CN118607773A - An intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipelines - Google Patents

Abstract

The invention discloses an intelligent calculation method for underground excavation footage safety of inclined shafts of different long-distance pipelines, which relates to the technical field of drilling, and comprises the steps of carrying out sectional sampling and analysis on cores through a mine design scheme and a target mine position, obtaining a drilling information set, drawing a geological section diagram from the ground to the mine, marking three-dimensional coordinate information at a plurality of layers of junctions or abnormal points in the obtained geological section diagram, counting the total number n of level marks and the total number m of abnormal point marks to form a drawing information set, establishing a geological obliquity association analysis model, carrying out training to obtain a level mark regulation coefficient Cjxs and an abnormal point mark regulation coefficient Ycxs, obtaining a geological evaluation index Pgzs after fitting, and matching with a preset geological inclined shaft obliquity fluctuation evaluation threshold P, so as to obtain an underground excavation footage regulation scheme of the current geological inclined shaft, improve the safety and scientificity of inclined shaft excavation, and provide reliable technical support for mine construction.

Description

An intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipelines

Technical Field

The invention relates to the technical field of drilling, and in particular to an intelligent calculation method for the safety of excavation footage under different inclination angles of inclined shafts of long-distance pipelines.

Background Art

Long-distance pipeline engineering is an important field in modern infrastructure construction, involving the long-distance transportation of energy such as oil and natural gas. The design and construction of pipeline inclined shafts is one of the key technologies. Specifically, the excavation of pipeline inclined shafts at different inclination angles is a complex and challenging link in long-distance pipeline engineering.

In the existing practice of pipeline inclined shaft excavation, traditional methods mostly rely on experience and simple geological parameter analysis, and lack systematic and intelligent calculation methods. This leads to unforeseen risks in the excavation process under complex geological conditions, including rock collapse and equipment damage. In addition, due to the diversity and uncertainty of geological conditions, existing methods are often difficult to accurately predict and respond to these risks, resulting in the need for temporary adjustments to the plan during the construction process, which increases construction time and costs.

Summary of the invention

In view of the deficiencies in the prior art, the present invention provides an intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts, which solves the problems mentioned in the background technology.

To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for intelligently calculating the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts, comprising the following steps:

S1. Based on the mine design and the target ore vein location, the core is sampled and analyzed in sections to determine the physical properties of the rock formation, such as hardness, density, porosity and water content, and the core analysis data is recorded and sorted to form a drilling information group;

S2. Surface geological mapping is performed through drone mapping to record topography, landforms and geological features. Based on the drilling information group, a geological profile from the ground to the ore vein is drawn to show the distribution, thickness and inclination of different strata. The three-dimensional coordinate information of the intersections of several layers or abnormal points in the obtained geological profile is marked, and the total number of layer marks n and the total number of abnormal point marks m are obtained to form a mapping information group;

S3. Establish a geological dip correlation analysis model for the drilling information group and the mapping information group by using a machine learning algorithm, and obtain the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs after training and analyzing the geological dip correlation analysis model;

S4. Fit the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs to obtain the geological evaluation index Pgzs, and match it with the preset geological inclined shaft inclination fluctuation assessment threshold P to obtain the excavation footage control plan under the current geological inclined shaft inclination.

Preferably, the location and number of drill holes are arranged according to the mine design plan and the target ore vein location, drilling is carried out using drilling equipment, continuous core samples are obtained, the cores are sampled and analyzed in sections, the physical properties of the rock formation, such as hardness, density, porosity and water content, are determined, the core analysis data are recorded and organized, and a drilling information group is formed, including: borehole location information, core hardness information, core sample information, rock formation characteristic information and additional information.

Preferably, the mapping task is carried out by using drone equipment, wherein the mapping task includes covering the mine design area and the target vein location, and obtaining high-resolution images and LiDAR data of the surface by flying the drone along the planned route to record the topography, landforms and geological features;

The data collected by the drone is preprocessed simultaneously, including image stitching, point cloud generation and data cleaning to remove noise and outliers.

