon generation kinetic parameters after the non-negative processing are the final hydrocarbon generation kinetic parameters; wherein n is the number of discrete organic matter components in the discrete organic matter activation energy set, X fd ′(Ea dj ) is the optimal content of the jth discrete organic matter component; wherein the non-negative processing is preferably performed by the following method:

[0196]

[0197] wherein X fd+ ′(Ea dk ) is the content of the discrete organic matter component whose kth content in the optimal content of all discrete organic matter components is positive, the positive integer k ∈ [1, n-z], n is the number of discrete organic matter components in the discrete organic matter activation energy set, and z is the number of negative contents in the optimal content of all discrete organic matter components; X fd- ′(Ea dp ) is the content of the discrete organic matter component whose pth content in the optimal content of all discrete organic matter components is negative, X fd+ ″(Ea dkLet X be the non-negative content of the k-th discrete organic matter component with a positive content among all the optimal contents of discrete organic matter components. fd- "(Ea dp ) represents the non-negative content of the p-th discrete organic matter component whose content is negative among the optimal contents of all discrete organic matter components;

[0198] ③ If conditions ① and ② are not met, increase the penalty coefficient and repeat steps (3) and (4) until the final hydrocarbon generation kinetic parameters are determined.

[0199] Example 1

[0200] This example uses Group A source rocks in Region A to determine hydrocarbon kinetic parameters. Region A is located in the central part of a depression. After more than 20 years of oil and gas exploration, numerous oil and gas fields and hydrocarbon-bearing structures have been discovered. Region A contains two sets of source rocks, Group A and Group B. Group A is mainly composed of deep-latitude to medium-deep-latitude lacustrine sediments, with high organic matter abundance. The average organic carbon content is 2.35%, the average S1+S2 content is 11.81 mg / g, and the average HI content can reach 329 mg / g. The organic matter type is mainly type II1, which is the main source rock in Region A. The source rock sample S selected in this study is located in the periphery of Region A and has low maturity, making it suitable for kinetic studies. In addition, the pyrolysis S2 curve of this sample has a shoulder peak, which is difficult to optimize, making it suitable for verifying the effectiveness of the method for determining hydrocarbon kinetic parameters of source rocks provided in this invention.

[0201] The specific implementation process includes:

[0202] 1. Obtain the temperature-reaction rate domain spectrum of the S2 peak in the pyrolysis of source rock sample S (e.g., Figure 2 (as shown); from the starting temperature (T) of this spectrum initial =573.15K) to the final temperature (T) end =923.15K) The original data points were uniformly selected and recorded as discrete data points. A total of 93 data points were selected, and the temperature (T) of these 93 data points was recorded. i and the initial reaction rate V o (T i ), positive integer i∈[1, 93].

[0203] 2. Calculate the area of ​​the pyrolysis S2 peak in the temperature-reaction rate domain (A). S2 =3.51). The discrete data points selected in step 1 are normalized using the following method:

[0204]

[0205] In the formula, V(T) i ) represents the reaction temperature T at the i-th discrete data point. iCorresponding normalized reaction rate, mg / (g×K); V o (T i ) is the reaction temperature of the i th discrete data point of the target hydrocarbon source rock sample, in K. i Corresponding original reaction rate, mg / (g×K); T i is the reaction temperature of the i th data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, in K.

[0206] 3、According to literature research, the maximum and minimum activation energies of the four macerals of petroleum source material are 70×4185.85 J / mol and 40×4185.85 J / mol, respectively. In this embodiment, the upper limit Ea max of the activation energy of the organic matter of the hydrocarbon source rock sample S is set as 70×4185.85 J / mol, and the lower limit Ea min of the activation energy is set as 40×4185.85 J / mol.

[0207] 4、Construct the normal distribution model of activation energy.

