CN110968840A - Method for judging grade of tunnel surrounding rock based on magnetotelluric sounding resistivity - Google Patents
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Abstract
The invention discloses a method for judging the grade of tunnel surrounding rock based on magnetotelluric sounding resistivity, which comprises the following steps: (1) establishing a corresponding relation model of the tunnel surrounding rock grade and the resistivity interval according to the tunnel surrounding rock grade and the tunnel body resistivity numerical value sample of the known region; (2) acquiring a resistivity value of a region to be classified; (3) and (3) obtaining the tunnel surrounding rock grade of the region to be classified according to the resistivity of the region to be classified obtained in the step (2) and the corresponding relation model between the tunnel surrounding rock grade and the resistivity interval established in the step (1). By adopting the technical scheme, the method has stronger applicability and quantification, overcomes the error problem of field investigation and manual judgment, overcomes the defect that the drilling wave velocity can not be continuously calculated, overcomes the difficulty problem of solving the seismic wave velocity, can judge the grade of the surrounding rock according to the geodetic depth resistivity, and provides a reliable basis for the classification of the surrounding rock for tunnel design.
Description
Technical Field
The invention relates to a method for judging the grade of surrounding rocks of a tunnel based on magnetotelluric sounding resistivity, belongs to the technical field of geological exploration construction, and particularly relates to the field of a method for grading the surrounding rocks of a railway tunnel.
Background
In recent years, with the development of high-speed railways, railways in complex areas are constructed more and more, so that the more the design work of tunnels, the more the classification of tunnel surrounding rocks is the most important basis for tunnel design. The tunnels with different surrounding rock grades have great difference in construction cost, and inaccurate surrounding rock grades can cause a project capital budget gap to ensure that the project cannot be smoothly carried out. Different construction processes need to be adopted for different surrounding rock grades, and great construction risks are brought to inaccurate surrounding rock grade judgment. The classification of the surrounding rock is the basis for selecting a construction method, performing scientific management and correctly evaluating economic benefits, determining loads (loose loads) on a structure, determining the type and size of a lining structure, establishing labor quota, material consumption standard and the like.
In the tunnel design stage, the grade of the surrounding rock of the tunnel is determined according to factors such as field investigation, wave velocity of rock at the tunnel body, geophysical prospecting abnormity, burial depth and the like. The field investigation is to determine the tunnel surrounding rock grade of the rock mass by collecting geological data of the area, performing site reconnaissance, performing field outcrop geological mapping, analyzing the geological age of the rock, the lithology of the stratum and the like. According to the method, the surrounding rock grade is analyzed only according to the characteristics of outcrop rocks, and the characteristic error of deep rocks is large because the characteristic error of the deep rocks cannot be obtained. The method is visual and accurate, but only represents the rock wave velocity at the hole, the rock wave velocity of the whole area cannot be obtained, and the method has certain destructive effect on the environment. The geophysical prospecting abnormity, the burial depth and other factors generally mean that the tunnel portal is provided with 5 grades, the shallow buried section is provided with 4 grades (the burial depth is less than 40-50 m), the buried depth is generally provided with 3 grades and rarely provided with 2 grades, and if the structure such as fracture exists, the section of unfavorable factors such as geophysical prospecting abnormity, lithologic contact and the like generally can be improved by one grade. The method has large human factors and large errors.
Therefore, the tunnel surrounding rock grading in the prior art has different defects, and a simple, convenient and quick practical method is urgently needed to solve the problem.
Disclosure of Invention
Therefore, the invention aims to provide a method for judging the classification of the surrounding rocks of the tunnel based on the magnetotelluric sounding resistivity, which determines the grade of the surrounding rocks of the tunnel according to the magnetotelluric sounding resistivity and provides a reliable basis for the design of the tunnel.
In order to achieve the purpose, the method for judging the grade of the tunnel surrounding rock based on the magnetotelluric sounding resistivity comprises the following steps:
(1) establishing a corresponding relation model of the tunnel surrounding rock grade and the resistivity interval according to the tunnel surrounding rock grade and the tunnel body resistivity numerical value sample of the known region;
(2) acquiring a resistivity value of a region to be classified;
(3) and (3) obtaining the tunnel surrounding rock grade of the region to be classified according to the resistivity of the region to be classified obtained in the step (2) and the corresponding relation model between the tunnel surrounding rock grade and the resistivity interval established in the step (1).
The resistivity value is obtained by the following steps: acquiring magnetotelluric data with a surfer format as a standard result; extracting the GRID data file and the BLN data file of the hole body coordinate; reading the extracted GRID file and the extracted BLN data file of the hole body coordinate by adopting MapGen software, calculating and outputting the abscissa, ordinate and resistivity value at the intersection of the hole body line and the GRID data.
