Method for judging natural gas gathering time and gathering mode based on methane carbon isotope fractionation kinetic model

Abstract

The invention relates to a method for judging natural gas gathering time and gathering mode based on a methane carbon isotope fractionation kinetic model, which comprises the following steps: step 1, selecting low-maturity hydrocarbon source rock to carry out a thermal simulation experiment, and obtaining methane generation conversion rates and carbon isotope values at different evolution stages; 2, establishing a parallel primary reaction hydrocarbon generation kinetic model; 3, kinetic parameters generated by the 12CH4 are calculated; step 4, calculating kinetic parameters of the 13CH4; step 5, calculating the conversion rate of 12CH4 and 13CH4; and 6, determining the gathering mode and gathering time of the natural gas based on the evolution law of the methane carbon isotope value under the geological condition and the actually measured methane carbon isotope value of the gas reservoir. According to the method, the gathering mode of the natural gas in the gas reservoir can be determined according to the actually measured methane carbon isotope value in the current gas reservoir, and the specific gathering time of the natural gas in the current gas reservoir can be accurately represented.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geochemistry, specifically to a method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model. Background Technology

[0002] Currently, there is no definitive answer regarding the determination of the timing and accumulation pattern of natural gas reservoirs. The mainstream method for dating hydrocarbon reservoirs is to use the homogenized temperature of fluid inclusions combined with regional paleothermal reconstruction to determine the formation period and time. This method determines the formation period and time by analyzing the color, occurrence, location, and homogenized temperature of fluid inclusions. However, inclusions are formed during the reservoir formation period; if the reservoir is destroyed and dispersed later, this information cannot be obtained from the inclusions. Furthermore, hydrocarbons generally originate from deep strata, and their fluid temperatures are typically higher than the reservoir temperature. Therefore, the reconstructed homogenized temperature may be too high, leading to inaccurate measurements. The accumulation pattern of natural gas mainly relies on the qualitative judgment of geological elements such as source rocks, reservoirs, caprocks and tectonic movements. However, the natural gas generation window is relatively wide, including both early kerogen degradation gas and late crude oil cracking gas. At the same time, compared with crude oil, natural gas is more susceptible to damage and loss. Qualitative analysis from a geological perspective lacks direct evidence to indicate the generation time and accumulation pattern of natural gas in current gas reservoirs. A new method is urgently needed to quantitatively indicate the accumulation time and accumulation pattern of natural gas in gas reservoirs.

[0003] Due to the simple composition of natural gas, many important genetic information, such as the properties and thermal maturity of natural gas and its potential source rocks, migration paths, mixed-source gas, and the history of gas reservoir accumulation and loss, must be studied using its isotopic ratios. Generally speaking, the carbon isotopic composition of soluble organic matter in source rocks is closely related to its parent material source and sedimentary environment, and directly affects the carbon isotopic composition characteristics of the generated oil and gas. The carbon isotopes of the same type of organic matter will change to a certain extent during the thermal evolution of organic matter due to fractionation. With the increase of maturity, the carbon isotopic fractionation of natural gas components becomes more obvious. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention utilizes chemical kinetics to provide a method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model.

[0005] Terminology Explanation: 1. 12 CH4 13 CH4: In nature, carbon has two stable isotopes: 12C and 13C. 12 CH4 is 12-carbon methane. 13 CH4 is 13-carbon methane.

[0006] 2. Thermal simulation experiment: This is a commonly used experiment to study the characteristics of organic matter generating petroleum and natural gas. The specific operation involves selecting low-maturity organic matter and placing it in a reaction vessel. The sample is heated to a certain temperature at a certain heating rate to accelerate the generation of petroleum and natural gas from organic matter, thereby exploring the characteristics of organic matter generating oil and gas.

[0007] The technical solution of this invention is as follows: A method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model includes: Step 1: Select low-maturity source rocks to conduct thermal simulation experiments and obtain methane generation conversion rate and carbon isotope values ​​at different evolution stages; Step 2: Based on the Arrhenius equation, establish a parallel first-order reaction hydrocarbon generation kinetic model; Step 3: Based on experimental data, kinetic parameters for methane formation are calibrated using a parallel first-order reaction hydrocarbon generation kinetic model, which will serve as the basis for further analysis. 12 kinetic parameters of CH4 generation; Step 4: Based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 kinetic parameters of CH4; Step 5: 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; Step 6: Based on geological conditions 12 CH4 and 13 The evolution of CH4 was studied, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined.

[0008] Furthermore, in step 1, the low-maturity source rock serves as the source of hydrocarbon generation material for the natural gas reservoir.

