A method for determining rock mass stress value based on Kaiser effect

Abstract

The application provides a method for determining rock mass ground stress value based on Kaiser effect, comprising the following steps: performing indoor rock compression test to obtain acoustic emission activity characteristics of each rock sample in loading process; obtaining peak frequency characteristics of all acoustic emission impact signals of the rock sample; defining signals of the first 30% of acoustic emission peak frequency values as high-frequency acoustic emission signals according to the acoustic emission impact signal peak frequency-time diagram drawn according to the peak frequency characteristics; calculating fractal dimension of the high-frequency acoustic emission signals of the rock sample, and determining axial stress value corresponding to Kaiser effect occurrence time of the rock sample according to the calculated fractal dimension; and obtaining rock mass ground stress value at the sampling depth according to the positive axial stress value corresponding to Kaiser effect occurrence time of the rock sample. The application realizes accurate determination of rock mass ground stress value on the basis of scientifically finding Kaiser effect point of the rock.

Description

Technical Field

[0001] This invention belongs to the field of underground resource development and utilization technology, specifically relating to a method for determining rock mass stress values ​​based on the Kaiser effect. Background Technology

[0002] In recent years, with the depletion of surface and shallow Earth resources through large-scale development, people have begun to venture into deep underground engineering. The average reservoir depth of the world's deepest onshore oil and gas fields has exceeded 7,300 meters. Deep Earth resource extraction and underground space construction and utilization have become key directions in geotechnical engineering. In-situ stress is an important influencing factor on the deformation and instability of underground engineering projects. Determining the in-situ stress characteristics of the rock mass in the project site area is an important prerequisite for achieving safe engineering design.

[0003] Currently, methods for determining rock in-situ stress mainly fall into two categories: field testing methods and laboratory testing methods. Field testing methods mainly include hydraulic fracturing, total stress relief, and geophysical exploration methods. However, these methods have limitations such as high requirements for field testing conditions, long testing time, high cost, and susceptibility to many interference factors, resulting in poor application results in the practical measurement of in-situ stress in ultra-deep underground engineering.

[0004] Indoor testing methods include acoustic emission, inelastic strain recovery, and circumferential wave velocity anisotropy analysis. These methods have advantages such as simple operation, high repeatability, and convenient testing, but they also have problems such as difficulty in interpreting test data and low accuracy of test results. Taking acoustic emission as an example, when a material is subjected to an external load, the strain energy stored inside the material will emit elastic waves, producing an acoustic emission phenomenon. When the stress on the material is released from its historical maximum level and then reloaded, there is very little acoustic emission when the stress has not reached the previous maximum stress value. However, when the stress reaches or exceeds the historical maximum level, a large amount of acoustic emission occurs. This phenomenon is called the Kaiser effect, which is the fundamental theory for determining rock stress using acoustic emission methods.

[0005] The acquisition of the Kaiser effect point directly affects the results of rock in-situ stress measurement. Scientifically finding the Kaiser effect point of rocks is the key to achieving accurate measurement of their in-situ stress. Therefore, given the technical difficulties in determining rock in-situ stress using acoustic emission methods, there is an urgent need for a simple, easy-to-implement, and operable experimental method to achieve the scientific and accurate measurement of rock in-situ stress values. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method for determining the geostress value of rock mass based on the Kaiser effect, which addresses the shortcomings of the existing technology.

[0007] To solve the above-mentioned technical problems, the present invention includes:

[0008] A method for determining rock mass in-situ stress based on the Kaiser effect includes the following steps:

[0009] S1. Conduct indoor rock compression tests: For deep rock samples obtained in the field, place them vertically and establish a spatial rectangular coordinate system with the central axis of the rock sample as the Z-axis and the normal plane of the Z-axis as the XOY plane; then drill cores along the X, Y, Z and X45°Y, X45°Z, Y45°Z directions on the rock sample to obtain six rock samples in these six directions; conduct indoor triaxial rock compression tests on each rock sample to obtain the acoustic emission activity characteristics of each rock sample during loading;

[0010] S2, obtain the peak frequency characteristics of all acoustic emission impact signals of each rock sample, and use the peak frequency-time diagram of acoustic emission impact signals drawn accordingly to define the signals with the highest 30% of the acoustic emission peak frequency values ​​as high-frequency acoustic emission signals.

