Method for predicting coal seam pore evolution under action of low-temperature liquid nitrogen

Abstract

The invention discloses a coal seam pore evolution prediction method under the action of low-temperature liquid nitrogen, and relates to the technical field of coal seam pore evolution, and the method comprises the following steps: S1, obtaining a three-dimensional pore structure of a coal sample through micro-CT scanning, and calculating initial pore parameters; s2, collecting coal seam sample parameters and calibrating liquid nitrogen action key parameters through a liquid nitrogen experiment, wherein the liquid nitrogen action key parameters comprise a pore freezing point, an ice crystal growth rate and an ice expansion coefficient; s3, constructing a porosity evolution equation and solving a porosity predicted value and a pore size distribution function; s4, defining a pore type and calculating pore type conversion; and S5, generating a final coal seam pore structure evolution prediction result under the action of the low-temperature liquid nitrogen. According to the method, a numerical analysis and experimental research combined method is adopted, a dynamic evolution prediction model of the reservoir micro-pore structure under liquid nitrogen injection disturbance is constructed, and the action rule and mechanism of low-temperature liquid nitrogen fluid on the coal adsorption performance are revealed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal seam pore evolution, in particular to a coal seam pore evolution prediction method under the action of low-temperature liquid nitrogen. BACKGROUND

[0002] With the continuous development of coal seam permeability enhancement technology, water-free fracturing permeability enhancement technology as a new technology has attracted a lot of attention from experts and scholars. The characteristic of water-free fracturing permeability enhancement technology is to use non-water substances as the medium for fracturing and permeability enhancement of coal seams. Water-free fracturing permeability enhancement technology avoids water lock damage, water resource waste and coal reservoir pollution, so it will become the development trend of future coal seam permeability enhancement technology. In water-free fracturing permeability enhancement technology, the fracturing and permeability enhancement technology using liquid nitrogen as the medium has received extensive attention. When liquid nitrogen is injected into the coal seam at normal temperature and pressure, the temperature of the coal seam decreases, causing the liquid water in the coal seam pores and fissures to freeze and expand in volume. When the frost heaving force reaches the strength limit of the coal body, it can cause the coal body to break. On the other hand, due to the decrease in the temperature of the coal body, thermal stress is generated, which intensifies the damage to the pore and fissure structure of the coal body and accelerates the breakage of the coal body, thereby generating seepage channels that are conducive to the diffusion and seepage of coalbed methane. Liquid nitrogen fracturing can greatly alleviate the dependence on water resources for conventional hydraulic fracturing and the pressure in water-deficient areas, and will not cause pollution to the coalbed methane reservoir and the surrounding environment, thus having a very good application prospect in coal mine gas extraction.

[0003] The current conventional underground coal seam liquid nitrogen fracturing technology has the following problems: strong coal seam heterogeneity, complex pore and fissure development characteristics, insufficient research on the triple fracturing mechanism of gasification and expansion, freezing and low-temperature fracturing of liquid nitrogen on coal and rock mass, difficulty in directly and effectively obtaining the pore structure characteristics of liquid nitrogen fractured coal seams, unclear understanding of the pore and fissure system, and serious restriction on the industrial application of liquid nitrogen fracturing technology.

[0004] A high-cold region water conservancy concrete pore evolution monitoring device and monitoring method before initial setting is disclosed in Chinese Patent No. CN114577695B, which includes an environmental box, a concrete vibration table is arranged at the bottom of the environmental box, a concrete mixing device is arranged on the concrete vibration table, an air compressor, a humidifier and liquid nitrogen are arranged outside the environmental box, the air compressor is communicated with the environmental box through a pipeline A, the humidifier is communicated with the environmental box through a pipeline B, the inlet and outlet of the liquid nitrogen are communicated through a liquid nitrogen circulating pipeline, the liquid nitrogen circulating pipeline is arranged in the interior of the environmental box, a plurality of high-speed cameras are arranged around the environmental box, and a temperature, air pressure and humidity meter is arranged in the environmental box. The present application solves the problem that the existing device cannot obtain the pore evolution before the initial setting of the concrete.