[0208] It is assumed that the content of each organic matter component of the target hydrocarbon source rock sample and its activation energy obey a continuous normal distribution law; the content of the continuous organic matter component is represented by X c , and the distribution range of the activation energy X c (Ea) of the continuous organic matter component is (40, 70)×4185.85 J / mol, X c ~ N(Ea - , σ 2 ), the content (X c ) of each organic matter component and its activation energy X c (Ea) obey a continuous normal distribution with an expectation value of Ea - and a standard deviation of σ; under this distribution, the content X c (Ea) of the organic matter component with the activation energy Ea is a function of the activation energy Ea of the organic matter component, the expectation value Ea - , and the standard deviation σ, and is as follows:

[0209]

[0210] In the formula, X c (Ea) is the content of the organic matter component with the activation energy Ea, in %; Ea is the activation energy, in 4185.85 J / mol; Ea - is the expectation value of the normal distribution, in 4185.85 J / mol; and σ is the standard deviation of the normal distribution, in 4185.85 J / mol.

[0211] Construct the objective function of the optimized initial solution:

[0212] in,

[0213]

[0214] In the formula, A0 is the frequency factor of the organic matter component, in min⁻¹; V(T) i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate, in mg / (g·K); V(A0, Ea) - , σ, T i ) represents the frequency factor A0 and expected value Ea of the organic matter component. - Standard deviation σ, reaction temperature T i The reaction rate calculated under the given conditions, in mg / (g·K); T i Ea represents the reaction temperature of the i-th data point in the pyrolysis S2 peak spectrum of the target source rock sample, in K; - σ is the expected value of the normal distribution, in units of 4185.85 J / mol; σ is the standard deviation of the normal distribution, in units of 4185.85 J / mol; R is the ideal gas constant, in units of 8.314 J / (mol·K); D is the heating rate of the thermal simulation experiment corresponding to the S2 peak spectrum of the pyrolysis of the target source rock sample, which is 25 K / min in this embodiment.

[0215] 5. Determine the expected value Ea in the activation energy normal distribution model. - The distribution range of the standard deviation σ and the distribution range of the frequency factor A0 are set. In this embodiment, the expected value Ea in the activation energy normal distribution model is... - Maximum value (Ea) - max The value is 60 × 4185.85 J / mol, and the minimum value (Ea) is 60 × 4185.85 J / mol. - min The value is 50 × 4185.85 J / mol, and the specific determination method is as follows:

[0216]

[0217]

[0218] Furthermore, in this embodiment, the minimum standard deviation σ in the activation energy normal distribution model (σ min The value is 0×4185.85 J / mol, and the maximum value is (σ max )for The specific determination method is as follows:

[0219]

[0220] The range of frequency factor A0 is divided into two key parameter settings, a and b. The range of a is within the interval (0, 1), and the setting of b is determined according to the order of magnitude of the frequency factor of each organic matter micro component in the decimal system. The relationship between the frequency factor and the parameters a and b is shown in the following formula:

[0221] A0=a×10 b

[0222] Ea - The range of Ea is (50, 60)×4185.85 J / mol, and the range of σ is The range of a is (0, 1), and the range of b is [10, 20]. The genetic algorithm is used to solve the objective function in the normal distribution model of activation energy, and the continuous optimal solution X of the hydrocarbon source rock sample S in this embodiment is obtained fd (Ea d ): expected value Ea - = 50×4185.85 J / mol, standard deviation σ = 3×4185.85 J / mol, and frequency factor A0 = 4.144×10 14 min -1 ;

[0223] 6, set the discrete interval of activation energy ΔEa as 1. Determine the number of discrete organic matter components in this embodiment as 31. n is determined by the following formula:

[0224]

[0225] In the formula, ceil(…) is the rounding function to positive infinity.

