A method for predicting original rock temperature of deep buried tunnel

Abstract

The application provides a deep-buried tunnel original rock temperature prediction method, which utilizes field drilling measured data, tunnel surrounding rock measured temperature and data provided by a ground temperature database to obtain the original rock temperature of the whole tunnel through Akima spline interpolation method, wherein the ground temperature database is obtained through the following steps: collecting measured data of published ground temperature drilling in a certain area, pre-processing the measured data, and then performing spatial interpolation in the area by using a general Kriging method. The method solves the problems of great difficulty, long time consumption and high drilling cost in original rock temperature prediction of deep-buried tunnels, reduces the workload and calculation time on the basis of scientifically predicting the original rock temperature of deep-buried tunnels, is more suitable, is more in line with the actual engineering conditions, and improves the accuracy of the prediction result.

Description

Technical Field

[0001] This invention belongs to the field of tunnel original rock temperature prediction technology, specifically a method for predicting the original rock temperature of deeply buried tunnels. Background Technology

[0002] Indoor thermal and humidity environment control systems for large-scale hydropower stations, nuclear power plants, underground powerhouses, and other deeply buried underground projects typically introduce fresh air from the outside through underground passages such as ventilation tunnels and access tunnels. Furthermore, with the continuous expansion of railway and highway construction, the number of extra-long railway and highway tunnels is also constantly increasing, giving rise to the problem of thermal and humidity environment control in tunnels. Because these underground passages and tunnels (collectively referred to as tunnels) are usually characterized by large burial depths and large spatial spans, their temperature fields differ significantly from those of the outside air, causing heat and humidity exchange between the air entering the tunnel and the surrounding rock. When designing thermal and humidity environment control systems, it is necessary to calculate the heat exchange between the surrounding rock and the air, and the original rock temperature of the tunnel is a crucial parameter for this calculation. To obtain accurate heat exchange calculation results, a scientific and reasonable prediction of the original rock temperature of deeply buried tunnels is required.

[0003] Currently, the prediction of the original rock temperature of deeply buried tunnels usually involves conducting on-site drilling tests before tunnel construction to obtain data such as bottom hole temperature, rock thermal conductivity, geothermal gradient, and geothermal heat flux density. Then, the geothermal gradient method or numerical simulation method is used to obtain the original rock temperature field of the tunnel.

[0004] To reduce the workload of on-site geothermal measurements, geothermal databases have been established. However, these databases can only be used to query shallow surface temperatures or geothermal data at drilling points, and cannot query geothermal data at arbitrary geographical coordinates. Due to limitations in the number and location of wells, the test results often fail to fully reflect the unique geothermal characteristics of the tunnel site area, causing the predicted original rock temperature to deviate excessively from reality. This leads to unreasonable design of the underground engineering environmental control system, resulting in a poor underground environment or energy waste. Conducting a large number of drilling tests would significantly increase economic and time costs. Summary of the Invention

[0005] This invention provides a method for predicting the original rock temperature of deeply buried tunnels. The geothermal data required for the prediction include field drilling data, measured temperature of the tunnel surrounding rock, and geothermal gradient values ​​provided by a geothermal database. This method, while enabling scientific and reasonable prediction of the original rock temperature of deeply buried tunnels, reduces the cost of field drilling tests, decreases the workload of technical personnel, shortens calculation time, and also improves the accuracy of the prediction results to a certain extent.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] A method for establishing a geothermal database, characterized by comprising the following steps:

[0008] S1, Acquisition of Geothermal Drilling Data: Collect geographical coordinates, segmented geothermal gradient values, layered rock thermal conductivity, geothermal heat flux density values ​​and their quality categories of geothermal test wells in a certain region from published literature or publicly available data.

[0009] S2, Normality test of geothermal drilling data: Normality test and function transformation are performed on geothermal drilling data such as segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values.

[0010] S3, Global Trend Analysis of Geothermal Drilling Data: Global trend effect analysis is performed on data such as segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values, and the removal order of geothermal drilling data is determined.

