Numerical simulation method and system suitable for influence of clay minerals in continental facies shale on brittleness

Abstract

The invention discloses a numerical simulation method and system suitable for the influence of clay minerals in continental facies shale on brittleness, and belongs to the technical field of rock mechanical property research. In the digital rock core stress simulation process, a method for adjusting the number, coordinates, mechanical properties and boundary conditions of pixel points is adopted, the geological component content and distribution, the clay mineral type and changes caused along with deep burying in the clay mineral evolution process are simulated, and then the influence coefficient of each factor on the brittleness is determined. According to the method, the defect that a single factor of a natural sample is uncontrollable can be overcome, the three-dimensional digital core model is adjusted by adopting a dual verification method, and the authenticity and reliability of a simulation result are improved; meanwhile, the influence coefficient of each factor on the brittleness is integrated with the correlation and importance of each factor on the brittleness, and the deviation caused by a single index is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of rock mechanical property research, and more specifically to a numerical simulation method and system suitable for the influence of clay minerals on brittleness in continental shale. Background Art

[0002] China's shale oil is mostly developed in continental sedimentary environments. It is an important resource for achieving large-scale growth in oil and gas reserves and production. It is widely distributed in the Songliao, Bohai Bay, northern Jiangsu, Jianghan, Sichuan, Ordos, Junggar, Santanghu, Qaidam and other basins. Taking the Qingshankou Formation of the Upper Cretaceous in the Songliao Basin as an example (Gulong shale oil), the resource volume can reach 181.61×108t, with considerable prospects. However, China's continental shales have distinct characteristics in reservoir, oil content, fluidity and compressibility. There is no precedent for large-scale commercial development in the world, and the mature geological theory and engineering technology of marine shales are difficult to directly apply.

[0003] In terms of compressibility, brittleness is the key to achieving high production of shale through fracturing. After fracturing, high-brittle rock formations are prone to form complex network fractures, which can connect reservoirs over a large area and thus increase production; while low-brittle rock formations can only form simple double-wing fractures. North American exploration practices also show that the brittleness of shale oil zones that achieve commercial production after fracturing is relatively high, and the clay mineral content is generally less than 30%. It can be seen that clay minerals are closely related to the brittleness of shale, which in turn affects the production capacity of shale after fracturing.

[0004] However, the clay mineral content of China's continental shales is generally higher than the risk value of shale fracturing in North America, and whether brittleness can allow shale to achieve high yields after fracturing remains to be explored. The solution to this practical problem involves a key aspect: "Biogenic quartz in marine shales is conducive to the development of brittleness" has been widely recognized, but there is no consensus on "the evolution of clay minerals in continental shales can enhance brittleness." The evolution of clay minerals is accompanied by changes such as type transformation, quartz precipitation, pore development, and increased confining pressure. Whether these factors affect the brittleness of shale, which factor plays a dominant role, and what the fracturing effect is, there is no mature experience to learn from.

[0005] Therefore, it is a key issue that needs to be urgently solved in engineering to propose a numerical simulation method and system suitable for the effect of clay minerals on brittleness in continental shales and to study the influence mechanism of clay mineral development and evolution on shale brittleness. Summary of the invention

[0006] In view of this, the present invention provides a numerical simulation method and system suitable for the influence of clay minerals on brittleness in continental shale. Through digital core stress simulation, the uncontrollable defect of a single factor in natural samples is compensated, and a single parameter adjustment is performed on the relevant variables in the evolution process of clay minerals, the mechanical properties and fracture effects of shale are simulated, and a single control factor analysis of brittleness is performed.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] In one aspect, the present invention discloses a numerical simulation method applicable to the effect of clay minerals on brittleness in continental shale, comprising the following steps:

[0009] Perform pixel processing on CT images of drilling core samples in shale oil exploration areas to establish a three-dimensional digital core model;

[0010] Preliminarily adjusting the three-dimensional digital core model based on the pixel content of different media in the CT image; and secondarily adjusting the three-dimensional digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments;

[0011] Determine a digital core characterization unit body according to the adjustment process of the primary adjustment and the secondary adjustment;

[0012] Performing single factor simulation in the digital core characterization unit, the single factor including geological component content, geological component distribution, clay mineral type and associated burial depth;

[0013] Based on the single factor simulation results, the analysis is performed to calculate the influence coefficient of each factor on brittleness, and the degree of influence of each factor on brittleness is determined based on the coefficient.