[0009] Furthermore, in step 1, the thermal simulation experiment is a closed-system experiment.

[0010] Furthermore, in step 2, a parallel first-order reaction hydrocarbon generation kinetic model is established based on the Arrhenius equation; including: The parallel first-order reaction hydrocarbon generation kinetic model assumes that the hydrocarbon generation process from organic matter involves a series of parallel first-order reactions, with each parallel first-order reaction corresponding to an activation energy of E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X.i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i Then we have equation (I): ;

[0011] In the formula, K i Let be the rate constant of the i-th kerogen hydrocarbon generation reaction. According to the Arrhenius formula, equation (II) is obtained: ;

[0012] In the formula, R is the gas constant, and T is the absolute temperature in K; Since the organic matter pyrolysis experiment under laboratory conditions uses a constant heating rate, assuming the heating rate is D, we obtain equation (III): ;

[0013] Combining the above formulas, we can obtain the hydrocarbon generation amount of the i-th reaction. As shown in equation (IV); ;

[0014] Total hydrocarbon generation from N parallel reactions As shown in equations (V) and (VI): ;

[0015] (VI); The parallel first-order reaction hydrocarbon generation kinetic model is shown in Equation (V). In Equations (V) and (VI), N represents the number of parallel reactions, and the activation energy for each reaction is E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X. i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i .

[0016] According to a preferred embodiment of the present invention, in step 3, based on experimental data, the kinetic parameters of methane generation are calibrated using a parallel first-order reaction hydrocarbon generation kinetic model, and used as... 12 The kinetic parameters of CH4 generation include: The kinetic parameters of methane formation in the thermal simulation experiment were calibrated using a parallel first-order reaction hydrocarbon generation kinetic model. E , A, X ), and ( E , A, X As 12 kinetic parameters of CH4; E ,A These refer to the activation energy and pre-exponential factor, respectively; X is the proportion of a particular reaction in a parallel reaction to the total number of reactions, also known as the reaction fraction. Suppose that under certain isothermal experimental conditions, the methane conversion rate measured in the experiment is [value missing]. X1 Ɩj Under the same conditions, set the activation energy for the formation of 12C methane from organic matter in the i-th parallel reaction. E （12C）i Pre-exponential factors A （12C）i and reaction fraction X （12C）i0 Subsequently, the hydrocarbon conversion rate calculated by the parallel first-order reaction hydrocarbon generation kinetic model was... X Ɩj Then construct the objective function. As shown in equation (VII): (VII); In the formula, L Number of experimental groups; J This represents the number of sampling points from an experimental curve. E （12C）i The activation energy is determined by selecting the distribution range of the activation energy and the activation energy interval between adjacent parallel reactions. A （12C）i and X （12C）i0 Then an optimization algorithm is needed to solve it; the details are as follows: in addition, A （12C）i and X （12C）i0 Satisfaction Equation (VIII): (VIII); in, It is a small positive number; For any constraint, a penalty function is constructed. When the obtained extreme point satisfies the constraint, the function value is 0; otherwise, it is a positive number, as shown in equations (IX), (X), and (XI): (IX); (X); (XI); This yields the penalty item. G : , Choose a sufficiently large positive integer R1 , by objective function and penalty itemsG Construct penalty function As shown in equation (XII): (XII); The constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, i.e., the first-order partial derivative of the objective function is 0, as shown in equation (XIII): (XIII); in: , When i ≠ m, the partial derivative is 0, and at this time we have: , , Similarly, taking the partial derivative with respect to the penalty term, we get: (XIV); (XV); Here FN The symbol for the expression inside the parentheses is: (XVI); In theory, the minimum point should have: (XVII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to determine the direction of function value descent at any point, performing a one-dimensional search until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the parallel first-order reaction hydrocarbon generation kinetic model; thus... 12 CH4 generated A （12C） and X （12C） Calibration complete.

