Earth and rockfill dam leakage detection method based on combination of transient electromagnetic method and single-hole dilution method

Abstract

The invention mainly relates to the related technical field of earth and rockfill dam leakage detection, in particular to an earth and rockfill dam leakage detection method based on combination of a transient electromagnetic method and a single-hole dilution method. A leakage hidden danger area is rapidly scanned and positioned through a transient electromagnetic method, a single-hole dilution method is guided to conduct drilling in a key area, and invalid drilling is reduced; on the basis of a traditional dilution curve model, a drilling radius correction factor and a non-Darcy effect correction term are introduced, and the output precision of a vertical seepage profile is remarkably improved; a quantitative mapping model of the resistivity inversion image and the seepage velocity is established, and quantitative conversion from physical detection data to hydraulic parameters is achieved; leakage channel space distribution is automatically extracted based on the image recognition technology, and rapid calculation of the total dam leakage amount is achieved.

Description

Technical Field

[0001] The present invention mainly relates to the technical field related to leakage detection of earth-rock dams, and specifically to an earth-rock dam leakage detection method based on a combination of a transient electromagnetic method and a single-hole dilution method. Background Art

[0002] Leakage in earth-rock dams is one of the key hidden dangers threatening dam safety. Rapid and accurate quantitative assessment of leakage is crucial to project safety. Traditional leakage detection methods have significant limitations: Manual inspections, water level observations, temperature field monitoring and other methods mainly focus on locating leakage points or making qualitative judgments, making it difficult to accurately calculate the amount of leakage. Although methods such as drilling water pressure tests and water injection tests can obtain local seepage parameters, their implementation efficiency is low, their coverage is limited, and it is difficult to characterize the complex distribution of seepage channels inside the dam body.

[0003] Existing single geophysical exploration technologies (such as transient electromagnetic method) can quickly detect and invert to obtain the resistivity profile of the dam body, effectively identify low-resistance anomaly areas and locate the scope of leakage risks. However, this method essentially provides the electrical characteristics of the dielectric and cannot be directly converted into leakage flow rate or flow rate. High-precision point measurement methods (such as single-hole dilution method) can directly measure the vertical seepage flow rate in the borehole, and the results are accurate and reliable, but the data only represents the information of a single point or a local small area. In addition, the cost of laying a large number of boreholes is high and the efficiency is low, making it impossible to obtain the overall seepage field distribution of the dam body economically and efficiently. Summary of the Invention

[0004] In order to address the shortcomings of current technology, the present invention combines existing technologies and, based on practical applications, provides an earth-rock dam leakage detection method based on the transient electromagnetic method and the single-hole dilution method, which can realize rapid detection of earth-rock dam leakage.

[0005] The technical solutions of the present invention are as follows: The earth-rock dam leakage detection method based on the transient electromagnetic method and the single-hole dilution method includes the following steps: S1. Obtain resistivity profile images based on transient electromagnetic method to locate leakage risk areas; S2. Determine the drilling location and depth based on the leakage risk area located by transient electromagnetic method, and calculate the seepage velocity based on the single-hole dilution method; S3, extracting features from the resistivity profile image, establishing a quantitative mapping relationship between the seepage velocity and the resistivity profile image, and obtaining a correlation model; S4. Identify, segment, and extract the leakage risk areas of the entire earth-rock dam profile. Calculate the leakage volume of the entire dam profile based on the established seepage velocity-resistivity profile image correlation model.

[0006] Furthermore, in step S1, the transient electromagnetic method is to send a pulsed magnetic field into the ground through the transmitting coil, and measure the induced secondary field during the shutdown period. The leakage risk area has a low resistance characteristic due to the high water content, forming an abnormal area in the resistivity profile.

[0007] Furthermore, in step S2, when the seepage velocity is calculated using the single-hole dilution method, a correction factor for the borehole radius is introduced. β and non-Darcy effect correction c , the corrected flow rate calculation formula is as follows: v z修正 = β · c · πr 2 / (2 α 1 t )·ln( C 0 / C t ); Among them, the drilling radius correction factor β The expression is as follows: β =(1+ r / L ) n ; Non-Darcy effect correction term c The expression is as follows: c =1+ a 2. Re; Where, v z修正 For depth Z The seepage velocity value at the location, C 0 For time t =0 when the conductivity; C t For time t The conductivity at ; t To measure time; r is the radius of the drill hole; α 1 is the correction factor, L is the characteristic length of the water layer, n is the experience index, a 2 is the empirical coefficient, Re is the Reynolds number.

