Rock mechanical parameter determination method based on nanoindentation experiment

Abstract

The invention discloses a rock mechanical parameter determination method based on a nanoindentation experiment, which comprises the following steps: S1, randomly selecting a small part of a target rock to carry out the nanoindentation experiment, and testing the elastic modulus, hardness and fracture toughness micromechanical parameters of the target rock; s2, constructing a multi-scale structure model of the target rock by considering internal cracks, pores, organic matters and proportion factors of each mineral component of the target rock based on the micromechanics parameters obtained by the nanoindentation experiment; s3, on the basis of the multi-scale structure model of the target rock, performing multi-scale transformation by utilizing a reformed group theory to obtain a simplified structure model of the target rock, and calculating mechanical parameters of the simplified structure model; and S4, carrying out a macromechanics experiment on the target rock, calculating mechanical parameters, and then checking the reliability of the method for calculating the mechanical parameters of the target rock based on the nanoindentation experiment. According to the method, the efficiency and precision of calculating the macromechanical parameters of the rock can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of rock mass engineering, and in particular to a method for determining rock mechanics parameters based on nano-indentation experiments. Background Art

[0002] In the field of rock engineering, mechanical parameters such as uniaxial compressive strength, elastic modulus and fracture toughness of rocks are basic indicators for evaluating the stability of rock structures, and are crucial for construction scheme design, engineering structure optimization and geological disaster prediction. However, under special geological conditions, the collection, preparation and testing of rock samples will encounter many challenges. As a natural multiphase material, rock has a complex internal microstructure, including cracks, pores, organic matter and various mineral components, showing significant heterogeneity and multi-scale characteristics, which makes the mechanical behavior of rock extremely complex and difficult to effectively predict.

[0003] Although traditional testing methods can reveal the macroscopic mechanical behavior of rock materials to a certain extent, they often ignore the influence of microstructure on macroscopic mechanical behavior, such as microscopic effects such as cracks, pores and interactions between minerals. Therefore, it is crucial to fully consider the heterogeneity and multi-scale characteristics of rocks in determining rock mechanical parameters. Summary of the invention

[0004] In order to overcome the above technical problems, the present invention proposes a method for determining rock mechanics parameters based on nanoindentation experiments. This method not only overcomes the limitations of traditional tests, but also improves the efficiency and accuracy of calculating rock macroscopic mechanical parameters, providing new ideas for rock mechanics research and engineering practice. This method has broad application prospects in oil and gas exploration and development, tunnel and underground engineering stability analysis, and nuclear waste disposal repository design.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for determining rock mechanics parameters based on nanoindentation experiments comprises the following steps:

[0007] S1: A small part of the target rock is randomly selected for nanoindentation experiment to test its micromechanical parameters, including elastic modulus, hardness and fracture toughness;

[0008] S2: Based on the micromechanical parameters, considering the internal cracks, pores, organic matter and the proportion of each mineral component of the target rock block, a multi-scale structural model (M model) of the target rock block is constructed;

[0009] S3: Based on the multi-scale structural model (M model) of the target rock block, the renormalization group theory is used to perform multi-scale transformation to obtain the simplified structural model (S model) of the target rock block, and the mechanical parameters of the simplified structural model (S model) are calculated;

[0010] S4: Conduct macroscopic mechanical experiments on the target rock and calculate the mechanical parameters, and then verify the reliability of the method for calculating the mechanical parameters of the target rock based on nanoindentation experiments.

[0011] This method will be widely used in various rock engineering practices, as described below: In oil and gas exploration and development, it can optimize mining strategies and improve resource recovery rates; in the stability analysis of tunnels and underground projects, this method can more comprehensively consider the heterogeneity and multi-scale characteristics of rocks and improve analysis accuracy; in the design of nuclear waste disposal repositories, it is of great significance for evaluating the long-term safety of rock barriers.