[0005] The above patents all have the problem proposed in the background: the pore and fissure structure damage evolution law and the permeability enhancement mechanism of coal under the action of liquid nitrogen freezing and thawing are not clear. Therefore, it is necessary to study the pore and fissure damage evolution law and the permeability enhancement mechanism of coal under the action of liquid nitrogen freezing and thawing, to provide a theoretical basis for liquid nitrogen freezing and thawing for permeability enhancement of coal, and to provide a new method for coalbed methane extraction and reduction of coal mine gas disaster accidents. SUMMARY

[0006] The technical problem to be solved by the present application is to provide a multi-level network congestion control method for a smart computing center to solve the problems of the prior art.

[0007] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is:

[0008] The low-temperature liquid nitrogen action coal seam pore evolution prediction method comprises the following steps:

[0009] Step S1, obtain the three-dimensional pore structure of the coal sample by micro-CT scanning and calculate the initial pore parameters;

[0010] Step S2, collect the coal seam sample parameters and calibrate the key parameters of liquid nitrogen action through liquid nitrogen experiment, including pore freezing point, ice crystal growth rate and ice expansion coefficient;

[0011] Step S3, construct the pore evolution equation and solve the porosity prediction value and the pore size distribution function;

[0012] Step S4, define the pore type and calculate the pore type conversion;

[0013] Step S5, generate the final low-temperature liquid nitrogen action coal seam pore structure evolution prediction result.

[0014] Further, the step S1 specifically comprises the following steps:

[0015] Step S1.1, drill a standard cylindrical core sample from the target coal seam;

[0016] Step S1.2, use a micro-CT scanner to perform fault scanning on the sample to obtain a three-dimensional gray scale image data set;

[0017] Step S1.3, use software to process the image and reconstruct the pore network model, specifically including: threshold segmentation to distinguish between solid matrix and pores; pore space binary processing; constructing a three-dimensional pore topology network model;

[0018] Step S1.4, calculate the initial pore parameters according to the reconstructed pore network model;

[0019] The initial pore parameters include porosity, fractal dimension and pore internal surface area;

[0020] Wherein, the porosity is the percentage of the total volume of the sample; the fractal dimension is calculated based on the natural logarithm of the ratio of the maximum pore radius to the minimum pore radius, and is used to quantify the complexity of the pore structure; and the pore internal surface area is the total surface area of all pore walls per unit volume.

[0021] Further, the initial pore parameter calculation formula is:

[0022]

[0023] Wherein, φ0 represents the initial porosity of the coal sample, V pore represents the total volume of all pores in the coal sample, V total represents the total volume of the coal sample, D f represents the fractal dimension of the pore structure, which is used to describe the complexity of the pore structure, and the greater the value, the more complex the pore distribution, and respectively represent the maximum pore radius and the minimum pore radius, S pore represents the internal surface area of all pores per unit volume of the coal sample, N represents the total number of pores, and r p,i represents the radius of the i-th pore, L p,i represents the length of the i-th pore throat.

[0024] Further, the step S2 specifically comprises the following steps:

[0025] Liquid nitrogen circulation experiments are carried out in a low-temperature reaction kettle;

[0026] The actual freezing point of the nanopores is calculated, and the relationship between the pore radius and the freezing point is inversely proportional, which is calculated by the Gibbs-Thomson equation;

[0027] The growth rate of ice crystals is observed by a low-temperature scanning electron microscope, and the growth rate is calculated by dividing the change rate of the ice crystal radius by the square of the supercooling degree;

[0028] The ice expansion coefficient is determined by strain measurement, and the ice expansion coefficient is calculated by dividing the change in the volume of the sample by the product of the water saturation and the ice volume expansion rate.

[0029] Further, in the step S3, the specific formula of the dynamic pore evolution equation is:

[0030]

[0031] Wherein, represents the change rate of the porosity with time, α T represents the thermal cracking coefficient, which is used to represent the influence strength of temperature on thermal cracking, and ΔT represents the difference between the current temperature and the initial temperature, temperature gradient, t represents the duration of liquid nitrogen action, τ represents the saturation time of ice crystal growth, e eff represents the net stress that the coal sample bears, i.e. the total stress minus the pore pressure.