[0226] The set of activation energies of discrete organic matter components Ea d is [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70], and the calculation method of Ea d is as follows: the activation energy of the jth organic matter component is Ea dj , and the calculation formula of n is:

[0227] Ea dj = Ea min +(j-1)ΔEa

[0228] In this embodiment, the content X d (Ea dj) is [0.000, 0.000, 0.006, 0.009, 0.019, 0.034, 0.055, 0.081, 0.106, 0.125, 0.131, 0.125, 0.106, 0.081, 0.055, 0.034, 0.019, 0.009, 0.006, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000]. The determination method is divided into two steps:

[0229] Step A, the determination method of the content of the initial discrete organic matter component is as follows:

[0230]

[0231] Step B, the determination method is as follows:

[0232]

[0233] 7, construction of the final optimized objective function

[0234]

[0235]

[0236] In the formula, A0 is a frequency factor, which is 4.144x10 14 min -1 ; Ea d is the activation energy set of the discrete organic matter component, which is [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70]x4185.85 J / mol; Ea dj is the activation energy of the jth organic matter component in the activation energy set of the discrete organic matter, j is a positive integer, j∈[1, n], unit 4185.85 J / mol; n is the number of discrete organic matter components in the activation energy set of the discrete organic matter; X fd (Ea d ) is the content of the final each discrete organic matter component to be optimized; X fd (Ea dj ) is the content of the jth discrete organic matter component; T i is the reaction temperature of the ith data point of the pyrolysis S2 peak spectrum of the target hydrocarbon source rock sample, unit K; V(T i ) is the reaction temperature of the ith discrete data point T iCorresponding normalized reaction rate, unit: mg / (g·K); γ is a penalty function coefficient, the selection principle of the penalty coefficient is one of [1000, 5000, 10000, 50000, 100000].

[0237] 8. Select the smallest penalty function.

[0238] 9. The content X of the discrete organic matter component d (Ea dj ) = [0.000, 0.000, 0.006, 0.009, 0.019, 0.034, 0.055, 0.081, 0.106, 0.125, 0.131, 0.125, 0.106, 0.081, 0.055, 0.034, 0.019, 0.009, 0.006, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.000] × 4185.85 J / mol as the initial solution; set the variance of the objective function value in the latest 1000 iterations to be less than 10 -2 as the iteration stopping condition; use the quasi-Newton method to solve the final optimization objective function constructed to determine the optimal content X of each discrete organic matter component fd ′(Ea dj ) to obtain the optimal hydrocarbon generation kinetic parameters of the target source rock sample; wherein the Hessen matrix used by the quasi-Newton method should be a positive definite matrix.

[0239] 10. Determine that the allowable error limit of the final optimization objective function is 0.05, and then based on the optimal content X of each discrete organic matter component obtained in step 9 fd ′(Ea dj ) to make a final hydrocarbon generation kinetic parameter judgment:

[0240] ① If for a non-negative integer, it satisfies and the final optimization objective function value is less than ∈, then the optimal hydrocarbon generation kinetic parameters of the target source rock sample obtained in step 9 are the final hydrocarbon generation kinetic parameters;

[0241] ② If for a non-negative integer j, it satisfies then the optimal content of each discrete organic matter component is non-negative processed, and if the final optimization objective function value corresponding to the non-negative processed hydrocarbon generation kinetic parameters is less than ∈, then the non-negative processed hydrocarbon generation kinetic parameters are the final hydrocarbon generation kinetic parameters; wherein the non-negative processing is preferably performed by the following way:

[0242]

[0243] In the formula, X fd+ ′(Eadk ) is the content of the kth discrete organic matter component with positive content in the optimal content of all discrete organic matter components, and k is a positive integer in [1, n-z], n is the number of discrete organic matter components in the set of activation energies of discrete organic matter, and z is the number of negative contents in the optimal content of all discrete organic matter components; X fd- ′(Ea dp ) is the content of the pth discrete organic matter component with negative content in the optimal content of all discrete organic matter components, X fd+ ″(Ea dk ) is the non-negative processed content of the kth discrete organic matter component with positive content in the optimal content of all discrete organic matter components, X fd- ″(Ea dp ) is the non-negative processed content of the pth discrete organic matter component with negative content in the optimal content of all discrete organic matter components.