[0011] S3, calculate the fractal dimension of the high-frequency acoustic emission signal of each rock sample, and determine the axial stress value corresponding to the moment when the Kaiser effect occurs based on the calculated fractal dimension.

[0012] S4. Based on the positive axial stress values ​​corresponding to the time when the Kaiser effect occurs in the six rock samples, the rock mass in-situ stress value at the sampling depth is obtained.

[0013] Furthermore, in step S1, the diameter of the rock sample is not less than 120 mm; the rock sample is a standard cylindrical sample with a diameter of 50 mm and a height of 100 mm.

[0014] Furthermore, in step S1, when conducting an indoor triaxial compression test on the rock sample, the confining pressure for the triaxial compression test is set to... Where γ is the rock unit weight and h is the burial depth of the sample; acoustic emission sensors are deployed around the rock sample to collect acoustic emission information during the rock sample fracture and damage process; statistical analysis of the test data yields six sets of axial stress-time curves, acoustic emission impact count rate-time curves, acoustic emission signal waveform characteristics, and occurrence time of the rock sample during the test process.

[0015] Furthermore, in step S2, the calculation step for the peak frequency characteristics of the acoustic emission impact signal of each rock sample is as follows:

[0016] S21, for each acoustic emission impact signal, obtain the time data length value L of the acoustic emission impact signal waveform. n , where n is the number of acoustic emission signals, and this length value L i The maximum value of the waveform scaling width 'a' is used as a reference.

[0017] S22, determine the comparison waveform, and scale the comparison waveform multiple times: the scaling width 'a' of the comparison waveform starts from 1 and increases sequentially according to the unit length until it reaches the maximum value L. n ;

[0018] S23, For each scaled comparison waveform, first align the acoustic emission impact signal waveform with the starting point of the comparison waveform, then shift the comparison waveform to the right along the time axis at unit time τ until it covers the entire length of the acoustic emission impact signal waveform; during this process, calculate the approximation value WT between the acoustic emission impact signal waveform at time t and the comparison waveform under different comparison orders according to the following formula. a-1 , ...,

[0019] Where a = 1, ..., L n ;

[0020] S24, Obtain the approximation range The maximum value in, where j n =1,…,L n Based on the scaling width value a′ corresponding to the maximum value, the characteristics of the comparison waveform under the scaling width condition are obtained. Then, the center frequency value of the comparison waveform is calculated according to the following formula.

[0021] In the formula F C To compare the original standard center frequency of the waveform, F S The acoustic emission sampling frequency;

[0022] S25, using time as the X-axis, frequency as the Y-axis, and voltage as the Z-axis, construct a three-dimensional time-frequency diagram for each acoustic emission impact signal, and obtain the peak frequency F corresponding to the maximum voltage. n .

[0023] Furthermore, in step S22, the comparison waveform is based on the formula... It has been confirmed.

[0024] Furthermore, in step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample... i The calculation steps are as follows:

[0025] S3-1, For each high-frequency acoustic emission signal, the grid width δ is selected sequentially in descending order of unit length. k =[L i L i -1,L i -2, ..., 1], k = 1, ..., L i L iis the time data length value of the acoustic emission impact signal waveform, and i is the number of high-frequency acoustic emission signals;

[0026] S3-2, for the selected grid width δ k The voltage-time graph of the high-frequency acoustic emission signal is divided into sections with a width of δ. k The number N of intersections between the acoustic emission signal waveform curve and the equally spaced squares is obtained. k ;

[0027] S3-3, with grid width δ k Let N be the number of squares where the acoustic emission signal waveform curve intersects the grid. k Plot logδ along the Y-axis. k -logN k The curve is calculated, and an approximate straight line segment is fitted to the curve using the least squares method to obtain the slope K of the straight line segment. This slope K is denoted as the fractal dimension D of the high-frequency acoustic emission signal. i .

