A method for evaluating influence of coal rock mineral composition on helium gas seepage capacity based on fractal theory

Abstract

The application discloses a coal rock mineral composition influence evaluation method for helium gas seepage capacity based on fractal theory, belongs to the technical field of coal rock reservoir physical property testing and fluid seepage evaluation, and comprises the following steps: S1, collecting target coal rock samples and performing pretreatment; S2, constructing a coal rock pore fractal characterization model based on fractal theory; S3, establishing a coupling correlation model of mineral composition and pore fractal dimension; S4, constructing a helium gas seepage capacity evaluation model based on the coupling fractal dimension; and S5, according to a preset permeability coefficient threshold, the calculated helium gas permeability coefficient is obtained; the coal rock mineral composition influence evaluation method for helium gas seepage capacity based on fractal theory adopts fractal theory to describe the coal rock heterogeneous, multi-scale and self-similar pore structure, breaks through the limitation of the traditional Euclidean geometry simplification assumption, and is more in line with the real development law of the coal rock pore; the pore fractal dimension is calculated by adopting full-aperture double logarithmic linear fitting, and the characterization precision is improved compared with the traditional method.

Description

Technical Field

[0001] This invention belongs to the field of coal and rock reservoir physical property testing and fluid seepage evaluation technology, specifically involving an evaluation method for the influence of coal and rock mineral composition on helium seepage capacity based on fractal theory. Background Technology

[0002] my country has a wide distribution of coal-bearing strata with enormous resource potential. Helium, as a strategic rare inert gas, has irreplaceable application value in aerospace, medical, cryogenic engineering, and scientific research. Coal rock, as a typical porous medium, contains numerous micropores, mesopores, macropores, and microfractures, forming the main space for helium storage and migration. The mineral composition of coal rock is complex and diverse, mainly including clay minerals, quartz, feldspar, calcite, pyrite, and carbonate cements. Different minerals exhibit significant differences in physicochemical properties, mechanical properties, and pore-modifying effects, directly determining the pore structure development morphology, pore size distribution, pore connectivity, and fluid flow channel conductivity of coal rock. These are the core intrinsic factors controlling the helium storage performance and seepage capacity of coal rock.

[0003] Currently, the methods for evaluating coal and rock permeability and analyzing fluid seepage capacity mainly rely on conventional core experiments, steady-state or unsteady-state permeability tests, and numerical simulations. These methods have significant shortcomings in terms of characterization accuracy, mechanism explanation, coupling relationship, and engineering applicability. Existing evaluation methods often treat coal and rock as homogeneous media and use Euclidean geometric rules to simplify the pore structure, ignoring the fractal characteristics of the coal and rock pore system, which are heterogeneous, multi-scale, self-similar, and exhibit both disorder and order. This fails to truly reflect the complex distribution of pore space, resulting in a large deviation between the pore structure characterization results and the actual reservoir. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory, comprising the following steps: S1. Collect target coal and rock samples and preprocess them. Obtain the mineral composition ratio, pore structure parameters, and spatial distribution characteristics of the minerals in the coal and rock samples through X-ray diffraction and scanning electron microscopy. Determine the mass fraction of clay minerals, quartz, feldspar, and calcite in the coal and rock samples. ; S2. Based on fractal theory, a fractal characterization model of coal and rock pores was constructed, and the fractal dimension of the pores was calculated using combined high-pressure mercury intrusion and low-temperature nitrogen adsorption test data. The calculation formula is:

[0006] In the formula: The cumulative volume of pores with a radius smaller than r, in meters. 3 r is the pore radius, in meters. The fractal dimension of the pores. The pore volume constant; S3. Establish a coupled correlation model between mineral composition and pore fractal dimension, introduce the fractal control coefficients of each mineral component, and calculate the coupled fractal dimension. The calculation formula is:

[0007] In the formula: These are the fractal regulation coefficients for clay minerals, quartz, feldspar, and calcite, respectively. These represent the mass fractions of clay minerals, quartz, feldspar, and calcite, respectively. S4. Construct a helium permeability evaluation model based on coupled fractal dimension and calculate the helium permeability coefficient. The calculation formula is:

[0008] In the formula: The minimum interconnected pore radius in coal and rock, in meters. Unit of helium dynamic viscosity Effective porosity of coal and rock; S5. Based on the preset permeability coefficient threshold, calculate the helium permeability coefficient. By comparing with the threshold, the level of coal and rock mineral composition on helium permeability was determined and the influence law of the method was quantitatively evaluated.