When the tunnel body resistivity is extracted through the MapGen software, if the tunnel body line does not have an intersection point with the calculated resistivity value, the tunnel body resistivity is obtained by adopting the weighted average of the resistivity values.
And (3) performing normal distribution probability density function calculation on the resistivity value at least twice continuously, and removing the value of which the calculation result is less than 99.7% each time.
The corresponding relation between the tunnel surrounding rock grade and the resistivity interval is the corresponding relation between the tunnel surrounding rock grade and the resistivity interval with different lithology.
The magnetotelluric data acquisition interval is 5-10 m.
The number of the counted resistivity values is more than 20000.
And removing abnormal values of the resistivity caused by the acquisition according to the influence factors of magnetotelluric acquisition.
And drawing a resistivity section diagram, and explaining the distribution condition of the resistivity, the range of the resistivity and the grade of the tunnel surrounding rock by sections according to the lithology and the resistivity of the stratum of the tunnel body, so as to realize the evaluation of the grade of the tunnel surrounding rock.
And determining an applicable area for judging the grade of the tunnel surrounding rock based on the resistivity interval according to the source area of the resistivity numerical value sample.
By adopting the technical scheme, compared with the prior art, the method for judging the grade of the surrounding rock of the tunnel based on the magnetotelluric sounding resistivity has stronger applicability and quantificationity, overcomes the error problem of field investigation and manual judgment, overcomes the defect that the drilling wave velocity can not be continuously calculated, overcomes the difficulty problem of solving the seismic wave velocity, can judge the grade of the surrounding rock according to the magnetotelluric sounding resistivity, and provides a reliable basis for grading the surrounding rock for tunnel design.
Drawings
FIG. 1 is a script code screenshot of an extract GRID data file.
Fig. 2 is a graph of raw data for resistivity at different points in different wall rock classes.
Fig. 3 is a diagram of data after the first positive distribution.
Fig. 4 is a diagram of data after a second positive distribution.
Fig. 5 is a graph showing data after the third positive distribution.
Fig. 6 is a schematic diagram of plotting a resistivity profile.
Detailed Description
The invention is described in further detail below with reference to the figures and the detailed description.
The invention provides a method for judging the grade of tunnel surrounding rock based on magnetotelluric sounding resistivity, which comprises the steps of establishing a data model according to a known resistivity value of a certain region and a tunnel surrounding rock grade sample, acquiring magnetotelluric data of a region to be classified of the region, extracting the resistivity value and obtaining the grade of the tunnel surrounding rock through the established data model.
In the embodiment, taking a completed tunnel in the northeast region as an example, statistics is performed on the surrounding rock grade values of the tunnel, magnetotelluric data corresponding to the region are collected, the resistivity of the hole body is extracted by using MapGen software, 21055 sample points with 8 lithologies are counted, and obvious abnormal points are removed in the counting process.
Specifically, after the results of standard parameter processing under the unified processing platform are obtained through the magnetotelluric detection, the numerical value of the resistivity at the tunnel body needs to be extracted for comparison with the surrounding rock of the tunnel body. The obtained standard result is in a surfer format, therefore, the hole body resistivity is extracted under a surfer platform, namely, a result graph is gridded under the surfer platform, the hole body elevation is drawn in a grid, the intersection point of a hole body line and a measuring point is defined as a gridded coordinate, the resistivity attribute is found out according to the coordinate, and the resistivity value is read out to form a resistivity file. The Surfer graph contains the contour line generated by the GRID, the GRID file is extracted firstly, but the Surfer operation interface does not provide the extraction function of the GRID data file, the extraction function of the GRID file hidden by the Surfer can be realized through the script code shown in the figure 1, and a foundation is laid for further processing and analysis of data. Next, the hole body line bln file is extracted. Some of the hole body lines are realized by leading-in bln whitening boundary files by using actual coordinates, and some of the hole body lines are represented by drawing lines on Surfer by using multi-segment lines. The BLN whitening file is generally a boundary, a feature line, etc. of a GRID data file, and is specifically referred to as a hole body line, and a hole body line file diagram needs to be extracted for subsequent hole body line data extraction. Different processing modes are adopted in different situations, the Surfer platform can be directly used for extracting the hole body line processing of the real coordinate, and the click extraction can be carried out through a mouse for representing the hole body line condition by drawing lines on the Surfer by using a multi-segment line. The calculation and acquisition of the cave body data are completed by adopting special software MapGen. The software reads in the extracted GRID file and hole body coordinate bln file, calculates the abscissa, ordinate and resistivity value at the intersection of the hole body line and the GRID data through a mathematical algorithm, and forms file output. And if the tunnel body line does not have an intersection point with the calculated resistivity value, obtaining the tunnel body line by adopting the weighted average of the resistivity values.