[0032] Further, in the step S3, the solution of the pore evolution equation specifically comprises the following steps:

[0033] discretize the coal body into a finite element grid of 1mm 3 ;

[0034] An explicit time step method is used for iterative calculation, wherein the time step is 0.1 seconds, and the updated porosity is equal to the current porosity plus the porosity change multiplied by the time step;

[0035] wherein the porosity change includes a thermal cracking amount, an ice expansion amount and a compression amount, wherein the thermal cracking amount represents the coal body cracking expansion amount caused by the temperature gradient, the ice expansion amount represents the volume increment generated by the ice crystal growth extrusion of the pore wall, and the compression amount represents the compression effect of the pore by the ground stress;

[0036] synchronously update the pore size distribution, and the updated pore distribution function is equal to the current pore distribution function plus the porosity distribution change multiplied by the time step;

[0037] wherein the porosity distribution change includes a temperature driving term and an ice expansion driving term, wherein the temperature driving term is proportional to the temperature difference and the temperature related exponential decay function, and the ice expansion driving term is proportional to the product of the negative fractal dimension power of the pore radius and the ice volume change rate.

[0038] Further, in the step S4, the calculation formula of the pore type conversion is:

[0039]

[0040] wherein, and respectively represent the micro-pore proportion, the meso-pore proportion and the macro-pore proportion at the moment m, X represents the pore type conversion matrix, and respectively represent the micro-pore proportion, the meso-pore proportion and the macro-pore proportion at the initial moment, and b represents the driving term vector.

[0041] wherein the micro-pore is a pore with a pore size less than 2nm, the meso-pore is a pore with a pore size of 2-50nm, and the macro-pore is a pore with a pore size greater than 50nm.

[0042] Further, in the pore type conversion matrix, the diagonal elements represent the pore type self-retention probability, and the non-diagonal elements represent the type conversion probability: wherein X[1][1] represents the proportion of the original micropore that is still micropore after conversion, X[1][2] represents the proportion of the original mesopore that is converted into micropore, X[1][3] represents the proportion of the original macropore that is converted into micropore, X[2][1] represents the proportion of the original micropore that is converted into mesopore, X[2][2] represents the proportion of the original mesopore that is still mesopore after conversion, X[2][3] represents the proportion of the original macropore that is converted into mesopore, X[3][1] represents the proportion of the original micropore that is directly converted into macropore, wherein the micropore is not allowed to directly jump to the macropore, so it is 0, X[3][2] represents the proportion of the original mesopore that is converted into macropore, and X[3][3] represents the proportion of the original macropore that is still macropore after conversion.

[0043] Further, the driving vector includes three driving factors of temperature difference, ice expansion and damage degree, wherein the micropore proportion change is negatively correlated with the temperature difference, the mesopore proportion change is positively correlated with the ice expansion, and the macropore proportion change is positively correlated with the damage degree.

[0044] Further, in the step S5, the final low-temperature liquid nitrogen effect, the pore structure evolution prediction result includes: the porosity prediction value calculated in the step S3, the pore size distribution function and the pore type conversion result calculated in the step S4.

[0045] Compared with the prior art, the present application has the following beneficial effects:

[0046] 1. The present application realizes high-precision prediction of the spatiotemporal evolution of porosity by fusing the micro-CT three-dimensional pore network and the liquid nitrogen phase change dynamics parameters, and establishing a thermal cracking-ice expansion-compression coupling equation.

[0047] 2. The present application adopts the method of combining numerical analysis and experimental research to construct a dynamic evolution prediction model of reservoir micro-pore structure under the disturbance of liquid ammonia injection, and reveals the action law and mechanism of low-temperature liquid nitrogen fluid on the adsorption performance of coal.

[0048] 3. The porosity prediction value, pore size distribution function and pore type conversion result calculated and predicted by the present application can guide the optimization of liquid nitrogen engineering parameters and early warning of fracture out-of-control risk. BRIEF DESCRIPTION OF DRAWINGS

[0049] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments made with reference to the accompanying drawings:

[0050] Figure 1 The flowchart of the embodiment of the present application is shown in the figure;

[0051] Figure 2 A schematic diagram of a heat-ice-force coupling mechanism for an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be described in detail below with reference to the drawings and specific embodiments.

[0053] As Figure 1 shown, the coal seam pore evolution prediction method under the action of low-temperature liquid nitrogen comprises the following steps:

[0054] Step S1, obtain the three-dimensional pore structure of the coal sample by micro-CT scanning and calculate the initial pore parameters;

[0055] Step S2, collect the coal seam sample parameters and calibrate the key parameters of liquid nitrogen action through liquid nitrogen experiments, including pore freezing point, ice crystal growth rate and ice expansion coefficient;

[0056] Step S3, construct the pore evolution equation and solve the porosity prediction value and the pore size distribution function;

[0057] Step S4, define the pore type and calculate the pore type conversion;

[0058] Step S5, generate the final coal seam pore structure evolution prediction result under the action of low-temperature liquid nitrogen.