[0014] Preferably, pixel processing is performed on the CT image of the drilling core sample in the shale oil exploration area to establish a three-dimensional digital core model, including:

[0015] S11. Perform gray value optimization processing, threshold region segmentation processing, and median filtering processing on the CT image in sequence to obtain an image to be processed;

[0016] S12. Distinguishing pixels of different media on the image to be processed, and extracting pixel coordinates of each medium;

[0017] S13. According to the medium corresponding to each pixel point, initial mechanical parameters are assigned to the pixel point, and a three-dimensional digital core model is constructed.

[0018] Preferably, the three-dimensional digital core model is initially adjusted, including:

[0019] The pixel content of different media in the three-dimensional digital core model is queried, and compared with the pixel content of different media in the CT image. According to the pixel content comparison result, whether the model pixel of the three-dimensional digital core model is reliable is judged. If the judgment result is that the model pixel is unreliable, S11-S13 are repeated until the judgment result is that the model pixel is reliable.

[0020] Preferably, the three-dimensional digital core model is adjusted twice, including:

[0021] Performing stress simulation on the three-dimensional digital core model and outputting digital simulation stress-strain characteristics;

[0022] Conduct rock mechanics tests on core samples from the shale oil exploration area to obtain rock mechanics stress-strain characteristics and rock mechanics property parameters;

[0023] The digital simulation stress-strain characteristics and the rock mechanics stress-strain characteristics are compared, and whether the model characteristics of the three-dimensional digital core model are reliable is judged according to the stress-strain characteristic comparison result; if the judgment result is that the model characteristics are unreliable, the initial mechanical parameters in S13 are adjusted using the rock mechanics property parameters until the judgment result is that the model characteristics are reliable.

[0024] Preferably, the process of determining the digital core characterization unit body is as follows:

[0025] According to the judgment process of the model pixel reliability and the model feature reliability of the three-dimensional digital core model, the correlation between the side length / pixel of the digital core and the mechanical parameters is statistically analyzed;

[0026] The minimum digital core side length / pixel when the mechanical parameters are stable is selected as the side length / pixel of the characterization unit body, and then the digital core characterization unit body is established according to the relationship between the CT image pixel and the real length.

[0027] Preferably, a single factor simulation is performed in the digital core characterization unit, including:

[0028] By adjusting the number of pixels in different media, the changes in the content of geological components can be simulated;

[0029] By adjusting the pixel coordinates of different media, the distribution changes of geological components can be simulated;

[0030] By adjusting the initial mechanical parameters of different types of clay mineral pixels, the changes in clay mineral types are simulated;

[0031] By adjusting the boundary conditions, the accompanying burial depth changes are simulated.

[0032] Preferably, the influence coefficient K of the i-th factor on brittleness is i Correlation coefficient a based on the i-th factor i1 and the weight a of the i-th factor i2 OK, the formula is as follows:

[0033] K i =a i1 ×a i2 ;

[0034] Among them, the correlation coefficient a of the i-th factor isi1 Based on the univariate analysis, the weight a of the i-th factor is i2 Based on AHP hierarchical analysis;

[0035] The influence coefficient of each factor is standardized and ranked from high to low according to the standardized results to determine the degree of influence of each factor on brittleness.

[0036] On the other hand, the present invention also discloses a numerical simulation system applicable to the effect of clay minerals on brittleness in continental shale, comprising:

[0037] The model building module is used to process pixels of CT images of drilling core samples in shale oil exploration areas and build a three-dimensional digital core model;

[0038] A model adjustment module, used to make a preliminary adjustment to the three-dimensional digital core model based on the pixel content of different media in the CT image; and to make a secondary adjustment to the three-dimensional digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments;

[0039] A characterization unit body determination module, used for determining a digital core characterization unit body according to an adjustment process of a primary adjustment and a secondary adjustment;

[0040] A single factor simulation module, used for performing single factor simulation in the digital core characterization unit, wherein the single factor includes geological component content, geological component distribution, clay mineral type and associated burial depth;

[0041] The influence degree analysis module is used to analyze based on the single factor simulation results, calculate the influence coefficient of each factor on brittleness, and determine the influence degree of each factor on brittleness according to the coefficient.

