A Method for Selecting the Roughness REV of the Fracture Surface of Laser-Cracked Rock

Abstract

The present invention discloses a method for selecting the representative elementary volume (REV) of the roughness of a laser-induced rock fracture surface, which comprises the following steps: 1) obtaining the rock fracture surface and point cloud data after laser-induced fracturing; 2) processing the point cloud data; 3) calculating the roughness index of the entire rock fracture surface; 4) selecting and calculating the representative element of the rock fracture surface roughness; 5) determining the REV of the fracture surface roughness. The present invention can characterize the roughness of a large-size rock fracture surface without being affected by the large local undulation characteristics of the rock fracture surface, and can generate automated processing software and equipment for use in the fields of rock mechanics, fracture mechanics, and rock fracture seepage and convective heat transfer, etc., to analyze the mutual influence of the fracture surface roughness characteristics on its mechanical characteristics and water-rock interaction, and has wide practicability in this technical field.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser-assisted rock breaking, and particularly relates to a method for selecting the Representative Elementary Volume (REV) of the roughness of a laser-induced rock fracture surface. Background Art

[0002] The characterization of the rock fracture surface after laser treatment is crucial for understanding and revealing the rock fracture mechanism. The Joint Roughness Coefficient (JRC) of the rock joint surface profile is one of the key parameters for measuring the roughness of the rock fracture surface, and it is crucial for understanding and studying the generation of the rock fracture surface and the flow of rock.

[0003] In recent years, the laser rock breaking technology has been regarded as one of the most potential auxiliary rock breaking methods due to its high efficiency and environmental friendliness. Researchers have conducted a large number of studies from the perspectives of the temperature field distribution, mechanical characteristics, and fracture distribution of rocks under the action of lasers, and have made great contributions to the research on the failure mode and mechanism of rocks under the action of lasers. In addition, researchers have carried out a large number of quantitative studies on the roughness characteristics of the rock fracture surface under test conditions such as Brazilian splitting and uniaxial compression. However, the research on the roughness of the rock fracture surface after laser action is relatively less, because there are significant differences between the rock fracture surface after laser irradiation and the fracture surfaces obtained by Brazilian splitting and uniaxial compression. On the one hand, an inhomogeneous transient temperature field is generated inside the rock after laser irradiation. Due to the differences in the physical and chemical properties between mineral particles, zones characterized by different temperature stages appear inside the rock. These zones have large temperature differences, which in turn affect the morphology of the rock fracture surface, resulting in large undulation characteristics locally on the rock fracture surface, which is not conducive to the characterization of the roughness of the large-size rock fracture surface. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for selecting the Representative Elementary Volume (REV) of the roughness of a laser-induced rock fracture surface, which can characterize the roughness of the large-size rock fracture surface without being affected by the large local undulation characteristics of the rock fracture surface.

[0005] To achieve the above purpose, the present invention provides a method for selecting the Representative Elementary Volume (REV) of the roughness of a laser-induced rock fracture surface, including the following steps:

[0006] 1) Acquisition of the rock fracture surface and point cloud data after laser fracturing;

[0007] Obtain the rock fracture surface after laser fracturing; then, use 3D laser scanning to obtain the data of the rock fracture surface after laser fracturing and store it as a three-dimensional point cloud data file in stl format.

[0008] 2) Point cloud data processing;

[0009] According to the accuracy requirement, the sampling interval of the point cloud data is determined as δx. The point cloud data is discretized based on the Kriging interpolation method. The data at the required positions is retained in the original point cloud data, and the data information at the redundant positions is deleted. Then, the absolute elevation in the data is converted into relative elevation, and the converted data is saved as a csv format file containing three columns of information, namely the x, y, and z coordinate values, and output, denoted as Mnn(x, y, z);

[0010] 3) Calculate the roughness index of the entire rock fracture surface;

[0011] According to the Mnn(x, y, z) data, calculate the profile roughness coefficient of the fracture surface, denoted as JRC_M. Take the average value of the obtained profile roughness coefficients as the roughness index of the fracture surface;