[0028] Furthermore, in step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample is calculated. i The process also includes the following steps to determine the axial stress value σ corresponding to the moment the Kaiser effect occurs in each rock sample. N :

[0029] S3-4, the fractal dimension D i The minimum value D min The corresponding time is recorded as the moment when the Kaiser effect occurs;

[0030] S3-5, based on the axial stress-time curves of the rock samples obtained from the indoor tests, obtain the axial stress value σ corresponding to the moment when the Kaiser effect occurs for each rock sample. N , where N is the number of rock samples.

[0031] Furthermore, step S4 specifically includes the following steps:

[0032] S41, using the six axial normal stress values ​​σ corresponding to the Kaiser effect points of six rock samples. N+ The six stress component values ​​σ are calculated according to the following formula. x σ y σ z τ xy τ yz and τ zx :

[0033] σ N+ =σ x l 2 +σ y m 2 +σz n 2 +2τ xy lm+2τ yz lm+2τ zx nl

[0034] In the formula, l, m, and n are the cosine values ​​of the angles between the outer normal direction of the rock sample and the X, Y, and Z axes, respectively;

[0035] S42, using the six stress component values ​​obtained from the calculation, the three intermediate variables P, W, and θ are calculated respectively according to the following formula:

[0036]

[0037] In the formula:

[0038]

[0039]

[0040] S43, using the three intermediate variables P, W and θ obtained from the calculation, the rock mass in-situ stress values ​​σ1, σ2 and σ3 at the sampling depth are calculated according to the following formula:

[0041]

[0042] Furthermore, in step S4, after calculating the rock mass stress values ​​σ1, σ2, and σ3 at the sampling depth, the method further includes the following step: calculating the dip angle and azimuth angle of the principal stresses.

[0043] S44. Using the calculated rock mass in-situ stress values ​​σ1, σ2, and σ3 at the sampling depth, the cosine value m of the angle between the principal stress direction and the coordinate axes X, Y, and Z is calculated according to the following formula. i n i and l i :

[0044]

[0045] In the formula,

[0046] S45, calculate the inclination angles α1, α2, and α3 of the principal stresses and the azimuth angles β1, β2, and β3 according to the following formula:

[0047] In the formula, i = 1, 2, 3.

[0048] The beneficial effects of this invention are:

[0049] The method for determining rock mass stress based on the Kaiser effect of the present invention is simple, easy to implement, and operable. Based on the scientific search for the Kaiser effect point in the rock, it realizes the accurate determination of rock mass stress value. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of rock sampling according to the present invention;

[0051] Figure 2 This is a schematic diagram of the acoustic emission sensor layout for the triaxial compression test of the salt rock sample according to the present invention;

[0052] Figure 3 This is a schematic diagram of the stress-acoustic emission impact count rate-time relationship of the salt rock sample according to the present invention;

[0053] Figure 4 This is a schematic diagram of the acoustic emission signal waveform of the present invention;

[0054] Figure 5 This is a frequency-voltage-time diagram of the acoustic emission waveform of the present invention;

[0055] Figure 6 This is a schematic diagram of the acoustic emission peak frequency-time of the present invention;

[0056] Figure 7 This is a schematic diagram of the acoustic emission signal voltage-time of the present invention;

[0057] Figure 8 This is a schematic diagram of the double logarithmic curve of the grid width and the number of intersections in this invention;

[0058] Figure 9 This is a schematic diagram of the spatial distribution of rock mass stress according to the present invention. Detailed Implementation

[0059] To facilitate understanding of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the invention and should not be considered as specific limitations thereof.

[0060] Example 1

[0061] This invention provides a method for determining rock mass in-situ stress based on the Kaiser effect, comprising the following steps:

[0062] S1, conduct indoor rock compression tests to obtain the acoustic emission characteristics of the rock during loading.

[0063] In this step, core drilling is used to obtain deep rock samples at a depth of approximately 3000m. The diameter of the cylindrical rock samples drilled is 120mm. For deep rock samples obtained in the field, they are placed vertically with the central axis of the rock sample as the Z-axis and the normal plane of the Z-axis as the XOY plane, establishing a spatial rectangular coordinate system, such as... Figure 1 As shown, OX is the X-axis direction, OY is the Y-axis direction, and point O is the intersection of the OX, OY, and OZ axes, which are mutually perpendicular. Then, using the core drilling method, cores were drilled in the rock sample along the X, Y, Z, X45°Y, X45°Z, and Y45°Z directions to obtain six rock samples in these six directions. The rock samples were standard cylindrical samples with a diameter of 50 mm and a height of 100 mm. The six standard cylindrical samples obtained in the six directions were subjected to indoor triaxial compression tests to obtain the acoustic emission activity characteristics of each rock sample during the loading process.