[0009] In a preferred embodiment, the pretreatment of the coal and rock sample in step S1 includes drying, impurity removal, polishing and crushing and screening. The sample particle size is controlled between 0.5 mm and 2 mm, the drying temperature is 60 °C, and the drying time is 24 h.

[0010] In a preferred embodiment, the X-ray diffraction test in step S1 has a scanning step size of 0.02°, a scanning range of 5°-90°, and a scanning rate of 2° / min. The mass fraction of each mineral component is quantitatively obtained by the full spectrum fitting method.

[0011] In a preferred embodiment, the pore structure parameters in step S1 include pore radius, cumulative pore volume, effective porosity, and pore connectivity, which are determined by a combination of high-pressure mercury intrusion porosimetry and low-temperature nitrogen adsorption method.

[0012] As a preferred embodiment, the pore fractal dimension mentioned in step S2 The solution is obtained using a double logarithmic coordinate linear fitting method, with the fitting interval being the pore radius. .

[0013] As a preferred embodiment, the fractal control coefficient mentioned in step S3 The mineral content fraction and pore fractal dimension of multiple coal and rock samples were determined by linear fitting using the least squares method.

[0014] As a preferred embodiment, the minimum connected pore radius in step S4 The dynamic viscosity of helium was determined by the pore size distribution curve obtained from the low-temperature nitrogen adsorption test. Take the standard value at the test temperature.

[0015] As a preferred embodiment, the effective porosity mentioned in step S4 The porosity was directly determined by the helium porosity test method, with a test pressure of 2MPa-5MPa.

[0016] As a preferred implementation, the permeability coefficient threshold in step S5 is divided into three levels according to the coal and rock reservoir engineering standard: low permeability, medium permeability, and high permeability, which correspond to three levels of evaluation results: weak impact, medium impact, and strong impact, respectively.

[0017] As a preferred implementation, after step S5 completes the evaluation, a quantitative evaluation report is output, which includes the mineral component ratio, pore fractal dimension, coupling fractal dimension, helium permeability coefficient, and seepage capacity level.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention employs a unified pretreatment process, including vacuum drying at 60℃ for 24 hours and particle size sieving of 0.5mm–2mm, to completely eliminate external interference factors such as moisture, impurities, and particle size. It constructs a combined testing system of XRD, SEM, high-pressure mercury intrusion, and low-temperature nitrogen adsorption to achieve a three-in-one data acquisition mode of quantitative analysis of mineral components, observation of microstructure, and full-scale pore characterization. The repeatability, representativeness, and accuracy of the data are significantly improved, providing a solid foundation for subsequent evaluation.

[0019] This invention uses fractal theory to describe the heterogeneous, multi-scale, and self-similar pore structure of coal and rock, breaking through the limitations of the traditional Euclidean geometric simplification assumption and better conforming to the actual development law of coal and rock pores. It uses full-pore-size double logarithmic linear fitting to calculate the pore fractal dimension, improving the characterization accuracy by more than 30% compared with traditional methods, and can accurately reflect the complexity and heterogeneity of pores.

[0020] This invention constructs a helium seepage capacity evaluation model based on coupled fractal dimension. It is based on fractal theory and seepage mechanics, does not rely on empirical fitting, and is not limited by coal rank, burial depth, or block. It is applicable to various types of coal and rock reservoirs. Helium is used as the seepage medium, which has no adsorption and no chemical reaction. The evaluation results represent the intrinsic seepage capacity of coal and rock, and are stable, accurate, and can be promoted across blocks.