[0017] According to a preferred embodiment of the present invention, in step 4, based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 The kinetic parameters of CH4 include: First, construct the objective function, assuming that the carbon isotope value of methane measured in the experiment is obtained when heated to a certain time under certain isothermal experimental conditions. Y1 Ɩj Under the same conditions, set 13 CH4 E i , A i , X i0 Then, the calculated carbon isotope values Y ƖjThen, the objective function is constructed as shown in equation (XVIII): (XVIII); in, Y Ɩj , Z =( f ( / 1000+1)×1123.72, f X represents the final carbon isotope value of methane in the pyrolysis products; Z represents the total potential ratio, and X represents the total potential ratio. 13C for 13 CH4 conversion rate; A （13C）i and X （13C）i0 Satisfaction formula (XIX): (XIX); For any constraint, a penalty function is constructed such that when the obtained extreme point satisfies the constraint, the function value is 0, otherwise it is a positive number, as shown in equations (XX), (XXI), and (XXII): (XX); (XXI); (XXII); This yields the penalty item. : , Choose a sufficiently large positive integer R1 , by objective function and penalty items Construct penalty function : (XXIII); The constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, i.e., the first-order partial derivative of the objective function is 0, as shown in equation (XXIV): (XXIV); in: , , When i ≠ m, the partial derivative is 0, and at this time we have , Similarly, taking the partial derivative with respect to the penalty term, we get: (XXV); (XXVI); Here FN The symbol for the expression inside the parentheses is: (XXVII); In theory, the minimum point should have: (XXVIII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to find the direction of function value descent at any point, and a one-dimensional search is performed until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the chemical kinetic model.

[0018] According to a preferred embodiment of the present invention, in step 5, the... 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; including: according to 13 CH4 and 12 By combining the kinetic parameters of CH4 with the burial history, thermal history, and total potential ratio of the study area, the geological conditions of the area at any given geological period can be obtained. 13 CH4 and 12 The amount of CH4 generated will be compared to the same geological period. 13 CH4 and 12 The amount of CH4 generated is calculated using the methane carbon isotope formula, thus yielding the methane carbon isotope value for any geological period. X As shown in equation (XXIX): X =( Z ×(13C) / (12C) / 1123.72-1)×1000 (XXIX); Calculation of chemical reaction kinetics under geological conditions based on the principle of organic matter thermal evolution 12 CH4 and 13 CH4 conversion rate.

[0019] According to a preferred embodiment of the present invention, in step 6, based on geological conditions... 12 CH4 and 13 The evolution of CH4 was analyzed, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined; including: The resulting geological conditions 12 CH4 and 13The evolution of CH4 was compared with the measured methane carbon isotope values ​​of the natural gas reservoirs in the study area under geological conditions. 12 CH4 and 13 The evolutionary law of CH4 refers to 12 CH4 and 13 The evolution of CH4 conversion rate on geological timescales; the geological time corresponding to the measured methane carbon isotope value evolution curve under geological conditions is used to determine the natural gas accumulation pattern. If the corresponding geological time is earlier, that is, the corresponding geological time is in the first half of the organic matter thermal evolution history, that is, the first 50% of the geological time, it indicates that the natural gas is in an early accumulation mode and the natural gas did not accumulate in the later stage; otherwise, it indicates that the natural gas is in a cumulative accumulation mode, and the natural gas continuously injects into the reservoir to form a reservoir after its generation.

[0020] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the above-described method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model.

[0021] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model.

[0022] The beneficial effects of this invention are as follows: This invention can determine the accumulation pattern of natural gas in a gas reservoir based on the measured carbon isotope values ​​of methane in the reservoir. It can accurately characterize the specific time of natural gas accumulation in the reservoir. Traditional methods only reflect the preservation conditions of the strata from the perspective of geological element analysis. If the preservation conditions are good, the natural gas is considered to be "accumulated accumulation type", and if the conditions are poor, it is considered to be "early accumulation type". This method is more inclined to qualitative analysis and does not have intuitive data to prove it. Attached Figure Description

[0023] Figure 1 This is a flowchart of the method for determining the accumulation time and accumulation mode of natural gas based on the methane carbon isotope fractionation kinetics model of the present invention; Figure 2 For the purposes of this invention 13 CH4 and 12 Schematic diagram of the kinetic parameters of CH4 generation; Figure 3 This is a schematic diagram showing the application results of the present invention in a certain work area; Figure 4 This is a schematic diagram showing the application results of the present invention in a certain work area. Detailed Implementation

[0024] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0025] Example 1 A method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model, such as... Figure 1 As shown, it includes: Step 1: Select low-maturity source rocks to conduct thermal simulation experiments and obtain methane generation conversion rate and carbon isotope values ​​at different evolution stages; Step 2: Based on the Arrhenius equation, establish a parallel first-order reaction hydrocarbon generation kinetic model; the methane carbon isotope fractionation model is established on the basis of the parallel first-order reaction model. Specifically, the parallel first-order reaction model is first used to evaluate methane generation, and then the isotope fractionation kinetics is used to further separate methane into 12C methane and 13C methane.