[0059] Porosity: the percentage of the total volume of pores to the total volume of the sample;

[0060] Fractal dimension: the maximum / minimum value ratio based on the pore size distribution, quantifying the complexity of the pore structure (the larger the value, the more irregular the structure);

[0061] Pore internal surface area: the total of all pore wall surface areas per unit volume (determines the liquid nitrogen-coal contact efficiency).

[0062] The step S1 specifically comprises the following steps:

[0063] Step S1.1, drill a standard cylindrical core sample from the target coal seam;

[0064] Step S1.2, use a micro-CT scanner to perform fault scanning on the sample to obtain a three-dimensional gray scale image data set;

[0065] Step S1.3, use software to process the image and reconstruct the pore network model, specifically including: threshold segmentation to distinguish between solid matrix and pores; pore space binary processing; constructing a three-dimensional pore topology network model;

[0066] Step S1.4, calculate the initial pore parameters according to the reconstructed pore network model;

[0067] The initial pore parameters include porosity, fractal dimension, and pore internal surface area.

[0068] Pore freezing point calibration:

[0069] The actual freezing point of water in pores of different diameters is measured by low-temperature differential scanning calorimetry (DSC), and a "pore diameter-freezing point" relationship model is established (the smaller the pore diameter, the lower the freezing point).

[0070] Ice crystal growth rate calibration:

[0071] Liquid nitrogen is injected into a low-temperature reaction kettle, and the ice crystal growth process is observed in situ using a cryogenic electron microscope (Cryo-SEM), and the radial expansion speed of ice crystals under unit supercooling degree is calculated.

[0072] Ice expansion coefficient calibration:

[0073] Liquid nitrogen freeze-thaw experiments are carried out in a true triaxial pressure system, the volume expansion rate of the coal sample is measured by a strain sensor, and the ice expansion efficiency coefficient is calculated in combination with the water saturation.

[0074] The calculation formula of the initial pore parameters is:

[0075]

[0076] wherein φ0 represents the initial porosity of the coal seam sample, V pore represents the total volume of all pores in the coal seam sample, V total represents the total volume of the coal seam sample, D f represents the fractal dimension of the pore structure, which describes the complexity of the pore structure, and the larger the value, the more complex the pore distribution, and respectively represent the maximum pore radius and the minimum pore radius, S pore represents the internal surface area of all pores per unit volume of the coal sample, N represents the total number of pores, r p,i represents the radius of the i-th pore, L p,i represents the length of the i-th pore throat.

[0077] Coal seam sample basic parameter determination: provides necessary initial formation condition parameters for liquid nitrogen experiment (S2) and pore evolution modeling (S3-S4).

[0078] Key parameters and determination methods:

[0079] Initial water saturation: immediately after drilling the coal sample, it is sealed, and the laboratory uses the weighing method (drying method). The original mass of the coal sample is measured, and the dry coal mass is measured by drying at 105°C to a constant weight. The initial water saturation is calculated by the water mass / (pore volume*water density).

[0080] Initial pore pressure: laboratory simulated formation pressure recovery (triaxial pressure chamber) for net stress calculation.

[0081] Coal mechanical parameters: laboratory uniaxial / triaxial compression test to determine elastic modulus, Poisson's ratio, and uniaxial compressive strength.

[0082] The step S2 specifically comprises the following steps:

[0083] Liquid nitrogen circulation experiment in a low-temperature reaction kettle;

[0084] Calculate the actual freezing point of nanopores, and the calculation formula is:

[0085]

[0086] Wherein, T f represents the actual freezing point of water in a pore with a radius of r p , represents the standard freezing point of water corresponding to the Kelvin temperature, σ iw represents the ice-water interfacial tension, ρ ice represents the density of ice, L f represents the heat released per unit mass of water when it freezes, r p represents the pore radius;

[0087] Wherein, the specific parameter values are shown in Table 1:

[0088] Table 1

[0089]

[0090] Observe ice crystal growth by low-temperature scanning electron microscopy and calculate the growth rate, and the calculation formula is:

[0091]

[0092] Wherein, k g represents the ice crystal growth rate constant, which quantifies the speed of ice crystal growth, r ice represents the ice crystal radius, and T represents the real-time temperature of the environment in which the pore is located;

[0093] Determine the ice expansion coefficient by strain measurement, and the calculation formula is:

[0094]

[0095] Wherein, β represents the ice expansion coefficient, which quantifies the volume strain caused by unit water saturation and unit ice volume expansion rate, ε v represents the volume change of the coal seam sample measured by experiment, φ w represents the water saturation of the coal seam sample, i.e., the volume ratio of water in the pore, ΔV iceφice represents the volume expansion rate when water freezes, a fixed value of 0.09.