[0012] S1, specifically, randomly selects a small portion of the target rock sample, and processes it to meet the nanoindentation test standard. Then, a nanoindentation test is performed on the sample using a nanoindentation tester, and the load-displacement curve data is recorded in detail. Based on the data, the key micromechanical parameters such as the hardness (H) and elastic modulus (E) of the minerals in the rock are calculated and extracted. The hardness H m and elastic modulus E m The calculation is based on the following formula:

[0013]

[0014] Among them, P max is the maximum indentation load, A is the contact area between the indenter and the specimen, β is the geometric parameter of the indenter, and S is the contact stiffness.

[0015] S2, specifically, is as follows: based on X-ray diffraction and CT scanning data, a three-dimensional model of a target rock block containing mineral particles, cracks, pores and organic particles is constructed using Abaqus, and material properties are randomly assigned in Abaqus through a Python script to realize the construction of a multi-scale structural model (M model);

[0016] The specific construction process includes:

[0017] (1) Construction of mineral particle model: Based on the X-ray diffraction results and the actual content of each mineral particle, a three-dimensional model of the target rock block containing mineral particles is constructed using Abaqus modeling software;

[0018] (2) Construction of fracture and pore model: The fracture and pore information analyzed from the CT scanning data is imported into the three-dimensional model of the target rock block containing mineral particles, and then a three-dimensional model of the target rock block containing fracture and pore structure is constructed;

[0019] (3) Embedding of organic particles: Based on the morphology and spatial distribution of organic matter analyzed from the CT scanning data, organic particles are embedded in the corresponding positions in the model constructed in (2) above to complete the overall construction of the three-dimensional model of the target rock block;

[0020] (4) Construction of multiscale structural model (M model): In order to realistically simulate the heterogeneity of the internal structure of the rock and realize the random distribution of material properties within the three-dimensional model grid of the target rock block, the Abaqus model software is imported by writing a Python script and the script is run to realize the construction of the multiscale structural model (M model) of the rock.

[0021] The S3 is specifically: based on the multi-scale structural model (M model) of the target rock block, using the renormalization group theory to perform in-depth cross-scale analysis and calculation;

[0022] First, the scale level division is clarified, and the model is subdivided into different levels such as microscopic (mineral particles), mesoscopic (cracks, pore networks) and macroscopic (whole rock blocks);

[0023] Secondly, the gradual merging and renormalization process is initiated to gradually integrate adjacent scale units starting from the smallest scale. At the same time, with the help of the "coarse-graining" strategy of the renormalization group theory, the microscopic details are abstracted into high-level representative parameters to achieve model simplification without losing key information. After multiple merging and renormalization iterations, a series of simplified structural models (S models) that match the target rock structure are generated. Finally, mechanical loading simulation is performed on these simplified structural models (S models) to accurately calculate the mechanical parameters of the rock.

[0024] The S4 is specifically: using a universal testing machine to carry out macroscopic mechanical experiments of tension, compression, and three-point bending on the target rock block, and then calculating its macroscopic mechanical parameters, and verifying the reliability of the method for calculating the mechanical parameters of the multi-scale structural model (M model) of the target rock block based on the nanoindentation experiment.

[0025] Beneficial effects of the present invention:

[0026] Step S1 meets the high-precision requirements of the nanoindentation experiment by finely processing a small portion of the target rock. The nanoindentation tester is used to accurately record the load-displacement curve, thereby calculating the hardness (H), elastic modulus (E) and other key micromechanical parameters of the mineral, providing basic data for the subsequent construction of the multi-scale structural model (M model) and the calculation of mechanical parameters.

[0027] Step S2 combines X-ray diffraction and CT scanning technology to deeply analyze the complex structure inside the rock, such as cracks, pores, organic matter distribution and mineral composition ratio. At the same time, combined with nanoindentation experimental data, comprehensive consideration of various key factors, and the construction of an accurate multi-scale structural model (M model) is based on both microscopic characteristics and macroscopic structures, fully considering the heterogeneity of rocks.

[0028] Step S3 uses the renormalization group theory to perform multi-scale analysis. Through gradual merging and renormalization, the interaction and mechanical transfer effects between internal units of the rock mass are taken into account, significantly improving the accuracy of calculation of micro-to-macroscopic mechanical parameters.