[0012] 4) Selection and calculation of representative units of the rock fracture surface roughness;

[0013] Denote the center point of the projection plane of the fracture surface in the XOY direction as the center point of the rectangle. Take a rectangle with length and width of a and b respectively. The fracture surface area corresponding to this rectangular area is used as the representative unit, denoted as Rnn(x, y, z). Then, according to the calculation method in step 3), the structural roughness coefficient of the fracture surface Rnn(x, y, z) can be obtained, denoted as JRC_R;

[0014] 5) Judgment of the REV of the fracture surface roughness;

[0015] By continuously changing the values of a and b with the sampling interval as the step size, the updated JRC_R value can be obtained, and the relative error between the JRC_M and JRC_R values is calculated. The data with an error ≤ 5% is obtained, and the fracture surface area of Rnn(x, y, z) with the smallest a and b values is determined as the REV of the rock fracture surface roughness.

[0016] As a further solution of the present invention: in step 3), the profile roughness coefficient is calculated by the following formula:

[0017] JRC = 32.2 + 32.47Log 10 Z2

[0018]

[0019] In the formula, Z2 is the root mean square of the first-order difference of the two-dimensional profile coordinates of the fracture, dimensionless; Z i,j is the coordinate of the z value of the two-dimensional fracture profile at the jth point in the y direction when the x value is the same, in mm; M is the number of sampling points; δx is the sampling interval; through calculation, the profile roughness coefficients of several contour lines along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire fracture surface.

[0020] As a further solution of the present invention: in step 4), when selecting the projection plane, the side lengths of the selected area have the following characteristics: a / b = Xmax / Ymax, and a ∈ [Xmin, Xmax], b ∈ [Ymin, Ymax].

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0022] It can characterize the roughness of large-sized rock fracture surfaces without being affected by the characteristics of large local undulations on the rock fracture surfaces.

[0023] Based on the profile roughness coefficient, the roughness of the intact rock fracture surface after laser irradiation is characterized by the roughness of the representative unit, which can reduce the workload of calculating the roughness of large-sized rock fracture surfaces.

[0024] This method can generate automated processing software and equipment for fields such as rock mechanics, fracture mechanics, and rock fracture seepage and convective heat transfer, analyze the mutual influence of fracture surface roughness characteristics on their mechanical characteristics and water-rock interaction, and has wide practicability in this technical field. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic flow chart of the method for selecting the REV of the roughness of the laser-induced rock fracture surface of the present invention;

[0026] Figure 2 In (a), it is the granite fracture surface obtained by laser preparation;

[0027] Figure 2 In (b), it is the result of the granite fracture surface reconstructed by software;

[0028] Figure 2 In (c), it is the elevation data distribution obtained by discretizing the point cloud data of the granite fracture surface scanned by 3D laser;

[0029] Figure 2 In (d), it is the statistical result of the elevation distribution of the granite fracture surface;

[0030] Figure 3 It is the calculation result of the roughness coefficient of each divided unit. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The present invention will be further described below through embodiments.

[0032] As Figure 1 shown, a method for selecting the REV of the roughness of the laser-induced rock fracture surface includes the following steps:

[0033] 1) Obtaining the rock fracture surface and point cloud data after laser fracturing;

[0034] Obtain the rock fracture surface after laser fracturing; then, use 3D laser scanning to obtain the data of the rock fracture surface after laser fracturing and store it as a 3D point cloud data file in stl format; among them, the rock fracture surface after laser fracturing can be obtained by conducting a laser fracturing rock experiment;

[0035] 2) Point cloud data processing;

[0036] Determine the point cloud data sampling interval as δx according to the accuracy requirement, discretize the point cloud data based on the Kriging interpolation method, retain the data at the required positions in the original point cloud data and delete the data information at redundant positions, then convert the absolute elevation in the data into relative elevation, and save the converted data as a csv format file containing three columns of information which are the x, y, and z coordinate values for output, denoted as Mnn(x,y,z);

[0037] 3) Calculate the roughness index of the entire rock fracture surface;

