Method for determining roof rock fracturing horizon based on multi-scale rock mechanics characterization

Abstract

The present application relates to the technical fields of rock mechanics and deep stratum reconstruction engineering, and discloses a method for determining roof rock stratum fracturing horizon based on multi-scale rock mechanics characterization, which comprises the following steps: firstly, obtaining drilling cuttings to prepare nano-indentation test pieces, and carrying out grid dotting test and mineral scanning; secondly, calculating micro-mechanical parameters such as reduced modulus, fracture toughness, elastic index and plastic work ratio based on test data; then, constructing a macro-mechanical model by using micro-mechanical parameters and mineral distribution characteristics to carry out numerical simulation, and obtaining macro-elastic modulus and uniaxial compressive strength; finally, normalizing and weighting the macro-micro parameters to construct comprehensive compressibility index and comprehensive brittleness index, and optimizing the target fracturing horizon and perforation position according to the index. The present application realizes the cross-scale coupling of micro-component attributes and macro-mechanical response, solves the problem of parameter acquisition caused by deep stratum heterogeneity, overcomes the limitation of single-scale evaluation, and improves the fracturing horizon identification accuracy and engineering success rate.

Description

Technical Field

[0001] This invention relates to the field of rock mechanics and deep strata modification engineering technology, specifically a method for determining the fracturing horizon of the top strata based on multi-scale rock mechanics characterization. Background Technology

[0002] In deep coal mining, hydraulic fracturing of the roof strata is a crucial step in achieving formation stress control and preventing rockburst disasters. The accuracy of fracturing site selection and the rationality of perforation location directly determine the fracture network propagation morphology and the final engineering outcome. Currently, the evaluation of rock mechanical properties in engineering projects mainly relies on standard plunger uniaxial or triaxial compression tests recommended by the International Society for Rock Mechanics (ISRM), combined with well logging interpretation to obtain macroscopic mechanical parameters.

[0003] However, with the increasing depth of coal mining and the increasing complexity of geological conditions, existing technologies face many limitations in practical applications. Coal seam roof drilling and coring operations are costly and have low core recovery rates, especially for severely fractured roof strata. It is often difficult to prepare intact rock samples that meet standard size requirements, resulting in a lack of measured mechanical parameters and the inability to construct continuous formation mechanical profiles. While open-hole logging technology can construct profiles with continuously varying mechanical parameters with formation depth, the interpretation results are based on traditional empirical models, and the obtained dynamic mechanical parameters (elastic modulus and Poisson's ratio) require complex parameter correction through macroscopic mechanical testing of cored rocks from the same stratum. This leads to significant differences in interpretation results for different types of coal seam roof rocks, resulting in low accuracy.

[0004] Furthermore, most existing perforation schemes employ geometric segmentation or simple logging parameter cutoff methods, failing to fully consider the fluctuating characteristics of the rock's microscopic fracturability along the depth direction. This extensive fracturing approach easily leads to perforation locations falling in areas with high horizontal stress differences, high fracture toughness, or enrichment in ductile minerals, resulting in abnormally high initiation pressure, monotonous fracture morphology, or premature fracture termination, making it difficult to form an effective complex volumetric fracture network. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for determining the fracturing location of the top strata based on multi-scale rock mechanics characterization, which eliminates the need for the special requirements on rock sample size in traditional macroscopic mechanical experiments, as well as the complex process of correcting open-hole logging interpretation parameters.

[0006] To achieve the above objectives, the present invention provides a method for determining the fracturing horizon of the top strata based on multi-scale rock mechanics characterization.

[0007] This method first obtains drilling cuttings samples from different depths of the target top rock strata and processes them into nanoindentation specimens for micromechanical testing. Next, high-precision gridded point testing is performed on the nanoindentation specimens, recording the load-displacement changes in real time throughout the entire process of indenter loading and unloading, generating load-displacement curves that include information on the elastoplastic response of the rock's microstructure.

[0008] Based on this, the load-displacement curves are analyzed to calculate the micromechanical parameters. This calculation process not only obtains the reduced modulus and microelastic modulus, which characterize the micro-deformation capacity, but also obtains the fracture toughness, which characterizes the micro-crack resistance, through energy dissipation analysis.

[0009] Subsequently, mineral types at different indentation sites were matched using mineral scanning technology to obtain mineral distribution characteristics and component proportions.

[0010] Based on this, a macroscopic uniaxial compression model or triaxial compression model is constructed using the aforementioned microscopic mechanical parameters and mineral distribution characteristics, thereby obtaining the macroscopic mechanical parameters of rocks at different depths. These parameters include at least the macroscopic elastic modulus, macroscopic Poisson's ratio, and macroscopic uniaxial compressive strength.

[0011] Subsequently, the aforementioned macroscopic mechanical parameters were normalized and weighted, and combined with well logging interpretation of horizontal geostress magnitude, a comprehensive compressibility index was constructed. Based on the variation characteristics of the comprehensive compressibility index with depth, depth ranges whose values ​​meet preset conditions were selected and identified as target fracturing layers.

[0012] Within the target fracturing layer, brittle minerals are identified based on the elasticity index and plasticity work ratio, and a mineral brittleness index (the proportion of brittle minerals) is calculated. The proportion of brittle minerals, fracture toughness, and the difference coefficient of horizontal in-situ stress from well logging are normalized and weighted to construct a comprehensive brittleness index. Based on the variation characteristics of the comprehensive brittleness index with depth, depth locations that meet preset conditions are selected and designated as target perforation locations to guide on-site fracturing operations.

[0013] This invention provides specific calculation logic for micromechanical parameters to accurately characterize the intrinsic properties of rock microstructures.

[0014] Regarding the calculation of the reduced modulus, this invention employs a contact mechanics analysis method, extracting the slope of the tangent at the top of the unloading segment in the load-displacement curve as the contact stiffness. The reduced modulus is derived using the ratio of contact stiffness to the square root of the contact projected area. Furthermore, a correction coefficient related to the indenter geometry is introduced during the calculation process to eliminate the influence of indenter shape deviations on the measurement results.

[0015] Regarding the calculation of the micro-elastic modulus, this invention separates the intrinsic properties of rock materials from the reduced modulus through a physical transformation relationship. Specifically, it establishes a summation relationship between the reciprocal of the reduced modulus and the ratio of material properties: the first term is related to the micro-Poisson's ratio and micro-elastic modulus of the rock material, and the second term is related to the Poisson's ratio and elastic modulus of the indenter material. By solving this relationship using known indenter parameters, the true micro-elastic modulus of the rock after eliminating the influence of the test system stiffness is obtained.