[0029] In step S4, macroscopic mechanical experiments are used to obtain mechanical parameters, which are compared and verified with the calculated values ​​of the multi-scale structural model (M model). This effectively verifies the reliability of the model's mechanical parameter calculation method and ensures the scientificity and rigor of the research process.

[0030] The present invention has broad application prospects in rock engineering fields such as oil and gas exploration, tunnel engineering, and nuclear waste disposal repository design. It can optimize mining strategies, improve analysis accuracy, and effectively evaluate the long-term safety of rock barrier layers, providing solid technical support for related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Flow chart of the method of the present invention.

[0032] Figure 2 Photograph of the micro-scale nano-indentation specimen of the fabrication experiment of the present invention.

[0033] Figure 3 The experimental instrument of the present invention is a nanoindenter.

[0034] Figure 4 Microscale load-displacement curves of the present invention.

[0035] Figure 5 X-ray diffraction pattern of the nanoindentation sample of the present invention.

[0036] Figure 6 Diagram of the rock multi-scale structural model (M model) constructed by the present invention.

[0037] Figure 7 The present invention uses the renormalization group theory to achieve a schematic diagram of structural model simplification (S model).

[0038] Figure 8 Schematic diagram of the merging result based on the renormalization rule of "the minority obeys the majority" in an embodiment of the present invention.

[0039] Fig. 9 Comparison diagram of the macroscopic rock mechanical parameters of the present invention and the renormalized mechanical parameters of the multi-scale structural model (M model). DETAILED DESCRIPTION

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0041] like Figure 1 As shown in the figure, it is a flow chart of the method of the present invention, a method for determining rock mechanical parameters based on nanoindentation experiment, comprising the following steps:

[0042] Rock nanoindentation experiment:

[0043] (1) Randomly select small samples of the target rock blocks and finely process them to meet the nanoindentation test standards. Sample preparation includes sampling and cutting, cold mounting and fixation, step-by-step grinding and polishing until smooth, and ultrasonic cleaning. The specific steps are as follows: First, cut a sample of 25 mm in length, 25 mm in width, and 10 mm in height from the core, then use sandpaper of different finenesses to grind step by step, and polish with diamond suspension. Finally, after ultrasonic cleaning and vacuum drying, the sample is tested by atomic force microscopy to ensure that its roughness meets the standard.

[0044] (2) Use a nanoindentation tester to perform nanoindentation experiments on rock samples, record the load-displacement curve, and calculate and obtain the micromechanical parameters of the rock's constituent minerals, such as hardness (H) and elastic modulus (E). m and elastic modulus E m The calculation is based on the following formula:

[0045]

[0046] Among them, P max is the maximum indentation load, A is the contact area between the indenter and the specimen, β is the geometric parameter of the indenter, and S is the contact stiffness.

[0047] Multi-scale rock modeling:

[0048] Based on X-ray diffraction and CT scanning data, Abaqus was used to construct a three-dimensional model of the target rock block containing mineral particles, cracks, pores and organic particles. The material properties were randomly assigned in Abaqus through Python scripts to realize the construction of a multi-scale structural model (M model) of the target rock block.

[0049] Applications of Renormalization Group Theory:

[0050] (1) Based on the multi-scale structural model (M model) of the target rock mass, the renormalization group theory is used to merge adjacent microscopic units into larger units (such as microscopic cracks or pores) by considering the interaction and mechanical transmission effect between different units within the rock mass. (where N is the number of microscopic units, E i is the effective characteristic of the i-th micro-unit) to calculate the effective characteristics of the merged unit. Repeat the above coarse-graining process, continuously update the renormalization parameters, and gradually advance to a larger scale.

