Post-excavation stratum reinforcement grouting effect visualization method based on multi-field coupling

Abstract

The invention discloses a post-excavation stratum reinforcement grouting effect visualization method based on multi-field coupling, and the method comprises the steps: firstly obtaining the stratum condition, rock mechanics data and grouting parameters of a grouting region, and carrying out the simulation calculation of the distribution condition of effective principal stress after excavation through a specific model; based on the distribution of the effective principal stress in the mechanical field in the porous medium, simulating and calculating the porosity distribution and the permeability coefficient after formation fracturing; analyzing a slurry diffusion path by adopting a specific model, and obtaining the overall change conductivity of the porous medium and the slurry through analog calculation; parameters of a resistivity hole lane combined monitoring system are determined according to the changing conductivity, and the potential value of each point position in the grouting reinforcement process is actually measured through the monitoring system; finally, the actually measured data and the model calculation data are compared and analyzed, the diffusion path and the reinforcement effect of the grout in the grouting reinforcement process are continuously obtained, and dynamic visualization of the stratum reinforcement grouting effect before and after excavation is achieved through comprehensive analysis of the multi-physics field coupling condition.

Description

Technical Field

[0001] This invention belongs to the field of grouting effect monitoring, specifically a visualization method for post-mining stratum reinforcement grouting effect based on multi-field coupling. Background Technology

[0002] In tunnel excavation, subway construction, and mining, the excavation of the working face disturbs the original stress of the strata, generating disturbance fissures and causing accidents such as ground subsidence and water inrush. To control the strata and protect groundwater resources and surface structures, grouting reinforcement is necessary. Grouting reinforcement technology involves injecting grout into geological structures such as overburden delamination and collapse columns to form a supporting structure, effectively reducing ground subsidence and deformation, and has significant application value. During this process, dynamic monitoring of the grout allows for a clearer understanding of the grouting reinforcement process and its effectiveness. However, existing grouting monitoring technologies have many shortcomings and are insufficient to meet the needs of practical engineering projects.

[0003] Currently, commonly used grouting monitoring methods include borehole sampling, ground-penetrating radar (GPR), and seismic wave methods. Borehole sampling can only obtain localized information and cannot monitor the dynamic diffusion of grout in real time. While GPR and seismic wave methods can provide some imaging information, their resolution and accuracy are limited under complex geological conditions, and continuous dynamic monitoring is difficult to achieve. Most of these methods only consider a single physical field (such as a mechanical or fluid field) and ignore the relationships between multiple physical fields.

[0004] In geotechnical engineering, multiphysics coupling analysis is of great significance. During grouting, there are significant correlations between physical fields such as mechanical fields, fluid fields, and electric fields. For example, the porosity and permeability distribution of the coal seam after mining affects the flow of grout in the overburden separation layer. Simultaneously, due to the electrical difference between the grout and the coal seam, the diffusion of the grout can be reflected by observing changes in potential. Current technology lacks a visualization method for grouting effects that comprehensively considers multiphysics coupling, which to some extent limits the optimization and application of grouting technology.

[0005] To address the aforementioned problems, this invention aims to provide a new method that can monitor and comprehensively analyze multiple physical fields, thereby achieving dynamic visualization of the grouting effect before and after mining. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a visualization method for post-mining grouting reinforcement effects based on multi-field coupling, which can effectively solve the above-mentioned technical problems.

[0007] To achieve the above objectives, the technical solution adopted by this invention is: a method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling, comprising the following steps:

[0008] Step 1: Before grouting, obtain the geological conditions, rock mechanics data, and grouting parameters of the grouting area;

[0009] Step 2: Based on the stress balance equation, a rock mechanics physical field model is constructed. This model is used to simulate the stratum mining process and obtain the stratum conditions after mining.

[0010] Step 3: Based on the simulated geological conditions after mining in Step 2, calculate the distribution of effective principal stress after tunneling;

[0011] Step 4: Based on the distribution of effective principal stress in the mechanical field in the porous medium, calculate the porosity distribution after formation fracturing; then calculate the permeability coefficient of the porous medium after fracturing and use it in the subsequent slurry diffusion medium;

[0012] Step 5: Construct a two-phase Darcy's law physical field model based on the seepage equation, and use this model to simulate the slurry diffusion process and analyze the slurry diffusion path;

[0013] Step 6: Set the initial parameters of the grout-driven air model according to the preset grouting parameters;

[0014] Step 7: Set up a resistivity pore tunnel joint monitoring system according to the location of the slurry diffusion area to be monitored, and set the electrical parameters and electric field boundary conditions of the slurry and porous media.

