Rock in-situ static elastic modulus inversion method and anisotropic wave velocity testing device

Abstract

The invention provides a rock mass in-situ static elastic modulus inversion method and an anisotropic wave velocity testing device, and relates to the technical field of rock mass engineering, the method combines the convenience and high efficiency of a sound wave testing technology with the precision of a drilling elastic modulus testing technology, deeply excavates the connotation of data, and obtains the anisotropy wave velocity of the rock mass. According to the method, uncertainty and complex nonlinear correlation between two types of data are fully considered, a Gaussian process regression model is adopted for learning the data to obtain a prediction model, and full-hole interval inversion of the rock mass static elastic modulus under the complex geological condition can be achieved through the prediction model. The method can improve the accuracy and reliability of rock mass static elastic modulus testing, and has wide application prospects and important engineering value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rock mass engineering, in particular to a rock mass in-situ static elastic modulus inversion method and an anisotropic wave velocity testing device. BACKGROUND

[0002] The elastic modulus of rock mass plays a crucial role in rock mass engineering design and is a core parameter for evaluating the stability of rock mass. In particular, this mechanical index is particularly important in the stability analysis of dam foundation in hydropower engineering, the deformation prediction of tunnel surrounding rock, and the deformation evaluation of nuclear island foundation in nuclear power engineering.

[0003] Currently, the methods for measuring the elastic modulus of engineering rock mass can be mainly divided into two categories: dynamic method and static method.

[0004] The dynamic method focuses on analyzing the characteristics of seismic waves or sound waves propagating in the rock mass in the in-situ borehole, and then establishing the correlation between these wave parameters and the dynamic elastic modulus of the rock mass. The advantage of the dynamic method is that it can quickly measure in a large range, but the main shortcomings of this method are: first, the shear wave velocity in the wave parameter is difficult to measure, which limits the use of this method, and second, the measured is usually the dynamic elastic modulus, but the static elastic modulus of the rock mass is often needed for engineering design.

[0005] The static method can accurately measure the deformation of the rock mass under static load and obtain the key deformation parameter of the static elastic modulus of the rock mass by means of the principles and formulas of elasticity. The most representative method in the static method is the borehole elastic modulus test, but this test has the following defects: the high integrity requirement of the borehole wall, the limited displacement stroke of the displacement of the borehole modulus meter in the fracture zone, and other factors, which result in limited test points in the borehole and cannot be continuously and comprehensively observed.

[0006] Based on the defects of the dynamic method and the static method, it is not possible to accurately measure the static elastic modulus of the rock mass in the whole hole interval under complex geological conditions. SUMMARY

[0007] The present application aims to provide a rock mass in-situ static elastic modulus inversion method and an anisotropic wave velocity testing device to overcome the shortcomings of the prior art.

[0008] To achieve the above-mentioned purpose, the technical solutions adopted by the embodiments of the present application are as follows: In one aspect of the embodiments of the present application, a rock mass in-situ static elastic modulus inversion method is provided, which comprises: obtaining test data, the test data including the wave velocity values and static elastic modulus test values of multiple test points in the borehole; The wave velocity value and the static elastic modulus test value of a single test point are used as a sample, and samples corresponding to multiple test points are combined to form a sample set; A Gaussian process regression model is used to learn the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample in the sample set, and a prediction model is obtained, which is used to represent the relationship between the wave velocity measured value and the static elastic modulus predicted value of each prediction point in the borehole.

[0009] Optionally, the sample is a data pair composed of the position information, the wave velocity value and the static elastic modulus test value of a single test point.