Preferably, the drone mapping data and drilling information group are integrated to form a complete geological model, including using geological modeling software to construct a three-dimensional geological model to display the stratigraphic structure and characteristics, using geological modeling software to generate a geological profile along a selected profile line to display the distribution, thickness and inclination of the rock strata from the ground to the vein, marking geological features in the profile, including faults, fissures, rock strata interfaces, rock strata dip and inclination, groundwater level, sedimentary structure and intrusive rock mass, and recording their three-dimensional coordinate information (x, y, z), and simultaneously recording and marking the number of rock strata interfaces to obtain the total number of hierarchical marks n, recording and marking abnormal geological features to obtain the total number of abnormal point marks m, and abnormal geological features including: faults, fissures, groundwater level and lithology mutations.

Preferably, the drilling information group and the mapping information group are preprocessed, including data cleaning processing, data standard processing, data normalization processing and data integration, to form a preprocessed drilling information group and mapping information group;

The drilling information group includes: core rock hardness value Dyz, core rock density value Mdz, sampling depth value Sdz and drilling sampling core coordinates (qx, qy, qz);

The mapping information group includes: the total number of level marks n, the level boundary coordinates (bx, by, bz), the total number of outlier marks m and the outlier coordinates (yx, yy, yz);

Then, a machine learning algorithm is used to establish a geological dip correlation analysis model for the preprocessed drilling information group and mapping information group. After training and analyzing the geological dip correlation analysis model, the layer marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs are obtained.

Preferably, the hierarchical labeling control coefficient Cjxs is obtained by the following calculation method:

Where, Cjxs represents the layer mark control coefficient, n represents the total number of layer marks, i represents the i-th layer, Dyz represents the core rock hardness value, Mdz represents the core rock density value, Sdz represents the sampling depth value, qx, qy, qz represent the x-axis, y-axis, and z-axis values of the drilling sampling core coordinates, respectively. They represent the x-axis, y-axis and z-axis values of the average coordinates of the drilling sampling core, c1 represents the proportional coefficient of the core rock hardness value Dyz and the sampling depth value Sdz, c2 represents the proportional coefficient of the core rock density value Mdz and the sampling depth value Sdz, c3 represents the drilling sampling core coordinates (qx, qy, qz) and the average coordinates of the drilling sampling core The proportionality factor of the calculated result;

Among them, 0≤c1≤1, 0≤c2≤1, 0≤c3≤1, and c1+c2+c3＝1.

Preferably, the outlier mark control coefficient Ycxs is obtained by the following calculation formula:

Wherein, Ycxs is the regulation coefficient of the abnormal point mark, n represents the total number of level marks, i represents the i-th level rock layer, bx, by, bz represent the x-axis, y-axis, and z-axis values of the level boundary coordinates, m represents the total number of abnormal point marks, yx, yy, yz represent the x-axis, y-axis, and z-axis values of the abnormal point coordinates, y1 represents the proportional coefficient of the calculation results of the total number of level marks n and the total number of abnormal point marks m, and y2 represents the proportional coefficient of the calculation results of the level boundary coordinates (bx, by, bz) and the abnormal point coordinates (yx, yy, yz);

Among them, 0≤y1≤1, 0≤y2≤1, and y1+y2＝1.

Preferably, the level mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs are fitted to obtain the geological evaluation index Pgzs;

The geological evaluation index Pgzs is obtained by the following calculation formula:

Where Pgzs represents the geological evaluation index, Cjxs represents the level marking control coefficient, Ycxs represents the abnormal point marking control coefficient, p1 and p2 represent the proportional coefficients of the level marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs respectively;

Among them, 0≤p1≤1, 0≤p2≤1, and p1+p2＝1, and K represents a correction constant.

Preferably, the excavation footage control scheme under the current geological inclined shaft inclination angle is obtained by matching the preset geological inclined shaft inclination fluctuation assessment threshold value P with the geological assessment index Pgzs;

The excavation footage control scheme under the inclination of the geological inclined shaft is obtained by the following matching method:

The geological assessment index Pgzs is less than the geological inclined shaft inclination fluctuation assessment threshold P. The current geological design inclined shaft inclination and excavation footage depth are obtained without abnormality, and the excavation footage depth or length and the angle information of the inclined shaft inclination are not adjusted;

The geological assessment index Pgzs≥geological inclined shaft inclination fluctuation assessment threshold P, obtain the current geological design inclined shaft inclination and excavation depth anomalies, adjust the excavation depth or length and the angle information of the inclined shaft inclination, send a notification to the relevant staff, change the relevant inclined shaft inclination angle information, excavation footage information or related positioning position, and then execute steps S1 to S5 again for cyclic detection.