[0015] Step 8: Use the slurry-driven gas model from Step 6 to simulate and obtain the saturation s of the slurry at different times. g The overall change in conductivity of the porous medium and the slurry was calculated.

[0016] Step 9: Determine the parameters of the resistivity borehole monitoring system based on the change in conductivity obtained in Step 8, and obtain the potential values ​​at each point during the grouting reinforcement process through the resistivity borehole monitoring system.

[0017] Step 10: Normalize the measured data obtained in Step 9, remove noise and outliers, and then use the MSE error function to quantify the difference between the measured potential data and the model calculated data; use a genetic algorithm to iteratively correct the seepage model based on the error, thereby continuously obtaining the diffusion path of the grout and the reinforcement effect during the grouting process.

[0018] Furthermore, the rock mechanics data includes: the elastic modulus, Poisson's ratio, density, thickness, tensile strength, initial porosity, initial permeability coefficient, and burial depth of each rock layer; the grouting parameters include: the preset grout mix ratio, borehole length, borehole diameter, and grouting pressure.

[0019] Furthermore, in step two, to ensure the model runs and calculates effectively, the following conditions are set for the model:

[0020] ①Ignore the interface effect between rock strata and assume that the same rock strata exhibit isotropy and homogeneity;

[0021] ②The stress field generated by the self-weight of the rock strata is used as the initial stress field;

[0022] ③ The bottom surface of the porous medium is a fixed constraint;

[0023] ④ Supported by rollers on all four sides;

[0024] ⑤ Apply an equivalent load to the upper boundary to replace the self-weight stress of the upper rock strata;

[0025] ⑥ Assume that the strata in the grouting area are porous media filled with air.

[0026] Furthermore, step three specifically includes:

[0027]

[0028] Where: σ xx σ yy and σ zz It is the normal stress component along the x, y, and z axes, σ xy σ xz σ yx σ yz σ zx and σ zy These are shear stress components, the values ​​of which are obtained through geological mining simulations.

[0029] The effective principal stresses σ1, σ2, and σ3 are solutions to the following characteristic equation:

[0030] det(σ ij -σI)=0

[0031] Where: I is the identity matrix, and det represents the determinant; the equation is a cubic equation, and its solution is the three principal stresses.

[0032] Furthermore, the formula for calculating the porosity distribution in step four is as follows:

[0033]

[0034] Where: φ0 is the porosity of the coal and rock mass under initial stress, φ r Both α and α represent the porosity limit of coal and rock mass under high pressure stress, and their values ​​were obtained experimentally. φ It is the stress sensitivity coefficient, taken as α. φ =5.0×10 ―8 pa ―1 ; It is the average effective stress;

[0035] The formula for calculating the permeability coefficient is:

[0036] K = K0(φ / φ0) 3 exp(α k D)

[0037] Where: K0 is the permeability coefficient under initial stress, m / s; α k Let α be the coefficient of influence of damage on the permeability coefficient. k =5.0; D is the damage coefficient, 0≤D≤1.

[0038] Furthermore, in step five, to ensure the model runs and calculates effectively, the following conditions are set for the model:

[0039] (i) The flow of the slurry is continuous;

[0040] (ii) The slurry is an isotropic and incompressible fluid, and its bulk density remains constant and its flow rate is stable during the flow process;

[0041] (iii) The flow of the slurry is laminar;

[0042] (iv) Set the porous medium to have a flow-free interface around its perimeter and on its top and bottom surfaces.

[0043] Furthermore, the initial parameters of the slurry-driven air model in step six include: grouting pressure, slurry density, slurry dynamic viscosity, relative permeability of 1, relative permeability of air and slurry, air density, and aerodynamic viscosity.

[0044] Furthermore, step seven specifically involves: the slurry resistivity being 10 Ω·m and the relative permittivity being 1; the porous medium resistivity being 2000 Ω·m and the permittivity being 1; and the electric field boundary condition being set to: the bottom surface of the porous medium being grounded.

[0045] Furthermore, the formula for calculating the changing conductivity in step eight is as follows:

[0046] σ=σ s ×(1-φ)+σ g ×s g ×φ

[0047] Where: σ s σ represents the initial electrical conductivity of each coal and rock mass; g The electrical conductivity of the slurry.