[0010] Optionally, the Gaussian process regression model is used to learn the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample in the sample set, and the prediction model is obtained, which includes: Based on the mean function, a plurality of Gaussian process regression models are constructed by using different types of kernel functions. The samples in the sample set are divided into a training set and a validation set, the wave velocity value of the sample in the training set is used as the input value of the Gaussian process regression model, and the static elastic modulus test value is used as the output value of the Gaussian process regression model. Each Gaussian process regression model is trained using the training set to obtain a trained Gaussian process regression model. The validation set is used to evaluate the trained Gaussian process regression model by using the mean absolute error, the root mean square error, the mean absolute percentage error and / or the determination coefficient, and the trained Gaussian process regression model with the smallest error is used as the prediction model.

[0011] Optionally, the kernel function includes a square exponential kernel function, an exponential kernel function and a Matern kernel function.

[0012] Optionally, the method further includes: Obtaining the static elastic modulus test value of each test point obtained by the elastic modulus test of the borehole; Obtaining the wave velocity value of each test point obtained by the ultrasonic wave test.

[0013] Optionally, the borehole includes an orifice section and a body section which are sequentially connected along the depth direction, and the multiple test points are distributed in the orifice section and the body section, and the method of obtaining the test data includes: Obtaining image information of the orifice section; Dividing the orifice section into at least one interval section along the borehole axis direction; Obtaining the characteristic angle and the number of structural surfaces in each interval section according to the image information of the orifice section, the characteristic angle of the structural surface being the included angle between the structural surface and the borehole axis direction; Based on the empirical mapping relationship between the rock mass integrity coefficient and the number of structural surfaces, the average wave velocity in each interval section is obtained. The wave velocity test is performed on the core at the position of the hole mouth section to obtain a first average directional influence factor of each interval section; According to the distribution relationship between the test points and the interval sections, the first average directional influence factor, and the average wave velocity in each interval section, a wave velocity value of each test point in the hole mouth section is obtained; A wave velocity value of each test point in the hole body section obtained through the ultrasonic test; A static elastic modulus test value of each test point in the hole mouth section and the hole body section obtained through the drilling elastic modulus test.

[0014] Optionally, the wave velocity test is performed on the core at the position of the hole mouth section to obtain a first average directional influence factor of each interval section includes: The wave velocity test is performed on the core at the position of the hole mouth section to obtain a wave velocity test value corresponding to each structural plane in the hole mouth section; Based on the maximum wave velocity and the wave velocity test value corresponding to each structural plane, a directional influence factor of each structural plane is obtained, the maximum wave velocity being a wave velocity obtained when the strike direction of the structural plane is parallel to the direction of the test wave incident on the core; An average value of the directional influence factors of the structural planes in the interval section is taken as the first average directional influence factor of the interval section.

[0015] Optionally, according to the distribution relationship between the test points and the interval sections, the first average directional influence factor, and the average wave velocity in each interval section, a wave velocity value of each test point in the hole mouth section is obtained includes: According to the characteristic angle of the structural plane, a number of structural planes in the direction where each test point is located is determined; According to the number of structural planes in the direction where each test point is located and the directional influence factor of each structural plane in the direction, a second average directional influence factor of the direction where each test point is located is obtained; According to the maximum wave velocity and the second average directional influence factor of the direction where each test point is located, a wave velocity value of each test point is obtained.

[0016] Optionally, in the plurality of test points, at least part of the test points are located in different directions and depths.

[0017] Optionally, the method further includes: At a preset depth interval, a wave velocity measured value of each predicted point of the drilling hole is obtained; Based on the prediction model, an elastic modulus field of the drilling hole is obtained.

[0018] In another aspect of the embodiments of the present application, an anisotropic wave velocity testing device is provided, which is applied to any one of the rock mass in-situ static elastic modulus inversion methods, and is used for testing wave velocity values of at least part of test points in a borehole. The anisotropic wave velocity testing device comprises a probe head, a gas charging and discharging device, and a processor. The probe head comprises: a base; a probe rod fixed to the base and provided with a sound wave emitter, a first sound wave receiver and a second sound wave receiver in the axial direction of the probe rod; a plurality of gas charging rods fixed to the base, the plurality of gas charging rods being arranged in parallel with the probe rod and surrounding the probe rod; a plurality of air bags, each of the plurality of gas charging rods being wrapped with an air bag, and the gas charging rod being in communication with the air bag, the air bag being in contact with the inner wall of the borehole and the probe rod after being inflated; the gas charging and discharging device and the plurality of gas charging rods being connected through independent gas paths, and the gas charging and discharging device being used for independently controlling inflation and deflation of each air bag; the processor being electrically connected with the sound wave emitter, the first sound wave receiver and the second sound wave receiver.