[0064] In this step, when conducting indoor triaxial compression tests on the rock samples, the confining pressure of the triaxial compression test is set to pressure. Where γ is the rock specific gravity, taken as 2.3 g / cm³. 3 The sample was buried at a depth h of 3000m; acoustic emission sensors were deployed around the salt rock sample, such as... Figure 2 As shown, acoustic emission information was collected during the fracture and damage process of the rock samples; the experimental data were statistically analyzed to obtain six sets of axial stress-time curves, acoustic emission impact count rate-time curves, acoustic emission signal waveform characteristics, and occurrence times of the rock samples during the test process. Figure 3 As shown.

[0065] S2, obtain the peak frequency characteristics of all acoustic emission impact signals for each rock sample, and use the peak frequency-time plot of the acoustic emission impact signals drawn accordingly, such as... Figure 6 As shown, the signal with the first 30% of the peak frequency of acoustic emission is defined as a high-frequency acoustic emission signal;

[0066] S3, calculate the fractal dimension of the high-frequency acoustic emission signal of each rock sample, and determine the axial stress value corresponding to the moment when the Kaiser effect occurs based on the calculated fractal dimension.

[0067] S4. Based on the positive axial stress values ​​corresponding to the time when the Kaiser effect occurs in the six rock samples, the rock mass in-situ stress value at the sampling depth is obtained.

[0068] Example 2

[0069] In step S2, the calculation steps for the peak frequency characteristics of the acoustic emission impact signal of each rock sample are as follows:

[0070] S21, for each acoustic emission impact signal, obtain the time data length value L of the acoustic emission impact signal waveform. n , where n is the number of acoustic emission signals, and this length value L n The maximum value of the waveform scaling width 'a' is used as a reference.

[0071] S22, according to formula Determine the comparison waveform and scale it multiple times: the scaling width 'a' of the comparison waveform starts from 1 and increases sequentially by unit length until it reaches the maximum value L. n ;

[0072] S23, For each scaled comparison waveform, first align the acoustic emission impact signal waveform with the starting point of the comparison waveform, then shift the comparison waveform to the right along the time axis at unit time τ until it covers the entire length of the acoustic emission impact signal waveform; during this process, calculate the approximation value WT between the acoustic emission impact signal waveform at time t and the comparison waveform under different comparison orders according to the following formula. a-1 , ...,

[0073] Where a = 1, ..., L n ;

[0074] S24, Obtain the approximation range The maximum value in, where j n =1,…,L n Based on the scaling width value a′ corresponding to the maximum value, the characteristics of the comparison waveform under the scaling width condition are obtained. Then, the center frequency value of the comparison waveform is calculated according to the following formula.

[0075] In the formula F C To compare the original standard center frequency of the waveform, F S The acoustic emission sampling frequency;

[0076] S25, using time as the X-axis, frequency as the Y-axis, and voltage as the Z-axis, construct a three-dimensional time-frequency diagram for each acoustic emission impact signal, and obtain the peak frequency F corresponding to the maximum voltage. n .

[0077] The following description uses the original acoustic emission impact signal waveform as an example to illustrate this embodiment.