[0026] Step 3: Based on experimental data, kinetic parameters for methane formation are calibrated using a parallel first-order reaction hydrocarbon generation kinetic model, which will serve as the basis for further analysis. 12 kinetic parameters of CH4 generation; Step 4: Based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 kinetic parameters of CH4; Step 5: 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; Step 6: Based on geological conditions 12 CH4 and 13 The evolution of CH4 was studied, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined.

[0027] Example 2 The method for determining the accumulation time and accumulation mode of natural gas based on the methane carbon isotope fractionation kinetic model described in Example 1 differs in that: In step 1, low-maturity source rocks serve as the source of hydrocarbon generation material for natural gas reservoirs.

[0028] In step 1, the thermal simulation experiment is a closed-system experiment. The thermal simulation experiment used is a closed-system gold tube thermal simulation experiment, which is an existing and mature experiment in the industry.

[0029] Since methane accounts for the majority of natural gas reservoirs and its formation occurs throughout the entire reservoir formation process, methane was selected as the calibration target. In step 1, the conversion rate and carbon isotope value of methane formation were detected.

[0030] In step 2, a parallel first-order reaction hydrocarbon generation kinetic model is established based on the Arrhenius equation; including: The parallel first-order reaction hydrocarbon generation kinetic model assumes that the hydrocarbon generation process from organic matter consists of a series (N) of parallel first-order reactions, with each parallel first-order reaction corresponding to an activation energy of E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X. i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i Then we have equation (I): ;

[0031] In the formula, K i Let be the rate constant of the i-th kerogen hydrocarbon generation reaction. According to the Arrhenius formula, equation (II) is obtained: ;

[0032] In the formula, R is the gas constant, 8.31447 kJ·mol⁻¹ -1 ·K -1 T represents absolute temperature, expressed in K. Since the organic matter pyrolysis experiment under laboratory conditions uses a constant heating rate, assuming the heating rate is D, we obtain equation (III): ;

[0033] Combining the above formulas, we can obtain the hydrocarbon generation amount of the i-th reaction. As shown in equation (IV); ;

[0034] Total hydrocarbon generation from N parallel reactions As shown in equations (V) and (VI): ;

[0035] (VI); The parallel first-order reaction hydrocarbon generation kinetic model is shown in Equation (V). In Equations (V) and (VI), N represents the number of parallel reactions, and the activation energy for each reaction is E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X.i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i .

[0036] In step 3, based on experimental data, a closed-system gold tube thermal simulation experiment was conducted. Specifically, the experimental data included the methane production at different temperature points. The kinetic parameters of methane production were calibrated using a parallel first-order reaction hydrocarbon generation kinetic model. 12 Kinetic parameters of CH4 generation; such as Figure 2 As shown, it includes: The kinetic parameters of methane formation in the thermal simulation experiment were calibrated using a parallel first-order reaction hydrocarbon generation kinetic model. E , A, X ), and ( E , A, X As 12 kinetic parameters of CH4; E , A These refer to the activation energy and pre-exponential factor, respectively; X represents the proportion of a single reaction in a parallel reaction, also known as the reaction fraction; in geochemistry, it's called the "reaction fraction." In petroleum and gas geology theory, oil and natural gas are considered to be generated from organic matter through heating. Since organic matter is a mixture, the formation of petroleum and gas involves many reactions. To address this, parallel first-order reactions were developed, decomposing the reaction of organic matter into several reactions with different activation energies. This is because... 12 CH4 makes up the majority of methane, so the conversion rate of methane in the experiment can be approximated as... 12 CH4 conversion rate.

[0037] Suppose that under certain isothermal experimental conditions, the methane conversion rate measured in the experiment is [value missing]. X1 Ɩj Under the same conditions, set the activation energy for the formation of 12C methane from organic matter in the i-th parallel reaction. E （12C）i Pre-exponential factors A （12C）i and reaction fraction X （12C）i0 Subsequently, the hydrocarbon conversion rate calculated by the parallel first-order reaction hydrocarbon generation kinetic model was... X Ɩj Then construct the objective function. As shown in equation (VII): (VII); In the formula, L Number of experimental groups; J This represents the number of sampling points from an experimental curve. E（12C）i The activation energy is determined by selecting the distribution range of the activation energy and the activation energy interval between adjacent parallel reactions. A （12C）i and X （12C）i0 Then an optimization algorithm is needed to solve it; the details are as follows: E （12C）i Typically, an equally spaced distribution is used. In this invention, the upper and lower limits of activation energy are 340 kJ / mol and 150 kJ / mol, respectively, with an interval of 10 kJ / mol, for a total of 20 parallel reactions.