[0048] Compared with existing technologies, this invention first obtains the geological conditions, rock mechanics data, and grouting parameters of the grouting area. It then simulates the mining process using a rock mechanics physical field model, and subsequently simulates and calculates the distribution of effective principal stress after excavation. Based on the distribution of effective principal stress in the porous medium within the mechanical field, it simulates and calculates the porosity distribution after fracturing the formation. Next, it calculates the permeability coefficient of the porous medium after fracturing. Then, it uses a two-phase Darcy's law physical field model to simulate the slurry diffusion process, analyzes the slurry diffusion path, and sets the initial parameters of the slurry gas-driving model according to preset grouting parameters. Through simulation calculations, it obtains the overall changing conductivity of both the porous medium and the slurry. Based on the simulated changing conductivity, it determines the parameters of the resistivity borehole-tunnel joint monitoring system. Using the resistivity borehole-tunnel joint monitoring system, it measures the potential values ​​at various points during the grouting reinforcement process. Finally, it compares and analyzes the measured data with the model calculation data, continuously acquiring the slurry diffusion path and reinforcement effect during the grouting reinforcement process. Through comprehensive analysis of the multi-physics coupling, it achieves dynamic visualization of the grouting reinforcement effect before and after mining. Attached Figure Description

[0049] Figure 1 This is an overall flowchart of an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the electrical principle of the Wenner-α device in an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of the layout of the resistivity orifice-tunnel joint monitoring system in an embodiment of the present invention.

[0052] In the diagram: 1. Electrode; 2. Slurry diffusion area; 3. Tunnel; 4. Borehole. Detailed Implementation

[0053] The present invention will be further described below.

[0054] like Figure 1 As shown, this embodiment includes the following steps:

[0055] Step 1: Before grouting, obtain the geological conditions, rock mechanics data, and grouting parameters of the grouting area. The rock mechanics data includes: the elastic modulus, Poisson's ratio, density, thickness, tensile strength, initial porosity, initial permeability coefficient, and burial depth of each rock layer. The grouting parameters include: the preset grout mix ratio, borehole length, borehole diameter, and grouting pressure.

[0056] Step 2: A rock mechanics physical field model based on the stress balance equation is constructed. This model is used to simulate the stratum mining process and obtain the stratum conditions after mining. To ensure the effective operation and calculation of the model, the following conditions are set for the model: ① Ignore the interface effect between rock strata and assume that the same rock stratum exhibits isotropy and homogeneity; ② Use the stress field generated by the self-weight of the rock strata as the initial stress field; ③ The bottom surface of the porous medium is a fixed constraint; ④ Roller support is used around the perimeter; ⑤ An equivalent load is applied to the upper boundary to replace the self-weight stress of the upper rock strata; ⑥ It is assumed that the stratum in the grouting area is a porous medium filled with air.

[0057] Step 3: Based on the simulated geological conditions after mining in Step 2, calculate the distribution of effective principal stress after tunneling, specifically as follows:

[0058]

[0059] Where: σ xx σ yy and σ zz It is the normal stress component along the x, y, and z axes, σ xy σ xz σ yx σ yz σ zx and σ zy These are shear stress components, the values ​​of which are obtained through geological mining simulations.

[0060] The effective principal stresses σ1, σ2, and σ3 are solutions to the following characteristic equation:

[0061] det(σ ij -σI)=0

[0062] Where: I is the identity matrix, and det represents the determinant; the equation is a cubic equation, and its solution is the three principal stresses.

[0063] Step 4: Based on the distribution of effective principal stresses in the mechanical field within the porous medium, calculate the porosity distribution after formation fracturing; then calculate the permeability coefficient of the porous medium after fracturing and apply it to the subsequent slurry diffusion medium; the formula for calculating the porosity distribution is as follows:

[0064]

[0065] Where: φ0 is the porosity of the coal and rock mass under initial stress, φ r Both α and α represent the porosity limit of coal and rock mass under high pressure stress, and their values ​​were obtained experimentally. φ It is the stress sensitivity coefficient, taken as α. φ =5.0×10 ―8 pa ―1 ; It is the average effective stress;

[0066] The formula for calculating the permeability coefficient is:

[0067] K = K0(φ / φ0) 3 exp(α k D)

[0068] Where: K0 is the permeability coefficient under initial stress, m / s; α k Let α be the coefficient of influence of damage on the permeability coefficient. k =5.0; D is the damage coefficient, 0≤D≤1.