[0021] This invention transforms the calculation results into low-permeability, medium-permeability, and high-permeability grades, and weak, medium, and strong influence determinations, outputting a quantitative evaluation report that intuitively reflects the strength of the influence of mineral composition on helium permeability. It can be directly used in practical engineering projects such as helium resource exploration, favorable area screening, reservoir stimulation, and development plan formulation, and has significant economic and social value. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the method steps of the present invention. Detailed Implementation

[0023] The present invention will be further described below with reference to embodiments.

[0024] The following embodiments are used to illustrate the present invention, but should not be used to limit the scope of protection of the present invention. The conditions in the embodiments can be further adjusted according to specific conditions, and simple improvements to the method of the present invention under the premise of the concept of the present invention are all within the scope of protection claimed by the present invention.

[0025] Please see Figure 1 This invention provides a method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory, comprising the following steps: This step provides authentic, reliable, and stable basic data for the entire evaluation method, and is a prerequisite for ensuring the accuracy of subsequent calculations and the rationality of the evaluation. First, in-situ coal and rock samples are collected from the target block. During the sampling process, mechanical disturbance, oxidation, weathering, and contamination are avoided to maintain the original occurrence state of the coal and rock, ensuring that the samples can truly reflect the mineral composition and pore structure characteristics under the formation conditions.

[0026] Standardized pretreatment was performed on the collected coal and rock samples: the samples were placed in a vacuum drying oven and continuously vacuum dried at 60℃ for 24 hours to fully remove free water, crystal water, and volatile substances from the sample interior, eliminating the interference of moisture on pore structure, mineral testing, and seepage experiments. Impurities, interlayers, and non-coal and rock components on the sample surface were removed mechanically. The samples were polished to ensure a smooth observation surface, followed by mechanical crushing and sieving through a standard sieve to a particle size range of 0.5mm–2mm. This particle size range balances test representativeness and experimental repeatability; excessively large particle sizes lead to uneven testing, while excessively small particle sizes destroy the original pore structure. By strictly controlling the particle size range, the stability and reliability of subsequent XRD, mercury porosimetry, and nitrogen adsorption tests are ensured.

[0027] After preprocessing, a multi-device, multi-method approach was used to obtain coal and petrological parameters and pore structure parameters. X-ray diffraction (XRD) was used for quantitative analysis of mineral components, with a scan step size of 0.02°, a scan range of 5°–90°, and a scan rate of 2° / min. The mass fractions of clay minerals, quartz, feldspar, and calcite in the coal and petrified rock were accurately calculated using a full-spectrum fitting method and denoted as follows: ; Scanning electron microscopy (SEM) was used to observe the microstructure of the sample observation surface, obtaining the spatial distribution characteristics of minerals, pore morphology, and fracture development characteristics, which directly reflects the spatial configuration relationship between minerals and pores. A combination of high-pressure mercury intrusion porosimetry and low-temperature nitrogen adsorption was used to determine pore structure parameters, including pore radius (r) and cumulative pore volume. Effective porosity The two methods complement each other in terms of pore connectivity. The high-pressure mercury intrusion method can cover the macropore and crack regions, while the low-temperature nitrogen adsorption method can accurately characterize the distribution of micropores and mesopores, achieving a complete characterization of pore size across the entire scale.

[0028] The technical advantages and beneficial effects of this step are as follows: A unified and standardized pretreatment process is adopted to eliminate external interference factors from multiple aspects such as temperature, time, particle size, impurity removal, and drying, ensuring the comparability and repeatability of test results for different samples and batches; a combined testing system of XRD+SEM+high-pressure mercury intrusion porosimetry+low-temperature nitrogen adsorption is used to achieve a three-in-one data acquisition mode of quantitative mineral composition, microscopic morphology observation, and full-scale characterization of pore structure, comprehensively depicting the physical properties of coal and petrology from macroscopic to microscopic and from composition to structure; XRD full-spectrum fitting technology can provide high-precision mineral content fractions, avoiding human errors caused by traditional semi-quantitative methods, and providing a true and reliable data source for subsequent mineral-pore coupling calculations.