[0019] Optionally, a plurality of air flow holes are formed on the gas charging rod, and the plurality of air flow holes are arranged in sequence along the length direction of the gas charging rod.

[0020] Optionally, the adjacent air bags are arranged in close contact after being inflated.

[0021] The present application has the following beneficial effects: The present application provides a rock mass in-situ static elastic modulus inversion method, which comprises: obtaining test data, the test data comprising wave velocity values and static elastic modulus test values of a plurality of test points in a borehole; forming samples with the wave velocity values and the static elastic modulus test values of a single test point, and combining the samples corresponding to the plurality of test points to form a sample set; learning the mapping relationship between the wave velocity values and the static elastic modulus test values of the same sample in the sample set by using a Gaussian process regression model to obtain a prediction model, the prediction model being used for representing the relationship between the wave velocity measured values and the static elastic modulus predicted values of each prediction point in the borehole. The present application combines the convenience and efficiency of the sound wave testing technology with the accuracy of the borehole elastic modulus testing technology, deeply mines the connotation of the data, fully considers the uncertainty and complex nonlinear correlation between the two types of data, learns the prediction model by using the Gaussian process regression model, and realizes the full-hole interval inversion of the rock mass static elastic modulus under complex geological conditions by using the prediction model. The method can improve the accuracy and reliability of the rock mass static elastic modulus test, and has wide application prospect and important engineering value.

[0022] The application provides an anisotropic wave velocity testing device which can realize wave velocity test in any selected direction by controlling inflation of a proper number of air bags to form smooth sound wave propagation in the selected direction and sound wave insulation in the non-selected direction, so that the obtained wave velocity is directional, and can be especially applied to analysis of anisotropy of rock mass. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed to be used in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some of the embodiments of the application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0024] Figure 1 A flow chart of a rock mass in-situ static elastic modulus inversion method provided by the embodiments of the application; Figure 2 A structural schematic diagram of a borehole and a receiving hole in a rock mass provided by the embodiments of the application; Figure 3 A variation trend schematic diagram of a longitudinal wave velocity, a static elastic modulus test value and a static elastic modulus prediction value provided by the embodiments of the application; Figure 4 A schematic diagram of a static elastic modulus prediction value range in a 95% confidence interval; Figure 5 A schematic diagram of a static elastic modulus prediction value range in an 80% confidence interval; Figure 6 A structural schematic diagram of an anisotropic wave velocity testing device provided by the embodiments of the application; Figure 7 A schematic diagram of a state of an air bag before inflation in a detection head provided by the embodiments of the application; Figure 8 A schematic diagram of a state of an air bag after inflation in a detection head provided by the embodiments of the application; Figure 9 A radial cross-sectional schematic diagram of a detection head provided by the embodiments of the application; Figure 10 A schematic diagram of a rock core provided by the embodiments of the application.

[0025] Icons: 110-drill hole; 111-test point; 113-core; 114-coupling medium; 120-receiving hole; 200-anisotropic wave velocity testing device; 210-inflating and deflating device; 220-processor; 230-detection rod; 231-acoustic wave transmitter; 232-first acoustic wave receiver; 233-second acoustic wave receiver; 240-inflating rod; 241-airflow hole; 250-air bag. DETAILED DESCRIPTION

[0026] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the description is only part of the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can be modified and varied in various ways. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0027] In one aspect of the embodiment of the present application, a method for in-situ static elastic modulus inversion of rock mass is provided, such as Figure 1 As shown, the method includes: S10: Acquire test data, where the test data includes wave velocity values ​​and static elastic modulus test values ​​at multiple test points in the borehole.