The surrounding rock grade division is carried out by utilizing the resistivity, and a large amount of resistivity and surrounding rock grade data need to be collected. Different units and people implement different methods in the collected data, the influences of secondary field sources such as field human noise, thunderstorms and the like are different, different determined surrounding rock grades recognized by different geologists are different, different lithological resistivities are influenced by lithology, hydrological conditions, weathering and the like, the differences have larger influences on certain resistivities, and the errors generated by the differences can be considered to be random and discrete after the data are put into the data. Under the condition of big data, the single lithology resistivity and the surrounding rock grading are subject to normal distribution. The normal distribution is also called "normal distribution", also called gaussian distribution, and is a very important probability distribution in the fields of mathematics, physics, engineering, etc., and has a great influence on many aspects of statistics. Normal distributions are often used in random errors, i.e., uncontrollable, subtle errors. Uncontrollable, i.e. a predicted positive or negative error of 50%, may be high or low with no clear possibility of error. The term "fine" means that many errors are superimposed, and none or some of the errors may be left or right. In fact, many errors have different influences, some errors have large influence and some errors have small influence, and the estimated positive and negative errors have not a complete 50% probability, so that the errors of a certain plane are more. However, in most cases, when such a large amount of fine errors are encountered, fitting calculation is performed by using normal distribution. Assuming that the resistivity is a random variable x, the random variable obeys a probability distribution where the location parameter μ can be understood as a mathematical expectation, the scale parameter σ can be understood as a variance, and the probability density function is:
according to the theory of positive distribution, when the index of the probability density function is less than 99.7%, it can be understood that the small probability event is almost impossible to occur according to the mathematical theory, so the present embodiment deletes the resistivity value of the original data which is outside the interval. Meanwhile, the corresponding relations between the resistivity of different lithologies and the surrounding rock grades are different, so that the resistivity of different lithologies and the surrounding rock grades are distinguished.
After the first normal distribution probability density function calculation of various lithologies is completed, the resistivities of most lithologies are relatively discrete, so normal distribution is performed again on the basis of the first normal distribution probability density function calculation result until the third normal distribution is achieved, the resistivity intervals are relatively concentrated, and as shown in fig. 2-5, the resistivities of different points in different surrounding rock grades are illustrated by taking the lithology as the rock pulp only as an example.
The corresponding relations between the surrounding rock grades and the resistivity of different lithologies are different, the relation between the resistivity and the surrounding rock grades cannot be directly given in original data, the result of primary normal distribution is discrete, secondary normal analysis is carried out on the basis of the primary normal distribution, the result of secondary normal distribution is relatively concentrated, but the range of the resistivity between the surrounding rock grades is large, the cross range between the grades is large, and specific results are shown in the following table 1:
TABLE 1 results of second order normal distribution
After the third normal distribution is performed on the basis of the second normal distribution, the corresponding relation between the resistivity and the surrounding rock grade can be clearly shown, as shown in the following table 2:
TABLE 2 results of cubic normal distribution
According to the results of the second and third normal distributions, the corresponding relationship between the resistivity and the surrounding rock is given by comprehensive analysis as the following table 3:
TABLE 3 results of the comprehensive analysis
After a corresponding relation model of the tunnel surrounding rock grade and the resistivity interval of the area is established, magnetotelluric data of an area to be classified in the area can be acquired by utilizing MTU-5, magnetotelluric acquisition intervals of 5-10 m are adopted, the specific intervals are determined according to field conditions, east-west-south-north polar tanks are 12.5m away from a measuring point, the resistivity of the east-west-south-north polar tanks is smaller than 1000 ohms, and magnetic rods are vertical. And after data acquisition, obtaining a resistivity profile of the area through inversion, gridding by utilizing sufer software according to a Kriging difference method, extracting the resistivity of the tunnel body by utilizing MapGen software with a gridding interval of 5m by 5m and an interval of 5m of resistivity, and analyzing according to the statistical result of the table 3, wherein the tunnel mileage is obtained through actual measurement, and the lithology is obtained according to drilling data.