[0078] (1) The time data length value L1 = 5120 of the original acoustic emission impact signal waveform is calculated, and this value is taken as the maximum value of the waveform scaling width a; (2) The comparison waveform is scaled according to the width a = 1, such as Figure 4As shown; (3) Align the starting point of the original acoustic emission impact signal waveform with the comparison waveform, and calculate the approximation value WT of the original acoustic emission impact signal waveform and the comparison waveform at time t. 1-1 =0.0000261; (4) Shift the comparison waveform to the right along the time axis by one unit time τ, and calculate the approximation value WT between the original acoustic emission impact signal waveform and the comparison waveform at time t. 1-2 =0.0000903; (5) Repeat step (4) until the entire length of the original acoustic emission impact signal waveform is covered, and calculate the approximation value WT obtained after 5118 scaling operations. 1-3 =0.0000719, WT 1-4 =0.0000665, ..., WT 1-5120 =0; (6) Increase the scaling width a by unit length to obtain a = 2, ..., 5120 respectively; (7) When a = 2, scale the comparison waveform by width 2, repeat steps (3)-(5) to obtain the approximation value WT under different comparison orders. 2-1 =0.000178, WT 2-2 =0.000103, ..., WT 2-5120 =0; When a=3, the comparison waveform is scaled by a width of 3, and steps (3)-(5) are repeated to obtain the approximation value WT under different comparison orders. 3-1 =0.000117, ..., WT 3-5120 =0; ...; When a = 5120, the comparison waveform is scaled according to the width 5120, and steps (3)-(5) are repeated to obtain the approximation value WT under different comparison orders. 5120-1 =0.001, ..., WT 5120-5120 =0.000355.

[0079] (8) When j1 = 1, select the approximation range [WT]. 1-1 =0.0000261, WT 2-1 =0.000178, ..., WT 5120-1 The maximum value in [ = 0.001] is used to obtain the scaling width value corresponding to this maximum value, and then the characteristics of the comparison waveform under this scaling width condition are obtained. The center frequency value of the comparison waveform is calculated to be F1 = 139.67kHz. Where the original standard center frequency F of the comparison waveform is... C =0.667, acoustic emission sampling frequency F S =1000kHz.

[0080] (9) When j1 = 2, select the approximation range [WT]. 1-2 =0.0000903, WT 2-2 =0.000103, ..., WT5120-2 =0.00035] The maximum value in the range is used to repeat step (8) to obtain the center frequency value of the comparison waveform F2 = 95.23kHz; when j1 = 3, the approximation range [WT] is selected. 1-3 =0.0000719, WT 2-3 =0.0000865, ..., WT 5120-3 =0.00047] The maximum value in the range is used to repeat step (8) to obtain the center frequency value of the comparison waveform F3 = 119.14kHz; ...; When j1 = 5120, the approximation range [WT] is selected. 1-5120 =0,WT 2-5120 =0, ...,WT 5120-5120 =0.000355] is the maximum value, and step (8) is repeated to obtain the center frequency value F of the comparison waveform. 5120 =333.34kHz.

[0081] (10) Plot a three-dimensional time-frequency diagram of the original acoustic emission impact signal with time as the X-axis, frequency as the Y-axis, and voltage as the Z-axis, and determine the frequency F1 = 81kHz corresponding to the maximum voltage; (11) Based on steps (1)-(10), obtain the peak frequencies F2 = 258kHz, F3 = 146kHz, ..., F of all acoustic emission impact signals during the experiment. 313 =85kHz.

[0082] (11) Plot the peak frequency-time graph of all acoustic emission impact signals, and define the signals with the highest peak frequencies in the top 30% as high-frequency acoustic emission signals, such as... Figure 6 As shown.

[0083] Example 3

[0084] In step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample is... i The calculation steps are as follows:

[0085] S3-1, For each high-frequency acoustic emission signal, the grid width δ is selected sequentially in descending order of unit length. k =[L i L i -1,L i -2, ..., 1], k = 1, ..., L i L i is the time data length value of the acoustic emission impact signal waveform, and i is the number of high-frequency acoustic emission signals;

[0086] S3-2, for the selected grid width δ k The voltage-time graph of the high-frequency acoustic emission signal is divided into sections with a width of δ. k Equally spaced squares, such as Figure 7As shown (δ) k =100), obtain the number N of intersections between the acoustic emission signal waveform curve and the grid. k ;

[0087] S3-3, with grid width δ k Let N be the number of squares where the acoustic emission signal waveform curve intersects the grid. k Plot logδ along the Y-axis. k -logN k The curve is calculated, and an approximate straight line segment is fitted to the curve using the least squares method to obtain the slope K of the straight line segment. This slope K is denoted as the fractal dimension D of the high-frequency acoustic emission signal. i .