[0028] S20: The wave velocity value and the static elastic modulus test value of a single test point are used to form a sample, and the samples corresponding to multiple test points are combined to form a sample set.

[0029] S30: A Gaussian process regression model is used to learn the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample in the sample set to obtain a prediction model. The prediction model is used to characterize the relationship between the wave velocity measured value and the static elastic modulus predicted value of each prediction point in the borehole.

[0030] like Figure 2 As shown, a borehole 110 is opened at a selected location in the rock mass, and multiple test points 111 are planned within borehole 110. Then, a wave velocity value and a static elastic modulus test value are obtained for each test point 111 through testing. All of the obtained wave velocity values ​​and static elastic modulus test values ​​are used as convenient test data. This test data is derived from actual rock mass measurements and can therefore more accurately reflect the actual state of the rock mass.

[0031] Although the test points 111 are relatively limited and difficult to be continuous, the static elastic modulus test value of each test point 111 is relatively accurate. Considering that the longitudinal wave velocity in the borehole 110 is easier to measure than the shear wave velocity, the velocity value can be the longitudinal wave velocity value.

[0032] After the test data is obtained through S10, the test data needs to be analyzed and processed, and the purpose is to construct a sample set. Among them, the wave velocity value and the static elastic modulus test value of a single test point 111 form a single sample, so that multiple test points 111 can form multiple samples, and the collection of multiple samples is used as a sample set.

[0033] After the sample set is constructed through S20, the Gaussian process regression model is used to learn the samples contained in the sample set. Specifically, the Gaussian process regression model learns the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample, thereby obtaining a prediction model. In this way, the prediction model can establish the corresponding relationship between the wave velocity and the static elastic modulus based on the test data of the limited test points 111, and realize the full-hole interval inversion of the elastic modulus in the rock mass in-situ borehole 110 under complex geological conditions. For example, when the static elastic modulus prediction value of any point (prediction point) in the borehole 110 needs to be predicted, the wave velocity measured value (such as the longitudinal wave velocity) of the point can be first measured, and then input into the prediction model, so that the static elastic modulus prediction value of the point can be output from the prediction model. In other words, the prediction model can represent the relationship between the wave velocity measured value and the static elastic modulus prediction value of each prediction point in the borehole 110.

[0034] Since the wave velocity measured value can be obtained in a convenient and efficient manner based on acoustic wave testing technology, the static elastic modulus corresponding to each point in the borehole 110 can be quickly, efficiently and accurately predicted by means of the prediction model of the present application. This method can improve the accuracy and reliability of rock mass static elastic modulus testing, and has wide application prospect and important engineering value.

[0035] In addition, it should be understood that the wave velocity value of the test point 111 can reflect the dynamic elastic modulus of the test point 111, and therefore, when the Gaussian regression process model is learned, the dynamic elastic modulus reflected by the wave velocity value can be mapped to the static elastic modulus test value.

[0036] Optionally, when the test points 111 are arranged in the borehole 110, at least a part of the test points 111 can be arranged along the depth direction of the borehole 110, that is, the multiple test points 111 at least include test points 111 with different depths. In this way, the test data contains information about the distribution of wave velocity values and static elastic modulus test values along the depth direction of the borehole 110, and when the Gaussian process regression model is used to learn the mapping relationship in the sample set, the information can also be learned together, thereby improving the accuracy when the elastic modulus in the rock mass in-situ borehole 110 is inversed in the full-hole interval.

[0037] During the formation and evolution of rock mass, it is affected by various geological processes, and structural planes such as bedding, schistosity, interlayer and directional fracture system are formed. The existence of these structural planes leads to significant differences in the physical and mechanical properties of rock mass in different directions, that is, anisotropy. This anisotropy has an important influence on the engineering properties and application of rock mass.