[0069] Step 5: Construct a two-phase Darcy's law physical field model based on the seepage equation of Darcy's law. Use this model to simulate the slurry diffusion process and analyze the slurry diffusion path. To ensure the effective operation and calculation of the model, the following conditions are set for the model: (i) The flow of slurry is continuous; (ii) The slurry is an isotropic and incompressible fluid, and the slurry density remains constant and the flow velocity is stable during the flow process; (iii) The flow of slurry is laminar; (iv) The porous medium is set to have no flow interface around its perimeter and on its top and bottom surfaces.

[0070] Step Six: Set the initial parameters of the grout-driven air model according to the preset grouting parameters, including: grouting pressure, grout density, grout dynamic viscosity, relative permeability of 1, relative permeability of air and grout, air density, and aerodynamic viscosity; by default, the porous media is initially completely filled with air, and as time increases, the grout replaces the air in filling the porous media. That is: s a +s g =1. s when t=0 a =1; when t=∞, s g =1. Here s a s g These represent the saturation levels of air and slurry, respectively. The slurry-driven gas model employs a capillary model, where the capillary diffusion coefficients of the slurry and air are related to their respective permeabilities.

[0071] Step 7: Set up a resistivity borehole-tunnel combined monitoring system according to the location of the slurry diffusion area to be monitored, such as... Figure 3 As shown, electrodes are evenly distributed in the roadway and borehole to form a joint monitoring system to monitor the slurry diffusion area. The electrical parameters and electric field boundary conditions of the slurry and porous medium are set. Specifically, the slurry resistivity is 10 Ω·m and the relative permittivity is 1. The porous medium resistivity is 2000 Ω·m and the permittivity is 1. The electric field boundary condition is set as follows: the bottom surface of the porous medium is grounded.

[0072] Step 8: Use the slurry-driven gas model from Step 6 to simulate and obtain the saturation s of the slurry at different times. g The overall change in conductivity of the porous medium and the slurry was calculated using the following formula:

[0073] σ=σ s ×(1-φ)+σ g ×s g ×φ

[0074] Where: σ s σ represents the initial electrical conductivity of each coal and rock mass; g The electrical conductivity of the slurry.

[0075] Step Nine: Determine the parameters of the resistivity borehole monitoring system based on the changing conductivity obtained from the slurry-driven gas-expelling model simulation in Step Eight. These parameters include: electrode distance, power supply time, and power supply current. The resistivity borehole monitoring system is used to acquire the potential values ​​at various points during the grouting reinforcement process. The electrical resistivity device in the system is a Winner-α device, and its principle is as follows: Figure 2 As shown, the potential values ​​at different measuring points are obtained using the following method:

[0076] Arrange the power supply electrodes A and B, and the measuring electrodes M and N in the order AMNB, with the distance between adjacent electrodes being na, where a is the unit electrode distance. n takes values ​​of 1, 2, 3, ... When n = 1, the distance between adjacent AMNB electrodes is a. Calculate the potential value at the midpoint of MN using the following formula. Keeping the electrode distance between AMNB constant, move the electrodes one unit electrode distance a to the right and repeat the above calculation until electrode B reaches the far right. This yields the apparent resistivity values ​​for each measuring point in the first layer. When n = 2, the distance between adjacent AMNB electrodes is 2a. Calculate the potential value at the midpoint of MN using the following formula. Again, keeping the distance between electrodes constant, move the electrodes one unit electrode distance a to the right and repeat the above calculation until electrode B reaches the far right. This yields the apparent resistivity values ​​for each measuring point in the second layer. And so on...

[0077]

[0078] K = 2πa

[0079] Where: K is the device coefficient; a is the electrode distance; Δu is the potential difference between measuring electrodes M and N, the potentials of M and N are directly calculated from the points in the electric field simulation; I is the excitation current; finally, the measuring points are arranged in an inverted triangle shape. After interpolation calculation based on the position of the measuring points and the apparent resistivity value at the measuring points, the contour map of the contour points is formed to perform apparent resistivity imaging.

[0080] Step 10: Normalize the measured data obtained in Step 9, remove noise and outliers, and then use the MSE error function to quantify the difference between the measured potential data and the model calculated data; use a genetic algorithm to iteratively correct the seepage model based on the error, thereby continuously obtaining the diffusion path of the grout and the reinforcement effect during the grouting process.