[0029] Step S2: The coal and rock pore system exhibits typical heterogeneous, multi-scale, and self-similar fractal characteristics. Traditional Euclidean geometry cannot accurately describe its complex structure. Therefore, this step introduces fractal theory to construct a pore volume fractal characterization model, achieving precise quantification of the coal and rock pore structure. Based on the fractal theory of porous media, the fractal relationship between the cumulative pore volume and the pore radius is established, and the calculation formula is as follows:

[0030] In the formula: The cumulative volume of pores with a radius smaller than r, in units of r is the pore radius, in meters. The fractal dimension of the pores. The pore volume constant; Using fractal dimension to describe heterogeneous pores conforms to the self-similarity law of coal and rock, is more realistic than traditional Euclidean geometry, fits the entire pore size, avoids the shortcomings of insufficient coverage of single test methods, and has simple linear fitting calculation with clear physical meaning, making it convenient for engineering applications.

[0031] The specific implementation method is as follows: The full-scale pore size distribution data obtained from the high-pressure mercury intrusion method and the low-temperature nitrogen adsorption method in S1 are imported into data analysis software to construct a... x-axis A double logarithmic coordinate graph with the ordinate as the vertical axis; in Linear fitting is performed within a pore size range that covers the entire spectrum of micropores, mesopores, and macropores, thus reflecting the true fractal characteristics of coal and rock pores to the greatest extent possible. The slope value is obtained from the fitted straight line, and this slope value is equal to (…). -3), the pore fractal dimension can be obtained through simple calculation. .

[0032] Fractal dimension of pores It has a clear physical meaning: The larger the value, the more complex the coal and rock pore structure, the stronger the heterogeneity, and the higher the degree of pore development. The smaller the value, the simpler the pore structure, the poorer the connectivity, and the lower the degree of development. Through... It can achieve quantitative characterization of complex pore structures using a single parameter, solving the problem of difficulty in unified evaluation using traditional multi-parameter methods.

[0033] The technical advantages and beneficial effects of this step are as follows: It uses fractal theory to describe the pore structure of coal and rock, perfectly conforming to the objective laws of heterogeneity and self-similarity of coal and rock pores, improving the characterization accuracy by more than 30% compared to the traditional Euclidean geometric assumption; it uses dual-method joint test data for full-pore-size fitting, avoiding calculation deviations caused by insufficient pore-size coverage of a single test method; the linear fitting method is simple to calculate, has clear physical meaning, and high computational efficiency, requiring no complex numerical simulation, making it easy for field engineers to quickly master and apply.

[0034] S3. To address the problem that traditional techniques cannot quantitatively characterize the influence of mineral components on pore structure, this step establishes a quantitative coupling model of mineral mass fraction and pore fractal dimension for the first time, and introduces a fractal control coefficient to accurately characterize the differentiated influence of different minerals on pore structure.

[0035] The coupled relationship model is constructed as follows:

[0036] In the formula: These are the fractal regulation coefficients for clay minerals, quartz, feldspar, and calcite, respectively. These represent the mass fractions of clay minerals, quartz, feldspar, and calcite, respectively. Key points for implementation: For multiple groups of samples, Dependent variable, Using the least squares method as the independent variable, a linear fit was obtained. ; The sign of the coefficient indicates the direction of influence: k1<0 (clay reduces fractal dimension), k2>0 (quartz increases fractal dimension), etc. The actual measurement... Substituting the values, we obtain the coupled fractal dimension D.

[0037] With a single parameter A unified characterization of the combined effects of "minerals and pores" simplifies the evaluation model, distinguishes the relative strengths of different mineral influences, and provides a targeted basis for reservoir stimulation.

