Electronization logging method for geologic drilling of water-power engineering

Abstract

The invention belongs to the technical field of hydroelectric engineering geological exploration, and particularly relates to a hydroelectric engineering geological borehole electronic logging method. The invention relates to a hydroelectric engineering geological drilling electronic recording method, which comprises the following steps of: taking a drilled hydroelectric engineering geological drilling core picture, taking a core box with a fixed specification as a reference, judging and marking the development condition of a structural surface through a method of automatic image identification and auxiliary manual recheck confirmation, and marking the relative coordinate difference of positions by adjacent structural surfaces to obtain the hydroelectric engineering geological drilling core picture. According to the method, the lithology box is used as a core, the length characteristic of the core is calculated according to the actual length specification of the lithology box, classified statistics is carried out according to requirements, and therefore the drilling recording process is completed, the steps are simple and easy to learn, electronic recording work in field work is reduced to the maximum extent, and meanwhile repeated recording work of later recording is avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of hydropower engineering geological exploration, and in particular relates to an electronic cataloging method for hydropower engineering geological boreholes. Background Art

[0002] Hydropower engineering geological drilling is a small-diameter hole that uses a drill bit or other auxiliary means to drill into the stratum and obtain rock cores (samples) in the early stage of hydropower engineering survey to explore underground resources and geological conditions. The purpose of hydropower engineering geological drilling is to obtain rock cores. The obtained rock cores are generally catalogued on-site by geological professionals to obtain data such as the core collection rate, acquisition rate, and rock quality index (RQD), and to describe the core characteristics through text, so as to evaluate the geological conditions of the underground space at the proposed project location.

[0003] The cores obtained in hydropower engineering geological drilling are usually divided into overburden cores and bedrock cores according to the material composition characteristics. The overburden core has a loose structure and relatively uniform properties; the bedrock core is affected by the cutting of the structural surface, and usually after coring, it will be broken along the structural surface to form block, short column or long column core samples. Geological logging is the work of statistically describing the sampling rate, rock quality indicators, lithology, color, material composition, degree of structural surface development and special geological phenomena of various core samples.

[0004] In the existing geological cataloging work, the paper recording method is mainly used. Usually, the size of the core sample is measured with a tape measure, and its block diameter (block core) or length (columnar core) is recorded, and the inclination of its structural surface is measured with a protractor, and a paper record is formed in a specific format. The advantage of this working method is that it is simple and easy to learn and easy to master. The disadvantage is that the measurement and recording process is too cumbersome, and the paper data formed by the record needs to be electronically sorted and entered later, which increases the workload of on-site geological cataloging. In view of this, in recent years, with the popularity of electronic handheld devices at any time, many software development companies have softwareized the above-mentioned paper recording process and formed software that can be used for borehole cataloging on handheld device terminals (tablets or smart phones), but its working methods and processes are not essentially different from traditional paper cataloging, and it only reduces the electronic sorting of paper records. On the contrary, since the on-site record input of electronic devices is not as convenient as paper records, it increases the working time of on-site cataloging, and lacks effective help in improving the efficiency of borehole cataloging. Summary of the invention

[0005] In view of the above problems, the purpose of the present invention is to provide an electronic cataloging method for geological boreholes in hydropower engineering. The method is based on digital image recognition technology, has simple steps and is easy to learn. It minimizes the electronic data entry work in field work, and also avoids the repeated entry of later records. It greatly improves the efficiency of geological borehole cataloging in hydropower engineering.

[0006] The technical solution of the present invention is: a method for electronic cataloging of hydropower engineering geological boreholes, comprising the following steps: S1: Place the cores drilled in the core box in the order in which they were taken; S2: Definition of basic information for drilling, including project name, borehole number, borehole location, main lithology of the drilled core, and core box specifications. The core box specifications include the length and number of single cells of the core box. S3: Take photos of the cores in sequence. When taking photos, the cores in a single core box should fill the camera frame, and the lens should be centered and pointed vertically downward for overhead shooting; S4: performing tilt correction and cropping on the core photos taken to form core images; S5: After the correction and cropping of the core image, the layer position is outlined with short lines and the attributes are defined. The outlined layer position is divided into three types of attributes, namely, round division, stratum division and base-cover boundary division; S6: Taking the lower left corner of the core image as the coordinate origin and the pixel point as the scale, record the midpoint coordinates of the various layer positions outlined in step S5; S7: According to the core category, the core box is divided into boxes and sections. If the segmented core category is bedrock, the length is estimated. The length estimation is based on the single-cell length of the core box. The true length between adjacent short lines of the same attribute is calculated by the midpoint coordinates of the short lines drawn or identified. If the segmented core category is overburden, the structural surface of the bedrock section core is identified. S8: Verify the actual length of each attribute short line according to the actual situation of the on-site core; S9: Repeat steps S3 to S8 until all the core photos of the borehole are cataloged; S10: storing the intermediate data generated in the above steps and calculating and generating reports; S11: Based on the basic data statistics of lithology cataloging and combined with field observations, expand and improve the geological description of the drill core; S12: The cataloging is completed, and a cataloging table and a core photo with a watermark are generated.