[0016] Regarding the calculation of fracture toughness, this invention innovatively employs a calculation strategy based on the energy balance principle. First, the total input energy is obtained by integrating the area below the loading segment of the load-displacement curve, and the elastic recovery energy is obtained by calculating the area below the unloading segment. Second, the irreversible deformation energy is obtained by subtracting the elastic recovery energy from the total input energy. Further, the energy consumed by pure plastic deformation is estimated based on the ratio function of residual depth to maximum indentation depth. This pure plastic deformation energy is then subtracted from the irreversible deformation energy, thereby separating the fracture energy used to drive crack initiation and propagation. Finally, the critical energy release rate is determined based on the ratio of fracture energy to the contact projected area, and the microscopic fracture toughness is derived using the product of the critical energy release rate and the reduced modulus. This method effectively distinguishes between plastic dissipation and fracture dissipation, improving the accuracy of brittleness assessment.

[0017] At the microscopic testing level, to ensure the statistical representativeness and independence of the data, a matrix of measurement points was divided on the surface of the nanoindentation specimen. The spacing between adjacent measurement points was strictly controlled to be greater than a multiple threshold of the diameter of the residual indentation mark, so as to completely eliminate the stress field interference effect caused by adjacent indentations. At the same time, outlier data falling at mineral grain boundaries or pores were removed, and the arithmetic mean of the effective measurement points was used as the micromechanical indicator of the rock strata at that depth.

[0018] In terms of sample preparation, in order to eliminate the interference of machining damage on nanoscale testing, this invention adopts a fine processing process of step-by-step grinding combined with diamond polishing fluid until the surface roughness of the sample is reduced to the preset nanoscale precision threshold, and is supplemented by ultrasonic cleaning to ensure that the original mineral skeleton of the rock is exposed on the test surface.

[0019] In the final stratigraphic selection decision, this invention not only focuses on the extreme characteristics of the comprehensive compressibility index but also introduces engineering constraints related to in-situ stress and rock layer thickness. Threshold intervals are identified by plotting a comprehensive compressibility index profile curve, and the corresponding horizontal in-situ stress is inverted using well logging data. Only when the rock layer thickness corresponding to this interval meets the minimum engineering fracturing requirements and the horizontal in-situ stress is higher than the critical threshold is it determined as the target fracturing layer. Furthermore, the comprehensive brittleness index is used to select perforation locations within the target fracturing layer, and local maxima are identified by plotting a comprehensive brittleness index profile. When a local maxima of the comprehensive brittleness index is higher than the critical threshold, it is determined as the target perforation location. This logic ensures that the fracturing layer is preferentially selected in thick, hard rock layers with high strength and stress, and where complex fracture networks are easily formed. This ensures that hydraulic fracturing can cut through the thick, hard roof, blocking the stress propagation path and effectively preventing dynamic disasters such as coal mine rockbursts.

[0020] This invention provides a method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization. It has the following beneficial effects:

[0021] 1. This invention overcomes the limitations of traditional single-scale evaluation methods by organically combining microscale nanoindentation testing with macroscale numerical simulation. It utilizes nanoindentation technology to accurately obtain the mineral mechanical properties of micro-components and maps them into a macroscopic mechanical model. This effectively solves the problems of difficult coring of roof strata in deep coal seam mining and the distortion of mechanical parameters caused by strong heterogeneity, thus improving the accuracy and representativeness of rock mechanical characterization.

[0022] 2. This invention introduces the plastic work ratio and elastic index based on microscopic energy dissipation characteristics as discrimination indicators, and modifies the damage evolution criteria in the macroscopic numerical model accordingly. By establishing a functional relationship between local fracture energy and microscopic plastic work ratio, it achieves refined simulation of complex failure modes such as brittle splitting to ductile yielding for different mineral components. This enables more realistic prediction of the macroscopic mechanical properties of rocks, as well as the crack initiation, propagation, and arrest behavior during fracturing, providing reliable mechanistic support for fracturing site selection and parameter design.

[0023] 3. This invention constructs a comprehensive brittleness index and a comprehensive compressibility index model, incorporating the proportion of brittle minerals, micromechanical parameters, macromechanical parameters, and geostress. Through parameter normalization and a multi-factor weighted algorithm, it achieves a leap from qualitative judgment to quantitative decision-making. This method can automatically identify geological sweet spots that exhibit both high brittleness and low propagation resistance, and, combined with neighborhood stability and boundary avoidance constraints, determine precise perforation locations. This effectively avoids perforating projectiles directly hitting interlayers or lithological interfaces with poor physical properties, improving the complexity of the fracture network and the success rate of on-site fracturing operations. Attached Figure Description

[0024] Figure 1 The present invention provides a schematic diagram of the nanoindentation test process and a typical load-displacement curve ((a) is a schematic diagram of the nanoindentation test; (b) is a typical load-displacement curve).

[0025] Figure 2 This is a schematic diagram of the mineral distribution and typical indentation morphology characteristics of the dot matrix nanoindentation test area in an embodiment of the present invention ((a) high-resolution scanning electron microscope grayscale image of the dot matrix nanoindentation test area; (b) mineral distribution characteristics of the test area; (c) to (e) typical mineral indentation morphology).

[0026] Figure 3 This is the macroscopic uniaxial compression mechanics simulation process of an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram illustrating the determination of rock strata fracturing locations according to an embodiment of the present invention;

[0028] Figure 5 This is an overall process flow diagram of an embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram illustrating the energy dissipation calculation principle based on load-displacement curves in an embodiment of the present invention. Detailed Implementation

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] See attached document Figure 5 This embodiment provides a method for determining the fracturing horizon of roof strata based on multi-scale rock mechanics characterization. This method aims to solve the technical problems of obtaining the mechanical parameters of roof strata and accurately identifying the fracturing horizon of thick, hard roofs in deep coal mining by coupling microscopic testing with macroscopic simulation across scales.

[0032] This method is a systematic and complete process, which includes the following steps: First, the rock cuttings returned from the well are collected and the depth is recorded. The rock cuttings are then cleaned, dried, and resin-embedded. Finally, a microscopic rock sample that meets the requirements for nanoscale testing is prepared by combining mechanical polishing and argon ion polishing techniques.

[0033] Subsequently, point matrix nanoindentation tests were performed on selected test areas on the sample surface to obtain real-time monitoring data of load and displacement. Based on the principle of energy balance, the load-displacement curve was integrally calculated to obtain energy characteristic parameters including total energy, elastic recovery energy, pure plasticity and fracture energy. Based on these parameters, the contact area, reduced modulus, elastic modulus, hardness, fracture toughness, as well as the elastic index and plastic work ratio used to characterize the brittleness and ductility of minerals were calculated.

[0034] Meanwhile, scanning electron microscopy and energy dispersive spectroscopy were used to scan and identify the mineral composition of the test area, and a spatial mapping relationship between mineral distribution and nanoindentation lattice was established. Brittle minerals were identified based on elasticity index and plasticity work ratio, and boundary feature points located at the junctions of different mineral grains were extracted.