[0244] ③ If neither of the conditions ① and ② is met, then the penalty coefficient is increased, and steps 9 and 10 are repeated until the final hydrocarbon generation kinetic parameters are determined.

[0245] In this example, the iteration at the penalty coefficient of 1000 obtained the final hydrocarbon generation kinetic parameters, and the content of each discrete organic matter component in the final hydrocarbon generation kinetic parameters was [0.064, 0.011, 0.053, 0.032, 0.044, 0.028, 0.051, 0.022, 0.036, 0.098, 0.166, 0.152, 0.083, 0.049, 0.027, 0.026, 0.015, 0.011, 0.014, 0.006, 0.007, 0.007, 0.005, 0.003, 0.001, 0.001, 0.000, 0.000, 0.000, 0.000, 0.000].

[0246] In summary, the hydrocarbon generation kinetic parameters of the hydrocarbon source rock sample S of the example are as shown in Table 1: Figure 3 The frequency factor is 4.144 x 10 14 min -1The activation energy set of the discrete organic matter components is [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70]; the corresponding content of each discrete organic matter component is [0.064, 0.011, 0.053, 0.032, 0.044, 0.028, 0.051, 0.022, 0.036, 0.098, 0.166, 0.152, 0.083, 0.049, 0.027, 0.026, 0.015, 0.011, 0.014, 0.006, 0.007, 0.007, 0.005, 0.003, 0.001, 0.001, 0.000, 0.000, 0.000, 0.000, 0.000].

[0247] In order to verify the accuracy of the results, the determined hydrocarbon source rock sample S hydrocarbon generation kinetics parameters are used to perform numerical simulation to obtain the pyrolysis S2 temperature-reaction rate domain spectrum, and the comparison between the determined S2 temperature-reaction rate domain spectrum and the original pyrolysis S2 temperature-reaction rate domain spectrum is as shown in the figure Figure 4 It is shown that the coincidence rate of the two spectra is high, and it is indicated that the determined hydrocarbon generation kinetics parameters in the embodiment are accurate.