[0081] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for visualizing the effect of post-mining grouting reinforcement based on multi-field coupling, characterized in that, Includes the following steps: Step 1: Before grouting, obtain the geological conditions, rock mechanics data, and grouting parameters of the grouting area; Step 2: Based on the stress balance equation, a rock mechanics physical field model is constructed. This model is used to simulate the stratum mining process and obtain the stratum conditions after mining. Step 3: Based on the simulated geological conditions after mining in Step 2, calculate the distribution of effective principal stress after tunneling; Step 4: Based on the distribution of effective principal stress in the mechanical field in the porous medium, calculate the porosity distribution after formation fracturing; then calculate the permeability coefficient of the porous medium after fracturing and use it in the subsequent slurry diffusion medium; Step 5: Construct a two-phase Darcy's law physical field model based on the seepage equation, and use this model to simulate the slurry diffusion process and analyze the slurry diffusion path; Step 6: Set the initial parameters of the grout-driven air model according to the preset grouting parameters; Step 7: Set up a resistivity pore tunnel joint monitoring system according to the location of the slurry diffusion area to be monitored, and set the electrical parameters and electric field boundary conditions of the slurry and porous media. Step 8: Use the slurry-driven gas model from Step 6 to simulate and obtain the saturation s of the slurry at different times. g The overall change in conductivity of the porous medium and the slurry was calculated. Step 9: Determine the parameters of the resistivity borehole monitoring system based on the change in conductivity obtained in Step 8, and obtain the potential values ​​at each point during the grouting reinforcement process through the resistivity borehole monitoring system. Step 10: Normalize the measured data obtained in Step 9, and use the MSE error function to quantify the difference between the measured potential data and the model calculated data; use a genetic algorithm to iteratively correct the seepage model based on the error, thereby continuously obtaining the diffusion path of the grout and the reinforcement effect during the grouting process.

2. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, The rock mechanics data include: elastic modulus, Poisson's ratio, density, thickness, tensile strength, initial porosity, initial permeability coefficient and burial depth of each rock layer; the grouting parameters include: preset grout mix ratio, borehole length, borehole diameter and grouting pressure.

3. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, In step two, to ensure the model runs and calculates effectively, the following conditions are set for the model: ①Ignore the interface effect between rock strata and assume that the same rock strata exhibit isotropy and homogeneity; ②The stress field generated by the self-weight of the rock strata is used as the initial stress field; ③ The bottom surface of the porous medium is a fixed constraint; ④ Supported by rollers on all four sides; ⑤ Apply an equivalent load to the upper boundary to replace the self-weight stress of the upper rock strata; ⑥ Assume that the strata in the grouting area are porous media filled with air.

4. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, Step three specifically involves: Where: σ xx σ yy and σ zz It is the normal stress component along the x, y, and z axes, σ xy σ xz σ yx σ yz σ zx and σ zy These are shear stress components, the values ​​of which are obtained through geological mining simulations. The effective principal stresses σ1, σ2, and σ3 are solutions to the following characteristic equation: det(s ij -σI)=0 Where: I is the identity matrix, and det represents the determinant.

5. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, The formula for calculating the porosity distribution in step four is as follows: Where: φ0 is the porosity of the coal and rock mass under initial stress, φ r Both α and α represent the porosity limit of coal and rock mass under high pressure stress, and their values ​​were obtained experimentally. φ It is the stress sensitivity coefficient; It is the average effective stress; The formula for calculating the permeability coefficient is: K=K0(φ / φ0) 3 exp(a k D) Where: K0 is the permeability coefficient under initial stress, m / s; α k denoted as the influence coefficient of damage on the permeability coefficient; D is the damage coefficient, 0≤D≤1.

6. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, In step five, to ensure the model runs and calculates effectively, the following conditions are set for the model: (i) The flow of the slurry is continuous; (ii) The slurry is an isotropic and incompressible fluid, and its bulk density remains constant and its flow rate is stable during the flow process; (iii) The flow of the slurry is laminar; (iv) Set the porous medium to have a flow-free interface around its perimeter and on its top and bottom surfaces.

7. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, The initial parameters of the slurry-driven air model in step six include: grouting pressure, slurry density, slurry dynamic viscosity, relative permeability of 1, relative permeability of air and slurry, air density, and aerodynamic viscosity.

8. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, Step seven specifically involves: the slurry resistivity is 10 Ω·m, the relative permittivity is 1, the porous medium resistivity is 2000 Ω·m, and the permittivity is 1; the electric field boundary condition is set as follows: the bottom surface of the porous medium is grounded.

9. The method for visualizing the grouting effect of post-mining reinforcement based on multi-field coupling according to claim 1, characterized in that, The formula for calculating the changed conductivity in step eight is as follows: s = s s ×(1-φ)+σ g ×s g ×φ Where: σ s σ represents the initial electrical conductivity of each coal and rock mass; g The electrical conductivity of the slurry.

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