Preferably, specific notification and prompting of relevant staff are carried out according to the content of the excavation footage control plan under the geological inclined shaft inclination, including: conveying the excavation footage control plan to the on-site workers, so that the relevant workers understand the current excavation footage and inclined shaft inclination problems, storing the content of the excavation footage control plan under the geological inclined shaft inclination, and updating it at a fixed period;

Among them, notification methods include SMS, email, communication software pop-up prompts and preset language prompts.

The present invention provides an intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts, which has the following features:

Beneficial effects:

(1) Through steps S1 to S5, the mine design plan and the target ore vein position are sampled and analyzed in sections, a drilling information group is obtained, and a geological profile from the ground to the ore vein is drawn. The three-dimensional coordinate information of several layer intersections or abnormal points in the obtained geological profile is marked, and the total number of layer marks n and the total number of abnormal point marks m are statistically obtained to form a mapping information group. Then, a geological inclination correlation analysis model is established. After training and analyzing the geological inclination correlation analysis model, the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs are obtained. After fitting, the geological evaluation index Pgzs is obtained, and matched with the preset geological inclined shaft inclination fluctuation evaluation threshold P, the excavation footage control plan under the current geological inclined shaft inclination is obtained, which greatly improves the safety and scientificity of inclined shaft excavation and provides reliable technical support for mine construction.

(2) By calculating the hierarchical marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs, combined with the three-dimensional geological model and geological profile, the areas with complex or abnormal geological conditions can be identified and marked. With the support of quantitative and visualized geological data, the influence of human factors on decision-making is reduced, ensuring the scientificity and reliability of decision-making. In addition, it can process a large amount of geological data and reduce the time and errors of manual operations.

(3) By calculating the geological assessment index Pgzs, the excavation progress control plan under the inclination of the geological inclined shaft is obtained, and the data of different levels of rock strata and abnormal points are combined to make the geological assessment more comprehensive and accurate, which is helpful to identify geological anomalies and potential risks and improve the scientific nature of the geological assessment. At the same time, when the geological conditions are abnormal, the system will send a notification to the relevant staff through SMS, email, communication software pop-up prompts and preset language prompts to ensure that the control plan is communicated in time, thereby improving construction safety and efficiency, as well as comprehensive monitoring and management.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the steps of an intelligent calculation method for the safety of excavation footage of a long-distance pipeline under different inclined shaft inclination angles according to the present invention.

DETAILED DESCRIPTION

The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

Long-distance pipeline engineering is an important field in modern infrastructure construction, involving the long-distance transportation of energy such as oil and natural gas. The design and construction of pipeline inclined shafts is one of the key technologies. Specifically, the excavation of pipeline inclined shafts at different inclination angles is a complex and challenging link in long-distance pipeline engineering.

In the existing practice of pipeline inclined shaft excavation, traditional methods mostly rely on experience and simple geological parameter analysis, and lack systematic and intelligent calculation methods. This leads to unforeseen risks in the excavation process under complex geological conditions, including rock collapse and equipment damage. In addition, due to the diversity and uncertainty of geological conditions, existing methods are often difficult to accurately predict and respond to these risks, resulting in the need for temporary adjustments to the plan during the construction process, which increases construction time and costs.

Example 1

The present invention provides an intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts, referring to FIG1 , comprising the following steps:

S1. Based on the mine design and the target ore vein location, the core is sampled and analyzed in sections to determine the physical properties of the rock formation, such as hardness, density, porosity and water content, and the core analysis data is recorded and sorted to form a drilling information group;

S2. Surface geological mapping is performed through drone mapping to record topography, landforms and geological features. Based on the drilling information group, a geological profile from the ground to the ore vein is drawn to show the distribution, thickness and inclination of different strata. The three-dimensional coordinate information of the intersections of several layers or abnormal points in the obtained geological profile is marked, and the total number of layer marks n and the total number of abnormal point marks m are obtained to form a mapping information group;

S3. Establish a geological dip correlation analysis model for the drilling information group and the mapping information group by using a machine learning algorithm, and obtain the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs after training and analyzing the geological dip correlation analysis model;

S4. Fit the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs to obtain the geological evaluation index Pgzs, and match it with the preset geological inclined shaft inclination fluctuation assessment threshold P to obtain the excavation footage control plan under the current geological inclined shaft inclination.