[0038] According to the Mnn(x,y,z) data, calculate the profile roughness coefficient of this fracture surface, denoted as JRC_M, and take the average value of the obtained profile roughness coefficients as the roughness index of this fracture surface;

[0039] 4) Selection and calculation of representative units of rock fracture surface roughness;

[0040] Denote the center point of the projection plane of this fracture surface in the XOY direction as the center point of the rectangle, take a rectangle with length and width being a and b respectively, and regard the fracture surface area corresponding to this rectangular area as the representative unit, denoted as Rnn(x,y,z). Then, according to the calculation method in step 3), the structure roughness coefficient of the fracture surface Rnn(x,y,z) can be obtained, denoted as JRC_R;

[0041] 5) Judgment of REV of fracture surface roughness;

[0042] By continuously changing the values of a and b with the sampling interval as the step size, the updated JRC_R values can be obtained, and calculate the relative error between the JRC_M and JRC_R values. Obtain the data with an error ≤ 5%, and determine the Rnn(x,y,z) fracture surface area with the smallest a and b values as the REV of the roughness of this rock fracture surface.

[0043] Further, in step 3), the profile roughness coefficient is calculated by the following formula:

[0044] JRC = 32.2 + 32.47Log 10 Z2 (1)

[0045]

[0046] wherein, Z2 is the root mean square of the first-order difference of the two-dimensional cross-section coordinates of the crack, dimensionless; Z i,j is the coordinate of the z value of the two-dimensional crack cross-section at the j-th point in the y direction when the x value is the same, in mm; M is the number of sampling points; δx is the sampling interval; by calculation, several contour line roughness coefficients along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire crack surface.

[0047] Furthermore, in step 4), when selecting the projection plane, the side length of the selected area has the following characteristics: a / b = Xmax / Ymax, and a ∈ [Xmin, Xmax], b ∈ [Ymin, Ymax].

[0048] Example:

[0049] The specific steps are as follows:

[0050] 1), Select a disc-shaped granite specimen of a certain mineral and conduct a laser splitting test to obtain the rock splitting effect as Figure 2 (a) shown, and its splitting surface size is approximately 50 mm × 25 mm (length × width);

[0051] 2), Use 3D laser scanning to obtain the point cloud data of the rock crack surface and save it as an stl format file;

[0052] 3), Use processing software (such as Surfer, Geomagic, etc.) to open the obtained stl format data file of the rock structure surface topography, set the sampling interval δx to 0.2 mm, use the Kriging interpolation method to discretize the data, delete redundant data points, and perform grid sparsification processing on the data to obtain approximately 31496 rows and 3 columns of data. The 3 columns of data are the x, y, and z coordinate value information respectively. Subsequently, save the processed data as a dat format file;

[0053] 4), Considering the differences between crack surfaces and the influence of boundary effects, etc. on the surface topography, use software such as Matlab to process the exported dat format file, convert the absolute elevation therein to relative elevation, and save the processed data as a csv format file, Figure 2 (b) is the result of the crack surface topography obtained by reconstructing with relative elevation;

[0054] 5), Use the processing software (such as Surfer, Geomagic, etc.) to open the csv format file processed in the above steps again, with a sampling interval of 0.2 mm, and the elevation distribution result of the crack surface after grid sparsification processing can be obtained, as Figure 2 (c) shown, where there are a total of 100 × 51 data points representing elevation information, and the elevation distribution result of the crack surface obtained through mathematical statistics, as Figure 2(d), it is found that the average elevation of the fracture surface is about 3.211 mm;

[0055] 6), Use Matlab programming to calculate the characteristic parameter Z2 that constitutes the contour line of the structural plane in the data, and calculate the contour line roughness coefficient according to the Z2 value using formula (1) and formula (2).