[0038] in addition, A （12C）i and X （12C）i0 (Expressed as a percentage of the total reactive quantity) Satisfies equation (VIII): (VIII); in, It is a small positive number; it is an extremely small natural number, infinitely close to 0; Therefore, the problem of obtaining the dynamic parameters in the model is transformed into finding the minimum point of the non-negative objective function when the constraints are satisfied. For any constraint, a penalty function is constructed. When the obtained extreme point satisfies the constraint, the function value is 0; otherwise, it is positive, as shown in equations (IX), (X), and (XI):

[0039] (IX); (X); (XI); This yields the penalty item. G : , Choose a sufficiently large positive integer R1 , by objective function and penalty items G Construct penalty function As shown in equation (XII): (XII); If the desired minimum point exceeds the constraints, then make R1 Gradually increase, when R1 When the value is infinitely large, the minimum solution of the penalty function is the minimum solution of the objective function. Therefore, the constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, that is, the first-order partial derivative of the objective function is 0, as shown in equation (XIII): (XIII); in: , When i ≠ m, the partial derivative is 0, and at this time we have: , , Similarly, taking the partial derivative with respect to the penalty term, we get: (XIV); (XV); Here FN The symbol for the expression inside the parentheses is: (XVI); In theory, the minimum point should have: (XVII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to determine the direction of function value descent at any point, performing a one-dimensional search until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the parallel first-order reaction hydrocarbon generation kinetic model; thus... 12 CH4 generated A （12C） and X （12C） Calibration complete.

[0040] Because of the two isotopes of methane, 12 CH4 accounted for 98.9%. 13 CH4 accounts for only 1.1%, therefore, in step 3, the kinetic parameters of the methane formation reaction in the experiment are approximated as... 12 kinetic parameters generated by CH4.

[0041] In step 4, based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 The kinetic parameters of CH4 include: First, construct the objective function, assuming that the carbon isotope value of methane measured in the experiment is obtained when heated to a certain time under certain isothermal experimental conditions. Y1 Ɩj Under the same conditions, set 13 CH4 E i , A i , X i0 Then, the calculated carbon isotope values Y Ɩj Then, the objective function is constructed as shown in equation (XVIII): (XVIII); in, Y Ɩj , Z =( f ( / 1000+1)×1123.72, f X represents the final carbon isotope value of methane in the pyrolysis products; Z represents the total potential ratio, and X represents the total potential ratio. 13C for 13 CH4 conversion rate; Obtaining the evolution of methane carbon isotope values ​​requires calculations of different geological periods. 13 CH4 and 12 The amount of CH4 generated, while step 5 calculates the amount generated in different geological periods. 13 CH4 and 12 The conversion rate of CH4 generation therefore needs to be considered in relation to the total potential (Z), i.e. 13 CH4 and 12 The ratio of the total amount of CH4 ultimately produced is obtained by converting the carbon isotope values ​​of methane in the final pyrolysis products. This allows for the comparison of different geological periods. 13 CH4 and 12 The ratio of CH4 conversion rates is converted into the ratio of production rates; Similarly, A （13C）i and X （13C）i0 (Expressed as a percentage of total reactive matter) It should satisfy equation (XIX): (XIX); Therefore, the problem of obtaining the dynamic parameters in the model is transformed into finding the minimum point of the non-negative objective function when the constraints are satisfied. For any constraint, a penalty function is constructed such that the function value is 0 when the obtained extreme point satisfies the constraint, and positive otherwise, as shown in equations (XX), (XXI), and (XXII):

[0042] (XX); (XXI); (XXII); This yields the penalty item. : , Choose a sufficiently large positive integer R1 , by objective function and penalty items Construct penalty function : (XXIII); If the desired minimum point exceeds the constraints, then make R1 Gradually increase, when R1 When the value is infinitely large, the minimum solution of the penalty function is the minimum solution of the objective function. Therefore, the constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, that is, the first-order partial derivative of the objective function is 0, as shown in equation (XXIV): (XXIV); in: , , When i ≠ m, the partial derivative is 0, and at this time we have , Similarly, taking the partial derivative with respect to the penalty term, we get: (XXV); (XXVI); Here FN The symbol for the expression inside the parentheses is: (XXVII); In theory, the minimum point should have: (XXVIII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to find the direction of function value descent at any point, and a one-dimensional search is performed until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the chemical kinetic model.