[0051] (2) In the renormalization process, a series of simplified structural models (S models) similar to the target rock structure are obtained by using multi-scale transformation, specifically: the meshing step is used to mesh the target rock to obtain a unit cell aggregate, where each cell has only one material property. The aggregate represents the target rock, and the target rock after meshing is regarded as an aggregate of cellular structures; the renormalization step is used to treat the target rock as the 0th level structure, starting from the 0th level, and renormalizing step by step to obtain a series of hierarchical structures. When the Nth level structure is obtained, the renormalization ends, where N is a positive integer. The simplified structural model (S model) is obtained according to the renormalization group theory, and the rock mechanical parameters of the simplified structure (S model) are calculated.

[0052] Check the reliability of the calculation results:

[0053] (1) Conduct macroscopic mechanical experiments such as tension, compression, and three-point bending on the target rock and calculate the macroscopic mechanical parameters. The experimental steps are briefly described as follows:

[0054] Compression test: First, select representative rock samples and process them into standard 50×100mm cylinders to ensure that the surface is smooth and defect-free. Then, place the sample between the fixtures of the universal testing machine to ensure centering to prevent eccentric loading. Finally, after applying a preload to eliminate the gap, load at a constant rate, and simultaneously record the loading force and deformation. In the elastic stage, draw the stress-strain curve and calculate the slope to obtain the elastic modulus. At the same time, monitor and record the longitudinal and transverse strain data, and calculate the Poisson's ratio. Continue loading until the sample fails, record the maximum pressure, and calculate the compressive strength (i.e., the maximum pressure divided by the original cross-sectional area of ​​the sample).

[0055] Tensile test: First, select representative rock blocks and process them into dumbbell-shaped or dog-bone-shaped tensile specimens, and accurately install them in the tensile fixture of the universal testing machine to ensure correct alignment. Then, apply tensile force at a steady rate until the specimen breaks, and immediately record the maximum tensile force value. Based on this, the tensile strength is obtained by dividing the maximum tensile force by the original cross-sectional area of ​​the specimen.

[0056] Three-point bending test: First, select representative rock blocks and process them into samples with prefabricated cracks, place them in the three-point bending fixture of the universal testing machine, and then load them at a constant rate until the cracks expand and cause fracture. Record the load and displacement data throughout the loading process, and based on these data and the principles of fracture mechanics, calculate the specific value of fracture toughness.

[0057] (2) Carry out macroscopic mechanical experiments on the target rock and calculate the mechanical parameters. Then, verify the reliability of the method for calculating the mechanical parameters of the target rock based on the nanoindentation experiment. This method will be widely used in various rock engineering practices. The specific explanations are as follows: In oil and gas exploration and development, it can optimize mining strategies and improve resource recovery rates. In the stability analysis of tunnels and underground projects, this method can more comprehensively consider the heterogeneity and multi-scale characteristics of rocks and improve the analysis accuracy. In the design of nuclear waste disposal repositories, it is of great significance for evaluating the long-term safety of rock barriers.

[0058] like Figure 2 As shown in the figure, it is a photo of the rock micro-scale nano-indentation sample prepared in the present invention, and the mechanical properties of the micro-scale sample are measured by the nano-indentation method; in this embodiment, the indentation experiment is carried out using a diamond Bosch indenter to study the mechanical properties of the marble micro-scale sample, the angle between the center line of the indenter and each edge is 77.05°, and the tip radius is about 40nm.

[0059] like Figure 3 The figure shows the nanoindentation test instrument TI990 of the present invention, which is based on Bruker's Performech II advanced control module and has made significant progress in precise control and test bandwidth, test flexibility, applicability, sensitivity, measurement accuracy and system modularity. The powerful basic configuration of TI990 includes quantitative nanoindentation and microindentation, nanoscratch, nanofriction and wear, high-resolution in-situ scanning probe microscope (SPM) imaging, dynamic nanoindentation and high-speed performance imaging.