And drawing a resistivity profile, as shown in FIG. 6, wherein the numerical values and the contour lines are resistivity numerical values which represent the resistivity of the stratum, the distribution range of the resistivity can be seen from the profile, and the grade of the surrounding rock at the tunnel body is explained according to the resistivity and the table 3. The surrounding rock grade also exists in the actual tunnel excavation process, and according to the comparison of the geophysical prospecting result and the actual result, the geophysical prospecting result can better reflect the actual surrounding rock grade, and only local adjustment is carried out. As can be seen from FIG. 6, the resistivity of the section is mainly medium-high resistance and is obviously compared with low resistance on the small-mileage side, and the lithology of the rock and the lithology of the small-mileage on the right side are different and relatively complete, and the fracture does not develop. The geophysical prospecting conjecture tunnel surrounding rock grade is V, VI and VIII, and the actual excavation result is consistent.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method for judging the grade of tunnel surrounding rock based on magnetotelluric sounding resistivity is characterized by comprising the following steps:
(1) establishing a corresponding relation model of the tunnel surrounding rock grade and the resistivity interval according to the tunnel surrounding rock grade and the tunnel body resistivity numerical value sample of the known region;
(2) acquiring a resistivity value of a region to be classified;
(3) and (3) obtaining the tunnel surrounding rock grade of the region to be classified according to the resistivity of the region to be classified obtained in the step (2) and the corresponding relation model between the tunnel surrounding rock grade and the resistivity interval established in the step (1).
2. The method for determining the grade of a tunnel wall rock based on magnetotelluric resistivity as claimed in claim 1, wherein the resistivity value is obtained by: acquiring magnetotelluric data with a surfer format as a standard result; extracting the GRID data file and the BLN data file of the hole body coordinate; reading the extracted GRID file and the extracted BLN data file of the hole body coordinate by adopting MapGen software, calculating and outputting the abscissa, ordinate and resistivity value at the intersection of the hole body line and the GRID data.
3. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric depth-sounding resistivity as claimed in claim 2, wherein: when the tunnel body resistivity is extracted through the MapGen software, if the tunnel body line does not have an intersection point with the calculated resistivity value, the tunnel body resistivity is obtained by adopting the weighted average of the resistivity values.
4. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric depth-sounding resistivity as claimed in claim 2, wherein: and (3) performing normal distribution probability density function calculation on the resistivity value at least twice continuously, and removing the value of which the calculation result is less than 99.7% each time.
5. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric resistivity as claimed in any one of claims 1 to 4, wherein: the corresponding relation between the tunnel surrounding rock grade and the resistivity interval is the corresponding relation between the tunnel surrounding rock grade and the resistivity interval with different lithology.
6. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric resistivity as claimed in any one of claims 2 to 4, wherein: the magnetotelluric data acquisition interval is 5-10 m.
7. The method of determining a grade of a tunnel wall rock based on geodetic electromagnetic sounding resistivity of claim 6, wherein: the number of the counted resistivity values is more than 20000.
8. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric resistivity as claimed in any one of claims 1 to 4, wherein: and removing abnormal values of the resistivity caused by the acquisition according to the influence factors of magnetotelluric acquisition.
9. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric resistivity as claimed in any one of claims 1 to 4, further comprising, after the step 3: and drawing a resistivity section diagram, and explaining the distribution condition of the resistivity, the range of the resistivity and the grade of the tunnel surrounding rock by sections according to the lithology and the resistivity of the stratum of the tunnel body, so as to realize the evaluation of the grade of the tunnel surrounding rock.
10. The method for determining the grade of the surrounding rock of the tunnel based on the magnetotelluric resistivity as claimed in any one of claims 1 to 4, wherein: and determining an applicable area for judging the grade of the tunnel surrounding rock based on the resistivity interval according to the source area of the resistivity numerical value sample.
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| CN111913226A (en) * | 2020-06-28 | 2020-11-10 | 中铁第一勘察设计院集团有限公司 | Railway tunnel extremely-high ground stress identification method based on aviation geophysical prospecting three-dimensional inversion result |
| CN112329099A (en) * | 2020-10-27 | 2021-02-05 | 中国铁路设计集团有限公司 | Intelligent matching method for main tunnel of railway mountain tunnel based on custom database |
| CN114355447A (en) * | 2022-01-13 | 2022-04-15 | 中国安能集团第三工程局有限公司 | Tunnel engineering surrounding rock grade rapid division method and device |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111913226A (en) * | 2020-06-28 | 2020-11-10 | 中铁第一勘察设计院集团有限公司 | Railway tunnel extremely-high ground stress identification method based on aviation geophysical prospecting three-dimensional inversion result |
| CN111913226B (en) * | 2020-06-28 | 2023-08-08 | 中铁第一勘察设计院集团有限公司 | Railway tunnel extremely high ground stress identification method based on aviation geophysical prospecting three-dimensional inversion result |
| CN112329099A (en) * | 2020-10-27 | 2021-02-05 | 中国铁路设计集团有限公司 | Intelligent matching method for main tunnel of railway mountain tunnel based on custom database |
| CN112329099B (en) * | 2020-10-27 | 2023-04-14 | 中国铁路设计集团有限公司 | Intelligent matching method for main tunnel of railway mountain tunnel based on custom database |
| CN114355447A (en) * | 2022-01-13 | 2022-04-15 | 中国安能集团第三工程局有限公司 | Tunnel engineering surrounding rock grade rapid division method and device |
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