[0038] When considering the anisotropy of rock mass, test points 111 with different directions need to be arranged, such as test points 111 with different horizontal directions at the same depth. Specifically, when setting test points 111, the directions and depths of at least some of the test points 111 in the plurality of test points 111 are different, such as Figure 2 In the figure, six test points 111 are shown, of which three test points 111 on the left inner wall are distributed at intervals along the depth direction of the borehole 110, and three test points 111 on the right inner wall are the same. On this basis, the directions of the test points 111 on the left and right are different. Of course, there can be cases where the depths of some test points 111 are the same. It should be understood that the direction of the test point 111 can be understood as the direction of the line from the center axis of the borehole 110 to the test point 111.

[0039] In this way, test data in different directions can be obtained, and based on this, when learning the mapping relationship in the sample set using the Gaussian process regression model, test data in different directions can also be learned, so that the prediction model can perform full-hole interval inversion of the static elastic modulus of rock mass under anisotropic complex geological conditions.

[0040] Of course, when the isotropy of rock mass needs to be considered, the directionality of the test points 111 can be ignored, and the depth can be considered, or the average wave speed value and average static elastic modulus test value corresponding to the depth can be obtained by averaging the wave speed values and static elastic modulus test values of the test points 111 with the same depth but different directions.

[0041] Optionally, the method further comprises: S40: Obtain the static elastic modulus test value of each test point 111 obtained by the elastic modulus test of the borehole 110.

[0042] S50: Obtain the wave speed value of each test point 111 obtained by the ultrasonic test.

[0043] When performing the elastic modulus test of the borehole 110, the following steps can be performed: Step (1): Before the test, the actual situation of the exploration core 113 should be checked to determine the condition of the inner wall of the borehole 110. When the conditions are not met, borehole camera can be used to select the complete section of the borehole 110 inner wall to carry out the elastic modulus test of the borehole 110. The test instrument can use a rigid elastic modulus meter.

[0044] Step (2): Calculate the static elastic modulus value of the rock mass at the test point 111 according to the following formula: wherein, is the static elastic modulus, is the three-dimensional correction coefficient (related to the length-diameter ratio of the elastic modulus meter), is the pressure correction coefficient (related to the elastic modulus meter), is the diameter of the borehole 110, is the pressure increment, is the deformation increment, is the coefficient related to the width of the pressure plate (the corresponding circumferential angle when the pressure plate contacts the hole wall) and the Poisson's ratio of the rock mass, such as .

[0045] Step (3): For anisotropic rock mass, adjust the direction of the pressure plate of the elastic modulus meter to test the static elastic modulus in the set direction (i.e. selected direction).

[0046] When performing ultrasonic test, the following steps can be followed: Continue to refer to Figure 2 Drill a plurality of side holes around the borehole 110, with the borehole 110 as the transmitting hole and the side holes as the receiving holes 120.

[0047] Step (1): Use clean water as the coupling medium when testing in the borehole 110, and ensure full water coupling in the testing section of the hole.

[0048] Step (2): Use the push-pull rod to push the transducers to the test point 111 of the transmitting hole and the receiving hole 120 respectively, and ensure that the transmitting and receiving transducers have the same depth in the borehole 110 (the depth refers to the vertical depth from the borehole 110 mouth).

[0049] Step (3): Usually move the transmitting transducer and the receiving transducer from the bottom of the hole to the mouth of the hole continuously, and move the transmitting transducer and the receiving transducer at the same time, collect data and save waveform data.

[0050] Step (4): Check the depth of the test point once every 10 test points for the transmitting transducer and the receiving transducer.

[0051] Step (5): For anisotropic rock mass, adjust the positional relationship between the transmitting hole and the different receiving holes 120 to realize wave velocity test in different directions.