In this embodiment, through steps S1 to S5, the mine design plan and the target ore vein position are analyzed and the rock core is sampled and analyzed in sections to obtain a drilling information group, and a geological profile from the ground to the ore vein is drawn. The three-dimensional coordinate information of several layer intersections or abnormal points in the obtained geological profile is marked, and the total number of layer marks n and the total number of abnormal point marks m are statistically obtained to form a mapping information group. Then, a geological inclination correlation analysis model is established, and the geological inclination correlation analysis model is trained and analyzed to obtain the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs. After fitting, the geological evaluation index Pgzs is obtained, and it is matched with the preset geological inclined shaft inclination fluctuation evaluation threshold P to obtain the excavation footage control plan under the current geological inclined shaft inclination, which greatly improves the safety and scientificity of inclined shaft excavation and provides reliable technical support for mine construction.

Example 2

This embodiment is explained in Embodiment 1, please refer to FIG1 , specifically: by designing the mine and the target ore vein, arranging the location and number of the boreholes, drilling with drilling equipment, obtaining continuous core samples, sampling and analyzing the cores in sections, determining the physical properties of the hardness, density, porosity and water content of the rock formation, recording and collating the core analysis data, forming a drilling information group, including: borehole location information, core hardness information, core sample information, rock formation characteristic information and additional information.

The mapping mission is carried out by using drone equipment, including covering the mine design area and the location of the target vein, and obtaining high-resolution images and LiDAR data of the surface by flying the drone along the planned route to record the topography, landforms and geological features;

The data collected by the drone is preprocessed simultaneously, including image stitching, point cloud generation and data cleaning to remove noise and outliers.

Example 3

This embodiment is an explanation of the embodiment 1, please refer to Figure 1, specifically: integrating the UAV mapping data and the drilling information group to form a complete geological model, including using geological modeling software to build a three-dimensional geological model to display the stratigraphic structure and characteristics, using the geological modeling software to generate a geological profile along the selected profile line to display the distribution, thickness and inclination of the rock strata from the ground to the vein, marking geological features in the profile, including faults, fissures, rock strata interfaces, rock strata dip and inclination, groundwater level, sedimentary structure and intrusive rock mass, and recording their three-dimensional coordinate information (x, y, z), synchronously recording and marking the number of rock strata interfaces to obtain the total number of hierarchical marks n, recording and marking abnormal geological features to obtain the total number of abnormal point marks m, and abnormal geological features including faults, fissures, groundwater level and lithology mutations.

Preprocessing the drilling information group and the mapping information group, including data cleaning, data standard processing, data normalization and data integration, to form a preprocessed drilling information group and a mapping information group;

Data cleaning: Identify and remove incomplete, erroneous, inaccurate or irrelevant parts of the data. Data cleaning helps identify and remove noise data, duplicate data or other invalid data in the information to ensure the accuracy and reliability of subsequent analysis.

Data standard processing: Data standardization refers to converting data into a unified format and unit, including unit conversion and data type conversion;

Data normalization: Normalization ensures that the data are within the same scale range and eliminates the dimensional effects between different variables, making the comparison between different variables more comparable and easier to perform subsequent data analysis and model building;

The drilling information group includes: core rock hardness value Dyz, core rock density value Mdz, sampling depth value Sdz and drilling sampling core coordinates (qx, qy, qz);

The mapping information group includes: the total number of level marks n, the level boundary coordinates (bx, by, bz), the total number of outlier marks m and the outlier coordinates (yx, yy, yz);

Then, a machine learning algorithm is used to establish a geological dip correlation analysis model for the preprocessed drilling information group and mapping information group. After training and analyzing the geological dip correlation analysis model, the layer marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs are obtained.