[0007] In step S1, the core boxes are placed horizontally, and the distance between adjacent core boxes is ≥15 cm.

[0008] In step S5, the round division is used to determine the round cycles of the core in this box, and is outlined according to the placement position of the single-round core label; the stratum division is used to determine the geological stratification of the borehole. When the core in this box is of a single lithology, the stratum division can be omitted; the base-cover boundary division is used to determine whether the core category belongs to bedrock or overburden. When the core in this box is of a single core category, the base-cover boundary division can be omitted, and the short lines outlining the stratification position are distinguished by different colors according to the attributes.

[0009] The process of identifying the structural surface of the bedrock core in step S7 is as follows: S71: image preprocessing, preprocessing the segmented images of the bedrock core, including grayscale image conversion and filtering; S72: edge detection is performed on the preprocessed image to detect and identify the development of the core structure surface and mark it with short lines; S73: Manually review and modify the detected core structural surfaces; perform manual intervention and modification on the structural surfaces that are misidentified or missed, including deleting the short-line markings of the misidentified structural surfaces and outlining the short-line markings of the missed structural surfaces; S74: Taking the lower left corner of the core photo as the coordinate origin and the pixel points as the scale, record the midpoint coordinates, length and inclination of the short line of the structural surface marked in step S72 and step S73.

[0010] The specific process of grayscale processing and filtering processing in the image preprocessing of step S71 is as follows: S711: Read the RGB value matrix of the image. For an image with m×n pixels, three color component matrices R(m×n), G(m×n), and B(m×n) can be obtained. S712: The average value method is used to calculate the average value of the RGB three components of the image to obtain the gray value matrix Gray(m×n) of the image. The algorithm is Gray(m×n)= (R(m×n), G(m×n), B(m×n)) / 3.

[0011] S713: Read the gray value matrix Gray (m×n) of the image and set a Gaussian template with a standard deviation of σ=15 and a window size of 5×5; S714: Move the central element of the Gaussian template, and convolve a 5×5 window data in the image with the Gaussian template in order from top to bottom and from left to right. The final result is the Gaussian filtering result of the current center point. S715: Replace the grayscale values ​​in the original image matrix with the Gaussian filtering result, thereby obtaining a filtered image.

[0012] In step S72, edge detection is performed on the pre-processed image to detect and identify the development of the core structural surface. The specific process is as follows: S721: construct a LOG convolution operator, the LOG convolution operator is a log operator with a LOG filter standard deviation σ=1.1 and a filter size (n×n) of 9×9; S722: Convolve the Gaussian filter image obtained in step S72 with the log convolution operator; S723: According to the convolution calculation result, the zero crossing points in the detection result are obtained to obtain a binary image matrix, thereby determining the edge of a single core in the core box, that is, the location where the structural surface is developed.

[0013] The process of length estimation in step S7 is as follows: S701: automatically classify the short lines and their attached coordinate information according to the attributes of the short lines. According to the attributes of the short lines identified or drawn above, the short lines can be classified into four types: short lines for round division, short lines for stratum division, short lines for basement division and short lines for structural plane division; S702: Determine the real size of the image according to the predefined core box specifications. The specific process is: Knowing the net length of the lithology box L0, the edge width of the core box L W0 , then the actual size of the lithology box photo L = L0 + 2L W0 , through the predefined core box specifications: core box grid number n, single grid width d w ; Then the actual length L of the core in this box can be calculated 总 =n* L0, and at the same time, the lower left corner of the core box is taken as the origin, the x-axis length is X=L, and the y-axis length is Y=n×d w +2L W0 The true length of the reference coordinate system; S703: Determine the real coordinates of each attribute short line. The main algorithm is as follows: According to the image information, the pixel resolution of the image is obtained to be m×n. Similarly, with the lower left corner of the image as the origin, an image pixel coordinate system with an x-axis length of m and a y-axis length of n can be established. Then, the real coordinates of any pixel point (m0, n0) in the image are x0=X*(m0 / m), y0=Y*(n0 / n); S704: Correction of the inclination of the real coordinates, based on the inclination α and length information L of the short line d , the above true length is corrected to ensure the accuracy of the length data when calculating the rock quality index. The formula for inclination correction is x= (x0-0.5*L d *cosα), y=y0; S705: According to the classification results, the actual horizontal spacing between adjacent short lines of each attribute is calculated one by one. The specific process is as follows: given that the coordinates of short line A are (x1, y1) and the coordinates of short line B are (x2, y2), the number of grids between short line A and short line B is i=[(y2-y1) / d w], the real horizontal distance between short line A and short line B is S=i*L0+x2-x1; S706: Mark the actual horizontal spacing calculation result between adjacent short lines according to the color of the short lines.