[0008] Furthermore, in step S3, the specific steps of resistivity profile image feature extraction are as follows: S311. Perform two-dimensional grayscale processing on the resistivity profile generated by transient electromagnetic inversion, and convert the RGB image into a grayscale matrix. The expression is as follows: ; Where, I gray ( X , Z ) is the grayscale matrix value; R、G、B are the red, green and blue channel values ​​respectively; l r 、 l g 、 l b They are R、 G、B Corresponding coefficient value; X , Z is the pixel coordinate, X is the horizontal direction, Z is the vertical direction; S312, use the median filter method to perform denoising on the grayscale matrix, the expression is as follows: ; Where: k is the filter window radius; i is the horizontal offset, which indicates the horizontal moving step of the filter window. j is the vertical offset, which indicates the moving step of the filter window in the vertical direction; S313: Leakage area segmentation. Otsu adaptive threshold segmentation based on grayscale value is used to generate a binary mask. The hidden danger area is 1 and the normal area is 0. The threshold segmentation expression is as follows: ; Where: T is the threshold for segmenting the image, below T Pixels with a value higher than T The pixels are considered as normal areas; is the optimal threshold, 、 are lower than T and higher than T Pixel ratio; 、 They are 、 The grayscale mean of these two types of pixels.

[0009] Furthermore, in step S3, the association model is established as follows: S321, Data pairing: vertical seepage velocity measured by single hole dilution method vz修正 Gray value of resistivity profile image I gray ( X , Z ) accurately align at the same drilling location and depth to construct a modeling dataset; S322, spatial positioning: extract the vertical distribution curve of resistivity gray value on the borehole axis I gray ( Xz , Z j ), Xz is the coordinate of the drilling hole in the horizontal direction, Z j The single-hole dilution method measures the seepage velocity at different depth intervals in the same borehole. v zj修正 , forming a discrete data set { v zj修正 , Z j}; S323, Depth Alignment: Grayscale Value I gray ( Xz , Z j ) uses cubic spline interpolation to match the sampling point depth of the single-hole dilution method. The grayscale value after interpolation is expressed as follows: I inter ( Xz , Z j )=spline( I gray ( Xz , Z j ), Z j ); The paired data set expression is as follows: D={ I inter ( Xz , Z j ), v zj修正}; S324, Nonlinear Regression Modeling: Establishing Seepage Velocity v zj修正 Grayscale value of resistivity I inter ( Xz , Z j) to reflect the characteristics of low resistance and high flow rate in the leakage channel. The weighted least squares method is used for parameter fitting, and the fitting objective function is: ; Where: w i is the weight value, and the weight value of high velocity area is w i =ln( v zj修正 +1); or 1 is the proportional coefficient, reflecting the permeability of the medium; or 2 is the sensitivity index, which reflects the response intensity of flow velocity to resistivity changes.

[0010] Furthermore, the nonlinear regression modeling parameters are solved by the LM iteration method, and the algorithm convergence condition is: ; Where: Δ or 1 for or The change of 1; Δ or 2 for or The change of 2.

[0011] Beneficial effects of the present invention: The present invention provides a rapid detection method for earth-rock dam leakage based on the transient electromagnetic method and the single-hole dilution method. The transient electromagnetic method is used to quickly scan and locate leakage risk areas, and the single-hole dilution method is used to guide drilling in key areas, thereby reducing ineffective drilling. Based on the traditional dilution curve model, a drilling radius correction factor and a non-Darcy effect correction term are introduced to significantly improve the accuracy of the vertical seepage profile output. A quantitative mapping model of resistivity inversion images and seepage velocity is established to achieve quantitative conversion of physical detection data into hydraulic parameters. Based on image recognition technology, the spatial distribution of leakage channels is automatically extracted to achieve rapid calculation of the total amount of dam leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a flow chart of the present invention; Figure 2 A schematic diagram of the abnormal area of ​​dam leakage potential obtained by transient electromagnetic method inversion; Figure 3 Schematic diagram for determining the drilling location based on the abnormal area; Figure 4 is a schematic diagram of grayscale values ​​of the resistivity profile; Figure 5 Schematic diagram of identification, segmentation and extraction of all leakage areas in the inversion profile. DETAILED DESCRIPTION

[0013] The present invention will be further described with reference to the accompanying drawings and specific embodiments. It should be understood that these embodiments are intended only to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the contents of the present invention, those skilled in the art may make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the present application.