The hierarchical marking control coefficient Cjxs is obtained by the following calculation method:

Where, Cjxs represents the layer mark control coefficient, n represents the total number of layer marks, i represents the i-th layer, Dyz represents the core rock hardness value, Mdz represents the core rock density value, Sdz represents the sampling depth value, qx, qy, qz represent the x-axis, y-axis, and z-axis values of the drilling sampling core coordinates, respectively. They represent the x-axis, y-axis and z-axis values of the average coordinates of the drilling sampling core, c1 represents the proportional coefficient of the core rock hardness value Dyz and the sampling depth value Sdz, c2 represents the proportional coefficient of the core rock density value Mdz and the sampling depth value Sdz, c3 represents the drilling sampling core coordinates (qx, qy, qz) and the average coordinates of the drilling sampling core The proportionality factor of the calculated result;

Among them, 0≤c1≤1, 0≤c2≤1, 0≤c3≤1, and c1+c2+c3＝1.

The outlier mark control coefficient Ycxs is obtained by the following calculation formula:

Wherein, Ycxs is the regulation coefficient of the abnormal point mark, n represents the total number of level marks, i represents the i-th level rock layer, bx, by, bz represent the x-axis, y-axis, and z-axis values of the level boundary coordinates, m represents the total number of abnormal point marks, yx, yy, yz represent the x-axis, y-axis, and z-axis values of the abnormal point coordinates, y1 represents the proportional coefficient of the calculation results of the total number of level marks n and the total number of abnormal point marks m, and y2 represents the proportional coefficient of the calculation results of the level boundary coordinates (bx, by, bz) and the abnormal point coordinates (yx, yy, yz);

Among them, 0≤y1≤1, 0≤y2≤1, and y1+y2＝1.

In this embodiment, by calculating the hierarchical marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs, combined with the three-dimensional geological model and geological profile, areas with complex or abnormal geological conditions are identified and marked. With the support of quantitative and visualized geological data, the influence of human factors on decision-making is reduced, ensuring the scientificity and reliability of decision-making. It is also possible to process a large amount of geological data and reduce the time and errors of manual operations.

Example 4

This embodiment is explained in Example 1, please refer to Figure 1, specifically: the level mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs are fitted to obtain the geological evaluation index Pgzs;

The geological evaluation index Pgzs is obtained by the following calculation formula:

Where Pgzs represents the geological evaluation index, Cjxs represents the level marking control coefficient, Ycxs represents the abnormal point marking control coefficient, p1 and p2 represent the proportional coefficients of the level marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs respectively;

Among them, 0≤p1≤1, 0≤p2≤1, and p1+p2＝1, and K represents a correction constant.

By matching the preset geological inclined shaft inclination fluctuation assessment threshold P with the geological assessment index Pgzs, the excavation footage control scheme under the current geological inclined shaft inclination is obtained;

The excavation footage control scheme under the inclination of the geological inclined shaft is obtained by the following matching method:

The geological assessment index Pgzs is less than the geological inclined shaft inclination fluctuation assessment threshold P. The current geological design inclined shaft inclination and excavation footage depth are obtained without abnormality, and the excavation footage depth or length and the angle information of the inclined shaft inclination are not adjusted;

The geological assessment index Pgzs≥the geological inclined shaft inclination fluctuation assessment threshold P, obtains the current geological design inclined shaft inclination and excavation depth anomalies, adjusts the excavation depth or length and the angle information of the inclined shaft inclination, sends a notification to the relevant staff, changes the relevant inclined shaft inclination angle information, excavation footage information or the relevant positioning position, and executes steps S1 to S5 again for cyclic detection. Combined with the three-dimensional geological model, the geological conditions and construction feasibility of the new positioning point are evaluated at the same time to ensure that the adjusted inclined shaft inclination and excavation depth or length meet the safety requirements.

According to the content of the excavation footage control plan under the geological inclined shaft inclination, specific notifications and reminders are given to relevant staff, including: conveying the excavation footage control plan to on-site workers, so that relevant staff can understand the current excavation footage and inclined shaft inclination issues, storing the content of the excavation footage control plan under the geological inclined shaft inclination, and updating it at a fixed period;

Among them, notification methods include SMS, email, communication software pop-up prompts and preset language prompts.