[0096] In the step S3, the specific formula of the dynamic pore evolution equation is as follows:

[0097]

[0098] wherein, φ represents the change rate of the porosity with time, α T φ represents the thermal cracking coefficient, a value of 0.018, used to represent the influence strength of the temperature on the thermal cracking, ΔT represents the difference between the current temperature and the initial temperature, φ represents the temperature gradient, t represents the duration of the liquid nitrogen action, τ represents the saturation time of the ice crystal growth, e eff φ represents the net stress borne by the coal sample, i.e., the total stress minus the pore pressure.

[0099] The thermal cracking term: the pore expansion caused by the temperature gradient (positively correlated with the temperature change amount and the gradient strength);

[0100] The ice expansion term: the pore volume increment caused by the ice crystal growth (positively correlated with the ice expansion coefficient, the water saturation, and the ice growth rate);

[0101] The compression term: the pore closure caused by the ground stress (negatively correlated with the effective stress strength).

[0102] In the step S3, the solution of the pore evolution equation specifically includes the following steps:

[0103] The coal body is discretized into a finite element grid of 1mm 3 ;

[0104] An explicit time step method is used for the iterative calculation, wherein the time step is 0.1 second, and the calculation formula is as follows:

[0105]

[0106] wherein, φ n+1 n+1 represents the predicted value of the porosity at the n+1 time, φ n n represents the porosity at the current time, i.e., the n time, ΔT n represents the temperature difference at the current time, φ represents the temperature gradient at the current time, φ represents the net stress borne by the coal sample at the current time, and Δt represents the time step;

[0107] The pore size distribution is updated synchronously, and the calculation formula is as follows:

[0108]

[0109] wherein, The pore size distribution function at the n+1 moment, The pore size distribution function at the current moment, R represents the gas constant, The ice volume change rate.

[0110] In the step S4, the calculation formula of the pore type conversion is:

[0111]

[0112] Wherein, And The micropore ratio, mesopore ratio and macropore ratio at the m moment are represented by X, respectively, and X represents the pore type conversion matrix. And The micropore ratio, mesopore ratio and macropore ratio at the initial moment are represented by b, respectively, and b represents the driving term vector.

[0113] Wherein, micropore is the pore with pore size <2nm, mesopore is the pore with pore size 2-50nm, and macropore is the pore with pore size >50nm.

[0114] In the pore type conversion calculation formula, the specific formula of the pore type conversion matrix is:

[0115]

[0116] The calculation formula of the driving term vector is:

[0117]

[0118] Wherein, D d Indicates the damage degree, which describes the damage degree of coal body caused by thermal stress.

[0119] The calculation formula of the damage degree is:

[0120]

[0121] Wherein, C represents the damage accumulation rate constant, and the typical value is 0.28, T ref Indicates the temperature scale factor, and the typical value is 293K, that is, 20℃.

[0122] In the step S5, the final low-temperature liquid nitrogen effect under the coal seam pore structure evolution prediction result includes: the porosity prediction value calculated in the step S3, the pore size distribution function and the pore type conversion result calculated in the step S4.

[0123] Wherein, the specific setting value of the pore type conversion matrix is shown in Table 2:

[0124] Table 2

[0125]

[0126]

[0127] As Figure 2 shown, the heat-ice-force coupling mechanism diagram:

[0128] 1. Liquid nitrogen is injected into the coal seam, causing a sudden temperature drop (-196°C)

[0129] 2. Low-temperature activated phase change, acting in two directions:

[0130] Pore water phase change to ice → volume expansion → generates frost heaving force

[0131] Non-uniform shrinkage of coal body → thermal stress cracking → new fractures are formed

[0132] 3. Frost heaving force and thermal stress synergistically drive pore expansion:

[0133] Original pore diameter increases, microcracks are connected to form seepage channels

[0134] 4. Pore structure optimization significantly improves adsorption / diffusion capacity:

[0135] Methane desorption rate increases, gas diffusion efficiency enhances.