[0011] S4, Select the fitting model: Plot the semi-variogram of data such as segmented geothermal gradient values, rock thermal conductivity, and geothermal heat flux density, and select the fitting model based on the function curve;

[0012] S5. Spatial interpolation using the ordinary Kriging method: Based on the selected fitting model, spatial interpolation is performed on the segmented geothermal gradient values, rock thermal conductivity, and geothermal heat flow density values ​​using the ordinary Kriging method to obtain the predicted values ​​of geothermal gradient, rock thermal conductivity, and geothermal heat flow density at any location in the region.

[0013] S6. The "cross-validation method" is used to verify the accuracy of the prediction results: Finally, the "cross-validation method" is used to verify the accuracy of the prediction results of the three types of data. The accuracy evaluation indicators include mean error (ME), standard mean error (MSE), root mean square error (RMSE), mean standard error (ASE), and root mean square standard error (RMSSE).

[0014] A method for predicting the temperature of the original rock in a deeply buried tunnel, characterized by the following steps:

[0015] S1, Selection of geothermal interpolation points: Select n geothermal interpolation points on the tunnel wall along the tunnel axis and determine the geometric parameters of each interpolation point.

[0016] S2, if the i-th interpolation point has a measured temperature T of the tunnel surrounding rock. i Then T i The original rock temperature at the i-th interpolation point;

[0017] S3, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i However, there is the measured geothermal gradient value (G) in the vertical direction of the interpolation point obtained from drilling. i If the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1), then the geothermal temperature T is calculated.i ;

[0018] Formula 1 is: T i =T i0 +(H i -h i )G i

[0019] In Formula 1, T i T is the original rock temperature at the i-th interpolation point. i0 H is the measured isothermal zone temperature value in the vertical direction of the drilling at the i-th interpolation point. i h is the burial depth at the i-th interpolation point. i G is the measured isothermal zone depth in the vertical direction of the i-th interpolation point, obtained from drilling. i It is the geothermal gradient measured by drilling in the vertical direction where the i-th interpolation point is located.

[0020] S4, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i There is no measured geothermal gradient value (G) in the vertical direction of the interpolation point. i Then, using the geographical coordinates of the tunnel site area, the geothermal gradient value (G) at that location is queried in the aforementioned geothermal database. i Then, the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1). i ;

[0021] S5, repeat steps S2 to S4, and sequentially calculate the original rock temperature T1, T2, ..., T at the n interpolation points. n ;

[0022] S6. Using the distance (X) from the n interpolation point to the tunnel entrance and the calculated original rock temperature (T), the original rock temperature of the entire tunnel is obtained by Akima spline interpolation.

[0023] In steps S3-S4, T is calculated using formula (1). i At that time, if there is no measured constant temperature value (T) from drilling, i0 If the annual average temperature is corrected for altitude using formula (2), then the constant temperature zone temperature value (T) is calculated. i0 );

[0024] Formula 2 is: T i0 =T Ni -Y h (A0-A i )

[0025] In Formula 2, T Ni A is the annual average temperature measured by the meteorological station of the town where the tunnel site is located, and A0 is the elevation of the ground in the vertical direction of the i-th interpolation point. iIt is the elevation of the meteorological station in the town where the tunnel site is located, Y h It is the temperature lapse rate (°C / m). When A0 is between 0 and 2000m, Y h =0.003~0.004; when A0 is greater than 2000m, Y h =0.005~0.006.

[0026] By adopting the technical solution described above, the present invention produces the following positive effects:

[0027] 1. This invention reduces the economic and time costs of on-site drilling and measurement by establishing and utilizing a geothermal database for predicting the original rock temperature of tunnels. It also solves the problem of inaccurate prediction results in the past due to the insufficient number of wells when predicting the original rock temperature of tunnels.

[0028] 2. The present invention uses an interpolation method to predict the original rock temperature of tunnels. There are three ways to obtain the original rock temperature at the interpolation point, which has wider applicability and is more in line with actual engineering conditions.

[0029] 3. Compared with previous methods for predicting the original rock temperature of tunnels, this invention reduces the workload of technicians, shortens the calculation time, and also improves the accuracy of the prediction results to a certain extent. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 A flowchart illustrating the steps of a method for establishing a geothermal database according to one embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the geometric parameters of the interpolation points used in a method for predicting the original rock temperature of a deeply buried tunnel, provided in one embodiment of the present invention.