[0014] This embodiment provides a method for detecting earth-rock dam leakage based on a combination of transient electromagnetic method and single-hole dilution method. The method is as follows: (1) Detection of leakage risk areas in earth-rock dams based on transient electromagnetic method

[0015] Transient electromagnetic method (TEM) sends a pulsed magnetic field into the ground through a transmitting coil and measures the induced secondary field during the off period. The leakage area has a low resistance characteristic due to high water content, forming an abnormal area in the resistivity profile, such as Figure 2 shown. (2) Leakage velocity measurement based on the single-hole dilution method

[0016] According to the transient electromagnetic method inversion, the leakage abnormal area (leakage potential area) is obtained, and the horizontal position and depth of the borehole are determined, such as Figure 3 shown.

[0017] Currently, the seepage velocity is commonly calculated based on the dilution curve (conductivity-time decay model), such as formula (1). However, this formula does not consider the impact of the borehole itself on the water velocity field, resulting in distortion of the velocity measurement value.

[0018] v = πr 2 / (2 α 1 t )·ln( C 0 / C t )(1) Where: C 0 For time t =0 when the conductivity; C t For time t The conductivity at ; t To measure time; r is the radius of the drill hole; α 1 is the correction coefficient (usually 1~2).

[0019] In order to reduce the deviation of velocity estimation caused by the geometric effect of the borehole itself (local velocity amplification) and non-Darcy seepage (inertia effect), the borehole radius correction factor is introduced based on formula (1): β and non-Darcy effect correction c, establish the revised flow rate formula.

[0020] Drilling radius correction factor β , this factor is related to the drilling radius r , characteristic length of aquifer L To correct the local flow field distortion caused by drilling, expression (2) is as follows: β =(1+ r / L ) n (2); Where: n is the empirical index (usually 1~2).

[0021] Non-Darcy effect correction term c , when the seepage velocity is high, the Reynolds number Re Exceeding the critical value Re crit When , the inertia term is introduced to correct the influence of the inertia term, and the expression (3) is as follows: c =1+ a 2. R e(3); Where: a 2 is the empirical coefficient.

[0022] The corrected seepage velocity calculation formula, expression (4) is as follows: v z修正 = β · c · πr 2 / (2 α 1 t )·ln( C 0 / C t )(4); Where: v z修正 For depth Z The seepage velocity value at the location. (III) Modeling based on the relationship between image recognition and flow velocity

[0023] Transient electromagnetic (TEM) analysis can quickly determine the resistivity distribution of a dam, but it cannot directly quantify seepage velocity. The single-hole dilution method accurately measures flow velocity within a hole, but only provides data at discrete points. Therefore, establishing a quantitative mapping between the two is crucial for converting resistivity images into seepage velocity. This mapping is established as follows. 3.1 Transient Electromagnetic Method (TEM) Image Feature Extraction

[0024] ① Perform two-dimensional grayscale processing on the resistivity profile generated by transient electromagnetic method inversion, and convert the RGB image into a grayscale matrix, such as Figure 4 As shown, expression (5) is as follows: (5); Where: I gray ( X , Z ) is the grayscale matrix value; R, G, B are the red, green, and blue channel values ​​respectively; l r 、 l g 、 l b They are the corresponding coefficient values ​​of R, G, and B respectively; X , Z is the pixel coordinate, X is the horizontal direction, Z In vertical direction.

[0025] ② Use the median filter method to denoise the grayscale matrix. Expression (6) is as follows: (6); Where: k is the filter window radius; i is the horizontal offset, which indicates the horizontal moving step of the filter window. j It is the vertical offset, which indicates the vertical moving step of the filter window.

[0026] ③ Leakage area segmentation Otsu adaptive threshold segmentation based on gray value is performed, and expression (7) is as follows: (7); Where: T is the threshold for segmenting the image, below T Pixels with a value higher than T The pixels are considered as normal areas; is the optimal threshold, 、 are lower than T and higher than T Pixel ratio; 、 They are 、 The grayscale mean of these two types of pixels.