[0052] In the ultrasonic test, the anisotropic wave speed testing device 200 shown in the subsequent embodiment can also be used, so that the sound wave test can be directly performed in the original hole of the borehole 110 first, without the need to open a side hole. It should be understood that the opening of the side hole requires relatively high requirements, such as the need to maintain a high-precision parallel relationship with the transmission hole, and therefore, the use of the anisotropic wave speed testing device 200 can effectively simplify the difficulty of wave speed acquisition and improve the accuracy of data. The specific test process is as follows: First, the anisotropic wave speed testing device 200 is introduced: The present application provides an anisotropic wave speed testing device 200, which can realize in-situ anisotropic wave speed measurement in a single hole. Of course, it can be applied to the rock mass in-situ static elastic modulus inversion method described above, and can also be applied to other scenes, and the present application does not limit it. The anisotropic wave speed testing device 200 can test the wave speed value of at least part of the test points 111 in the borehole 110.

[0053] As shown in Figure 6 , the anisotropic wave speed testing device 200 comprises a detection head, a gas charging and discharging device 210 and a processor 220.

[0054] As shown in Figures 7 to 9 , the detection head comprises a base and a detection rod 230 fixed to the base, a plurality of gas charging rods 240 Figure 7 and Figure 8 each showing two, Figure 9 four are shown) and a plurality of air bags 250 Figure 7 and Figure 8 each showing two, Figure 9 four are shown). Among them, the sound wave transmitter 231, the first sound wave receiver 232 and the second sound wave receiver 233 are arranged at intervals along the axis direction of the detection rod 230, the sound wave transmitter 231 can emit test sound waves, which are then received by the first sound wave receiver 232 and the second sound wave receiver 233. A plurality of gas charging rods 240 are arranged in parallel with the detection rod 230, and a plurality of gas charging rods 240 are arranged around the detection rod 230, such as Figure 9 four gas charging rods 240 are arranged around the detection rod 230, which are arranged around the detection rod 230 as the center, and the distance from each gas charging rod 240 to the detection rod 230 can be the same. Each gas charging rod 240 is wrapped with an air bag 250, and the gas charging rod 240 is in communication with the air bag 250, so as to facilitate the inflation and deflation of the air bag 250 by means of the gas charging rod 240. It should be understood that the more the number of surrounding gas charging rods 240 and air bags 250, the more directions can be measured.

[0055] The processor 220 is electrically connected with the sound wave transmitter 231, the first sound wave receiver 232 and the second sound wave receiver 233, such as Figure 6The processor 220 can control the sound wave emitter 231 to emit a test sound wave at the right time, and record the time when the first sound wave receiver 232 and the second sound wave receiver 233 respectively receive the test sound wave. In addition to the time, the waveform of the test sound wave can also be presented, and so on.

[0056] As shown in Figure 6 , the inflation and deflation device 210 and the plurality of inflation rods 240 are respectively connected through independent air paths. The inflation and deflation device 210 can independently control the inflation and deflation of each air bag 250, that is, the inflation and deflation device 210 can control the inflation or deflation of any air bag 250, and the control of different air bags 250 does not interfere with each other. For example, the inflation and deflation device 210 can simultaneously control the inflation of any number of air bags 250 and the non-inflation of any number of air bags 250. In order to achieve the above-mentioned independent control, control valves can be added in different air paths. The control valves can be manually or electrically opened and closed, and the control valves can be electrically connected with the processor 220 to realize electric control. The inflation and deflation device 210 can be a gas source containing a pump body. It can inject external gas into the corresponding air bag 250 through the independent air path and the inflation rod 240, so that the air bag 250 expands. It can also reversely extract the gas in the air bag 250, so that the air bag 250 shrinks.

[0057] It should be understood that, as shown in Figure 7 , the air bag 250 is in a state before inflation. At this time, the air bag 250 is in a deflated state. As shown in Figure 8 , the inflated and expanded air bag 250 can be in contact with the inner wall surface of the borehole 110 and the detection rod 230, respectively, to ensure that the inflated air bag 250 expels the coupling medium in the direction where it is located, so as to realize the sound wave isolation in the direction. After the test is completed, the inflated air bag 250 can be deflated, so that the air bag 250 shrinks. The deflated air bag 250 can be tightly attached to the inflation rod 240, reducing its impact, and also facilitating the movement of the detection head.