[0014] The technical effects of the present invention are as follows: 1. The present invention takes photos of the drilled hydropower engineering geological borehole cores, uses a core box of fixed specifications as a reference, and uses automatic image recognition assisted by manual review and confirmation to determine and mark the development of structural surfaces. The relative coordinate difference of the adjacent structural surface marking positions is used, and the length characteristics of the cores are calculated with reference to the actual length specifications of the lithology box, and classified and counted as required, thereby completing the process of borehole cataloging. The steps are simple and easy to learn, which reduces the electronic input work in field work to the greatest extent, and also avoids the repeated input of later records. 1. The present invention has a significant improvement in the efficiency of geological borehole cataloging for hydropower engineering projects; 2. The present invention avoids the tedious processes of measurement, recording and later electronic copying in the existing paper cataloging work, and realizes the workflow of carrying out geological cataloging of boreholes on portable electronic equipment terminals. At the same time, it well solves the problems of inconvenient recording and overly rigid processes in the existing electronic cataloging process; 3. The present invention uses core photo image recognition as the basic means, and completes the measurement work in the cataloging process through image coordinate calculation, which greatly simplifies the cataloging process. Its basic process and method are more in line with traditional cataloging habits and are easy to master; very little information needs to be manually input during the cataloging process, which greatly improves the efficiency of on-site work; the images and data of the cataloging process are displayed synchronously, and can be reviewed and compared with the on-site core conditions at any time, reducing the probability of cataloging errors; while collecting the geological characteristics and attributes of the core, its image data is also collected. After the cataloging work is completed, the relevant image data can be directly archived to the electronic core library for later reference and call.

[0015] The following is a further description with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flowchart of a method for electronic cataloging of geological boreholes in hydropower engineering according to an embodiment of the present invention.

[0017] Figure 2 The figure is a flow chart of structural surface identification according to an embodiment of the present invention.

[0018] Figure 3 This is a flow chart of length estimation according to an embodiment of the present invention. DETAILED DESCRIPTION Example 1

[0019] like Figure 1 As shown, a method for electronic cataloging of hydropower engineering geological boreholes includes the following steps: S1: Place the cores drilled in the core box in the order in which they were taken; S2: Definition of basic information for drilling, including project name, borehole number, borehole location, main lithology of the drilled core, and core box specifications. The core box specifications include the length and number of single cells of the core box. S3: Take photos of the cores in sequence. When taking photos, the cores in a single core box should fill the camera frame, and the lens should be centered and pointed vertically downward for overhead shooting; S4: performing tilt correction and cropping on the core photos taken to form core images; S5: After the correction and cropping of the core image, the layer position is outlined with short lines and the attributes are defined. The outlined layer position is divided into three types of attributes, namely, round division, stratum division and base-cover boundary division; S6: Taking the lower left corner of the core image as the coordinate origin and the pixel point as the scale, record the midpoint coordinates of the various layer positions outlined in step S5; S7: According to the core category, the core box is divided into boxes and sections. If the segmented core category is bedrock, the length is estimated. The length estimation is based on the single-cell length of the core box. The true length between adjacent short lines of the same attribute is calculated by the midpoint coordinates of the short lines drawn or identified. If the segmented core category is overburden, the structural surface of the bedrock section core is identified. S8: Verify the actual length of each attribute short line according to the actual situation of the on-site core; S9: Repeat steps S3 to S8 until all the core photos of the borehole are cataloged; S10: storing the intermediate data generated in the above steps and calculating and generating reports; S11: Based on the basic data statistics of lithology cataloging and combined with field observations, expand and improve the geological description of the drill core; S12: The cataloging is completed, and a cataloging table and a core photo with a watermark are generated.