[0035] Based on this, a core-scale finite element-discrete element (FDEM) coupled macroscopic mechanical model is constructed. The mechanical parameters of individual minerals obtained from microscopic testing are used to assign values ​​to the model elements. Specifically, the mechanical response characteristics of extracted boundary feature points are used to invert the contact stiffness parameters between different mineral grains. Furthermore, the evolution criterion for damage variables in the model is corrected using the microscopic plasticity work ratio, establishing a functional relationship between microscopic energy dissipation and macroscopic damage evolution.

[0036] Next, uniaxial compression simulations were performed on macroscopic models at different depths to calculate the macroscopic uniaxial compressive strength and macroscopic elastic modulus.

[0037] Finally, the proportion of brittle minerals, micromechanical parameters, macromechanical parameters, and geostress were normalized, and a profile was established based on the stratigraphic depth. According to the strength grading standards of the normalized parameters and the characteristics of the rock layer thickness distribution, the range of fracturing horizons and specific perforation locations in the top strata were comprehensively determined. Figure 4 As shown.

[0038] To obtain rock samples that meet the requirements of microscopic testing, drilling cuttings must be rigorously collected and pretreated in advance.

[0039] During drilling operations, drilling cuttings returned from the wellhead are collected using a vibrating screen or cuttings logging equipment. The sampling depth interval is set according to the accuracy requirements of the formation assessment, typically between 0.5 meters and 2.0 meters. The collected cuttings samples are placed in sealed, moisture-proof bags and labeled with the corresponding well number, stratigraphic position, and depth data.

[0040] The rock cuttings samples were then cleaned to remove drilling fluid, oil, mud, and foreign impurities adhering to the surface, ensuring the exposure of the original rock skeleton. The cleaning process was strictly differentiated according to the lithological characteristics and water sensitivity of the rock cuttings: for shale rock cuttings containing expansive clay minerals such as montmorillonite and illite / montmorillonite mixed layers, or those prone to hydration and disintegration, multi-stage rinsing was performed using chemically stable organic solvents (such as industrial kerosene, diesel, or anhydrous ethanol), and water-based solutions were prohibited to prevent structural disintegration of the rock cuttings due to hydration and expansion; for non-water-sensitive rock cuttings such as dense sandstone and limestone, repeated washing with clean water was performed until the cleaning solution was clear and free of suspended matter.

[0041] The cleaned rock fragments were placed in a constant-temperature forced-air drying oven and dried at a temperature range of 60℃ to 105℃ for at least 24 hours or until the sample mass was constant, to completely remove free water and volatile solvents from the rock pores. After drying, the rock fragments were screened using a standard sieve to select rock fragments with a diameter between 3 mm and 10 mm as the sample preparation material, while small fragments and powders with a diameter less than 3 mm were removed to ensure that the sample surface formed by subsequent resin embedding has sufficient effective testing area to accommodate the 10×10 nanometer indentation lattice.

[0042] See attached document Figure 2 (a) In order to obtain a smooth surface required for high-resolution imaging, the selected rock fragments must be resin-embedded and multi-stage polished.

[0043] Specifically, selected rock fragments with a diameter of 3 mm to 10 mm are placed at the bottom of a cylindrical mold with a diameter of 25 mm or 30 mm, ensuring that the fragments do not contact each other and are spread out as evenly as possible. Low-viscosity epoxy resin and curing agent are mixed and stirred evenly in a specified ratio (e.g., a mass ratio of 2:1), and then slowly poured into the mold until the rock fragments are covered. The mold is then placed in a vacuum drying oven for vacuum impregnation treatment, with the vacuum level set to -0.08 MPa to -0.1 MPa, and the evacuation time lasting 15 to 30 minutes to remove air bubbles from the mixture and ensure that the resin fully fills the micropores and cracks in the rock fragments, preventing the rock fragments from breaking or falling off during subsequent testing. After vacuum treatment, the mold is placed in a room temperature environment or a constant temperature chamber for static curing for at least 24 hours, and then demolded to obtain a cylindrical resin rock fragment sample.

[0044] The cured resin-bonded rock fragments samples underwent multi-stage mechanical grinding and polishing. First, a metallographic polishing machine was used with silicon carbide sandpaper for progressive grinding, with sandpaper grits of 400, 800, 1200, and 2000 grit selected sequentially. During grinding, non-water-sensitive rock samples were cooled with clean water, while water-sensitive samples were cooled with anhydrous ethanol or a special oil-based coolant. After each grinding stage, the samples were placed in an ultrasonic cleaner for 3 to 5 minutes to remove residual abrasive particles from the previous stage. After mechanical grinding, diamond polishing paste or suspension was used with polishing cloth for fine polishing. The diamond particle sizes were 9 micrometers, 3 micrometers, and 1 micrometer, respectively, until the sample surface showed no obvious scratches under an optical microscope.

[0045] Mechanical polishing generates a mechanical damage layer (work-hardened layer or amorphous layer) several to tens of micrometers thick on the rock surface. This damage layer severely interferes with the accuracy of nanoindentation testing of the intrinsic mechanical properties of rocks; therefore, argon ion polishing is necessary. The mechanically polished sample is placed in the vacuum chamber of an argon ion polisher. The accelerating voltage is set to 3kV to 6kV, the ion beam current to 100μA to 200μA, and the incident angle is set to a grazing incidence mode of 0° to 5°. The sample stage rotation or oscillation function is activated (oscillation amplitude ±30° to ±60°). Atomic-level physical sputtering is used to remove the mechanical damage layer and smooth the microstructure of the sample surface using a high-energy argon ion beam. The polishing time is set to 1 to 4 hours depending on the sample hardness. After argon ion polishing, the arithmetic mean roughness of the sample surface is... Controlled below 100nm, typically reaching the 10nm to 20nm level, it exposes a clear mineral lattice structure and intergranular boundaries, providing a standard-compliant test plane for subsequent dot matrix nanoindentation testing and high-precision mineral scanning.

[0046] The resin-coated rock chip sample, after argon ion polishing, is placed on the stage of the nanoindenter. The sample surface is observed using the instrument's built-in high-magnification optical microscope or atomic force microscope module. A region with a smooth surface and no obvious macroscopic cracks or pores is selected as the test area. A point matrix test scheme is set within this test area, typically using a 10×10 point array, totaling 100 test points. To avoid interference between the plastic deformation zones and stress fields generated by adjacent indentation points, which could affect the independence and accuracy of the test results, the spacing between adjacent test points is set to at least five times the maximum indentation depth, or a fixed spacing value (e.g., 20 μm to 50 μm).