[0136] The liquid nitrogen-coal rock interaction experiment platform architecture of the embodiment:

[0137] 1. The liquid nitrogen supply system delivers -196°C liquid nitrogen to the low-temperature reaction kettle;

[0138] 2. The coal rock sample in the reaction kettle produces thermal response due to sudden temperature drop;

[0139] 3. Low-temperature triggered phase change, double-path driven pore structure evolution;

[0140] 4. Real-time monitoring system synchronously collects:

[0141] Distributed optical fiber → temperature field spatial distribution, strain gauge → volume expansion, microseismic sensor → fracture development event;

[0142] 5. Imaging analysis system implements final state detection:

[0143] Micro-CT scanning → three-dimensional pore reconstruction, low-temperature electron microscope → ice crystal morphology observation, NMR nuclear magnetic resonance → pore size distribution inversion.

[0144] Experimental workflow:

[0145] Sample loading: Put 50x100mm coal sample into the reaction kettle, install strain gauge and optical fiber;

[0146] Initial scanning: Perform micro-CT baseline scanning to obtain initial pore structure;

[0147] Liquid nitrogen injection: inject liquid nitrogen at a set flow rate (e.g. 3 L / min) while DTS monitoring is on;

[0148] Dynamic monitoring: record temperature / strain field every 5 minutes, trigger cryo-TEM rapid imaging when temperature <-100℃;

[0149] Process scanning: perform micro-CT in-situ scanning at t=10 / 30 / 60 min, freeze the sample for pore size distribution measurement in NMR;

[0150] Data analysis: compare the change of porosity before and after freeze-thaw, establish the quantitative relationship between ice crystal growth and pore expansion.

[0151] Experimental comparison and verification:

[0152] Compare the predicted porosity spatial distribution map with the measured porosity after freeze-thaw by CT scanning, calculate the relative error: porosity error = |predicted value - measured value| / measured value x 100%;

[0153] Requirements: average error ≤8%, and maximum local error ≤15%;

[0154] Optimization mechanism: when the average error >8%, automatically adjust the ice swelling coefficient.

[0155] The examples described in the present application are only to describe the preferred embodiments of the present application, and do not limit the concept and scope of the present application. Without departing from the design idea of the present application, various modifications and improvements of the technical solutions of the present application made by the engineering and technical personnel in the field shall fall within the protection scope of the present application.

Claims

1. A method for predicting the evolution of coal bed porosity under the action of low-temperature liquid nitrogen, characterized in that, It comprises the following steps: Step S1, obtain the three-dimensional pore structure of the coal sample by micro-CT scanning and calculate the initial pore parameters; Step S2, collect the coal seam sample parameters and calibrate the key parameters of liquid nitrogen action through liquid nitrogen experiments, including pore freezing point, ice crystal growth rate and ice expansion coefficient; Step S3, construct the pore evolution equation and solve the porosity prediction value and pore size distribution function; Step S4, define the pore type and calculate the pore type conversion; Step S5, generate the final prediction result of the pore structure evolution of the coal seam under the action of low-temperature liquid nitrogen.

2. The method of claim 1, wherein, The step S1 specifically comprises the following steps: Step S1.1, drill a standard cylindrical core sample from the target coal seam; Step S1.2, use a micro-CT scanner to perform fault scanning on the sample to obtain a three-dimensional gray scale image data set; Step S1.3, use software to process the image and reconstruct the pore network model, specifically including: threshold segmentation to distinguish between solid matrix and pores; pore space binary processing; constructing a three-dimensional pore topology network model; Step S1.4, calculate the initial pore parameters according to the reconstructed pore network model; The initial pore parameters include: porosity, fractal dimension and pore internal surface area; The porosity is the percentage of the total pore volume to the total sample volume; the fractal dimension is calculated based on the natural logarithm of the ratio of the maximum pore radius to the minimum pore radius, which is used to quantify the complexity of the pore structure; the pore internal surface area is the total of the surface area of all pore walls per unit volume.