[0248] The above only describes the preferred embodiments of the present application and is not used to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining hydrocarbon generation kinetic parameters from source rocks, wherein, The method includes: Discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample are obtained; wherein, the pyrolysis S2 peak spectrum is the pyrolysis S2 peak temperature-reaction rate curve; Normalized discrete data points were obtained by normalizing the discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample. Determine the distribution range of activation energy in organic matter; Based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, a continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample is determined. Among them, the content of each organic matter component of the target source rock sample and its activation energy follow a normal distribution. The hydrocarbon generation kinetic parameters include the activation energy, content and frequency factor of each organic matter component of the target source rock sample. The continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample is discretized to obtain the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample; wherein, the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component, and the frequency factor of the discrete organic matter component. Discretization of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample is performed, and the content of each organic matter component is optimized to obtain the final hydrocarbon generation kinetic parameters of the target source rock sample. Among them, the continuous preliminary solution for determining the hydrocarbon generation kinetic parameters of the target source rock sample, based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum, includes: Construct a normal distribution model of activation energy; Based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, a continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample is determined using the activation energy normal distribution model. The construction of the activation energy normal distribution model includes: The content of each organic component in the target source rock sample and its activation energy are determined to follow an expected relationship, Ea. - A continuous normal distribution with standard deviation σ is used to determine the content of organic matter components with respect to the activation energy and expected value Ea of the organic matter components. - A function of standard deviation σ; Construct the objective function for optimizing the initial solution: in, In the formula, ΔT is the difference between the final reaction temperature and the initial reaction temperature in the S2 peak spectrum of the target source rock sample, in K; A0 is the frequency factor of the organic matter component, in min. -1 N represents the number of discrete data points in the pyrolysis S2 peak spectrum of the target source rock sample; V(T) i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate, in mg / (g·K); V(A0,Ea) - ,σ,T i ) represents the frequency factor A0 and expected value Ea of the organic matter component. - Standard deviation σ, reaction temperature T i The reaction rate calculated under the given conditions, in mg / (g·K); T i Ea represents the reaction temperature of the i-th data point in the pyrolysis S2 peak spectrum of the target source rock sample, in K; - σ is the expected value of the normal distribution, in units of 4185.85 J / mol; σ is the standard deviation of the normal distribution, in units of 4185.85 J / mol; R is the ideal gas constant, in units of 8.314 J / (mol·K); D is the heating rate of the thermal simulation experiment corresponding to the S2 peak spectrum of the pyrolysis of the target source rock sample, in units of K / min; Among them, based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, the continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample is determined using the activation energy normal distribution model, including: Based on the distribution range of activation energy of organic matter, determine the expected value Ea in the normal distribution model of activation energy. - The maximum and minimum values ​​are used to determine the expected value Ea in the activation energy normal distribution model. - The range of values ​​for ; The minimum value of the standard deviation σ in the activation energy normal distribution model is determined, and the maximum value of the standard deviation σ in the activation energy normal distribution model is determined based on the distribution range of activation energy of organic matter, thereby determining the range of values ​​for the standard deviation σ in the activation energy normal distribution model; Determine the range of values ​​for the frequency factor of the organic matter component in the activation energy normal distribution model; Based on the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, the expected value Ea in the activation energy normal distribution model is calculated. - Within the range of values ​​for the standard deviation σ and the frequency factor of the organic matter component, the activation energy normal distribution model is solved to determine the optimal expected value Ea. - The standard deviation σ and the frequency factor of organic matter components are used to determine the initial continuous solution of the hydrocarbon generation kinetic parameters of the target source rock sample.

2. The method according to claim 1, wherein, Discrete data points for obtaining the pyrolysis S2 peak spectrum of the target source rock sample include: Obtain the pyrolysis S2 peak spectrum of the target source rock sample; The original data points from the initial reaction temperature to the final reaction temperature of the pyrolysis S2 peak spectrum of the target source rock sample were uniformly obtained as discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample.

3. The method according to claim 1, wherein, Normalizing the discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample yields the following normalized discrete data points: Obtain the area of ​​the pyrolysis S2 peak of the target source rock sample in the temperature-reaction rate domain; Based on the area of ​​the pyrolysis S2 peak of the target source rock sample in the temperature-reaction rate domain, the discrete data points are normalized using the following formula: In the formula, V(T) i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate, mg / (g×K); V o (T i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding initial reaction rate, mg / (g×K); T i The reaction temperature of the i-th data point in the S2 peak spectrum of the pyrolysis of the target source rock sample is given in K.

4. The method according to claim 1, wherein, The content of organic matter components is related to the activation energy and expected value Ea of the organic matter components. - The function of standard deviation σ is: In the formula, X c (Ea) represents the content of organic matter components with activation energy Ea, in %; Ea represents the activation energy, in 4185.85 J / mol; Ea - σ is the expected value of the normal distribution, in units of 4185.85 J / mol; σ is the standard deviation of the normal distribution, in units of 4185.85 J / mol.

5. The method according to claim 1, wherein, Expected value Ea in the activation energy normal distribution model - The maximum and minimum values ​​are determined by the following formula: In the formula, Ea - max The expected value Ea in the activation energy normal distribution model - The maximum value, in units of 4185.85 J / mol; Ea - min The expected value Ea in the activation energy normal distribution model - The minimum value, in units of 4185.85 J / mol; Ea max Ea represents the upper limit of the activation energy distribution range of organic matter, expressed in units of 4185.85 J / mol. min The lower limit of the activation energy of organic matter is the range of activation energy distribution, expressed in units of 4185.85 J / mol.