[0027] Generate a binary mask with the hidden danger area as 1 and the normal area as 0. The expression (8) is as follows: (8); 3.2 Borehole velocity-resistivity correlation modeling

[0028] Data pairing: vertical seepage velocity measured by single-hole dilution method v z修正 Grayscale value of resistivity image inverted by transient electromagnetic method I gray ( X , Z ) are precisely aligned at the same drilling location and depth to construct a modeling dataset.

[0029] Spatial positioning: Extract the vertical distribution curve of resistivity grayscale value on the borehole axis I gray ( Xz , Z j ), Xz is the coordinate of the drilling hole in the horizontal direction, Z j The single hole dilution method measures the seepage velocity at different depths in the same borehole. v zj修正 , forming a discrete data set { v zj修正 , Z j}.

[0030] Depth alignment: Due to the difference in resolution between the two methods, depth interpolation is required. I gray ( Xz , Z j ) uses cubic spline interpolation to match the sampling point depth of the dilution method. The grayscale value after interpolation and the paired data set are formula (9) and formula (10), respectively: I inter ( Xz , Z j )=spline( I gray ( Xz , Z j ), Z j )(9); D={ I inter ( Xz , Z j ), v zj修正}(10); ② Nonlinear regression modeling: Establishing seepage velocity v zj修正 Grayscale value of resistivity I inter ( Xz , Z j ) to reflect the characteristics of low resistance and high flow rate in the leakage channel. The weighted least squares method is used for parameter fitting, and the fitting objective function is: (11); Where: w i is the weight value, and the weight value of high velocity area is w i =ln( v zj修正 +1); or 1 is the proportional coefficient, reflecting the permeability of the medium; or 2 is the sensitivity index (usually 0.8~1.5), which reflects the response intensity of flow velocity to resistivity changes.

[0031] The Levenberg-Marquardt (LM) iteration method can handle nonlinear least squares problems very well. LM is used to solve the problem. The convergence condition of the algorithm is formula (12): (12); Where: Δ or 1 for or The change of 1; Δ or 2 for or The change of 2. (IV) Calculation of earth-rock dam leakage

[0032] Formula (7) is used to obtain the leakage risk area of ​​the entire dam section, and then identify, segment and extract the area, as follows: Figure 5 According to the established borehole velocity-resistivity correlation model, the leakage rate of the entire dam section can be calculated.

[0033] The method provided in this embodiment uses the transient electromagnetic method to quickly scan and locate leakage risk areas, guide the single-hole dilution method to implement drilling in key areas, and reduce ineffective drilling; based on the traditional dilution curve model, it introduces a drilling radius correction factor and a non-Darcy effect correction term to significantly improve the accuracy of the vertical seepage profile output; establishes a quantitative mapping model between resistivity inversion images and seepage velocity, and realizes the quantitative conversion of physical detection data into hydraulic parameters; based on image recognition technology, it automatically extracts the spatial distribution of leakage channels and realizes the rapid calculation of the total amount of dam leakage.

Claims

1. A leakage detection method for earth-rock dams based on the combination of transient electromagnetic method and single-hole dilution method, characterized in that: The steps include: S1. Obtain resistivity profile images based on transient electromagnetic method to locate leakage risk areas; S2. Determine the drilling location and depth based on the leakage risk area located by transient electromagnetic method, and calculate the seepage velocity based on the single-hole dilution method; S3, extracting features from the resistivity profile image, establishing a quantitative mapping relationship between the seepage velocity and the resistivity profile image, and obtaining a correlation model; S4. Identify, segment, and extract the leakage risk areas of the entire earth-rock dam profile. Calculate the leakage volume of the entire dam profile based on the established seepage velocity-resistivity profile image correlation model.

2. The earth-rock dam leakage detection method based on the transient electromagnetic method combined with the single-hole dilution method according to claim 1 is characterized in that: In step S1, the transient electromagnetic method is to send a pulsed magnetic field into the ground through a transmitting coil and measure the induced secondary field during the shutdown period. The leakage risk area has a low resistance characteristic due to high water content, forming an abnormal area in the resistivity profile.

3. The earth-rock dam leakage detection method based on the combination of transient electromagnetic method and single hole dilution method according to claim 1 is characterized in that: In step S2, when the single-hole dilution method is used to calculate the seepage velocity, the influence of the borehole itself on the water velocity field is considered and the borehole radius correction factor is introduced. β and non-Darcy effect correction γ Correct the flow rate calculation formula.