[0042] Through the above technical solutions, it can be known that the present invention provides a numerical simulation method and system applicable to the influence of clay minerals on brittleness in continental shale. In the simulation process, the method of adjusting the number of pixels, coordinates, mechanical properties and boundary conditions is adopted to simulate the content and distribution of geological components (clay minerals, pores, felsic minerals (mainly quartz)) in the clay mineral evolution process, clay mineral types and mechanical property changes and fracture effects caused by deep burial (confining pressure), and then determine the influence coefficient of a single factor on brittleness. The present invention has the following beneficial effects:

[0043] 1. Through digital core stress simulation, the defects of single factor uncontrollable and high cost of natural samples in physical experiments can be compensated.

[0044] 2. The three-dimensional digital core model is adjusted by using a dual verification method of shale minerals / pores and rock mechanical properties, which improves the authenticity and reliability of the simulation results.

[0045] 3. The influence coefficient of the present invention integrates the relevance and importance of the influence of various factors on brittleness, which not only reflects the direct connection between the factors and brittleness, but also takes into account the relative importance of this connection in practical applications, reduces the deviation caused by a single indicator, and makes the final influence degree more convincing. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0047] Figure 1 A stress simulation flow chart based on a three-dimensional digital core model provided by the present invention;

[0048] Figure 2 The overall flow chart of the method provided by the present invention;

[0049] Figure 3 This is a system architecture diagram provided by the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] On the one hand, the embodiment of the present invention discloses a numerical simulation method applicable to the effect of clay minerals on brittleness in continental shale, referring to Figure 1-Figure 2 , the method comprises the following steps:

[0052] S1. Perform pixel processing on the CT image of the drilling core sample in the shale oil exploration area to establish a three-dimensional digital core model. This step is implemented based on MATLAB and includes:

[0053] S11. Perform gray value optimization processing, threshold segmentation processing, and median filtering processing on the CT image in sequence to obtain an image to be processed;

[0054] S12. distinguishing pixels of different media (i.e., geological components, including clay minerals, pores, felsic minerals (mainly quartz), etc.) on the image to be processed, and extracting pixel coordinates of each medium;

[0055] S13. According to the medium corresponding to each pixel point, initial mechanical parameters are assigned to the pixel points, and a three-dimensional digital core model is constructed.

[0056] S2. Perform preliminary adjustments to the three-dimensional digital core model based on the pixel content of different media in the CT image; perform secondary adjustments to the three-dimensional digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments.

[0057] Among them, preliminary adjustments were made to the three-dimensional digital core model, including:

[0058] The pixel content of different media in the three-dimensional digital core model is queried and compared with the pixel content of different media in the CT image. Whether the model pixel of the three-dimensional digital core model is reliable is judged according to the pixel content comparison result. If the judgment result is that the model pixel is unreliable, S11-S13 are repeated until the judgment result is that the model pixel is reliable.

[0059] The standard for the reliability of the model pixel point is: if the ratio of the pixel point content of a certain medium queried in the three-dimensional digital core model to the pixel point content of the medium in the CT image is not less than a preset threshold, the model pixel point is determined to be reliable, otherwise the model pixel point is determined to be unreliable, and S11-S13 are repeated.

[0060] Secondary adjustments are made to the 3D digital core model, including:

[0061] Perform stress simulation on the three-dimensional digital core model and output digital simulation stress-strain characteristics;

[0062] Conduct rock mechanics tests on core samples from shale oil exploration areas to obtain rock mechanics stress-strain characteristics and rock mechanics property parameters;

[0063] Compare the digital simulation stress-strain characteristics with the rock mechanics stress-strain characteristics, and judge whether the model characteristics of the three-dimensional digital core model are reliable based on the stress-strain characteristic comparison results. If the judgment result is that the model characteristics are unreliable, adjust the initial mechanical parameters in S13 using the rock mechanics property parameters until the judgment result is that the model characteristics are reliable.