[0060] The process of indentation test includes: loading stage, constant load stage and unloading stage. A rigid indenter with a regular shape is pressed into the surface of the test sample under the action of gradually increasing external force. After the external force reaches 2000mN, the external force is gradually removed. During the loading and unloading process, the displacement h of the indenter and the load F borne by the indenter are recorded to obtain the load-displacement curve of the sample, such as Figure 4 As shown. The indentation hardness and elastic modulus of the sample are calculated according to the Oliver-Pharr method. Hardness H m and elastic modulus E m Satisfy the following calculation formula:

[0061]

[0062] Among them, P max is the maximum indentation load, A is the contact area between the indenter and the sample, β is the geometric parameter of the indenter, and S is the contact stiffness. The microscopic mineral mechanics parameters obtained by calculation provide solid data support for the construction of the multi-scale structural model (M model).

[0063] like Figure 5The figure shows the X-ray diffraction diagram of the nanoindentation sample of the present invention, which intuitively shows the mineral components and their proportions in the marble, mainly including 14.2% dolomite, 85.5% calcite and trace amounts of organic matter. These data not only accurately define the mineral composition and content of the rock, but also further strengthen the data support for the construction of the multi-scale structural model (M model).

[0064] like Figure 6 The figure shows a schematic diagram of the rock multi-scale structural model proposed in the present invention. The model is based on X-ray diffraction and CT scanning data, and uses Abaqus to construct a three-dimensional model of the target rock block containing mineral particles, cracks, pores and organic particles. The material properties are randomly assigned in Abaqus through Python scripts to achieve the construction of a multi-scale structural model (M model). The specific construction process includes:

[0065] (1) Construction of mineral particle model: Based on the X-ray diffraction results and the actual content of each mineral particle, a three-dimensional model of the target rock block containing mineral particles is constructed using Abaqus modeling software;

[0066] (2) Construction of fracture and pore model: The fracture and pore information analyzed from the CT scanning data is imported into the three-dimensional model of the target rock block containing mineral particles, and then a three-dimensional model of the target rock block containing fracture and pore structure is constructed;

[0067] (3) Embedding of organic particles: Based on the morphology and spatial distribution of organic matter analyzed from the CT scanning data, organic particles are embedded in the corresponding positions in the model constructed in (2) above to complete the overall construction of the three-dimensional model of the target rock block;

[0068] (4) Construction of multiscale structural model (M model): In order to realistically simulate the heterogeneity of the internal structure of the rock and realize the random distribution of material properties within the three-dimensional model grid of the target rock block, the Abaqus model software is imported by writing a Python script and the script is run to realize the construction of the multiscale structural model (M model) of the rock.

[0069] Python script example:

[0070] import random

[0071] from abaqus import*

[0072] from abaqusConstants import*

[0073] #Get the unit collection in the model

[0074] model_name = 'Model-1'

[0075] part_name = 'Part-1'

[0076] assembly_name = 'Assembly-1'

[0077] instance_name = 'Instance-1'

[0078] myModel=mdb.models[model_name]

[0079] myPart=myModel.parts[part_name]

[0080] myAssembly=myModel.rootAssembly

[0081] myInstance=myAssembly.instances[instance_name]

[0082] #Get the unit collection

[0083] elements = myPart.elements

[0084] #Define material property range

[0085] E_min, E_max = 1e9, 5e9# Elastic modulus range

[0086] nu_min,nu_max=0.2,0.4#Poisson's ratio range

[0087] #Randomly assign material properties

[0088] for element in elements:

[0089] E=random.uniform(E_min,E_max)

[0090] nu=random.uniform(nu_min,nu_max)

[0091] element.MaterialOrientation(region=element.getRegion(), orientationType=SYST EM, localCsys=None, fieldName=”, additionalRotationType=ROTATION_NONE, angle=0.0, additionalRotationField=”, stackDirection=STACK_3)

[0092] element.SectionAssignment(offset=0.0,offsetField=”,offsetType=MIDDLE_SUR FACE,region=element.getRegion())

[0093] element.setValues(material='Material-1',E=E,nu=nu)

[0094] This script ensures automation and randomness in the model building process, which can improve the efficiency and accuracy of model building.