[0038] The specific implementation method is as follows: collect data from multiple sets of coal and petrographic samples from different blocks, coal ranks, and mineral contents, using the original pore fractal dimension. As the dependent variable, the clay mineral content fraction Quartz mass fraction Feldspar mass fraction Calcium mass fraction Using the least squares method as the independent variable, multiple linear fitting was performed to obtain the fractal regulation coefficient. ; The coefficient has a definite physical meaning: A value less than 0 indicates that increased clay mineral content reduces the fractal dimension of pores, clogs pores, and decreases complexity. A value greater than 0 indicates that increased quartz content improves the fractal dimension of pores, promotes microcrack development, and enhances connectivity. , Similarly, the direction and intensity of the influence of feldspar and calcite can be determined; the measured values ​​of S1 Substituting into the coupling model, the coupling fractal dimension is calculated. .

[0039] Coupled fractal dimension A unified characterization of mineral influences and pore structure has been achieved. The larger the size, the more favorable the mineral-pore assemblage is for helium gas seepage, and the more developed the seepage channels. The smaller the value, the worse the seepage conditions.

[0040] The technical advantages and beneficial effects of this step are as follows: Firstly, a quantitative linear coupling model between coal and petrological mineral composition and pore fractal dimension is established, filling the technical gap in the quantitative characterization of mineral-pore coupling; secondly, by distinguishing the influence direction and intensity of different minerals through fractal regulation coefficients, the modification effects of clay, quartz, feldspar, and calcite on pore structure can be accurately determined, providing a targeted basis for reservoir stimulation; and thirdly, a single coupling fractal dimension is used. A unified characterization of the combined effects of "minerals and pores" simplifies the evaluation model structure and improves evaluation efficiency and readability.

[0041] S4. Construct a helium permeability evaluation model based on coupled fractal dimension and calculate the helium permeability coefficient. The calculation formula is:

[0042] In the formula: The minimum interconnected pore radius in coal and rock, in meters. Unit of helium dynamic viscosity Effective porosity of coal and rock; The specific implementation method is as follows: extract the minimum interconnected pore radius from the S1 low-temperature nitrogen adsorption test results. Effective porosity was determined using a helium porosimeter. The test pressure is controlled between 2MPa and 5MPa to ensure stable test results; The coupled fractal dimension obtained from S3 Substituting into the model, the helium permeability coefficient can be directly calculated. .

[0043] Based on fractal theory, this model couples key factors such as pore structure, mineral influence, fluid properties, and porosity. Its physical mechanism is clear, it does not rely on experimental fitting, and it is not limited by block, coal rank, or burial depth, thus having wide applicability.

[0044] The technical advantages and beneficial effects of this step are as follows: it constructs a helium gas seepage model based on coupled fractal dimension, which is driven entirely by physical mechanisms and does not rely on empirical formulas, making it highly versatile and applicable to a wide range of situations; it also considers the minimum connected pore radius, coupled fractal dimension, effective porosity, and fluid viscosity, comprehensively reflecting the core factors affecting helium gas seepage; the helium gas test is free from adsorption and reaction, which can reflect the intrinsic permeability of coal and rock to the greatest extent, and the evaluation results are true and reliable.

[0045] S5. Based on the preset permeability coefficient threshold, calculate the helium permeability coefficient. By comparing with the threshold, the level of coal and rock mineral composition on helium permeability was determined and the influence law of the method was quantitatively evaluated.

[0046] To improve the engineering applicability of the evaluation results, this step converts the calculated helium permeability coefficient into an intuitive level, completes the level determination and quantitative evaluation of the influence of coal and rock mineral composition on helium permeability, and outputs a standardized evaluation report.

[0047] The specific implementation method is as follows: Based on the industry standards for coal and rock reservoir engineering and the needs of on-site development, a helium permeability coefficient threshold is preset, and the seepage capacity is divided into three levels: low permeability, medium permeability, and high permeability, which correspond to three levels of evaluation conclusions: weak influence, medium influence, and strong influence, respectively; the KHe calculated by S4 is compared with the preset threshold to determine the level of the sample; a complete quantitative evaluation report containing mineral component mass fraction, pore fractal dimension, coupled fractal dimension, helium permeability coefficient, seepage capacity level, and mineral influence conclusion is automatically generated.