[0047] The test was performed using a standard triangular pyramidal diamond glass indenter. The test process employed either load control or displacement control modes; this embodiment preferred load control mode. For each test point, the indentation test was strictly conducted according to the following three stages:

[0048] Loading stage: The indenter is controlled to be vertically pressed into the surface of the rock sample at a constant loading rate or a constant strain rate, and the load... With indentation depth The increase is due to the increase in [something]. During this process, the rock material undergoes both elastic and plastic deformation simultaneously. For example... Figure 1 As shown in (a), as the indenter is pressed in, a depression is formed on the material surface, and when the load reaches the set maximum value... At that time, the corresponding vertical indentation depth is recorded as the maximum indentation depth. .

[0049] Load holding phase: When the load reaches Then, maintain the load constant for a period of time (e.g., 5 to 30 seconds). The main purpose of setting the load holding phase is to eliminate the influence of the creep behavior of the rock material on the subsequent unloading curve and ensure that the unloading process mainly reflects the elastic recovery characteristics of the material.

[0050] Unloading phase: The pressure head gradually removes the load at a set unloading rate. During this process, the rock material undergoes elastic rebound and displacement. The displacement gradually decreases, but due to plastic deformation, it cannot return to zero. When the load is completely removed... When the indenter separates from the sample surface, the depth of the permanent indentation remaining on the sample surface at this point is recorded as the residual depth. .

[0051] The high-precision sensors of the nanoindenter record the load in real time throughout the entire process described above. With displacement Data is used to generate load-displacement curves, typical curves are shown below. Figure 1 As shown in (b). Furthermore, by analyzing the initial slope (contact stiffness) of the unloading curve... ) and maximum load Based on the Oliver-Pharr model and the indenter geometry function, the effective contact depth between the indenter and the specimen under maximum load is determined. .like Figure 1 As shown in (a). Usually less than The specific values ​​depend on the accumulation or settling behavior of the material around the indenter. These geometric parameters ( , , The complete load-displacement curve data, along with other data, form the basic data source for subsequent calculations of micromechanical parameters and energy characteristic indicators.

[0052] Based on the curve data, the Oliver-Pharr method was used to calculate the basic mechanical parameters of the rock's microscopic location, mainly including contact stiffness, contact area, hardness, and reduced modulus.

[0053] First, a power function is fitted to the upper half of the unloading curve (usually the 25% to 50% data segment of the unloading curve), and the fitting relationship is: ,in and The constant is the fitting constant. The fitting curve is obtained at the maximum indentation depth. Differentiate at point to determine contact stiffness (i.e., the slope of the tangent line of the unloading curve at the maximum load):

[0054] ;

[0055] Utilizing contact stiffness Combined with maximum load Calculate the true contact depth between the indenter and the sample surface. For glass indenters, their geometric correction factor The value is usually taken as 0.75, and the calculation formula is as follows:

[0056] ;

[0057] Based on contact depth The projected contact area is calculated based on the ideal geometric shape function of the glass indenter. Without considering non-ideal factors such as indenter tip passivation, the contact area and contact depth follow the following relationship:

[0058] ;

[0059] Based on this, the nanoindentation hardness of the test point was calculated. Hardness is defined as the average contact pressure exerted by a material during plastic deformation, i.e., the ratio of the maximum load to the projected contact area.

[0060] ;

[0061] Simultaneously, the reduced modulus of the sample is calculated. The reduced modulus reflects the overall elastic deformation response of the indenter-sample contact system. Its calculation depends on the contact stiffness and contact area, and the formula is:

[0062] ;

[0063] In the formula, Let be the shape constant of the indenter; for a triangular pyramidal glass indenter, The value is 1.034. This is the reduced modulus. Includes the elastic modulus of the sample material Compared to Poisson And the elastic modulus of the indenter material Compared to Poisson The two satisfy the relation Because diamond indenters have an extremely high modulus, they can usually be used directly. Characterizing the elastic properties of the rock's microstructure. Through the above steps, the fundamental mechanical parameters of each test point in the matrix are obtained. and .

[0064] To reveal the damage and failure mechanisms of rock microstructures in greater depth, this embodiment not only focuses on the geometric extremes of load and displacement, but also performs integral analysis on the area under the curve based on the principle of energy balance, and quantitatively calculates the energy dissipation characteristics of rock materials during the micro-indentation process.

[0065] See attached document Figure 6 Specifically, the total input energy during the nanoindentation process Defined as the area enclosed below the loading curve, it represents the total work done on the specimen by external forces during the indenter's insertion. This energy can be obtained by applying loads during the loading phase. Regarding displacement From 0 integral to maximum indentation depth get:

[0066] ;

[0067] During unloading, the rock material releases its stored elastic strain energy. Elastic recovery energy Defined as the area enclosed below the unloading curve, determined by the load during the unloading phase. Regarding displacement From residual depth Integrate to maximum indentation depth get:

[0068] ;

[0069] According to the law of conservation of energy, the total input energy From elastic recovery energy Pure plastic deformation energy And fracture energy used to drive crack propagation or create new surfaces It consists of three parts and satisfies the equilibrium equation. .

[0070] In order to separate the pure plastic deformation energy This embodiment employs a dimensionless analysis method based on contact mechanics. Assuming the indenter is a rigid cone and the material follows an elastoplastic constitutive relation, the proportion of pure plastic work to total energy can be determined by the residual depth. With maximum indentation depth The ratio function is derived from this. The specific calculation formula is as follows:

[0071] ;

[0072] Calculated based on the above formula Then, the fracture energy consumed by the initiation and propagation of microcracks during the indentation process can be obtained by subtraction.

[0073] ;

[0074] Obtain fracture energy Then, the projected contact area calculated in the aforementioned steps is used as a basis. Calculate the critical energy release rate This parameter reflects the energy required for crack propagation per unit area:

[0075] ;

[0076] Furthermore, utilizing the critical energy release rate With reduced modulus Calculate the microscale fracture toughness of materials based on linear elastic fracture mechanics equations.

[0077] ;

[0078] Through the above series of energy integrals and parameter derivations, the energy-based characterization of the entire process of rock micro-components from elastoplastic deformation to fracture failure was achieved.

[0079] To quantitatively characterize the transformation of rock microstructures from brittle to ductile, and to provide criteria for subsequent mineral brittleness classification and macroscopic constitutive model revision, this embodiment defines two key dimensionless characteristic discriminant indices: the elasticity index and the plasticity work ratio. First, the elasticity index is defined. This is the ratio of material hardness to elastic modulus, a value that comprehensively reflects the material's relative resistance to elastic and plastic deformation. The hardness is calculated based on the steps outlined above. With elastic modulus (Note: Here) Typically determined by the reduction modulus Calculated by combining pressure head parameters, or directly using... As an approximate representation (based on the modulus parameter selected in the actual calculation), the formula for calculating the elastic exponent is as follows:

[0080] ;

[0081] Elasticity Index The physical meaning of this term lies in describing the elastic limit strain capacity of a material during the process of being subjected to force. A higher... A high value generally indicates that the material has a lower tendency for plastic deformation and is more likely to exhibit brittle fracture characteristics at the microscopic level; conversely, a high value indicates a lower tendency for plastic deformation. The value corresponds to a stronger ability to undergo plastic deformation.