In this embodiment, by calculating the geological assessment index Pgzs and obtaining the excavation footage control plan under the inclination of the geological inclined shaft, the data of rock strata and abnormal points at different levels are combined to make the geological assessment more comprehensive and accurate, which is helpful to identify geological abnormal points and potential risks and improve the scientific nature of the geological assessment. At the same time, when the geological conditions are abnormal, the system will send a notification to the relevant staff through text messages, emails, communication software pop-up prompts and preset language prompts to ensure timely communication of the control plan, thereby improving construction safety and efficiency, and conducting comprehensive monitoring and management.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims (10)

1. An intelligent calculation method for the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts, characterized in that it includes the following steps: S1. Based on the mine design and the target ore vein location, the core is sampled and analyzed in sections to determine the physical properties of the rock formation, such as hardness, density, porosity and water content, and the core analysis data is recorded and sorted to form a drilling information group; S2. Surface geological mapping is performed through drone mapping to record topography, landforms and geological features. Based on the drilling information group, a geological profile from the ground to the ore vein is drawn to show the distribution, thickness and inclination of different strata. The three-dimensional coordinate information of the intersections of several layers or abnormal points in the obtained geological profile is marked, and the total number of layer marks n and the total number of abnormal point marks m are obtained to form a mapping information group; S3. Establish a geological dip correlation analysis model for the drilling information group and the mapping information group by using a machine learning algorithm, and obtain the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs after training and analyzing the geological dip correlation analysis model; S4. Fit the layer mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs to obtain the geological evaluation index Pgzs, and match it with the preset geological inclined shaft inclination fluctuation assessment threshold P to obtain the excavation footage control plan under the current geological inclined shaft inclination. 2. According to claim 1, a method for intelligently calculating the safety of excavation footage at different inclination angles of long-distance pipeline inclined shafts is characterized by: arranging the location and number of drill holes according to the mine design plan and the target ore vein location, drilling with drilling equipment, obtaining continuous core samples, sampling and analyzing the cores in sections, determining the physical properties of the hardness, density, porosity and water content of the rock formation, recording and arranging the core analysis data, and forming a drilling information group, including: drilling location information, core hardness information, core sample information, rock formation characteristic information and additional information. 3. According to claim 1, a method for intelligently calculating the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts is characterized by: using unmanned aerial vehicle equipment to carry out mapping tasks, wherein the mapping tasks include covering the mine design area and the target vein location, and obtaining high-resolution images and LiDAR data of the surface by flying the unmanned aerial vehicle according to the planned route, and recording the terrain, landform and geological characteristics; The data collected by the drone is preprocessed simultaneously, including image stitching, point cloud generation and data cleaning to remove noise and outliers. 4. According to claim 1, a method for intelligently calculating the safety of excavation footage at different inclination angles of long-distance pipeline inclined shafts is characterized in that: the drone mapping data and the drilling information group are integrated to form a complete geological model, including using geological modeling software to construct a three-dimensional geological model to display the stratigraphic structure and characteristics, using the geological modeling software to generate a geological profile along the selected profile line to display the distribution, thickness and inclination of the rock strata from the ground to the vein, marking geological features in the profile, including faults, cracks, rock strata interfaces, rock strata inclination and dip, groundwater level, sedimentary structure and intrusive rock mass, and recording their three-dimensional coordinate information (x, y, z), synchronously recording and marking the number of rock strata interfaces to obtain the total number of hierarchical marks n, recording and marking abnormal geological features to obtain the total number of abnormal point marks m, and abnormal geological features including: faults, cracks, groundwater level and lithology mutation. 5. According to the method of claim 1, the method is characterized by: pre-processing the drilling information group and the mapping information group, including data cleaning, data standard processing, data normalization and data integration, to form the pre-processed drilling information group and mapping information group; The drilling information group includes: core rock hardness value Dyz, core rock density value Mdz, sampling depth value Sdz and drilling sampling core coordinates (qx, qy, qz); The mapping information group includes: the total number of level marks n, the level boundary coordinates (bx, by, bz), the total number of outlier marks m and the outlier coordinates (yx, yy, yz); Then, a machine learning algorithm is used to establish a geological dip correlation analysis model for the preprocessed drilling information group and mapping information group. After training and analyzing the geological dip correlation analysis model, the layer marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs are obtained. 