[0033] Figure 3 This is a flowchart illustrating the steps for determining the original rock temperature at interpolation points in a method for predicting the original rock temperature of a deeply buried tunnel, as provided in one embodiment of the present invention.

[0034] Figure 4 This is a diagram showing the interpolation result of the original rock temperature of a tunnel provided in one embodiment of the present invention. Detailed Implementation

[0035] The present invention will now be described in detail with reference to specific embodiments. These embodiments are used to illustrate the present invention and are not limited to the scope of the present invention.

[0036] This invention provides a method for establishing a geothermal database and a method for predicting the original rock temperature of deeply buried tunnels. It utilizes data from multiple sources, including geothermal databases, measured geothermal data from drilling, and measured surrounding rock temperature values ​​during construction, to predict the original rock temperature of deeply buried tunnels, providing reliable computational boundary conditions for the design of thermal and humid environment control systems for underground engineering projects.

[0037] A method for establishing a geothermal database includes the following steps:

[0038] S1. Acquisition of geothermal drilling data: Collect geothermal drilling data such as geographical coordinates, segmented geothermal gradient values, layered rock thermal conductivity, geothermal heat flux density values ​​and their quality categories from published literature on geothermal test wells in a certain region.

[0039] In step S1, the specific steps for obtaining data such as the stratified geothermal gradient value and the thermal conductivity of stratified rocks are as follows:

[0040] S1a1, a distribution map of geothermal temperature in the depth direction is drawn from the actual drilling data. The geothermal temperature is divided into segments according to the different rates of change of geothermal temperature in the depth direction, and the geothermal gradient value of each segment is calculated.

[0041] S1a2, the thermal conductivity of rocks in each stratum in the lithology and stratigraphic distribution map is calculated from the actual drilling data;

[0042] S1a3, when entering the layered geothermal gradient value and the thermal conductivity of layered rocks into the database, they should be matched with their respective depth ranges.

[0043] S2, Normality test of geothermal drilling data: The frequency distribution histogram method and QQ plot method are used to test the normality of geothermal drilling data such as segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values, and then perform function transformation.

[0044] In step S2, the specific method for performing function transformation on the measured data is as follows:

[0045] If the original data such as segmented geothermal gradient values, layered rock thermal conductivity, and geothermal heat flux density do not exhibit a normal distribution, then appropriate functions such as Log and Box-Cox should be selected to transform the original data so that the data can exhibit a normal distribution.

[0046] S3, Global Trend Analysis of Geothermal Drilling Data: Global trend effect analysis is performed on data such as segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values, and the removal order of geothermal drilling data is determined.

[0047] S4, Select the fitting model: Plot the semivariograms of three types of data, namely, the piecewise geothermal gradient value, rock thermal conductivity, and geothermal heat flux density value, and select the fitting model based on the semivariogram curves.

[0048] S5. Spatial interpolation using the ordinary Kriging method: Based on the selected fitting model, spatial interpolation of data such as segmented geothermal gradient values, segmented rock thermal conductivity, and geothermal heat flow density is performed using the ordinary Kriging method to obtain predicted values ​​of geothermal gradient, rock thermal conductivity, and geothermal heat flow density at any location within the region.

[0049] In step S5, when spatially interpolating the geothermal gradient values ​​and the thermal conductivity of the layered rocks, the geothermal gradient values ​​and the thermal conductivity of the rocks within the same depth range can be interpolated in the same plane.

[0050] S6. The "cross-validation method" is used to verify the accuracy of the prediction results: Finally, the "cross-validation method" is used to verify the accuracy of the data prediction results. The accuracy evaluation indicators include mean error (ME), standard mean error (MSE), root mean square error (RMSE), mean standard error (ASE), and root mean square standard error (RMSSE). The ME and MSE of the best interpolation model should be close to 0, the RMSE should be as small as possible and close to the ASE, and the RMSSE should be close to 1.