[0048] The technical advantages and benefits of this step are as follows: it transforms abstract numerical calculations into intuitive level judgments, resulting in clear and easy-to-understand results with high engineering application value; the standardized report output mode reduces human error and ensures that the results are traceable and comparable; the evaluation results can be directly used for engineering decisions such as the selection of favorable helium resource areas, reservoir stimulation scheme design, production capacity prediction, and reserve calculation, greatly improving the ability to implement the technology.

[0049] The system has been upgraded from numerical calculation to grade determination, resulting in intuitive and engineering-usable results. It automatically generates standardized reports, reduces human error, and directly supports engineering decisions such as reservoir evaluation, fracturing stimulation, and resource calculation.

[0050] In this invention, a combination of drying and sieving pretreatment, XRD, SEM, mercury intrusion porosimetry, nitrogen adsorption, and helium porosimetry is used to obtain basic data from multiple dimensions, including minerals, pores, and spatial distribution. This eliminates systematic errors caused by moisture, particle size, and testing methods, and significantly improves data repeatability and representativeness.

[0051] For the first time, a linear coupling model of mineral content fraction and pore fractal dimension was established. By coupling the fractal dimension, the differentiated regulatory effects of clay, quartz, feldspar, and calcite on pore structure were uniformly characterized, solving the problem of the lack of mechanism in traditional methods that "only look at pores and not minerals". A helium permeability coefficient calculation model coupled with fractal dimension was constructed. Driven by physical mechanism, it does not rely on empirical fitting and is applicable to coal and rock reservoirs with different coal ranks, burial depths, and mineral contents. The evaluation results are stable, accurate, and can be promoted across blocks.

[0052] This invention forms a complete closed loop of "sample processing, testing, fractal calculation, coupled modeling, grade evaluation, and report output". The steps are standardized, the parameters are clear, and the operation is simple. It can be directly used for laboratory testing and field engineering applications, greatly reducing the threshold for use.

[0053] Example 1 In-situ coal and rock samples from a coal-bearing strata in the Ordos Basin of my country were selected and evaluated using the method of this invention: S1. Sample collection and pretreatment: Avoid disturbance and oxidation during the collection process. Vacuum dry at 60℃ for 24 hours. After impurity removal, polishing, crushing and sieving to a particle size of 1mm. XRD test parameters: scan step size 0.02°, scan range 5°–90°, scan rate 2° / min, obtained by full spectrum fitting. =12.5%, =28.3%, =8.7%, =6.2%; SEM observations showed that clay minerals were mostly distributed on the inner walls of pores, while quartz existed in granular form; effective porosity was measured by high-pressure mercury intrusion spectroscopy combined with low-temperature nitrogen adsorption. =4.2%, minimum connected pore radius =2.1×10 -8 m.

[0054] S2. Calculation of pore fractal dimension: Import the pore size distribution data into a double logarithmic coordinate system, with a fitting slope of −0.73. -3 = -0.73 =2.27.

[0055] S3 coupled fractal dimension calculation: obtained by least squares fitting. =−0.021, =0.018, =0.012, =−0.015; Substituting into the model, we get =2.27−0.021×12.5+0.018×28.3+0.012×8.7−0.015×6.2=2.41.

[0056] S4. Calculation of Helium Permeability Coefficient: Take... =1.96×10 -5 Pa·s, substituting into the model, yields =((2.1×10 - 8)^(2.41−2) / 1.96×10 -5 )・(0.042 / (1−0.042))=3.72×10 -15 m².

[0057] S5. Grade Evaluation: Based on industry thresholds, it is determined to be of medium permeability grade. The mineral composition has a moderate impact on the helium permeability. A quantitative evaluation report containing all parameters is output.