[0088] The following description uses the original acoustic emission impact signal waveform as an example to illustrate this embodiment.

[0089] (1) Select grid width δ k =δ1, δ1 is equal to the time data length value L1 = 5120 of the original acoustic emission impact signal waveform; (2) Divide the voltage-time diagram of the high-frequency acoustic emission signal into equally spaced squares with a width of δ1, and obtain the number of intersections between the acoustic emission signal waveform curve and the squares N1 = 1; (3) Divide the grid width δ k δ is obtained by decreasing the unit length respectively. k =5119, 5118, ..., 1. When the grid width δ k When δ = 5119, repeat step (2) to obtain the corresponding N2 = 1; when δ k When δ = 5118, repeat step (2) to obtain the corresponding N3 = 1; ...; when δ k When = 1, repeat step (2) to obtain the corresponding result. (4) Plot logδ with the grid width as the X-axis and the number of intersections between the acoustic emission signal waveform curve and the grid as the Y-axis. k -logN k Curves, such as Figure 8 As shown, the least squares method is used to fit the approximate straight line segment in the curve, and the slope of the straight line segment is obtained as K = 1.382. This K value is denoted as the fractal dimension D1 of the high-frequency acoustic emission signal. (5) According to steps (1)-(4), the fractal dimensions D2 = 1.348, D3 = 1.366, ..., D of all other high-frequency acoustic emission signals are calculated. i =1.362, where i is the number of high-frequency acoustic emission signals, obtaining [D1, D2, D3, ..., D i The minimum value of ] is 1.320, denoted as Dmin.

[0090] Example 4

[0091] In step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample is calculated. i The process also includes the following steps to determine the axial stress value σ corresponding to the moment the Kaiser effect occurs in each rock sample. N :

[0092] S3-4, the fractal dimension D i The minimum value D min The corresponding time is recorded as the moment when the Kaiser effect occurs;

[0093] S3-5, based on the axial stress-time curves of the rock samples obtained from the indoor tests, obtain the axial stress value σ corresponding to the moment when the Kaiser effect occurs for each rock sample. N , where N is the number of rock samples.

[0094] Example 5

[0095] In step S4, the calculation steps for the rock mass in-situ stress value at the sampling depth are as follows:

[0096] S41, using the six axial normal stress values ​​σ corresponding to the Kaiser effect points of six rock samples. N+ The six stress component values ​​σ are calculated according to the following formula. x σ y σ z τ xy τ yz and τ zx :

[0097] σ N+ =σ x l 2 +σ y m 2 +σ z n 2 +2τ xy lm+2τ yz lm+2τ zx nl

[0098] In the formula, l, m, and n are the cosine values ​​of the angles between the outer normal direction of the rock sample and the X, Y, and Z axes, respectively;

[0099] S42, using the six stress component values ​​obtained from the calculation, the three intermediate variables P, W, and θ are calculated respectively according to the following formula:

[0100]

[0101] In the formula: J1=σ x +σ y +σ z ,

[0102] S43, using the three intermediate variables P, W and θ obtained from the calculation, the rock mass in-situ stress values ​​σ1, σ2 and σ3 at the sampling depth are calculated according to the following formula:

[0103]

[0104] The maximum, minimum, and intermediate values ​​of σ1, σ2, and σ3 are respectively the maximum principal stress value, minimum principal stress value, and intermediate principal stress value of the rock mass.

[0105] The following section explains how to obtain the rock mass stress value using measured data.

[0106] (1) The normal stress values ​​corresponding to the Kaiser effect points of the six groups of rock samples were obtained as follows: σ Nx =59.41MPa, σ Ny =56.58MPa, σ Nz =67.97MPa, σ Nxy45 =59.68MPa, σ Nyz45 =63.59MPa, σ Nzx45 =67.71MPa; (2) The calculated values ​​of the six stress components are as follows: σ x =59.41MPa, σ y =56.58MPa, σ z =67.97MPa, τ xy =1.685MPa, τ yz =1.315MPa, τ zx =4.02MPa; (3) The intermediate variables J1, J2 and J3 were calculated as follows: J1 = 183.96, J2 = 11225, J3 = 227280; (4) The intermediate variables P, W and θ were calculated as follows: P = -55.8979, W = 0.5269, θ = -139.0422; (5) The rock mass in-situ stress values ​​σ1, σ2 and σ3 at the sampling depth were calculated as follows: σ1 = 69.82MPa, σ2 = 58.37MPa, σ3 = 55.76MPa, where σ1 is the maximum principal stress, σ 2 σ3 is the intermediate principal stress, and σ3 is the minimum principal stress, such as Figure 9 As shown.