4. The earth-rock dam leakage detection method based on the combination of transient electromagnetic method and single hole dilution method according to claim 3 is characterized in that: The flow rate calculation formula of the modified single-hole dilution method is as follows: v z修正 = β · γ · πr 2 / (2 α 1 t )·ln( C 0 / C t )； Among them, the drilling radius correction factor β The expression is as follows: β =(1+ r / L ) n ； Non-Darcy effect correction term γ The expression is as follows: γ =1+ a 2· Re; Where, v z修正 For depth Z The seepage velocity value at the location, C 0 For time t =0 when the conductivity; C t For time t The conductivity at ; t To measure time; r is the radius of the drill hole; α 1 is the correction factor, L is the characteristic length of the water layer, n is the experience index, a 2 is the empirical coefficient, Re is the Reynolds number.

5. The earth-rock dam leakage detection method based on the combination of transient electromagnetic method and single hole dilution method according to claim 1 is characterized in that: In step S3, the specific steps of resistivity profile image feature extraction are as follows: S311. Perform two-dimensional grayscale processing on the resistivity profile generated by transient electromagnetic inversion, and convert the RGB image into a grayscale matrix. The expression is as follows: ； Where, I gray ( X , Z ) is the grayscale matrix value; R, G, B are the red, green and blue channel values ​​respectively; λ r 、 λ g 、 λ b They are R, G, B Corresponding coefficient value; X , Z is the pixel coordinate, X is the horizontal direction, Z is the vertical direction; S312, use the median filter method to perform denoising on the grayscale matrix, the expression is as follows: ； Where: k is the filter window radius; i is the horizontal offset, which indicates the horizontal moving step of the filter window. j is the vertical offset, which indicates the moving step of the filter window in the vertical direction; S313: Leakage area segmentation. Otsu adaptive threshold segmentation based on grayscale value is used to generate a binary mask. The hidden danger area is 1 and the normal area is 0. The threshold segmentation expression is as follows: ； Where: T is the threshold for segmenting the image, below T Pixels with a value higher than T The pixels are considered as normal areas; is the optimal threshold, 、 are lower than T and higher than T Pixel ratio; 、 They are 、 The grayscale mean of these two types of pixels.

6. The earth-rock dam leakage detection method based on the combination of transient electromagnetic method and single hole dilution method according to claim 5 is characterized in that: In step S3, the association model is established as follows: S321, Data pairing: vertical seepage velocity measured by single hole dilution method v z修正 Gray value of resistivity profile image I gray ( X , Z ) accurately align at the same drilling location and depth to construct a modeling dataset; S322, spatial positioning: extract the vertical distribution curve of resistivity gray value on the borehole axis I gray ( Xz , Z j ), Xz is the coordinate of the drilling hole in the horizontal direction, Z j The single-hole dilution method measures the seepage velocity at different depth intervals in the same borehole. v zj修正 , forming a discrete data set { v zj修正 , Z j }; S323, Depth Alignment: Grayscale Value I gray ( Xz , Z j ) uses cubic spline interpolation to match the sampling point depth of the single-hole dilution method. The grayscale value after interpolation is expressed as follows: I inter ( Xz , Z j )=spline( I gray ( Xz , Z j ), Z j ); The paired data set expression is as follows: D={ I inter ( Xz , Z j ), v zj修正}； S324, Nonlinear Regression Modeling: Establishing Seepage Velocity v zj修正 Grayscale value of resistivity I inter ( Xz , Z j ) to reflect the characteristics of low resistance and high flow rate in the leakage channel. The weighted least squares method is used for parameter fitting, and the fitting objective function is: ; Where: w i is the weight value, and the weight value of high velocity area is w i =ln( v zj修正 +1); η 1 is the proportional coefficient, reflecting the permeability of the medium; η 2 is the sensitivity index, which reflects the response intensity of flow velocity to resistivity changes.

7. The earth-rock dam leakage detection method based on the transient electromagnetic method combined with the single-hole dilution method according to claim 6 is characterized in that: The nonlinear regression modeling parameters are solved by the LM iteration method, and the algorithm convergence condition is: ； Where: Δ η 1 for η The change of 1; Δ η 2 for η The change of 2.

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