[0051] In step S6, the "cross-validation" verification includes the following steps:

[0052] S6a1, Assuming the data of the i-th drilling point is unknown, the value of the point is estimated by the Kriging method based on the selected semivariance function model and the number of N-1 other measured points;

[0053] S6a2, let the measured value of the drilling measuring point be Z(x) i The predicted value is Z′(x). i The standardized values ​​of the two are Z(x) and Z(x). i ) and Z′(x i The mean error (ME), standard mean error (MSE), mean standard error (ASE), root mean square error (RMSE), and root mean square standard error (RMSSE) are calculated according to formulas (3) to (7).

[0054] Formula 3 is:

[0055] Formula 4 is:

[0056] Formula 5 is:

[0057] Formula 6 is:

[0058] Formula 7 is:

[0059] A method for predicting the temperature of the original rock in a deeply buried tunnel includes the following steps:

[0060] S1, Selection of geothermal interpolation points: Select n geothermal interpolation points on the tunnel wall along the tunnel axis, and determine the geometric parameters of each interpolation point. The geometric parameters include: burial depth of the interpolation point (H), distance of the interpolation point from the tunnel entrance (X), elevation of the ground in the vertical direction of the interpolation point (A), and isothermal zone depth in the vertical direction of the interpolation point (h);

[0061] S2, if the i-th interpolation point has a measured temperature T of the tunnel surrounding rock. i Then T i The original rock temperature at the i-th interpolation point;

[0062] S3, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i However, there is the measured geothermal gradient value (G) in the vertical direction of the interpolation point obtained from drilling. i ) and constant temperature zone (T) i0 If the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1), then the geothermal temperature T is calculated. i ;

[0063] Formula 1 is: T i =T i0 +(H i -h i )G i

[0064] In Formula 1, T i T is the original rock temperature at the i-th interpolation point. i0 H is the measured isothermal zone temperature value in the vertical direction of the drilling at the i-th interpolation point. i h is the burial depth at the i-th interpolation point. i G is the measured isothermal zone depth in the vertical direction of the i-th interpolation point, obtained from drilling. i It is the geothermal gradient measured by drilling in the vertical direction where the i-th interpolation point is located.

[0065] S4, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i There is no measured geothermal gradient value (G) in the vertical direction of the interpolation point. i Then, using the geographical coordinates of the tunnel site area, the geothermal gradient value (G) at that location is queried in the aforementioned geothermal database. i Then, the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1). i ;

[0066] In steps S3-S4, T is calculated using formula (1). i At that time, if there is no measured constant temperature value (T) from drilling, i0 If the annual average temperature is corrected for altitude using formula (2), then the constant temperature zone temperature value (T) is calculated. i0 );

[0067] Formula 2 is: T i0 =T Ni -Y h (A0-A i )

[0068] In Formula 2, T Ni A is the annual average temperature measured by the meteorological station of the town where the tunnel site is located, and A0 is the elevation of the ground in the vertical direction of the i-th interpolation point. i It is the elevation of the meteorological station in the town where the tunnel site is located, Y h It is the temperature lapse rate (°C / m). When A0 is between 0 and 2000m, Y h =0.003~0.004; when A0 is greater than 2000m, Y h =0.005~0.006.

[0069] S5, repeat steps S2 to S4, and sequentially calculate the original rock temperature T1, T2, ..., T at the n interpolation points. n ;

[0070] S6. Using the distance (X) from the tunnel entrance of n interpolation points and the calculated original rock temperature (T), the original rock temperature of the entire tunnel is obtained by Akima spline interpolation.

[0071] In step S6, the interpolation to obtain the original rock temperature distribution includes the following steps:

[0072] S6a1, Organize the calculated original rock temperature (T) of the interpolation point. i ) and its distance from the tunnel entrance (X i ), and the original rock temperature (T) i (X) is used as the vertical axis, representing the distance from the tunnel entrance. i () as the x-axis;

[0073] S6a2, Akima spline interpolation method was selected to determine the original rock temperature (T). i Interpolation is performed, with the minimum value of the x-axis set to 0 and the maximum value set to the total length of the tunnel, and the minimum value of the y-axis set to the average annual temperature.

[0074] Example:

[0075] This embodiment presents a method for establishing a geothermal database, such as... Figure 1As shown, the steps are as follows:

[0076] S1. Acquisition of geothermal drilling data: Geothermal data from 1452 geothermal test wells in China were collected from publicly published literature. The data included: geographic coordinates (latitude and longitude), average geothermal gradient value from 0 to 1000m, and geothermal heat flow density value. The drilling data were then entered into an EXCEL file.