[0020] The present invention takes photos of the drilled hydropower engineering geological borehole cores, takes the core box of fixed specifications as a reference, and uses automatic image recognition assisted by manual verification and confirmation to judge and mark the development of the structural surface. The relative coordinate difference of the adjacent structural surface marking positions is used, and the length characteristics of the core are calculated with reference to the actual length specifications of the lithology box, and classified and counted as required, thereby completing the process of borehole cataloging. The steps are simple and easy to learn, which reduces the electronic input work in the field work to the greatest extent, and also avoids the repeated input work of the later records. The efficiency of geological borehole cataloging for hydropower engineering is greatly improved; the present invention avoids the tedious processes of measurement, recording and later electronic copying in the existing paper cataloging work, realizes the workflow of borehole geological cataloging on portable electronic device terminals, and at the same time, well solves the problems of inconvenient recording and overly rigid processes in the existing electronic cataloging process; the present invention uses core photo image recognition as the basic means, completes the measurement work in the cataloging process by image coordinate calculation, greatly simplifies the cataloging process, and its basic process and method are more in line with traditional cataloging habits and easy to master; very little information needs to be manually input in the cataloging process, which greatly improves the efficiency of on-site work; the images and data of the cataloging process are displayed synchronously, and can be reviewed and compared with the on-site core conditions at any time, reducing the probability of cataloging errors; while collecting the geological characteristics and attributes of the core, its image data is also collected. After the cataloging work is completed, the relevant image data can be directly archived to the electronic core library for later reference and call.

[0021] In step S1, the core boxes are placed horizontally, and the distance between adjacent core boxes is ≥15 cm.

[0022] In step S5, the round division is used to determine the round cycles of the core in this box, and is outlined according to the placement position of the single-round core label; the stratum division is used to determine the geological stratification of the borehole. When the core in this box is of a single lithology, the stratum division can be omitted; the base-cover boundary division is used to determine whether the core category belongs to bedrock or overburden. When the core in this box is of a single core category, the base-cover boundary division can be omitted, and the short lines outlining the stratification position are distinguished by different colors according to the attributes.

[0023] like Figure 2 As shown, the process of identifying the structural surface of the bedrock core in step S7 is as follows: S71: image preprocessing, preprocessing the segmented images of the bedrock core, including grayscale image conversion and filtering; S72: edge detection is performed on the preprocessed image to detect and identify the development of the core structure surface and mark it with short lines; S73: Manually review and modify the detected core structural surfaces; perform manual intervention and modification on the structural surfaces that are misidentified or missed, including deleting the short-line markings of the misidentified structural surfaces and outlining the short-line markings of the missed structural surfaces; S74: Taking the lower left corner of the core photo as the coordinate origin and the pixel points as the scale, record the midpoint coordinates, length and inclination of the short line of the structural surface marked in step S72 and step S73.

[0024] The specific process of grayscale processing and filtering processing in the image preprocessing of step S71 is as follows: S711: Read the RGB value matrix of the image. For an image with m×n pixels, three color component matrices R(m×n), G(m×n), and B(m×n) can be obtained. S712: The average value method is used to calculate the average value of the RGB three components of the image to obtain the gray value matrix Gray(m×n) of the image. The algorithm is Gray(m×n)= (R(m×n), G(m×n), B(m×n)) / 3.

[0025] S713: Read the gray value matrix Gray (m×n) of the image and set a Gaussian template with a standard deviation of σ=15 and a window size of 5×5; S714: Move the central element of the Gaussian template, and convolve a 5×5 window data in the image with the Gaussian template in order from top to bottom and from left to right. The final result is the Gaussian filtering result of the current center point. S715: Replace the grayscale values ​​in the original image matrix with the Gaussian filtering result, thereby obtaining a filtered image.

[0026] In step S72, edge detection is performed on the pre-processed image to detect and identify the development of the core structural surface. The specific process is as follows: S721: construct a LOG convolution operator, the LOG convolution operator is a log operator with a LOG filter standard deviation σ=1.1 and a filter size (n×n) of 9×9; S722: Convolve the Gaussian filter image obtained in step S72 with the log convolution operator; S723: According to the convolution calculation result, the zero crossing points in the detection result are obtained to obtain a binary image matrix, thereby determining the edge of a single core in the core box, that is, the location where the structural surface is developed.