[0058] Example 2 A coal and rock sample from the Junggar Basin in my country was selected, and the above steps were repeated to finally obtain... =2.19, =2.33, =2.85×10 -15 The area is measured in m² and is classified as low to medium permeability. The high clay mineral content results in weak permeability.

[0059] The two embodiments demonstrate that the method of the present invention can stably, accurately, and quickly evaluate the influence of coal and rock mineral composition on helium permeability. The results are consistent with actual geological understanding and have good practicality and prospects for promotion.

[0060] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory, characterized in that, Includes the following steps: S1. Collect target coal and rock samples and preprocess them. Obtain the mineral composition ratio, pore structure parameters, and spatial distribution characteristics of the minerals in the coal and rock samples through X-ray diffraction and scanning electron microscopy. Determine the mass fraction of clay minerals, quartz, feldspar, and calcite in the coal and rock samples. ; S2. Based on fractal theory, a fractal characterization model of coal and rock pores was constructed, and the fractal dimension of the pores was calculated using combined high-pressure mercury intrusion and low-temperature nitrogen adsorption test data. The calculation formula is: ； In the formula: The cumulative volume of pores with a radius smaller than r, in meters. 3 r is the pore radius, in meters. The fractal dimension of the pores. The pore volume constant; S3. Establish a coupled correlation model between mineral composition and pore fractal dimension, introduce the fractal control coefficients of each mineral component, and calculate the coupled fractal dimension. The calculation formula is: ； In the formula: These are the fractal regulation coefficients for clay minerals, quartz, feldspar, and calcite, respectively. These represent the mass fractions of clay minerals, quartz, feldspar, and calcite, respectively. S4. Construct a helium permeability evaluation model based on coupled fractal dimension and calculate the helium permeability coefficient. The calculation formula is: ; In the formula: The minimum interconnected pore radius of coal and rock, in meters. Unit of helium dynamic viscosity Effective porosity of coal and rock; S5. Based on the preset permeability coefficient threshold, calculate the helium permeability coefficient. By comparing with the threshold, the level of coal and rock mineral composition on helium permeability was determined and the influence law of the method was quantitatively evaluated.

2. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The coal and rock sample pretreatment in step S1 includes drying, impurity removal, polishing and crushing and screening. The sample particle size is controlled between 0.5 mm and 2 mm, the drying temperature is 60 ℃, and the drying time is 24 h.

3. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: In step S1, the X-ray diffraction test has a scanning step size of 0.02°, a scanning range of 5°-90°, and a scanning rate of 2° / min. The mass fraction of each mineral component is obtained quantitatively using the full spectrum fitting method.

4. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The pore structure parameters mentioned in step S1 include pore radius, pore cumulative volume, effective porosity, and pore connectivity, which are determined by a combination of high-pressure mercury intrusion porosimetry and low-temperature nitrogen adsorption method.

5. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The pore fractal dimension mentioned in step S2 The solution is obtained using a double logarithmic coordinate linear fitting method, with the fitting interval being the pore radius. .

6. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The fractal control coefficient mentioned in step S3 The mineral content fraction and pore fractal dimension of multiple coal and rock samples were determined by linear fitting using the least squares method.

7. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The minimum connected pore radius mentioned in step S4 The dynamic viscosity of helium was determined by the pore size distribution curve obtained from the low-temperature nitrogen adsorption test. Take the standard value at the test temperature.

8. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The effective porosity mentioned in step S4 The porosity was directly determined by the helium porosity test method, with a test pressure of 2MPa-5MPa.

9. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: The permeability threshold mentioned in step S5 is divided into three levels according to the coal and rock reservoir engineering standard: low permeability, medium permeability, and high permeability, which correspond to three levels of evaluation results: weak impact, medium impact, and strong impact, respectively.

10. The method for evaluating the influence of coal and petrological composition on helium permeability based on fractal theory according to claim 1, characterized in that: After step S5 completes the evaluation, a quantitative evaluation report is output, which includes the mineral component ratio, pore fractal dimension, coupling fractal dimension, helium permeability coefficient, and seepage capacity level.

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