[0082] Secondly, define the plastic work ratio ( The plastic work ratio (PDR) is the ratio of plasticity to total energy, used to characterize the plastic deformation behavior of a material from the perspective of energy dissipation. Based on the aforementioned energy integral results, the formula for calculating the plastic work ratio is as follows:

[0083] ;

[0084] In the formula, Total plasticity includes pure plastic deformation energy. and fracture dissipation energy ,Right now . This represents the total input energy. The value directly reflects the proportion of work done by external forces that is converted into irreversible dissipated energy. When When the value approaches 1, it indicates that almost all the input energy is converted into plastic deformation or damage dissipation, and the material exhibits significant ductility or plasticity; when... When the value approaches 0, it indicates that the input energy is mainly stored in the form of elastic energy, and it is almost completely recovered after unloading, with the material exhibiting ideal brittle or elastic characteristics. These two indicators together constitute the core basis for identifying brittle minerals and revising the macroscopic damage evolution criteria in subsequent steps.

[0085] After completing the nanoindentation test, the rock chip sample was transferred to the sample chamber of a field emission scanning electron microscope (SEM) while maintaining its surface condition. This microscope is equipped with a high-throughput energy-dispersive X-ray spectrometer (EDS) and an automated mineral analysis system (such as QEMSCAN or MLA). To achieve a precise correspondence between mechanical data and mineral composition, the secondary electron (SE) or backscattered electron (BSE) imaging mode of the SEM was first used to identify the residual nanoindentation pit array on the sample surface as positioning markers, precisely locking the scanning area within a 10×10 point matrix test region.

[0086] The electron beam accelerating voltage was set to 15kV to 25kV, and the working distance to 10mm to 15mm. Grayscale images reflecting differences in average atomic number were acquired using backscattered electron signals. Simultaneously, point-by-point EDS spectral acquisition was performed on the region at a set pixel resolution (e.g., 1μm to 5μm step size) to obtain characteristic X-ray energy spectrum data for each pixel. The automated mineral analysis system, based on its built-in mineral standard spectral database, interpreted the acquired energy spectrum data into corresponding elemental contents and, combined with BSE grayscale values, identified the mineral phase (e.g., quartz, feldspar, calcite, illite, kaolinite, pyrite, or organic matter) of each pixel. Finally, a digital mineral composition distribution map of the test area was generated. Figure 2 In b, different colors represent different mineral types.

[0087] Establish the affine transformation relationship between the nanoindentation testing coordinate system and the mineral scanning coordinate system. Record the coordinates of 100 nanoindentation testing points. The indentation is projected onto a mineral composition distribution map. For each indentation point, its coordinates are queried to find the corresponding mineral category on the mineral distribution map, thus establishing a database. If the indentation point falls inside a single mineral grain, the mechanical parameters of that point represent the properties of that single mineral; if the indentation point falls at the interface of two or more minerals, it is marked as an intergranular boundary point for boundary feature extraction in subsequent steps.

[0088] After establishing the database, the mineral components inside the rock were classified according to their mechanical properties and their brittleness was determined based on the results of nanoindentation tests.

[0089] First, indentation points falling within a single mineral grain are screened, eliminating abnormal points that cross grain boundaries or are significantly affected by surface porosity or microcracks, retaining only valid test points that truly reflect the intrinsic mechanical properties of the mineral. These valid test points are then categorized and statistically analyzed according to their corresponding mineral types (e.g., quartz, feldspar, calcite, dolomite, clay minerals, etc.), and the average elastic index for each mineral phase is calculated. and average plastic work ratio .

[0090] Subsequently, the brittleness and ductility of each mineral phase were qualitatively and quantitatively determined based on the micromechanical criteria set in this embodiment. The determination criterion was set as follows: when the elastic index of a certain type of mineral... or plastic work ratio When the value is higher than 0.6, the mineral is judged to be a brittle mineral. This threshold (0.6) is an empirical value determined based on the statistical analysis of the fracture mechanics characteristics of the target formation rocks. The high elasticity index characterizes the low elastic deformation limit of the mineral under high hardness, implying a high tendency for brittle fracture. In this specific criterion, the introduction of the plasticity work ratio term is to comprehensively capture the energy dissipation anomalies of complex minerals at the microscale, and to screen out specific components that may have certain plastic deformation but are prone to forming complex fracture networks under fracturing conditions.

[0091] Based on the above discrimination results, minerals such as quartz, feldspar, calcite, and pyrite, which usually meet the above criteria, are classified as brittle mineral components; illite, chlorite, montmorillonite, and organic matter, which usually do not meet the above criteria (i.e., ≤0.6 and Minerals with a content of ≤0.6 are classified as plastic mineral components.

[0092] Finally, the microbrittleness index of the rock sample was calculated by combining the mineral area percentage obtained from the automated mineral analysis system (which is approximately equivalent to the volume percentage in dense rocks). This index is defined as the ratio of the total content of brittle minerals to the total content of minerals, or a weighted calculation based on the content of each mineral. This micro-brittleness index will serve as one of the important reference indicators for subsequently determining the location of perforations, and will be used to select stratigraphic layers that are prone to inducing crack initiation and propagation.

[0093] After classifying the mineral components, further fine extraction and feature enhancement processing of intergranular boundary points are performed to capture the mechanical response information of the microstructural interfaces within the rock. This step provides the data foundation for subsequent inversion of intergranular contact parameters.

[0094] First, based on the established spatial mapping relationship, image processing algorithms are used to identify grain boundary lines in the mineral distribution map. Nanoindentation test points whose center coordinates fall within a certain neighborhood on both sides of the grain boundary line (e.g., within ±2 μm of the boundary line), or test points whose EDS energy dispersive spectroscopy data simultaneously contain two adjacent mineral characteristic elements (e.g., simultaneously detecting Si in quartz and Al and K in illite), are preliminarily marked as potential boundary points.

[0095] Subsequently, morphological analysis was performed on the load-displacement curves of all potential boundary points to identify their unique mechanical response characteristics during the loading phase:

[0096] Step effect: Monitoring for sudden increases in displacement on the loading curve. That is, under load... Indentation displacement remains constant or increases by a very small amount A sudden and significant increase occurred ( This phenomenon, on the curve, appears as a nearly horizontal plateau or sawtooth-like fluctuation. This usually corresponds to the slippage of the intergranular cementation surface, the instantaneous initiation or propagation of microcracks induced during the indentation process.