6. The method according to claim 1, wherein, In the activation energy normal distribution model, the minimum standard deviation σ is 0.

7. The method according to claim 1, wherein, The maximum value of the standard deviation σ in the activation energy normal distribution model is determined by the following formula: In the formula, σ max Ea represents the maximum standard deviation σ in the activation energy normal distribution model, in units of 4185.85 J / mol. max Ea represents the upper limit of the activation energy distribution range of organic matter, expressed in units of 4185.85 J / mol. min The lower limit of the activation energy of organic matter is the range of activation energy distribution, expressed in units of 4185.85 J / mol.

8. The method according to claim 1, wherein, Determining the range of values ​​for the frequency factor of the organic matter component in the activation energy normal distribution model includes determining the range of values ​​for parameters a and b; the relationship between the frequency factor and parameters a and b is shown in the following formula: A0 = a × 10 b A0 is the frequency factor of the organic matter component, in min. -1 .

9. The method according to claim 8, wherein, The range of values ​​for 'a' is within the interval (0, 1).

10. The method according to claim 8, wherein, The range of values ​​for b is determined based on the order of magnitude of the frequency factor of each organic micro-component in decimal.

11. The method according to claim 1, wherein, A genetic algorithm is used to solve the activation energy normal distribution model.

12. The method according to claim 1, wherein, Discretization of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample: The discretization process of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample includes: Obtain the discrete interval of activation energy; Based on the distribution range of activation energy of organic matter and the discrete interval of activation energy, the set of activation energies of discrete organic matter components is determined; Based on the continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample, and combined with the set of activation energies of discrete organic matter components, the content of each discrete organic matter component is determined.

13. The method according to claim 7, wherein, The activation energies of organic matter components in the discrete set of organic matter component activation energies are: It dj =She min +(j-1)ΔEa In the formula, Ea min ΔEa represents the lower limit of the activation energy distribution range of organic matter, in units of 4185.85 J / mol; ΔEa is the activation energy dispersion interval, in units of 4185.85 J / mol; Ea dj is the activation energy of the j-th discrete organic matter component in the set of discrete organic matter activation energies, where j is a positive integer ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components in the set of discrete organic matter activation energies; The content of each discrete organic matter component is determined by the following formula: In the formula, X d_o (Ea dj The activation energy is Ea. dj The initial content of discrete organic matter components, in %; Ea dj X represents the activation energy of the j-th discrete organic matter component in the set of discrete organic matter activation energies, where j is a positive integer ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components in the set of discrete organic matter activation energies; ΔEa is the discrete interval of activation energies, and the unit is 4185.85 J / mol; c (Ea) represents the content of organic matter components with activation energy Ea, in %; Ea represents the activation energy, in 4185.85 J / mol; X d (Ea di The activation energy is Ea. dj The content of discrete organic matter components.