[0095] like Figure 7 As shown, it is a schematic diagram of the present invention using the renormalization group theory to achieve structural model simplification, which is the core of this patent and mainly includes the following steps:

[0096] (1) Meshing step: It is used to mesh the target object to obtain a collection of cells, where each cell has only one material property. This collection represents the target object. The target object after meshing is regarded as a collection of cellular structures. A cell is a simple collection of fixed shapes composed of a finite number of cells, and its dimensions and material properties are the same as those of the target rock. The cell scale is much smaller than the target rock scale, so the target rock after meshing can be regarded as a collection of cells or a collection of cells. The setting of the cell is mainly the scale. When the scale is determined, the corresponding number of cells will also be determined.

[0097] (2) Renormalization step: It is used to treat the target object as the 0th level structure, starting from the 0th level, and renormalizing step by step to obtain a series of hierarchical structures. When the Nth level structure is obtained, the renormalization ends, where N is a positive integer. The renormalization group is essentially a coarsening of the target object to obtain a simplified structure similar to the target object structure. Its basis is the cell and the renormalization rule. The renormalization rule is to regularize a cell into a unit cell. The commonly used rule is "the minority obeys the majority". Figure 8For a two-dimensional cell structure with a mesoscale of 3, the renormalization result is performed using the rule of "the minority obeys the majority". The specific steps are as follows:

[0098] S2.1. Let n be greater than or equal to 0 and less than N. Starting from level 0, divide the n-th level structure into different combinations of cells according to the scale of the cells.

[0099] S2.2. According to the renormalization rule of the previous step, each cell in the n-th level structure is regularized into a unit cell, thereby obtaining the n+1-th level structure.

[0100] S2.3, n=n+1.

[0101] S2.4, repeating steps S2.1-S2.3, and obtaining the 1st, 2nd, ... Nth level structures in turn, where the value of N is not fixed, and its range is between 2 and 7. Based on renormalization, the 1st to Nth level structures are gradually simplified, but they are all similar to the 0th level structure.

[0102] In order to verify the reliability of the method for calculating rock mechanical parameters based on nanoindentation experiments, four different marble samples were selected in this study: marble A (sample 1), marble B (sample 2), marble C (sample 3) and marble D (sample 4). First, the mineral composition of these four marbles was identified, and thin sections were made for detailed rock and mineral analysis under a microscope. The results showed that the average particle size of sample A was 0.24 mm, and the main components were 14.2% dolomite, 85.5% calcite and 0.3% organic matter; the average particle size of sample B was 0.52 mm, with dolomite accounting for 80%, tremolite accounting for 15%, and containing a small amount of calcite and muscovite, both belonging to dolomite marble; the average particle size of sample C was 0.48 mm, and the calcite content exceeded 95%; the average particle size of sample D was the smallest, at 0.08 mm, and the calcite content was as high as 99%. Subsequently, macroscopic mechanical experiments were conducted to determine key mechanical parameters of marble, such as elastic modulus and Poisson's ratio (see Table 1). At the same time, the present invention was used to calculate some results of mechanical parameters of marble (see Table 2). Fig. 9 The comparison results of macroscopic rock mechanical parameters and mechanical parameters renormalized by multi-scale model are presented intuitively. Fig. 9 (a) shows the comparison of compressive strength; Fig. 9 (b) shows the comparison of tensile strength; Fig. 9 (c) shows the comparison of elastic modulus; Fig. 9 (d) shows the comparison of fracture toughness; Fig. 9 (e) shows the comparison of Poisson's ratio. Through comparative analysis, not only the accuracy and reliability of the present invention in calculating rock mechanics parameters are clearly verified, but also its credibility in practical applications is enhanced.