[0097] Stiffness abrupt change: Calculate the slope of the tangent to the loading curve (i.e., the loading stiffness). The rate of change of the slope with indentation depth. If the slope of the curve changes significantly and discontinuously during continuous loading (e.g., a sudden drop in slope), it indicates that the stress field under the indenter is transferred from a harder mineral phase to a softer mineral phase, or penetrates the grain interface into adjacent particles.

[0098] Test points that meet the above spatial location conditions and exhibit significant stiffness abrupt changes or step effects on the mechanical curve are formally identified as boundary feature points. The slope data of the loading segment curves of these boundary feature points are extracted and marked as follows: The corresponding two adjacent mineral component types (e.g., quartz-clay boundary or feldspar-calcite boundary) are recorded. Simultaneously, within the same test matrix, the test point closest to this boundary point and belonging to the corresponding single mineral phase is selected, and its loading curve slope is extracted as a pure mineral reference value, marked as... .Will The resulting dataset is stored in the feature database and used for the mathematical inversion of contact element stiffness parameters in subsequent macroscopic mechanical models.

[0099] To map microscopic mechanical properties to macroscopic scales and simulate the entire failure process, a macroscopic numerical model conforming to rock mechanics testing standards needs to be constructed. This embodiment employs the finite element-discrete element coupled method (FDEM), which combines the finite element method's ability to accurately describe the deformation of continuous media with the discrete element method's ability to handle large displacements in discontinuous media motion and contact. This method can explicitly simulate the nonlinear evolution of rock from continuous deformation to local damage, crack initiation, propagation, and ultimately macroscopic fracture.

[0100] First, the geometric boundaries of the model are defined. In the preprocessing module of the numerical simulation software, a geometric domain is established whose geometric dimensions strictly correspond to those of a standard uniaxial compression specimen recommended by the International Society for Rock Mechanics. This geometric domain is set as a cylindrical structure with a base diameter of 50 mm and a height of 100 mm. In the case of a simplified two-dimensional simulation, a rectangular region with dimensions of 50 mm × 100 mm is constructed as the representative unit of the longitudinal section of the specimen.

[0101] Secondly, the geometric domain is discretized to generate a computational mesh. To avoid artificially induced anisotropic deviations in crack propagation paths caused by regular meshes, this embodiment employs an unstructured Delaunay triangulation algorithm for mesh generation. Setting the mesh size is crucial for achieving micro-to-macro scale mapping: based on the statistical distribution characteristics of mineral grain sizes obtained from mineral scanning, the average size of the mesh cells is set. To accurately reflect the heterogeneous structure inside rocks, it is required that... Smaller than the average mineral grain size of the rock (usually less than one order of magnitude, i.e.) ).

[0102] After triangular mesh generation, topology reconstruction is performed to introduce potential fracture paths. The system traverses the common boundaries of all triangular elements, embedding thicknessless four-node joint elements (also known as cohesive interface elements) between each pair of adjacent triangular elements. In the initial state, these joint elements connect adjacent solid elements through node sharing, ensuring the continuity of the medium. During loading, when the stress state on the joint element meets a specific fracture criterion, the joint element undergoes damage softening and eventually fractures, thereby achieving the separation of solid elements and simulating realistic explicit cracks.

[0103] See attached document Figure 3 Ultimately, the constructed FDEM numerical model consists of a large number of solid triangular elements (used to characterize the elastic deformation of mineral grains) and joint elements embedded therein (used to characterize the damage and fracture of intergranular cementation interfaces), providing an accurate geometric basis for subsequent material parameter assignment and constitutive calculation.

[0104] To ensure that the macroscopic numerical model accurately reflects the heterogeneous mechanical behavior of rocks, the acquired microscopic mechanical parameters must be precisely assigned to each element in the FDEM model. This mapping process consists of two parts: assigning values ​​to solid elements and assigning values ​​to joint elements.

[0105] Solid triangular elements are used to simulate the deformation behavior of mineral grains themselves. Their constitutive relation adopts a linear elastic model, and the required input parameter is the time modulus. Compared to Poisson .

[0106] First, the obtained mineral component distribution map (QEMSCAN map) is digitized to obtain a pixelated mineral matrix that completely overlaps with the geometric domain of the FDEM model.

[0107] Next, iterate through each triangular solid cell in the FDEM model. Obtain the geometric center coordinates of the cell and query the corresponding mineral type in the pixelated mineral matrix.

[0108] Then, the average elastic modulus corresponding to this mineral type is extracted from the database. and average Poisson ratio Assign these parameters to the current triangular solid element. For example, if the center of an element falls in the quartz grain region, set the elastic modulus of that element to the average elastic modulus of quartz measured by nanoindentation (e.g., 70 GPa), and the Poisson's ratio to a typical value for quartz (e.g., 0.08).

[0109] By performing the above traversal assignment on all entity units, the macroscopic FDEM model reproduces the mineral composition distribution of real rocks and the resulting spatial heterogeneity of elastic parameters at the microstructural level.

[0110] Parameter assignment for joint elements:

[0111] Joint elements simulate the mechanical response of mineral grain boundaries or transgranular cracks. Their behavior is controlled by a cohesive force model, and the required core parameters include normal stiffness. Tangential stiffness ,tensile strength and shear strength .

[0112] The parameter assignments for joint elements are also based on their location. Each joint element in the FDEM model is traversed to determine the mineral types of the two adjacent solid elements it connects to.

[0113] If two solid units belong to the same mineral (e.g., quartz to quartz), then the joint unit represents a transgranular fracture path. Its tensile strength... and shear strength The fracture toughness of the mineral was measured based on nanoindentation. The result is obtained through conversion.

[0114] If two solid units belong to different minerals (e.g., quartz to illite), then the joint unit represents an intergranular fracture path. Its stiffness parameter... and The stiffness is determined through inversion analysis. Specifically, using the extracted boundary feature point data, a micro-finite element model containing two adjacent minerals and a contact interface is established. The slope of the reaction force-displacement curve at the model's loading points is extracted as the simulated stiffness. The boundary loading stiffness measured in the experiment As the target value, the contact stiffness parameters in the microscopic model are adjusted through iterative calculations until the simulation results match the experimental data, thereby retrieving the intergranular normal stiffness of this type of mineral assemblage. and tangential stiffness .

[0115] In this way, the model not only considers the mechanical properties of the mineral particles themselves, but also accurately describes the strength and stiffness characteristics of the cementation interface between different minerals, achieving a comprehensive mapping of the mechanical information of the rock microstructure.

[0116] In order to realistically reproduce the complex failure modes caused by the heterogeneous micro-composition of rocks in macroscopic numerical simulation, this embodiment does not use a single fixed fracture energy parameter for joint elements.