[0064] In this embodiment, when the digital simulation stress-strain characteristics are highly consistent with the results of rock mechanics tests in terms of curve morphology, characteristic values ​​(such as peak stress, peak strain, elastic modulus, yield strength, etc.) and failure modes (such as splitting, shear, compression, etc.), the model characteristics of the three-dimensional digital core model can be considered reliable.

[0065] Quantitatively analyze the errors in the comparison results to ensure that the errors are within an acceptable range.

[0066] If the judgment result is that the model characteristics are unreliable, the initial mechanical parameters in the three-dimensional digital core model need to be adjusted according to the rock mechanical property parameters (such as elastic modulus, Poisson's ratio, tensile strength, compressive strength, etc.). After adjustment, numerical simulation is performed again and compared with the results of rock mechanics tests until the reliability standard is met.

[0067] S3. Determine a digital core characterization unit body according to the adjustment process of the primary adjustment and the secondary adjustment.

[0068] S31. According to the judgment process of the model pixel reliability and model feature reliability of the three-dimensional digital core model, the correlation between the digital core side length / pixel and the mechanical parameters is statistically analyzed.

[0069] By adjusting the resolution of the digital core model (i.e., changing the ratio of side length / pixel), multiple models with different resolutions are generated;

[0070] Perform stress simulation on each model with different resolutions, record and extract the corresponding mechanical parameters;

[0071] Observe the trend of mechanical parameters as a function of digital core side length / pixel.

[0072] S32. Select the minimum digital core side length / pixel when the mechanical parameters are stable as the side length / pixel of the characterization unit body, and then establish the digital core characterization unit body according to the relationship between the CT image pixels and the real length.

[0073] According to the change trend in S31, when the mechanical parameters tend to be stable after a certain side length / pixel value (that is, the change amplitude is within an acceptable range), this value is considered to be the minimum digital core side length / pixel when the mechanical parameters are stable, that is, the side length / pixel of the characterizing unit body.

[0074] Using the known CT image resolution (real length of each pixel), the selected characterization unit cell side length / pixel is converted to real length.

[0075] A characterization unit cell is constructed with the selected true length as the side length. This unit cell will be used in subsequent rock mechanics analysis and simulation to represent the mechanical behavior of the entire core.

[0076] S4. Single factor simulation is performed in the digital core characterization unit, where the single factors include geological component content, geological component distribution, clay mineral type and associated burial depth.

[0077] Specifically, the changes in the content of geological components are simulated by adjusting the number of pixels in different media;

[0078] By adjusting the pixel coordinates of different media, the distribution changes of geological components can be simulated;

[0079] By adjusting the initial mechanical parameters of different types of clay mineral pixels, the changes in clay mineral types are simulated;

[0080] By adjusting the boundary conditions (pressure, temperature, etc.), the accompanying changes in burial depth can be simulated.

[0081] S5. Analyze the results of single-factor simulation, calculate the influence coefficient of each factor on brittleness, and determine the degree of influence of each factor on brittleness based on the coefficient.

[0082] S51. The influence coefficient K of the i-th factor on brittleness i Correlation coefficient a based on the i-th factor i1 and the weight a of the i-th factor i2 OK, the formula is as follows:

[0083] K i =a i1 ×a i2 ;

[0084] Among them, the correlation coefficient a of the i-th factor i1 Based on univariate analysis, the weight of the i-th factor is a i2 It is obtained based on AHP hierarchical analysis.

[0085] In this embodiment, the brittleness index is calculated by combining elastic parameters, fracture toughness and stress-strain curve, and the relevant parameters in the calculation process are obtained based on digital core stress simulation.

[0086] The specific calculation formula of brittleness index B is as follows:

[0087] B=w1*B i +w2*K c +w3*B m

[0088] In the formula, B i represents the brittleness index based on elastic parameters; K c Represents the fracture toughness brittleness index; B m is the brittleness index based on the stress-strain curve, where:

[0089]

[0090] E is Young's modulus, ν is Poisson's ratio, E max represents the maximum Young's modulus of rock and E min represents the minimum Young's modulus, ν max is the maximum Poisson's ratio of rock, ν min is the minimum Poisson's ratio of rock.