[0077] S2, Normality test of geothermal drilling data: Using the histogram tool in the exploration data function of ArcGIS platform, the normality test of geothermal drilling data such as 0-1000m geothermal gradient value and geothermal heat flux density value was carried out. Both types of data were transformed by logarithmic function.

[0078] S3, Global Trend Analysis of Geothermal Drilling Data: Using the trend analysis tool in the ArcGIS platform's data exploration function, a global trend effect analysis was conducted on data such as the average geothermal gradient value from 0 to 1000m and the geothermal heat flow density value, and it was determined that the removal order for both types of data was 1.

[0079] S4, Selecting the Fitting Model: Using the variogram tool in the ArcGIS platform's data exploration function, we plotted the semi-variograms of two types of data: the average geothermal gradient value from 0 to 1000m and the geothermal heat flow density value. Based on the function curves, we selected the K-Bessel model and the rational quadratic equation model as the fitting models for the two types of data, respectively.

[0080] S5. In the ArcGIS platform, spatial interpolation is performed using the ordinary Kriging method: Based on the selected fitting model, the ordinary Kriging method is used to perform spatial interpolation on two types of data: the average geothermal gradient value from 0 to 1000m and the geothermal heat flow density value, to obtain the predicted values ​​of the average geothermal gradient from 0 to 1000m and the geothermal heat flow density at any location in the region.

[0081] S6. Cross-validation is used to verify the accuracy of the prediction results: Finally, cross-validation is used to verify the accuracy of the prediction results for the three types of data. The accuracy evaluation indicators include mean error (ME), standard mean error (MSE), root mean square error (RMSE), mean standard error (ASE), and root mean square standard error (RMSSE). The accuracy verification table is shown in Table 1.

[0082] Table 1. Accuracy Test Table for Ordinary Kriging Interpolation

[0083]

[0084] Note: G ＜1000 q represents the geothermal gradient at depths of 1000m and q represents the geothermal flow.

[0085] This embodiment presents a method for predicting the original rock temperature of deeply buried tunnels, the steps of which are as follows:

[0086] For example, in a deep underground tunnel in Chongqing (29.57°N, 106.55°E), the meteorological station at the project site is at an altitude of 260m, with an average annual temperature of 18.9℃. The tunnel is 1500m long. It is necessary to calculate the original rock temperature distribution along the axial direction of the tunnel.

[0087] S1, Selection of geothermal interpolation points: Five geothermal interpolation points are selected on the tunnel wall along the tunnel axis, and their distribution is as follows: Figure 2 As shown, the geometric parameters of the interpolation points and the measured ground temperature information are shown in Table 2. According to... Figure 3 The calculation process shown is used to calculate the original rock temperature at the 5 interpolation points in sequence;

[0088] Table 2. Interpolation Point Information Map

[0089]

[0090] S2, the fourth interpolation point has the measured temperature T4 of the surrounding rock of the tunnel, then T4 is taken as the original rock temperature at the fourth interpolation point;

[0091] S3, the measured temperature T of the surrounding rock without tunnel at the 1st, 3rd, and 5th interpolation points. i However, there is the measured geothermal gradient value (G) in the vertical direction of the interpolation point obtained from drilling. i If the original rock temperature T at the interpolation point is calculated using geothermal calculation formula 1, then the geothermal temperature T is calculated. i ;

[0092] Formula 1 is: T i =T i0 +(H i -h i )G i

[0093] In Formula 1, T i T is the original rock temperature at the i-th interpolation point. i0 H is the measured isothermal zone temperature value in the vertical direction of the drilling at the i-th interpolation point. i h is the burial depth at the i-th interpolation point. i G is the measured isothermal zone depth in the vertical direction of the i-th interpolation point, obtained from drilling. i It is the geothermal gradient measured by drilling in the vertical direction where the i-th interpolation point is located;

[0094] S4, the second interpolation point has no measured temperature T4 of the surrounding rock of the tunnel, and no measured geothermal gradient value (G4) of the well in the vertical direction where the interpolation point is located. Then, the geothermal gradient value G4 of the location is queried in the geothermal database established in Example 1 using the geographical coordinates of the tunnel site area. Then, the original rock temperature T4 of the interpolation point is calculated by geothermal calculation formula 1. The calculation results are shown in Table 2.