[0117] The mechanical behavior of joint elements follows the traction separation law. In the elastic stage, joint elements remain closed, and stress... With relative displacement They satisfy a linear relationship ,in To compensate for stiffness. When the equivalent traction force on the joint element reaches the tensile strength. Damage begins to develop when either the tensile failure (corresponding to tensile failure) or the Mohr-Coulomb criterion (corresponding to shear failure) is satisfied.

[0118] The stress-displacement relationship during the damage evolution stage is defined as follows:

[0119] ;

[0120] In the formula, It is a scalar damage variable, with a value range from 0 (no damage) to 1 (complete breakage).

[0121] To accurately describe the cross-scale mechanism from microscopic plasticity to macroscopic brittle / ductile failure, this invention proposes an exponential damage evolution equation based on a modified plasticity work ratio. This equation differs from traditional linear softening models by introducing a defined microscopic plasticity work ratio. As a key parameter controlling the shape of the softening curve, the modified damage variable... The calculation formula is as follows:

[0122] ;

[0123] In the formula, This represents the equivalent relative displacement at the current moment. To achieve peak intensity The critical elastic displacement at that time.

[0124] The core innovation lies in local fracture energy Definition. In a conventional FDEM, It is usually considered a constant. However, in this embodiment, It is a field variable that varies with spatial location, and it depends not only on the calculated critical energy release rate. It also utilizes plastic work ratio The scaling effect and ductile toughening are corrected. The corrected relationship is as follows:

[0125] ;

[0126] In the formula, To determine the critical energy release rate at the location of the joint element, the microscopic fracture energy formula is used. The baseline value obtained through mapping; This refers to the plastic work ratio of the corresponding mineral components; and The scale correction factor and shape factor are typically obtained through standard rock mechanics experiments (such as the three-point bending test) and the macroscopic fracture energy and microscopic... The statistical comparison and inversion were obtained. The specific inversion process employed the least squares method: using the fracture energy measured by macroscopic experiments as the objective function, adjusting... (Values ​​typically range from 0 to 10) and (The value range is usually between 0.5 and 2.0), so as to minimize the sum of squared residuals between the destructive energy consumption obtained from numerical simulation and the macroscopic experimental value.

[0127] The physical significance of this revised criterion lies in the fact that for brittle minerals such as quartz ( (lower) Approximate to microscopic test values The damage evolution curve shows a steep decline, simulating brittle splitting failure; for ductile components such as clay or organic matter ( (Higher), Correction Item This significantly increases the macroscopic fracture energy, causing the damage evolution curve to exhibit a gently sloping, long-tailed characteristic, simulating the plastic yielding and bridging effect at the crack tip. In this way, the energy dissipation characteristics at the nanoscale are effectively represented. It is directly coupled into the macroscopic constitutive model, enabling refined prediction of crack initiation, propagation, and arrest behavior during rock fracturing.

[0128] Bottom constraints and a constant top velocity load (0.05-0.1 m / s) were applied to the model, and the uniaxial compression process was simulated using an explicit solver. To simulate the quasi-static loading process in the explicit dynamic calculations, local non-viscous damping was introduced into the system, with damping coefficients set to 0.7 to 0.8 to dissipate non-physical high-frequency oscillatory energy. The simulation reproduced the entire process from linear elasticity, nonlinear damage propagation, to post-peak failure separation. Validation criterion: The simulated uniaxial compressive strength is required. With elastic modulus The errors relative to the measured values ​​were all controlled within ±10%, and the final macroscopic failure mode (crack path morphology) was consistent with the physical characteristics of the specimen. After the dual verification was passed, the model parameters and brittleness evaluation were confirmed to be effective.

[0129] The comprehensive compressibility index selects three key indicators and performs range normalization:

[0130] Positive indicators (higher values ​​are more favorable): macroscopic uniaxial compressive strength, macroscopic elastic modulus, and horizontal ground stress. Normalization formula:

[0131] ;

[0132] In the formula, Indicates the first The depth point, the first The original value of the parameter; and These represent the maximum and minimum values ​​of the parameter within the entire target longitudinal profile (well section), respectively. These are the normalized dimensionless parameter values.

[0133] The comprehensive fragility index uses three key indicators for range normalization:

[0134] Positive indicator (the higher the value, the better): Microfragility index Normalization formula:

[0135] ;

[0136] Negative index (the higher the value, the worse): Fracture toughness Horizontal principal stress difference coefficient Normalization formula:

[0137] ;

[0138] In the formula, Indicates the first The depth point, the first The original value of the parameter; and These represent the maximum and minimum values ​​of the parameter within the entire target longitudinal profile (well section), respectively. These are the normalized dimensionless parameter values.

[0139] The weight coefficients of the above evaluation indicators were determined by combining the Analytic Hierarchy Process (AHP) with the entropy weight method.

[0140] Comprehensive compressibility index: The indicators that are prone to forming thick, hard topspan rock layers (macroscopic uniaxial compressive strength, macroscopic elastic modulus, and horizontal geostress) are assigned positive weights and then summed.

[0141] Calculate the comprehensive compressibility index of rock cores at different depths. :

[0142] ;

[0143] In the formula, For the first The dimensionless values ​​of the parameters after range normalization; The corresponding weight coefficients, and satisfying .

[0144] Comprehensive brittleness index: Indicators that are conducive to the formation of pressure fracture network (micro brittleness index) are given positive weights. Indicators that hinder crack propagation (fracture toughness, horizontal stress difference coefficient) have been processed by negative formulas during normalization, and are uniformly weighted and summed here.

[0145] ;

[0146] In the formula, For the first The dimensionless values ​​of the parameters after range normalization; The corresponding weight coefficients, and satisfying The above calculations integrate macroscopic stress environment, microscopic mechanical properties, and mineral brittleness into a single quantitative evaluation index.

[0147] To ensure the feasibility and safety of the engineering operation, strict geometric constraints and engineering parameter verification were performed on the identified potential areas. The specific steps are as follows:

[0148] Step 1: Layer thickness screening.

[0149] Calculate the thickness of the potential fracturing layer (i.e., the difference between the bottom and top depths) and eliminate thinner interlayers. According to the engineering specifications of this embodiment, the thickness of the fracturing layer is required to be no less than 40m to ensure a volumetric basis for large-scale fracturing stimulation.

[0150] Step 2: Precisely determine the location of the perforation hole.

[0151] Within the fracturing zone that meets the thickness requirements, determine the specific set of perforation coordinates. The determination of the perforation location must simultaneously satisfy the following two constraints:

[0152] Cluster spacing constraint: In order to ensure the crack interference effect and optimize the modification volume, the spacing between adjacent perforation clusters is set to be no less than 5m.

[0153] Boundary safety avoidance constraints: To prevent uncontrolled crack initiation, the perforation location must satisfy the following inequality:

[0154] ;

[0155] In the formula, This represents the top depth of the fracturing section; This represents the bottom boundary depth of the fracturing section; For safe avoidance distance, it is set to 0.5 meters to 1.0 meter.