[0043] Let's define an objective function Q1, where Q1 is the difference between the experimental and calculated values ​​of methane carbon isotopes. A smaller Q1 value indicates higher calculation accuracy. The calculated values ​​of methane carbon isotopes are derived from... 12 CH4 and 13 CH4 is calculated using the carbon isotope value formula, which has already been obtained using parallel first-order reactions as described above. 12 The dynamic parameters of CH4 are therefore continuously adjusted using a variable-scale optimization algorithm while satisfying the above constraints. 13 The kinetic parameters of CH4 are calculated until the Q value is sufficiently small (less than a preset value), at which point the kinetic parameters are considered to be... 13 The dynamic parameters generated by CH4 can be optimized using the same variable-scale optimization algorithm, which is also a mature and readily available method.

[0044] At this point, 13 CH4 and 12 The kinetic parameters of CH4 have been obtained.

[0045] Carbon isotope values ​​are from 12 CH4 and 13 CH4 is calculated together, therefore in step 4, it can be based on 12 CH4 kinetic parameters and experimentally obtained methane carbon isotope values ​​were obtained. 13 Kinetic parameters of CH4.

[0046] In step 5, 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; including: Thermal simulation experiments follow the principle of "time-temperature complementarity," based on... 13 CH4 and 12 By combining the kinetic parameters of CH4 with the burial history, thermal history, and total potential ratio of the study area, the geological conditions of the area at any given geological period can be obtained. 13 CH4 and 12 The amount of CH4 generated will be compared to the same geological period. 13 CH4 and 12 The amount of CH4 generated is calculated using the methane carbon isotope formula, thus yielding the methane carbon isotope value for any geological period. X As shown in equation (XXIX): X =( Z ×(13C) / (12C) / 1123.72-1)×1000 (XXIX); Calculation of chemical reaction kinetics under geological conditions based on the principle of organic matter thermal evolution 12 CH4 and 13 CH4 conversion rate.

[0047] Since the thermal simulation experiment follows the principle of "time-temperature complementarity", in step 5, the evolution law of methane carbon isotope values ​​under laboratory conditions can be extrapolated to geological conditions by studying the burial history and thermal history of the strata in the work area. Obtaining the evolution of methane carbon isotope values ​​requires calculations of different geological periods. 12 CH4 and 13 The amount of CH4 generated, while step 5 calculates the amount generated in different geological periods. 12 CH4 and 13 The conversion rate of CH4 therefore needs to be considered in terms of the total potential (Z), i.e. 13 CH4 and 12 The ratio of the total amount of CH4 ultimately produced is obtained by converting the carbon isotope values ​​of methane in the final pyrolysis products. This allows for the comparison of different geological periods. 13 CH4 and 12The ratio of CH4 conversion rates is converted into the ratio of production rates; In step 6, based on geological conditions 12 CH4 and 13 The evolution of CH4 was analyzed, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined; including: The resulting geological conditions 12 CH4 and 13 The evolutionary pattern of CH4 was compared with the measured methane carbon isotope values ​​of natural gas reservoirs in the study area (obtained by sampling and testing existing underground natural gas reservoirs), under geological conditions. 12 CH4 and 13 The evolutionary law of CH4 refers to 12 CH4 and 13 The evolution of CH4 conversion rate over geological timescales; the evolution curve of methane carbon isotope values ​​under geological conditions obtained from the above (derived from the above). 12 CH4 and 13 The conversion rate of CH4 in different geological periods is calculated according to the formula. X =( Z The evolution curve of methane carbon isotope values ​​(×(13C) / (12C) / 1123.72-1)×1000 can be used to determine the geological time corresponding to the curve and judge the natural gas accumulation pattern. If the corresponding geological time is earlier, that is, the corresponding geological time is in the first half of the organic matter thermal evolution history, that is, the first 50% of the geological time, it indicates that the natural gas is in an early accumulation mode and the natural gas did not accumulate in the later stage; otherwise, it indicates that the natural gas is in a cumulative accumulation mode, and the natural gas continuously injects into the reservoir to form a reservoir after its generation.

[0048] Figure 3 This is a schematic diagram of the application results of the present invention in a certain work area. The application results show that the measured carbon isotope value of methane in the natural gas reservoir in this work area corresponds to a geological age of 0.4 Ma under geological conditions. This indicates that the natural gas accumulated in the reservoir is a product from the beginning of natural gas generation to 0.4 Ma, which is a typical cumulative accumulation model.

[0049] Figure 4 This is a schematic diagram of the application results of the present invention in a certain work area. The application results show that the measured carbon isotope value of methane in the natural gas reservoir in this work area corresponds to a geological age of 8 Ma under geological conditions. This indicates that the natural gas accumulated in the reservoir is a product from the beginning of natural gas generation to 8 Ma, which is a typical early accumulation mode.

[0050] Example 3 A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model as described in Embodiment 1 or 2.

[0051] Example 4 A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model as described in Embodiment 1 or 2.