[0027] like Figure 3 As shown, the length estimation process in step S7 is as follows: S701: automatically classify the short lines and their attached coordinate information according to the attributes of the short lines. According to the attributes of the short lines identified or drawn above, the short lines can be classified into four types: short lines for round division, short lines for stratum division, short lines for basement division and short lines for structural plane division; S702: Determine the real size of the image according to the predefined core box specifications. The specific process is: Knowing the net length of the lithology box L0, the edge width of the core box L W0 , then the actual size of the lithology box photo L = L0 + 2L W0 , through the predefined core box specifications: core box grid number n, single grid width d w ; Then the actual length L of the core in this box can be calculated 总 =n* L0, and at the same time, the lower left corner of the core box is taken as the origin, the x-axis length is X=L, and the y-axis length is Y=n×d w +2L W0 The true length of the reference coordinate system; S703: Determine the real coordinates of each attribute short line. The main algorithm is as follows: According to the image information, the pixel resolution of the image is obtained to be m×n. Similarly, with the lower left corner of the image as the origin, an image pixel coordinate system with an x-axis length of m and a y-axis length of n can be established. Then, the real coordinates of any pixel point (m0, n0) in the image are x0=X*(m0 / m), y0=Y*(n0 / n); S704: Correction of the inclination of the real coordinates, based on the inclination α and length information L of the short line d , the above true length is corrected to ensure the accuracy of the length data when calculating the rock quality index. The formula for inclination correction is x= (x0-0.5*L d *cosα), y=y0; S705: According to the classification results, the actual horizontal spacing between adjacent short lines of each attribute is calculated one by one. The specific process is as follows: given that the coordinates of short line A are (x1, y1) and the coordinates of short line B are (x2, y2), the number of grids between short line A and short line B is i=[(y2-y1) / d w ], the real horizontal distance between short line A and short line B is S=i*L0+x2-x1; S706: Mark the actual horizontal spacing calculation result between adjacent short lines according to the color of the short lines.

[0028] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for electronic cataloguing of geological boreholes in hydropower engineering, characterized by: The following steps are involved: S1: Place the cores drilled in the core box in the order in which they were taken; S2: Definition of basic information for drilling, including project name, borehole number, borehole location, main lithology of the drilled core, and core box specifications. The core box specifications include the length and number of single cells of the core box. S3: Take photos of the cores in sequence. When taking photos, the cores in a single core box should fill the camera frame, and the lens should be centered and pointed vertically downward for overhead shooting; S4: performing tilt correction and cropping on the core photos taken to form core images; S5: After the correction and cropping of the core image, the layer position is outlined with short lines and the attributes are defined. The outlined layer position is divided into three types of attributes, namely, round division, stratum division and base-cover boundary division; S6: Taking the lower left corner of the core image as the coordinate origin and the pixel point as the scale, record the midpoint coordinates of the various layer positions outlined in step S5; S7: According to the core category, the core box is divided into boxes and sections. If the segmented core category is bedrock, the length is estimated. The length estimation is based on the single-cell length of the core box. The true length between adjacent short lines of the same attribute is calculated by the midpoint coordinates of the short lines drawn or identified. If the segmented core category is overburden, the structural surface of the bedrock section core is identified. S8: Verify the actual length of each attribute short line according to the actual situation of the on-site core; S9: Repeat steps S3 to S8 until all the core photos of the borehole are cataloged; S10: storing the intermediate data generated in the above steps and calculating and generating reports; S11: Based on the basic data statistics of lithology cataloging and combined with field observations, expand and improve the geological description of the drill core; S12: The cataloging is completed, and a cataloging table and a core photo with a watermark are generated.

2. A method for electronic cataloging of hydropower engineering geological boreholes according to claim 1, characterized in that: In step S1, the core boxes are placed horizontally, and the distance between adjacent core boxes is ≥15 cm.

3. The method for electronic cataloging of hydropower engineering geological boreholes according to claim 1, characterized in that: In step S5, the round division is used to determine the round cycles of the core in this box, and is outlined according to the placement position of the single-round core label; the stratum division is used to determine the geological stratification of the borehole. When the core in this box is of a single lithology, the stratum division can be omitted; the base-cover boundary division is used to determine whether the core category belongs to bedrock or overburden. When the core in this box is of a single core category, the base-cover boundary division can be omitted, and the short lines outlining the stratification position are distinguished by different colors according to the attributes.