3. The method of claim 2, wherein, The calculation formula of the initial pore parameters is: where φ0represents the initial porosity of the coal sample, V pore represents the total volume of all pores in the coal sample, V total represents the total volume of the coal sample, D f represents the fractal dimension of the pore structure, which is used to describe the complexity of the pore structure, and the larger the value, the more complex the pore distribution, and respectively represent the maximum pore radius and the minimum pore radius, S pore represents the internal surface area of all pores per unit volume of coal sample, N represents the total number of pores, r p,i represents the radius of the ith pore, L p,i represents the length of the ith pore throat.

4. The method of claim 1, wherein, The step S2 specifically comprises the following steps: Perform liquid nitrogen circulation experiments in a low-temperature reaction kettle; Calculate the actual freezing point of the nanopore, which is inversely proportional to the pore radius through the Gibbs-Thomson equation; Observe the ice crystal growth through a low-temperature scanning electron microscope and calculate the growth rate, which is calculated by dividing the change rate of the ice crystal radius by the square of the supercooling degree; Determine the ice expansion coefficient through strain measurement, which is calculated by dividing the sample volume change by the product of the water saturation and the ice volume expansion rate.

5. The method of claim 4, wherein, In step S3, the specific formula of the dynamic pore evolution equation is: wherein, represents the rate of change of porosity with time, a T represents the thermal cracking coefficient, which is used to characterize the strength of the effect of temperature on thermal cracking, ΔT represents the difference between the current temperature and the initial temperature, represents the temperature gradient, t represents the duration of the action of liquid nitrogen, τ represents the saturation time of ice crystal growth, e eff represents the net stress to which the coal sample is subjected, i.e. the total stress minus the pore pressure.

6. The method of claim 5, wherein, In step S3, the pore evolution equation solving specifically comprises the following steps: The coal body is discretized into 1 mm 3 finite element meshes; Use explicit time stepping method for iterative calculation, where the time step is 0.1 seconds, and the updated porosity is equal to the current porosity plus the pore volume change multiplied by the time step; The pore volume change includes thermal cracking amount, ice expansion amount and compression amount, where the thermal cracking amount represents the coal body cracking expansion amount caused by temperature gradient, the ice expansion amount represents the volume increment generated by the ice crystal growth pressing the pore wall, and the compression amount represents the compression effect of the pore by the ground stress; Synchronously update the pore size distribution, and the updated pore distribution function is equal to the current pore distribution function plus the pore volume distribution change multiplied by the time step; The pore volume distribution change includes: temperature driving term and ice expansion driving term, where the temperature driving term is proportional to the temperature difference and the temperature related exponential decay function, and the ice expansion driving term is proportional to the negative fractal dimension power of the pore radius and the product of the ice volume change rate.

7. The method of claim 6, wherein, In step S4, the calculation formula of the pore type conversion is: wherein, and respectively represent the micropore ratio, the mesopore ratio and the macropore ratio at time m, X represents the pore type transition matrix, and respectively represent the micropore ratio, the mesopore ratio and the macropore ratio at the initial time, b represents the driving term vector; The micropore is a pore with a pore size less than 2 nm, the mesopore is a pore with a pore size of 2-50 nm, and the macropore is a pore with a pore size greater than 50 nm.

8. The method of claim 7, wherein, In the pore type conversion matrix, the diagonal elements represent the pore type self-retention probability, and the non-diagonal elements represent the type conversion probability: wherein X[1][1] represents the proportion of micropores that remain micropores after conversion, X[1][2] represents the proportion of mesopores that become micropores after conversion, X[1][3] represents the proportion of macropores that become micropores after conversion, X[2][1] represents the proportion of micropores that become mesopores after conversion, X[2][2] represents the proportion of mesopores that remain mesopores after conversion, X[2][3] represents the proportion of macropores that become mesopores after conversion, X[3][1] represents the proportion of micropores that directly become macropores after conversion, wherein micropores are not allowed to directly jump to macropores, so it is 0, X[3][2] represents the proportion of mesopores that become macropores after conversion, and X[3][3] represents the proportion of macropores that remain macropores after conversion.

9. The method of claim 8, wherein, The driving vector includes three driving factors of temperature difference, ice expansion and damage degree, wherein the micropore proportion change is negatively correlated with the temperature difference, the mesopore proportion change is positively correlated with the ice expansion, and the macropore proportion change is positively correlated with the damage degree.

10. The method of claim 9, wherein, In the step S5, the final low-temperature liquid nitrogen pore structure evolution prediction result includes: the porosity prediction value calculated in the step S3, the pore size distribution function, and the pore type conversion result calculated in the step S4.

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