[0056] In this example, only the roughness coefficient of the structural plane along the y direction is analyzed. Taking 51 points in the y-axis direction as a line segment, the roughness coefficient of this line segment can be calculated. By analogy, use Matlab programming to calculate the roughness coefficients of all 100 line segments in the y direction. Take the average value of the 100 roughness coefficients as the roughness coefficient of this fracture surface. The calculation result is 15.4311, denoted as JRC_M;

[0057] 7), Take a rectangle with length and width of a and b respectively. When a = 50 mm and b = 25 mm, the rectangle is the projection plane of the entire fracture surface in the XOY direction. To reduce the calculation amount, in this embodiment, rectangles of different sizes are taken with a step size of 5 mm, and 10 representative units of fracture surfaces of different sizes can be obtained. Use the above method to program with Matlab to calculate the roughness coefficients of the representative units, and the results are as Figure 3 shown;

[0058] 8), According to the above calculation results, calculate the relative error between the roughness coefficient of the representative unit and the roughness coefficient of the entire fracture surface, and determine that when the error is less than or equal to 5%, the representative unit with the smallest size is the REV of the roughness of this fracture surface.

[0059] It is found through calculation that when a×b = 30 mm×15 mm, it meets the selection criterion of REV, and its roughness coefficient is about 15.7966, and the relative error with the roughness coefficient of the entire fracture surface is only 2.37%. Therefore, in this embodiment, it is considered that the fracture surface with a length of 30 mm and a width of 15 mm is the REV of the roughness of this fracture surface.

Claims

1. A method for selecting the roughness REV of the crack surface of laser-induced rock fracture, characterized in that: The following steps are involved: 1) Acquisition of rock fracture surface and point cloud data after laser fracturing; Obtaining the rock fracture surface after laser fracturing; then, using 3D laser scanning to obtain the rock fracture surface data after laser fracturing, and storing it as a three-dimensional point cloud data file in stl format; 2) Point cloud data processing; According to the accuracy requirements, the sampling interval of the point cloud data is determined to be δx, and the point cloud data is discretized based on the Kriging interpolation method. The data of the required positions are retained in the original point cloud data and the data information of the redundant positions is deleted. Then, the absolute elevation in the data is converted into relative elevation, and the converted data is saved as a csv format file containing three columns of information, namely x, y, and z coordinate values, for output, recorded as Mnn(x, y, z); 3) Calculate the roughness index of the entire rock fracture surface; According to the Mnn (x, y, z) data, the profile roughness coefficient of the crack surface is calculated, recorded as JRC_M, and the average value of the obtained profile roughness coefficient is used as the roughness index of the crack surface; 4) Selection and calculation of representative units of rock fracture surface roughness; The center point of the projection plane of the crack surface in the XOY direction is recorded as the center point of the rectangle. A rectangle with a length and a width of b is taken. The crack surface area corresponding to the rectangular area is recorded as a representative unit as Rnn(x, y, z). Then, according to the calculation method of step 3), the structural roughness coefficient of the crack surface Rnn(x, y, z) can be obtained, which is recorded as JRC_R. 5) Determination of crack surface roughness REV; By continuously changing the values ​​of a and b with the sampling interval as the step size, the updated JRC_R value can be obtained, and the relative error between the JRC_M and JRC_R values ​​can be calculated to obtain data with an error of ≤5%, and the Rnn (x, y, z) fracture surface area with the smallest a and b values ​​is determined as the REV of the rock fracture surface roughness.

2. The method for selecting the roughness REV of the crack surface of a laser-induced rock fracture according to claim 1, characterized in that: In step 3), the profile roughness coefficient is calculated using the following formula: JRC=32.2+32.47Log 10 Z2 Where Z2 is the root mean square of the first-order difference of the two-dimensional fracture profile coordinates, dimensionless; i,j is the coordinate of the z value of the two-dimensional fracture profile of the jth point in the y direction when the x value is the same, mm; M is the number of sampling points; δx is the sampling interval; through calculation, the roughness coefficients of several contour lines along the x direction on the entire rock structure surface are obtained, and the average value of all contour line roughness coefficients is used as the roughness index of the entire fracture surface.

3. A method for selecting the roughness REV of a laser-fractured rock fracture surface according to claim 1 or 2, characterized in that: In step 4), when the projection plane is selected, the side length of the selected area has the following characteristics: a / b=Xmax / Ymax, and a∈[Xmin,Xmax], b∈[Ymin,Ymax].

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