14. The method according to claim 1, wherein, Discretization of the initial continuous solution of the hydrocarbon generation kinetic parameters of the target source rock sample was performed, and the contents of each organic matter component were optimized to obtain the final hydrocarbon generation kinetic parameters of the target source rock sample, including: 1) Construct the final optimization objective function: in, In the formula, ΔT is the difference between the final reaction temperature and the initial reaction temperature in the S2 peak spectrum of the target source rock sample, in K; A0 is the frequency factor of the discrete organic matter component, in min. -1 Ea d List of activation energies obtained from the discrete initial solution; Ea dj X represents the activation energy of the j-th discrete organic matter component, where j is a positive integer ∈ [1, n], and the unit is 4185.85 J / mol; n is the number of discrete organic matter components; X fd (Ea d X represents the final content of each discrete organic matter component to be optimized; fd (Ea dj ) represents the content of the j-th discrete organic matter component; T i V(T) represents the reaction temperature of the i-th data point in the pyrolysis S2 peak spectrum of the target source rock sample, in K; N is the number of discrete data points in the pyrolysis S2 peak spectrum of the target source rock sample; V(T) i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate Rate, in mg / (g·K); γ is the penalty function coefficient, and the penalty coefficient is selected from one of [1000, 5000, 10000, 50000, 100000]. 2) Select the minimum penalty function; 3) The initial solution is determined by the content of each discrete organic matter component in the discrete solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample. The iteration stopping condition is set based on the variance of the objective function in the latest iteration number. Based on the selected penalty function, the determined initial solution and the set iteration stopping condition, the final optimized objective function is solved to determine the optimal content of each discrete organic matter component and obtain the optimal hydrocarbon generation kinetic parameters of the target source rock sample. 4) Determine the allowable error limit of the final optimization objective function, and then determine the final hydrocarbon generation kinetic parameters based on the optimal content of each discrete organic matter component obtained in step 3): ① If for a non-negative integer j, the following conditions are met: X fd ′(Ea dj If )≥0, and the final optimization objective function value is less than ∈, then the optimal hydrocarbon generation kinetic parameters of the target source rock sample obtained in step S63 are the final hydrocarbon generation kinetic parameters; where n is the number of discrete organic matter components, X fd ′(Ea dj ) represents the optimal content of the j-th discrete organic matter component; ②If for a non-negative integer j, the following conditions are met: X fd ′(Ea dj If ) < 0, then the optimal content of each discrete organic matter component is subjected to non-negation processing. If the final optimization objective function value corresponding to the non-negation processing is less than ∈, then the hydrocarbon generation kinetic parameters after non-negation processing are the final hydrocarbon generation kinetic parameters; where n is the number of discrete organic matter components, X fd ′(Ea dj ) represents the optimal content of the j-th discrete organic matter component; ③ If conditions ① and ② are not met, increase the penalty coefficient and repeat steps 3) and 4) until the final hydrocarbon generation kinetic parameters are determined.

15. The method according to claim 14, wherein, The iteration stopping condition is that the variance of the objective function value in the latest m iterations is less than 10. -2 , where the positive integer m takes values ​​in the range of [1000, 10000].

16. The method of claim 14, wherein, The final optimization objective function is solved using the quasi-Newton method, where the Hessen matrix used in the quasi-Newton method is a positive definite matrix.

17. The method of claim 14, wherein, Nonnegation is handled as follows: X fd -"(It dp )=0 In the formula, X fd+ ′(Ea dk X represents the content of the k-th discrete organic matter component with a positive content among the optimal contents of all discrete organic matter components, where k ∈ [1, nz], n is the number of discrete organic matter components, and z is the number of discrete organic matter components with negative contents among the optimal contents of all discrete organic matter components; fd -′(Ea dp Let X be the content of the p-th discrete organic matter component with a negative content among all the optimal contents of discrete organic matter components. fd+ "(Ea dk Let X be the non-negative content of the k-th discrete organic matter component with a positive content among all the optimal contents of discrete organic matter components. fd- "(Ea dp ) represents the non-negative content of the p-th discrete organic matter component with a negative content among all the optimal contents of discrete organic matter components.