[0103] Table 1 Macroscopic mechanical parameters of marble

[0104]

[0105] Table 2 Mechanical parameters after renormalization

[0106]

Claims

1. A method for determining rock mechanical parameters based on nanoindentation experiments, characterized in that: The following steps are involved: S1: A small part of the target rock is randomly selected for nanoindentation experiment to test its micromechanical parameters, including elastic modulus, hardness and fracture toughness; S2: Based on the micromechanical parameters, considering the internal cracks, pores, organic matter and the proportion of each mineral component of the target rock block, a multi-scale structural model (M model) of the target rock block is constructed; S3: Based on the multi-scale structural model (M model) of the target rock block, the renormalization group theory is used to perform multi-scale transformation to obtain the simplified structural model (S model) of the target rock block, and the mechanical parameters of the simplified structural model (S model) are calculated; S4: Conduct macroscopic mechanical experiments on the target rock and calculate the mechanical parameters, and then verify the reliability of the method for calculating the mechanical parameters of the target rock based on nanoindentation experiments.

2. A method for determining rock mechanics parameters based on nanoindentation experiment according to claim 1, characterized in that: S1, specifically, randomly selects a small portion of the target rock sample, and processes it to meet the nanoindentation test standard. Then, a nanoindentation test is performed on the sample using a nanoindentation tester, and the load-displacement curve data is recorded in detail. Based on the data, the key micromechanical parameters such as the hardness (H) and elastic modulus (E) of the minerals in the rock are calculated and extracted. The hardness H m and elastic modulus E m The calculation is based on the following formula: Among them, P max is the maximum indentation load, A is the contact area between the indenter and the specimen, β is the geometric parameter of the indenter, and S is the contact stiffness.

3. The method for determining rock mechanics parameters based on nanoindentation experiment according to claim 1 is characterized in that: S2, specifically, is as follows: based on X-ray diffraction and CT scanning data, a three-dimensional model of a target rock block containing mineral particles, cracks, pores and organic particles is constructed using Abaqus, and material properties are randomly assigned in Abaqus through a Python script to realize the construction of a multi-scale structural model (M model); The specific construction process includes: (1) Construction of mineral particle model: Based on the X-ray diffraction results and the actual content of each mineral particle, a three-dimensional model of the target rock block containing mineral particles is constructed using Abaqus modeling software; (2) Construction of fracture and pore model: The fracture and pore information analyzed from the CT scanning data is imported into the three-dimensional model of the target rock block containing mineral particles, and then a three-dimensional model of the target rock block containing fracture and pore structure is constructed; (3) Embedding of organic particles: Based on the morphology and spatial distribution of organic matter analyzed from the CT scanning data, organic particles are embedded in the corresponding positions in the model constructed in (2) above to complete the overall construction of the three-dimensional model of the target rock block; (4) Construction of multiscale structural model (M model): In order to realistically simulate the heterogeneity of the internal structure of the rock and realize the random distribution of material properties within the three-dimensional model grid of the target rock block, the Abaqus model software is imported by writing a Python script and the script is run to realize the construction of the multiscale structural model (M model) of the rock.

4. The method for determining rock mechanics parameters based on nanoindentation experiment according to claim 1 is characterized in that: The S3 is specifically: based on the multi-scale structural model (M model) of the target rock block, using the renormalization group theory to perform in-depth cross-scale analysis and calculation; First, the scale level division is clarified, and the model is subdivided into different levels such as microscopic (mineral particles), mesoscopic (cracks, pore networks) and macroscopic (whole rock blocks); Secondly, the gradual merging and renormalization process is initiated to gradually integrate adjacent scale units starting from the smallest scale. At the same time, with the help of the "coarse-graining" strategy of the renormalization group theory, the microscopic details are abstracted into high-level representative parameters to achieve model simplification without losing key information. After multiple merging and renormalization iterations, a series of simplified structural models (S models) that match the target rock structure are generated. Finally, mechanical loading simulation is performed on these simplified structural models (S models) to accurately calculate the mechanical parameters of the rock.

5. The method for determining rock mechanics parameters based on nanoindentation experiment according to claim 1 is characterized in that: The S4 is specifically: using a universal testing machine to carry out macroscopic mechanical experiments of tension, compression, and three-point bending on the target rock block, and then calculating its macroscopic mechanical parameters, and verifying the reliability of the method for calculating the mechanical parameters of the multi-scale structural model (M model) of the target rock block based on the nanoindentation experiment.

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