[0107] Example 6

[0108] In step S4, after calculating the rock mass stress values ​​σ1, σ2, and σ3 at the sampling depth, the following steps are also included to calculate the dip angle and azimuth angle of the principal stresses:

[0109] S44. Using the calculated rock mass in-situ stress values ​​σ1, σ2, and σ3 at the sampling depth, the cosine value m of the angle between the principal stress direction and the coordinate axes X, Y, and Z is calculated according to the following formula. i n i and l i :

[0110]

[0111] In the formula,

[0112] S45, calculate the inclination angles α1, α2, and α3 of the principal stresses and the azimuth angles β1, β2, and β3 according to the following formula:

[0113] In the formula, i = 1, 2, 3.

[0114] The calculation of the inclination angle and azimuth angle of the principal stress is explained below using measured data.

[0115] (1) Calculate the cosine values ​​of the angles between the principal stress directions and the coordinate axes X, Y, and Z: l1 = 0.3762, l2 = 0.4736, l3 = 0.7963, m1 = 0.1389, m2 = -0.8786, m3 = 0.2717, n1 = 0.9161, n2 = -0.0613, n3 = -0.2357; (2) Calculate the inclination angles of the principal stresses: α1 = 66.36, α2 = -3.52, α3 = -13.63, and the azimuth angles: β1 = 11.42, β2 = -61.67, β3 = -64.57.

[0116] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for determining the geostress value of rock mass based on the Kaiser effect, characterized in that, The method includes the following steps: S1. Conduct indoor rock compression tests: For deep rock samples obtained in the field, place them vertically and establish a spatial rectangular coordinate system with the central axis of the rock sample as the Z-axis and the normal plane of the Z-axis as the XOY plane; then drill cores along the X, Y, Z and X45°Y, X45°Z, Y45°Z directions on the rock sample to obtain six rock samples in these six directions; conduct indoor triaxial rock compression tests on each rock sample to obtain the acoustic emission activity characteristics of each rock sample during loading; S2, obtain the peak frequency characteristics of all acoustic emission impact signals of each rock sample, and use the peak frequency-time diagram of acoustic emission impact signals drawn accordingly to define the signals with the highest 30% of the acoustic emission peak frequency values ​​as high-frequency acoustic emission signals. In this step, the calculation steps for the peak frequency characteristics of the acoustic emission impact signal of each rock sample are as follows: S21, For each acoustic emission impact signal, obtain the time data length value L of the acoustic emission impact signal waveform. n , where n is the number of acoustic emission signals, and this length value L n The maximum value of the waveform scaling width 'a' is used as a reference. S22, determine the comparison waveform, and scale the comparison waveform multiple times: the scaling width 'a' of the comparison waveform starts from 1 and increases sequentially according to the unit length until it reaches the maximum value L. n ; S23, for each scaled comparison waveform, first align the acoustic emission impact signal waveform with the starting point of the comparison waveform, then scale the comparison waveform along the time axis unit time. The waveform is moved sequentially to the right until it covers the entire length of the acoustic emission impact signal waveform. During this process, the approximation values ​​of the acoustic emission impact signal waveform at time t and the comparison waveform under different comparison orders are calculated according to the following formula. , ..., : where a=1,…,L n ; S24, Obtain the approximation range [ , , ..., The maximum value in ], where j n =1,…,L n Based on the scaling width value corresponding to this maximum value Obtain the characteristics of the contrast waveform under the scaling width condition, and then calculate the center frequency value of the contrast waveform according to the following formula. : In the formula To compare the original standard center frequency of the waveform, The acoustic emission sampling frequency; S25. Using time as the X-axis, frequency as the Y-axis, and voltage as the Z-axis, a three-dimensional time-frequency diagram is constructed for each acoustic emission impact signal, and the peak frequency F corresponding to the maximum voltage is obtained. n ; S3, calculate the fractal dimension of the high-frequency acoustic emission signal of each rock sample, and determine the axial stress value corresponding to the moment when the Kaiser effect occurs based on the calculated fractal dimension. S4. Based on the axial normal stress values ​​corresponding to the time when the Kaiser effect occurs in the six rock samples, obtain the rock mass in-situ stress value at the sampling depth.

2. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 1, characterized in that, In step S1, the diameter of the rock sample is not less than 120 mm; the rock sample is a standard cylindrical sample with a diameter of 50 mm and a height of 100 mm.

3. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 1, characterized in that, In step S1, when conducting an indoor triaxial compression test on the rock sample, the confining pressure for the triaxial compression test is set to... ,in The rock is of high density. The burial depth of the sample was determined; acoustic emission sensors were deployed around the rock sample to collect acoustic emission information during the rock sample fracture and damage process; the test data were statistically analyzed to obtain six sets of axial stress-time curves, acoustic emission impact count rate-time curves, acoustic emission signal waveform characteristics, and occurrence time of the rock sample during the test process.

4. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 1, characterized in that, In step S22, the comparison waveform is based on the formula It has been confirmed.

5. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 1, characterized in that, In step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample... i The calculation steps are as follows: S3-1, For each high-frequency acoustic emission signal, select the grid width sequentially in descending order of unit length. =[L i L i -1,L i -2, ..., 1], k=1, ..., L i L i is the time data length value of the acoustic emission impact signal waveform, and i is the number of high-frequency acoustic emission signals; S3-2, for the selected grid width The voltage-time graph of the high-frequency acoustic emission signal is divided into sections with a width of [missing information]. The number of intersections between the acoustic emission signal waveform curve and the grid of equally spaced squares is obtained. ; S3-3, with grid width The X-axis represents the number of intersections between the acoustic emission signal waveform curve and the grid. Plot the Y-axis The curve is calculated, and an approximate straight line segment is fitted to the curve using the least squares method to obtain the slope K of the straight line segment. This slope K is denoted as the fractal dimension D of the high-frequency acoustic emission signal. i .

6. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 5, characterized in that, In step S3, the fractal dimension D of the high-frequency acoustic emission signal of each rock sample is calculated. i The process also includes the following steps to determine the axial stress value corresponding to the moment when the Kaiser effect occurs in each rock sample. : S3-4, the fractal dimension D i The minimum value D min The corresponding time is recorded as the moment when the Kaiser effect occurs; S3-5, based on the axial stress-time curves of the rock samples obtained from the indoor tests, obtain the axial stress value corresponding to the time when the Kaiser effect occurs for each rock sample. , where N is the number of rock samples.

7. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 1, characterized in that, Step S4 specifically includes the following steps: S41, using the six axial normal stress values ​​corresponding to the Kaiser effect points of six rock samples. The six stress component values ​​are calculated according to the following formula. , , , , and : In the formula, These are the cosine values ​​of the angles between the outer normal direction of the rock sample and the X, Y, and Z axes, respectively. S42, using the calculated six stress component values, three intermediate variables are calculated according to the following formula. , and : ； In the formula: ； S43, using the three intermediate variables obtained from the calculation , and The rock mass stress value at the sampling depth is calculated according to the following formula. , and : 。 8. The method for determining rock mass in-situ stress based on the Kaiser effect according to claim 7, characterized in that, In step S4, the rock mass in-situ stress value at the sampling depth is calculated. , and After that, The calculation of the inclination and azimuth of the principal stresses includes the following steps: S44, The rock mass in-situ stress value at the sampling depth is obtained by calculation. , and The cosine values ​​of the angles between the principal stress directions and the X, Y, and Z coordinate axes are calculated using the following formula. , and : In the formula, , i = 1, 2, 3; S45, calculate the inclination angle of the principal stress according to the following formula. , and and azimuth , and : In the formula, i = 1, 2, 3.

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