[0095] In steps S3 to S4, T at the 3rd and 5th interpolation points is calculated using Formula 1. i At that time, there was no measured temperature value (T) in the isothermal zone. i0 Then, the constant temperature value (T) is calculated using the annual average temperature altitude correction formula 2. i0 The calculation results are shown in Table 2.

[0096] Formula 2 is: T i0 =T Ni -Y h (A0-A i )

[0097] In Formula 2, T Ni A is the annual average temperature measured by the meteorological station of the town where the tunnel site is located, and A0 is the elevation of the ground in the vertical direction of the i-th interpolation point. i It is the elevation of the meteorological station in the town where the tunnel site is located, Y h It is the temperature lapse rate (°C / m). When A0 is between 0 and 2000m, Y h = 0.003~0.004 (take 0.0035); when A0 is greater than 2000m, Y h =0.005~0.006 (take 0.0055);

[0098] S5. Using the distances (X) of the five interpolation points from the tunnel entrance and the calculated original rock temperature (T), the original rock temperature of the entire tunnel is determined using the Akima spline interpolation method in Origin. During interpolation, the minimum value of the x-axis is set to 0, the maximum value is set to the total tunnel length of 1500, and the minimum value of the y-axis and the original rock temperature at the entrance are set to the annual average temperature of 18.9℃. The interpolation results are shown below. Figure 4 .

[0099] This invention addresses the challenges of predicting the temperature of the original rock in deep-buried tunnels, including difficulties, time-consuming processes, and high drilling costs. It provides a method for establishing a geothermal database and a method for predicting the temperature of the original rock in deep-buried tunnels. This enriches the deep geothermal database, enables the scientific and reasonable prediction of the temperature of the original rock in deep-buried tunnels, reduces on-site drilling and testing costs, decreases the workload of technical personnel, shortens calculation time, and can also improve the accuracy of prediction results to a certain extent.

[0100] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention using the methods and techniques disclosed above, or modify them into equivalent embodiments with equivalent changes, without departing from the scope of the technical solutions of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall still fall within the protection scope of the technical solutions of the present invention.

Claims

1. A method for predicting the temperature of the original rock in a deeply buried tunnel, characterized in that, Includes the following steps: S1, Selection of geothermal interpolation points: Select n geothermal interpolation points on the tunnel wall along the tunnel axis and determine the geometric parameters of each interpolation point; S2, if the i-th interpolation point has a measured temperature T of the tunnel surrounding rock. i Then T i The original rock temperature at the i-th interpolation point; S3, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i However, there is the measured geothermal gradient value (G) in the vertical direction of the interpolation point obtained from drilling. i If the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1), then the geothermal temperature T is calculated. i ; Formula 1 is: T i =T i0 +(H i -h i )G i In Formula 1, T i T is the original rock temperature at the i-th interpolation point. i0 H is the measured isothermal zone temperature value in the vertical direction of the drilling at the i-th interpolation point. i h is the burial depth at the i-th interpolation point. i G is the measured isothermal zone depth in the vertical direction of the i-th interpolation point, obtained from drilling. i It is the geothermal gradient measured by drilling in the vertical direction where the i-th interpolation point is located; S4, if the measured temperature T of the surrounding rock at the i-th interpolation point is not in the tunnel. i There is no measured geothermal gradient value (G) in the vertical direction of the interpolation point. i Then, the geothermal gradient value (G) at that location can be queried using the geographical coordinates of the tunnel site area. i Then, the original rock temperature T at the interpolation point is calculated using the geothermal calculation formula (1). i ; S5, repeat steps S2 to S4, and sequentially calculate the original rock temperature T1, T2, ..., T at the n interpolation points. n ; S6. Using the distance (X) from the n interpolation point to the tunnel entrance and the calculated original rock temperature (T), the original rock temperature of the entire tunnel is obtained by Akima spline interpolation. In steps S3-S4, T is calculated using formula (1). i At that time, if no constant temperature value (T) is obtained from drilling measurements, i0 If the annual average temperature is corrected for altitude using formula (2), then the constant temperature zone temperature value (T) is calculated. i0 ); Formula 2 is: T i0 =T Ni -Y h (A0-A i ) In Formula 2, T Ni A is the annual average temperature measured by the meteorological station of the town where the tunnel site is located, and A0 is the elevation of the ground in the vertical direction of the i-th interpolation point. i It is the elevation of the meteorological station in the town where the tunnel site is located, Y h It is the temperature lapse rate (°C / m). When A0 is between 0 and 2000m, Y h =0.003~0.004; when A0 is greater than 2000m, Y h =0.005~0.