6. According to the method of intelligent calculation of the safety of excavation footage of long-distance pipelines under different inclined shaft inclination angles in claim 5, it is characterized in that: the hierarchical marking control coefficient Cjxs is obtained by the following calculation method: Where, Cjxs represents the layer mark control coefficient, n represents the total number of layer marks, i represents the i-th layer, Dyz represents the core rock hardness value, Mdz represents the core rock density value, Sdz represents the sampling depth value, qx, qy, qz represent the x-axis, y-axis, and z-axis values of the drilling sampling core coordinates, respectively. They represent the x-axis, y-axis and z-axis values of the average coordinates of the drilling sampling core, c1 represents the proportional coefficient of the core rock hardness value Dyz and the sampling depth value Sdz, c2 represents the proportional coefficient of the core rock density value Mdz and the sampling depth value Sdz, c3 represents the drilling sampling core coordinates (qx, qy, qz) and the average coordinates of the drilling sampling core The proportionality factor of the calculated result; Among them, 0≤c1≤1, 0≤c2≤1, 0≤c3≤1, and c1+c2+c3＝1. 7. According to claim 5, a method for intelligently calculating the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts is characterized in that: the abnormal point marking control coefficient Ycxs is obtained by the following calculation formula: Wherein, Ycxs is the regulation coefficient of the abnormal point mark, n represents the total number of level marks, i represents the i-th level rock layer, bx, by, bz represent the x-axis, y-axis, and z-axis values of the level boundary coordinates, m represents the total number of abnormal point marks, yx, yy, yz represent the x-axis, y-axis, and z-axis values of the abnormal point coordinates, y1 represents the proportional coefficient of the calculation results of the total number of level marks n and the total number of abnormal point marks m, and y2 represents the proportional coefficient of the calculation results of the level boundary coordinates (bx, by, bz) and the abnormal point coordinates (yx, yy, yz); Among them, 0≤y1≤1, 0≤y2≤1, and y1+y2＝1. 8. According to claim 1, a method for intelligently calculating the safety of excavation footage under different inclination angles of long-distance pipeline inclined shafts is characterized by: fitting the level mark control coefficient Cjxs and the abnormal point mark control coefficient Ycxs to obtain the geological evaluation index Pgzs; The geological evaluation index Pgzs is obtained by the following calculation formula: Where Pgzs represents the geological evaluation index, Cjxs represents the level marking control coefficient, Ycxs represents the abnormal point marking control coefficient, p1 and p2 represent the proportional coefficients of the level marking control coefficient Cjxs and the abnormal point marking control coefficient Ycxs respectively; Among them, 0≤p1≤1, 0≤p2≤1, and p1+p2＝1, and K represents a correction constant. 9. According to claim 1, a method for intelligently calculating the safety of excavation footage under different inclined shaft inclination angles of a long-distance pipeline, characterized in that: by matching a preset geological inclined shaft inclination fluctuation assessment threshold value P with a geological assessment index Pgzs, an excavation footage control scheme under the current geological inclined shaft inclination angle is obtained; The excavation footage control scheme under the inclination of the geological inclined shaft is obtained by the following matching method: The geological assessment index Pgzs is less than the geological inclined shaft inclination fluctuation assessment threshold P. The current geological design inclined shaft inclination and excavation footage depth are obtained without abnormality, and the excavation footage depth or length and the angle information of the inclined shaft inclination are not adjusted; The geological assessment index Pgzs≥geological inclined shaft inclination fluctuation assessment threshold P, obtain the current geological design inclined shaft inclination and excavation depth anomalies, adjust the excavation depth or length and the angle information of the inclined shaft inclination, send a notification to the relevant staff, change the relevant inclined shaft inclination angle information, excavation footage information or related positioning position, and then execute steps S1 to S5 again for cyclic detection. 10. According to claim 9, a method for intelligently calculating the safety of excavation footage under different inclined shaft inclination angles of a long-distance pipeline is characterized in that: specific notification and prompting of relevant staff members are made according to the content of the excavation footage control plan under the geological inclined shaft inclination angle, including: conveying the excavation footage control plan to the on-site workers so that the relevant staff members understand the current excavation footage and inclined shaft inclination angle problems, storing the content of the excavation footage control plan under the geological inclined shaft inclination angle, and updating it at a fixed period; Among them, notification methods include SMS, email, communication software pop-up prompts and preset language prompts.