[0156] The boundary avoidance constraint is set to prevent the perforation location from being too close to the lithological abrupt change interface, and to prevent the fracturing fluid from flowing directly along the bedding plane or prematurely breaking through to the upper and lower strata at the moment of fracturing initiation, thereby ensuring that the main energy of the fracture is used to expand the volume within the dominant stratum.

[0157] Finally, the output is the final set of coordinates after the above multiple constraint filtering. It is used to guide on-site perforation and fracturing operations.

Claims

1. A method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization, characterized in that, Includes the following steps: S1. Obtain rock samples at different depths of the target top stratum and process the rock samples into nano-indentation specimens for micromechanical testing. S2. Perform grid-based dot-mapping tests on the nano-indentation specimen, record the test data of load change with displacement during loading and unloading processes, and generate load-displacement curves. S3. Calculate the micromechanical parameters based on the load-displacement curve. The micromechanical parameters include at least the reduced modulus, microelastic modulus, fracture toughness, hardness, elastic index, and plasticity-to-work ratio. S4. Perform mineral composition scanning on the test area of ​​the nanoindentation specimen, establish the spatial mapping relationship between mineral distribution and nanoindentation lattice, and identify boundary feature points; S5. Construct a core-scale finite element-discrete element coupled macroscopic mechanical model. Assign values ​​to the model using microscopic mechanical parameters and mineral boundary feature points, and perform uniaxial compression simulation to obtain macroscopic mechanical parameters. The construction of the core-scale finite element-discrete element coupled macroscopic mechanical model includes: defining the geometric boundary of the model, discretizing the geometric domain, and generating a computational mesh. The unstructured Delaunay triangulation algorithm is used for mesh generation. The mesh size is based on the statistical distribution characteristics of mineral grain sizes obtained from mineral scanning, setting the average size of the mesh elements. The common boundary of all triangular elements is traversed, and four-node joint elements with no thickness are embedded between each pair of adjacent triangular elements. Initially, the joint elements are connected to adjacent solid elements through node sharing. During loading, when the stress state on the joint element meets a specific fracture criterion, the joint element undergoes damage softening and eventually fractures. S6. Normalize and weight the macroscopic mechanical parameters and the microscopic mechanical parameters to construct a multi-scale rock compressibility and brittleness evaluation model, and use the multi-scale rock compressibility and brittleness evaluation model to calculate the comprehensive compressibility index and comprehensive brittleness index of rock cores at different depths. S7. Based on the distribution of the comprehensive compressibility index and the comprehensive brittleness index with depth, select the depth range where the comprehensive compressibility index value meets the preset conditions and the maximum value point of the comprehensive brittleness index value within the range, and determine them as the target fracturing layer and the target perforation location, respectively. The step of determining the target fracturing layer in step S7 includes: The macroscopic elastic modulus, uniaxial compressive strength and well logging horizontal geostress are normalized and weighted to construct a comprehensive compressibility index; Plot the profile curve of the comprehensive compressibility index as a function of depth; Filter the depth ranges in the profile curve that meet the preset conditions; Determine whether the rock layer thickness corresponding to the depth range is greater than the minimum engineering fracturing thickness; If the above conditions are met, it is determined to be the target fracturing layer; The step of determining the target perforation location in step S7 includes: A comprehensive brittleness index was constructed by normalizing and weighting the brittle mineral content, fracture toughness, and well logging horizontal stress difference coefficient. Plot the profile curve of the overall brittleness index as a function of depth; Identify different local maxima points in the profile curve within the target fracturing layer; Determine whether the depth interval between the different local maxima is greater than the minimum perforation cluster spacing; If the above conditions are met, the location is determined to be the target firing hole.

2. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 1, characterized in that, The method for calculating the reduced modulus in step S3 is as follows: The slope of the tangent at the top of the unloading segment in the load-displacement curve is extracted as the contact stiffness. The reduced modulus is calculated using the ratio of contact stiffness to the square root of the contact projected area, with a geometric correction factor related to the shape of the indenter introduced during the calculation.

3. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 2, characterized in that, The calculation of the microelastic modulus in step S3 is based on the reduced modulus and the conversion relationship satisfies the following conditions: The reciprocal of the reduced modulus is equal to the sum of the first ratio term and the second ratio term; Wherein, the first ratio term is the ratio of the value obtained by subtracting the square of the microscopic Poisson's ratio of the rock material to the microscopic elastic modulus of the rock material; The second ratio is the ratio of the value obtained by subtracting the square of the Poisson's ratio of the indenter material to the elastic modulus of the indenter material.

4. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 1, characterized in that, The method for calculating fracture toughness in step S3 is as follows: The area under the loading curve in the load-displacement curve is calculated as the total energy; The area under the unloading curve in the load-displacement curve is calculated as the elastic recovery energy; Subtracting the elastic recovery energy from the total energy yields the irreversible deformation energy. The pure plastic deformation energy is calculated based on the ratio of residual depth to maximum indentation depth, and the fracture energy is obtained by subtracting the pure plastic deformation energy from the irreversible deformation energy. The critical energy release rate is determined based on the ratio of fracture energy to the contact projected area, and the fracture toughness is calculated using the square root of the product of the critical energy release rate and the reduced modulus.

5. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 1, characterized in that, The steps for performing gridded dot testing in step S2 include: A matrix of measurement points is divided on the test surface of the nanoindentation specimen, with the number of rows and columns of the matrix measurement points being no less than 5. The spacing between adjacent measuring points is controlled to be greater than five times the diameter of the residual indentation mark to eliminate the stress field interference effect; Abnormal data points that fall at mineral grain boundaries or pores in the matrix measurement points are removed, and the arithmetic mean of the remaining valid measurement points is taken as the test result of the rock at that depth.

6. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 1, characterized in that, The processing method for the nano-indentation specimen in step S1 includes: Cut drilling cuttings into thin slices of a predetermined thickness; The thin sheet was coarsely ground using sandpaper with progressively increasing grit. The coarsely ground thin sheet is mechanically polished using diamond polishing fluid until the surface roughness is less than the preset nanometer precision threshold. The polished surface is then ultrasonically cleaned and dried.

7. The method for determining the fracturing horizon of the top strata based on multi-scale rock mechanics characterization according to claim 3, characterized in that, The indenter material is diamond, with an elastic modulus ranging from 1100 GPa to 1200 GPa and a Poisson's ratio ranging from 0.05 to 0.

09.

8. The method for determining the fracturing horizon of the roof strata based on multi-scale rock mechanics characterization according to claim 1, characterized in that, The roof strata are coal seam roofs, and the maximum indentation depth of the gridded dot test is controlled between 2000nm and 3000nm.

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