4. The method for electronic cataloging of hydropower engineering geological boreholes according to claim 1, characterized in that: The process of identifying the structural surface of the bedrock core in step S7 is as follows: S71: image preprocessing, preprocessing the segmented images of the bedrock core, including grayscale image conversion and filtering; S72: Perform edge detection on the preprocessed image to detect and identify the development of the core structure surface and mark it with short lines; S73: Manually review and modify the detected core structural surfaces; perform manual intervention and modification on the structural surfaces that are misidentified or missed, including deleting the short-line markings of the misidentified structural surfaces and outlining the short-line markings of the missed structural surfaces; S74: Taking the lower left corner of the core photo as the coordinate origin and the pixel points as the scale, record the midpoint coordinates, length and inclination of the short line of the structural surface marked in step S72 and step S73.

5. A method for electronic cataloging of hydropower engineering geological boreholes according to claim 4, characterized in that: The specific process of grayscale processing and filtering processing in the image preprocessing of step S71 is as follows: S711: Read the RGB value matrix of the image. For an image with m×n pixels, three color component matrices R(m×n), G(m×n), and B(m×n) can be obtained. S712: The average value method is used to calculate the average value of the RGB three components of the image to obtain the gray value matrix Gray(m×n) of the image. The algorithm is Gray(m×n)= (R(m×n), G(m×n), B(m×n)) / 3.

6. S713: Read the gray value matrix Gray (m×n) of the image and set a Gaussian template with a standard deviation of σ=15 and a window size of 5×5; S714: Move the central element of the Gaussian template, and convolve a 5×5 window data in the image with the Gaussian template in order from top to bottom and from left to right. The final result is the Gaussian filtering result of the current center point. S715: Replace the grayscale values ​​in the original image matrix with the Gaussian filtering result, thereby obtaining a filtered image.

7. A method for electronic cataloging of hydropower engineering geological boreholes according to claim 5, characterized in that: In step S72, edge detection is performed on the pre-processed image to detect and identify the development of the core structural surface. The specific process is as follows: S721: construct a LOG convolution operator, the LOG convolution operator is a log operator with a LOG filter standard deviation σ=1.1 and a filter size (n×n) of 9×9; S722: Convolve the Gaussian filter image obtained in step S72 with the log convolution operator; S723: According to the convolution calculation result, the zero crossing points in the detection result are obtained to obtain a binary image matrix, thereby determining the edge of a single core in the core box, that is, the location where the structural surface is developed.

8. The method for electronic cataloging of hydropower engineering geological boreholes according to claim 1, characterized in that: The process of length estimation in step S7 is as follows: S701: automatically classify the short lines and their attached coordinate information according to the attributes of the short lines. According to the attributes of the short lines identified or drawn above, the short lines can be classified into four types: short lines for round division, short lines for stratum division, short lines for basement division and short lines for structural plane division; S702: Determine the real size of the image according to the predefined core box specifications. The specific process is: Knowing the net length of the lithology box L0, the edge width of the core box L W0 , then the actual size of the lithology box photo L = L0 + 2L W0 , through the predefined core box specifications: core box grid number n, single grid width d w ; Then the actual length L of the core in this box can be calculated 总 =n* L0, and at the same time, the lower left corner of the core box is taken as the origin, the x-axis length is X=L, and the y-axis length is Y=n×d w +2L W0 The true length of the reference coordinate system; S703: Determine the real coordinates of each attribute short line. The main algorithm is as follows: According to the image information, the pixel resolution of the image is obtained to be m×n. Similarly, with the lower left corner of the image as the origin, an image pixel coordinate system with an x-axis length of m and a y-axis length of n can be established. Then, the real coordinates of any pixel point (m0, n0) in the image are x0=X*(m0 / m), y0=Y*(n0 / n); S704: Correction of the inclination of the real coordinates according to the inclination α and length information L of the short line d , the above true length is corrected to ensure the accuracy of the length data when calculating the rock quality index. The formula for inclination correction is x=(x0-0.5*L d *cosα), y=y0; S705: According to the classification results, the actual horizontal spacing between adjacent short lines of each attribute is calculated one by one. The specific process is as follows: given that the coordinates of short line A are (x1, y1) and the coordinates of short line B are (x2, y2), the number of grids between short line A and short line B is i=[(y2-y1) / d w ], the real horizontal distance between short line A and short line B is S=i*L0+x2-x1; S706: Mark the actual horizontal spacing calculation result between adjacent short lines according to the color of the short lines.

Images