Claims

1. A method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model, characterized in that, include: Step 1: Select low-maturity source rocks to conduct thermal simulation experiments and obtain methane generation conversion rate and carbon isotope values ​​at different evolution stages; Step 2: Based on the Arrhenius equation, establish a parallel first-order reaction hydrocarbon generation kinetic model; Step 3: Based on experimental data, kinetic parameters for methane formation are calibrated using a parallel first-order reaction hydrocarbon generation kinetic model, which will serve as the basis for further analysis. 12 kinetic parameters of CH4 generation; Step 4: Based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 kinetic parameters of CH4; Step 5: 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; Step 6: Based on geological conditions 12 CH4 and 13 The evolution of CH4 was studied, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined.

2. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 1, low-maturity source rocks serve as the source of hydrocarbon generation material for natural gas reservoirs.

3. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 1, the thermal simulation experiment is a closed-system experiment.

4. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 2, a parallel first-order reaction hydrocarbon generation kinetic model is established based on the Arrhenius equation; including: The parallel first-order reaction hydrocarbon generation kinetic model assumes that the hydrocarbon generation process from organic matter involves a series of parallel first-order reactions, with each parallel first-order reaction corresponding to an activation energy of E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X. i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i Then we have equation (I): ; In the formula, K i Let be the rate constant of the i-th kerogen hydrocarbon generation reaction. According to the Arrhenius formula, equation (II) is obtained: ; In the formula, R is the gas constant, and T is the absolute temperature in K; Since the organic matter pyrolysis experiment under laboratory conditions uses a constant heating rate, assuming the heating rate is D, we obtain equation (III): ; Combining the above formulas, we can obtain the amount of hydrocarbons generated in the i-th reaction. As shown in equation (IV); ; Total hydrocarbon generation from N parallel reactions As shown in equations (V) and (VI): ; (WE); The parallel first-order reaction hydrocarbon generation kinetic model is shown in Equation (V). In Equations (V) and (VI), N represents the number of parallel reactions, and the activation energy for each reaction is E. i The pre-exponential factor is A i And assume that the initial hydrocarbon generation potential of organic matter corresponding to each reaction is X. i0 Let i = 1, 2, 3, …..N, and at a certain reaction time t, the amount of hydrocarbons generated by the i-th reaction is X. i .

5. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 3, based on experimental data, the kinetic parameters of methane formation are calibrated using a parallel first-order reaction hydrocarbon generation kinetic model, and used as... 12 kinetic parameters of CH4 generation; include: The kinetic parameters of methane formation in the thermal simulation experiment were calibrated using a parallel first-order reaction hydrocarbon generation kinetic model. E , A、 X ), and ( E , A, X As 12 kinetic parameters of CH4; E , A These refer to the activation energy and pre-exponential factor, respectively; X is the proportion of a particular reaction in a parallel reaction to the total number of reactions, also known as the reaction fraction. Suppose that under certain isothermal experimental conditions, the methane conversion rate measured in the experiment is [value missing]. X1 Ɩj Under the same conditions, set the activation energy for the formation of 12C methane from organic matter in the i-th parallel reaction. E （12C）i Pre-exponential factors A （12C）i and reaction fraction X （12C）i0 Subsequently, the hydrocarbon conversion rate calculated by the parallel first-order reaction hydrocarbon generation kinetic model was... X Ɩj Then construct the objective function. As shown in equation (VII): (VII); In the formula, L Number of experimental groups; J This represents the number of sampling points from an experimental curve. E （12C）i The activation energy is determined by selecting the distribution range of the activation energy and the activation energy interval between adjacent parallel reactions. A （12C）i and X （12C）i0 Then an optimization algorithm is needed to solve it; the details are as follows: in addition, A （12C）i and X （12C）i0 Satisfaction Equation (VIII): (VIII); in, It is a small positive number; For any constraint, a penalty function is constructed. When the obtained extreme point satisfies the constraint, the function value is 0; otherwise, it is a positive number, as shown in equations (IX), (X), and (XI): (IX); （X）； (XI); This yields the penalty item. G : ， Choose a sufficiently large positive integer R1 , by objective function and penalty items G Construct penalty function As shown in equation (XII): (XII); The constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, i.e., the first-order partial derivative of the objective function is 0, as shown in equation (XIII): (XIII); in: , When i ≠ m, the partial derivative is 0, and at this time we have: ， ， Similarly, taking the partial derivative with respect to the penalty term, we get: (XIV); (XV); Here FN The symbol for the expression inside the parentheses is: (XVI); In theory, the minimum point should have: (XVII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to determine the direction of function value descent at any point, performing a one-dimensional search until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the parallel first-order reaction hydrocarbon generation kinetic model; thus... 12 CH4 generated A （12C） and X （12C） Calibration complete.

6. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 4, based on carbon isotope values ​​and 12 The kinetic parameters of CH4 generation were calculated. 13 The kinetic parameters of CH4 include: First, construct the objective function, assuming that the measured carbon isotope value of methane is obtained when heated to a certain time under certain isothermal experimental conditions. Y1 Ɩj Under the same conditions, set 13 CH4 E i , A i , X i0 Then, the calculated carbon isotope values Y Ɩj Then, the objective function is constructed as shown in equation (XVIII): (XVIII); in, Y Ɩj , Z =( f ( / 1000+1)×1123.72, f X represents the final carbon isotope value of methane in the pyrolysis products; Z represents the total potential ratio, and X represents the total potential ratio. 13C for 13 CH4 conversion rate; A （13C）i and X （13C）i0 Satisfaction formula (XIX): (XIX); For any constraint, a penalty function is constructed such that when the obtained extreme point satisfies the constraint, the function value is 0, otherwise it is a positive number, as shown in equations (XX), (XXI), and (XXII): (XX); (XXI); (XXII); This yields the penalty item. : ， Choose a sufficiently large positive integer R1 , by objective function and penalty items Construct penalty function : (XXIII); The constrained extremum problem is transformed into an easily solvable unconstrained extremum problem, i.e., the first-order partial derivative of the objective function is 0, as shown in equation (XXIV): (XXIV); in: , ， When i ≠ m, the partial derivative is 0, and at this time we have ， Similarly, taking the partial derivative with respect to the penalty term, we get: (XXV); (XXVI); Here FN The symbol for the expression inside the parentheses is: (XXVII); In theory, the minimum point should have: (XXVIII); For solving unconstrained extremum problems, a variable-scale optimization algorithm is used to find the direction of function value descent at any point, and a one-dimensional search is performed until an approximate minimum point that meets the accuracy requirements is obtained, thereby calibrating the chemical kinetic model.

7. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 5, 12 The kinetic parameters of CH4 generation and 13 The kinetic parameters of CH4, combined with the burial history and thermal history of the target work area, were used to calculate the geological conditions. 12 CH4 and 13 CH4 conversion rate; include: according to 13 CH4 and 12 By combining the kinetic parameters of CH4 with the burial history, thermal history, and total potential ratio of the study area, the geological conditions of the area at any given geological period can be obtained. 13 CH4 and 12 The amount of CH4 generated will be compared to the same geological period. 13 CH4 and 12 The amount of CH4 generated is calculated using the methane carbon isotope formula, thus yielding the methane carbon isotope value for any geological period. X As shown in equation (XXIX): X =( Z ×(13C) / (12C) / 1123.72-1)×1000(XXIX); Calculation of chemical reaction kinetics under geological conditions based on the principle of organic matter thermal evolution 12 CH4 and 13 CH4 conversion rate.

8. The method for determining the accumulation time and accumulation mode of natural gas based on a methane carbon isotope fractionation kinetic model according to claim 1, characterized in that, In step 6, based on geological conditions 12 CH4 and 13 The evolution of CH4 was studied, and the evolution of methane carbon isotope values ​​under geological conditions was calculated. Based on the evolution of methane carbon isotope values ​​under geological conditions and the measured methane carbon isotope values ​​of gas reservoirs, the accumulation mode and accumulation time of natural gas were determined. include: The resulting geological conditions 12 CH4 and 13 The evolution of CH4 was compared with the measured methane carbon isotope values ​​of the natural gas reservoirs in the study area under geological conditions. 12 CH4 and 13 The evolutionary law of CH4 refers to 12 CH4 and 13 The evolution of CH4 conversion rate on geological timescales; the geological time corresponding to the measured methane carbon isotope value evolution curve under geological conditions is used to determine the natural gas accumulation pattern. If the corresponding geological time is earlier, that is, the corresponding geological time is in the first half of the organic matter thermal evolution history, that is, the first 50% of the geological time, it indicates that the natural gas is in an early accumulation mode and the natural gas did not accumulate in the later stage; otherwise, it indicates that the natural gas is in a cumulative accumulation mode, and the natural gas continuously injects into the reservoir to form a reservoir after its generation.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for determining the accumulation time and accumulation mode of natural gas based on the methane carbon isotope fractionation kinetic model as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for determining the accumulation time and accumulation mode of natural gas based on the methane carbon isotope fractionation kinetic model as described in any one of claims 1-8.

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