006.

2. The method for predicting the original rock temperature of a deep-buried tunnel according to claim 1, characterized in that: S1, Selection of geothermal interpolation points: Select n geothermal interpolation points on the tunnel wall along the tunnel axis and determine the geometric parameters of each interpolation point; the geometric parameters include: the burial depth of the interpolation point (H), the distance of the interpolation point from the tunnel entrance (X), the elevation of the ground in the vertical direction of the interpolation point (A), and the depth of the constant temperature zone in the vertical direction of the interpolation point (h). In step S6, the interpolation to obtain the original rock temperature distribution includes the following steps: S6a1, Organize the calculated original rock temperature (T) of the interpolation point. i ) and its distance from the tunnel entrance (X i ), and the original rock temperature (T) i (X) is used as the vertical axis, representing the distance from the tunnel entrance. i () as the x-axis; S6a2, Akima spline interpolation method was selected to determine the original rock temperature (T). i Interpolation is performed, with the minimum value of the x-axis set to 0 and the maximum value set to the total length of the tunnel, and the minimum value of the y-axis set to the average annual temperature.

3. The method for predicting the original rock temperature of a deep-buried tunnel according to claim 1, characterized in that: In the geothermal database, the geothermal gradient value (G) at the tunnel site is queried using the geographical coordinates of the tunnel site. i The method for establishing a geothermal database includes the following steps: S1, Acquisition of Geothermal Drilling Data: Collect geographical coordinates, segmented geothermal gradient values, layered rock thermal conductivity, terrestrial heat flux density values, and geothermal drilling data of a certain region from published literature or publicly available information. S2, Normality test of geothermal drilling data: Normality test and function transformation are performed on the geothermal drilling data of segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values. S3, Global Trend Analysis of Geothermal Drilling Data: Global trend effect analysis is performed on the data of segmented geothermal gradient values, layered rock thermal conductivity, and terrestrial heat flux density values, and the removal order of geothermal drilling data is determined. S4, Select the fitting model: Plot the semi-variogram of the data of segmented geothermal gradient, rock thermal conductivity, and geothermal heat flux density, and select the fitting model based on the function curve; S5. Spatial interpolation using the ordinary Kriging method: Based on the selected fitting model, spatial interpolation is performed on the segmented geothermal gradient values, rock thermal conductivity, and geothermal heat flow density values ​​using the ordinary Kriging method to obtain the predicted values ​​of geothermal gradient, rock thermal conductivity, and geothermal heat flow density at any location in the region. S6. The "cross-validation method" is used to verify the accuracy of the prediction results: Finally, the "cross-validation method" is used to verify the accuracy of the prediction results of the three types of data. The accuracy evaluation indicators include mean error (ME), standard mean error (MSE), root mean square error (RMSE), mean standard error (ASE), and root mean square standard error (RMSSE).

4. The method for predicting the original rock temperature of a deep-buried tunnel according to claim 3, characterized in that: In step S1, the acquisition of data on the stratified geothermal gradient and the thermal conductivity of the stratified rocks includes the following steps: S1a1, a distribution map of geothermal temperature in the depth direction is drawn from the actual drilling data. The geothermal temperature is divided into segments according to the different rates of change of geothermal temperature in the depth direction, and the geothermal gradient value of each segment is calculated. S1a2, the thermal conductivity of rocks in each stratum in the lithology and stratigraphic distribution map is calculated from the actual drilling data; S1a3, when entering the layered geothermal gradient value and the thermal conductivity of layered rocks into the database, they should be matched with their respective depth ranges.

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