[0091] During the shale gas fracturing process, type I and type II fractures are usually generated. The fracture toughness of type I and type II is normalized to obtain the fracture toughness index K. c :

[0092]

[0093] K Ⅰmax , K Ⅰmin are the maximum and minimum values ​​of fracture toughness of mode I cracks; K Ⅱmax , K Ⅱmin are the maximum and minimum values ​​of the fracture toughness of mode II cracks, respectively.

[0094] B m =B i1 +B i2

[0095]

[0096] B i1 , B i2 are two brittleness indices determined by the triaxial stress-strain curve, B i1 is the brittleness index characterized by the stress-strain curve parameters in the previous section, B i2 is the brittleness index characterized by the stress-strain curve parameters in the latter part; δ i , δ p are the crack initiation stress and peak stress respectively; ε i , ε p are the crack initiation strain and peak strain respectively; δ r is the residual stress; r is the residual strain.

[0097] w1, w2, w3 are B i , K c , B m The weight parameters of the three parameters (B i , K c , B m ) quantitatively compare two by two, and determine the factors (B i , K c , B m ) and establish a judgment matrix. By solving the maximum eigenvalue of the judgment matrix and the corresponding orthogonalized eigenvector, the weight parameters w1, w2, and w3 of each element at this level are obtained.

[0098] Use AHP hierarchical analysis to obtain the weight a of the i-th factor i2 The principle is the same as the process of determining w1, w2, and w3, and will not be repeated here.

[0099] When conducting single factor analysis on each factor, first determine the analysis factor, ensure that other factors are constant, set a series of test levels (different values ​​or conditions) for the analysis factor within the set range, change the level of the analysis factor one by one, and measure and record the brittleness index value at each test level.

[0100] Use statistical methods (such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc.) to calculate the correlation coefficient a between the analysis factors and the fragility index i1 These correlation coefficients provide a quantitative indicator of the strength of the linear relationship between the two.

[0101] S52. Standardize the influence coefficient of each factor, sort it from high to low according to the standardized result, and determine the degree of influence of each factor on brittleness.

[0102] The normalization formula is:

[0103] Where K' i is the standard value of the influence coefficient of the i-th factor, and n is the number of influencing factors.

[0104] The standardized values ​​of the influence coefficients of various factors are ranked from high to low. The larger the standardized value, the greater the influence of the factor on brittleness.

[0105] On the other hand, the present invention also discloses a numerical simulation system suitable for the influence of clay minerals on brittleness in continental shale, such as Figure 3 As shown, the system includes:

[0106] The model building module is used to process pixels of CT images of drilling core samples in shale oil exploration areas and build a three-dimensional digital core model;

[0107] The model adjustment module is used to make preliminary adjustments to the 3D digital core model based on the pixel content of different media in the CT image; and to make secondary adjustments to the 3D digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments;

[0108] A characterization unit body determination module, used for determining a digital core characterization unit body according to an adjustment process of a primary adjustment and a secondary adjustment;

[0109] Single factor simulation module, used to perform single factor simulation in digital core characterization unit, single factor includes geological component content, geological component distribution, clay mineral type and associated burial depth;

[0110] The impact degree analysis module is used to analyze based on the single factor simulation results, calculate the impact coefficient of each factor on brittleness, and determine the degree of impact of each factor on brittleness according to the coefficient.

[0111] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0112] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A numerical simulation method for the effect of clay minerals on brittleness in continental shale, characterized in that: The following steps are involved: Perform pixel processing on CT images of drilling core samples in shale oil exploration areas to establish a three-dimensional digital core model; Preliminarily adjusting the three-dimensional digital core model based on the pixel content of different media in the CT image; and secondarily adjusting the three-dimensional digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments; Determine a digital core characterization unit body according to the adjustment process of the primary adjustment and the secondary adjustment; Performing single factor simulation in the digital core characterization unit, the single factor including geological component content, geological component distribution, clay mineral type and associated burial depth; Based on the single factor simulation results, the analysis is performed to calculate the influence coefficient of each factor on brittleness, and the degree of influence of each factor on brittleness is determined based on the coefficient.