18. A system for determining hydrocarbon generation kinetic parameters from source rocks, wherein, The system includes: Sample data acquisition module: used to acquire discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample; wherein, the pyrolysis S2 peak spectrum is the pyrolysis S2 peak temperature-reaction rate curve; Sample data normalization module: used to normalize the discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample to obtain normalized discrete data points. Activation energy range determination module: used to determine the distribution range of activation energy of organic matter; The continuous preliminary solution determination module is used to determine the continuous preliminary solution of the hydrocarbon generation kinetic parameters of the target source rock sample based on the distribution range of organic matter activation energy and the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample. The content of each organic matter component in the target source rock sample and its activation energy follow a normal distribution. The hydrocarbon generation kinetic parameters include the activation energy, content, and frequency factor of each organic matter component in the target source rock sample. The continuous initial solution discretization module is used to discretize the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample, and obtain the discretized solution of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample. The discretization of the continuous initial solution of the hydrocarbon generation kinetic parameters of the target source rock sample includes the activation energy of each discrete organic matter component, the content of each discrete organic matter component, and the frequency factor of the discrete organic matter component. Final hydrocarbon generation kinetic parameters determination module: used to discretize the continuous preliminary solution of hydrocarbon generation kinetic parameters of the target source rock sample, optimize the content of each organic matter component, and obtain the final hydrocarbon generation kinetic parameters of the target source rock sample; The continuous initial solution determination module includes: Activation energy normal distribution model construction submodule: used to construct the activation energy normal distribution model; The continuous initial solution determination submodule is used to determine the continuous initial solution of hydrocarbon generation kinetic parameters of the target source rock sample based on the normalized discrete data points of the pyrolysis S2 peak spectrum of the target source rock sample, using the activation energy normal distribution model, based on the distribution range of organic matter activation energy. The activation energy normal distribution model construction submodule includes: The first function building unit is used to determine the relationship between the content of each organic component in the target source rock sample and its activation energy, which follows an expected value of Ea. - A continuous normal distribution with standard deviation σ is used to determine the content of organic matter components with respect to the activation energy and expected value Ea of the organic matter components. - A function of standard deviation σ; Second function construction unit 2412: Used to construct the objective function for optimizing the initial solution. in, In the formula, ΔT is the final reaction temperature (T) in the S2 peak spectrum of the pyrolysis of the target source rock sample. end ) and initial reaction temperature (T) initial The difference between (i.e., ΔT = T) end -T initial (), unit K; A0 is the frequency factor of organic matter components, unit min. -1 N represents the number of discrete data points in the pyrolysis S2 peak spectrum of the target source rock sample; V(T) i ) represents the reaction temperature T at the i-th discrete data point. i The corresponding normalized reaction rate, in mg / (g·k); V(A0,Ea) - ,σ,T i ) represents the frequency factor A0 and expected value Ea of the organic matter component. - Standard deviation σ, reaction temperature T i The reaction rate calculated under the given conditions, in mg / (g·K); T i Ea represents the reaction temperature of the i-th data point in the pyrolysis S2 peak spectrum of the target source rock sample, in K; - σ is the expected value of the normal distribution, in units of 4185.85 J / mol; σ is the standard deviation of the normal distribution, in units of 4185.85 J / mol; R is the ideal gas constant, in units of 8.314 J / (mod·K); D is the heating rate of the thermal simulation experiment corresponding to the S2 peak spectrum of the pyrolysis of the target source rock sample, in units of K / min; The continuous initial solution determination submodule includes: Expected value range determination unit 2421: Used to determine the expected value Ea in the normal distribution model of activation energy based on the distribution range of activation energy of organic matter. - The maximum and minimum values ​​are used to determine the expected value Ea in the activation energy normal distribution model. - The range of values ​​for ; Standard deviation range determination unit: used to determine the minimum value of the standard deviation σ in the activation energy normal distribution model, and to determine the maximum value of the standard deviation σ in the activation energy normal distribution model based on the activation energy distribution range of organic matter, thereby determining the range of values ​​for the standard deviation σ in the activation energy normal distribution model; Frequency factor range determination unit: used to determine the range of values ​​for the frequency factor of organic matter components in the activation energy normal distribution model; Continuous initial solution determination unit: This unit is used to determine the expected value Ea of the normalized discrete data points based on the pyrolysis S2 peak spectrum of the target source rock sample within the activation energy normal distribution model. - Within the range of values ​​for the standard deviation σ and the frequency factor of the organic matter component, the activation energy normal distribution model is solved to determine the optimal expected value Ea. - The standard deviation σ and the frequency factor of organic matter components are used to determine the initial continuous solution of the hydrocarbon generation kinetic parameters of the target source rock sample.

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