2. A numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 1, characterized in that: Perform pixel processing on CT images of drilling core samples in shale oil exploration areas to build a three-dimensional digital core model, including: S11. Perform gray value optimization processing, threshold region segmentation processing, and median filtering processing on the CT image in sequence to obtain an image to be processed; S12. Distinguishing pixels of different media on the image to be processed, and extracting pixel coordinates of each medium; S13. According to the medium corresponding to each pixel point, initial mechanical parameters are assigned to the pixel point, and a three-dimensional digital core model is constructed.

3. A numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 2, characterized in that: The three-dimensional digital core model is initially adjusted, including: The pixel content of different media in the three-dimensional digital core model is queried, and compared with the pixel content of different media in the CT image. According to the pixel content comparison result, whether the model pixel of the three-dimensional digital core model is reliable is judged. If the judgment result is that the model pixel is unreliable, S11-S13 are repeated until the judgment result is that the model pixel is reliable.

4. A numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 3, characterized in that: The three-dimensional digital core model is adjusted twice, including: Performing stress simulation on the three-dimensional digital core model and outputting digital simulation stress-strain characteristics; Conduct rock mechanics tests on core samples from the shale oil exploration area to obtain rock mechanics stress-strain characteristics and rock mechanics property parameters; The digital simulation stress-strain characteristics and the rock mechanics stress-strain characteristics are compared, and whether the model characteristics of the three-dimensional digital core model are reliable is judged according to the stress-strain characteristic comparison result; if the judgment result is that the model characteristics are unreliable, the initial mechanical parameters in S13 are adjusted using the rock mechanics property parameters until the judgment result is that the model characteristics are reliable.

5. A numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 4, characterized in that: The process of determining the digital core characterization unit body is as follows: According to the judgment process of the model pixel reliability and the model feature reliability of the three-dimensional digital core model, the correlation between the side length / pixel of the digital core and the mechanical parameters is statistically analyzed; The minimum digital core side length / pixel when the mechanical parameters are stable is selected as the side length / pixel of the characterization unit body, and then the digital core characterization unit body is established according to the relationship between the CT image pixel and the real length.

6. The numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 1, characterized in that: A single factor simulation is performed in the digital core characterization unit, including: By adjusting the number of pixels in different media, the changes in the content of geological components can be simulated; By adjusting the pixel coordinates of different media, the distribution changes of geological components can be simulated; By adjusting the initial mechanical parameters of different types of clay mineral pixels, the changes in clay mineral types are simulated; By adjusting the boundary conditions, the accompanying burial depth changes are simulated.

7. The numerical simulation method for the effect of clay minerals on brittleness in continental shale according to claim 1, characterized in that: The influence coefficient K of the i-th factor on brittleness i Correlation coefficient a based on the i-th factor i1 and the weight a of the i-th factor i2 OK, the formula is as follows: K i =a i1 ×a i2 ; Among them, the correlation coefficient a of the i-th factor is i1 Based on the results of univariate analysis, the weight a of the i-th factor is obtained. i2 Based on AHP hierarchical analysis; The influence coefficient of each factor is standardized and ranked from high to low according to the standardized results to determine the degree of influence of each factor on brittleness.

8. A numerical simulation system for the effect of clay minerals on brittleness in continental shale, characterized in that: include: The model building module is used to process pixels of CT images of drilling core samples in shale oil exploration areas and build a three-dimensional digital core model; A model adjustment module, used to make a preliminary adjustment to the three-dimensional digital core model based on the pixel content of different media in the CT image; and to make a secondary adjustment to the three-dimensional digital core model based on the rock mechanics stress-strain characteristics obtained from rock mechanics experiments; A characterization unit body determination module, used for determining a digital core characterization unit body according to an adjustment process of a primary adjustment and a secondary adjustment; A single factor simulation module, used for performing single factor simulation in the digital core characterization unit, wherein the single factor includes geological component content, geological component distribution, clay mineral type and associated burial depth; The influence degree analysis module is used to analyze based on the single factor simulation results, calculate the influence coefficient of each factor on brittleness, and determine the influence degree of each factor on brittleness according to the coefficient.

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