[0058] Optionally, as shown in Figure 7 or Figure 8 , a plurality of air flow holes 241 are formed on the inflation rod 240. The plurality of air flow holes 241 are arranged in sequence along the length direction of the inflation rod 240, which can improve the efficiency of inflation and deflation.

[0059] Optionally, as shown in Figure 9 , the adjacent air bags 250 are arranged in close contact after inflation. In this way, the inflated air bags 250 can fully expel the coupling medium 114 between them. For example, there is no coupling medium 114 between the adjacent inflated air bags 250.

[0060] Optionally, asFigure 7 As shown, the air bag 250 before inflation can present a wavy shape, which can improve its deformation ability.

[0061] Optionally, the air bag 250 can be made of wear-resistant material to improve its service life.

[0062] Next, the process of measuring wave velocity by the sound wave testing device is described: (1) A coupling medium, such as clear water, is arranged in the borehole 110. It should be ensured that the full water coupling is achieved.

[0063] (2) The probe head is placed at the test point 111 in the borehole 110. Before being placed, all the air bags 250 are not inflated.

[0064] (3) The inflation and deflation device 210 controls the inflation of the air bags 250 except the air bag 250 at the test point 111. For example, Figure 9 For the left test point 111, the inflation and deflation device 210 can control the inflation of the three air bags 250 on the upper, lower and left sides, while ensuring that the air bag 250 on the right side is not inflated.

[0065] (4) The processor 220 controls the sound wave transmitter 231 to emit sound waves, and records the time when the first sound wave receiver 232 and the second sound wave receiver 233 respectively receive the test sound waves. With the distance between the two receivers and the time difference of receiving the test sound waves, the wave velocity can be obtained. For example, Figure 9 As shown, the wave velocity value of the test point 111 can be measured.

[0066] Similarly, the wave velocity values of all the test points 111 can be tested. It should be understood that when a test point 111 is tested, the inflation and deflation device 210 should control all the air bags 250 to be deflated, and then the probe head position is moved or the test direction is changed, and the next test point 111 is tested.

[0067] Optionally, the sample is a data pair composed of the position information of a single test point 111, the wave velocity value and the static elastic modulus test value. Specifically, the sample of each test point 111 is written as a data pair structure, for example, (position information, wave velocity value, static elastic modulus), wherein the position information can be the depth of the test point 111 and the direction in which it is located. The direction in which it is located can be a direction intersecting the central axis of the borehole, such as a horizontal direction. The "depth" represents the vertical depth of the test point 111 from the mouth of the borehole 110. The "direction in which the test point 111 is located" is used to accurately identify the direction or relative position angle of the anisotropic characteristics, so as to ensure that the characteristics of different directions can be accurately distinguished during data analysis.

[0068] In some optional embodiments, the data in the data set with large magnitude difference of physical quantities (such as the depth in Table 1 is a single digit, but the wave velocity value reaches ten thousand) is subjected to 0-1 standardization processing, or the data is converted into a standard normal distribution with a mean of 0 and a variance of 1.

[0069] The Gaussian process regression process model can well solve the complex regression problems such as high dimension, small sample and high nonlinearity in the data, and has strong generalization ability.

[0070] When constructing the Gaussian process regression model, it can be constructed based on the mean function and the kernel function. Specifically, the static modulus in the borehole 110 is defined as a set of random variables E s , and it is assumed to obey a joint Gaussian distribution, the relationship between the position information and the wave velocity value in the data pair and E s f(x) The relationship between the position information and the wave velocity value in the data pair and

[0071] The Gaussian process is: .

[0072] where the mean function represents the trend of the design space, and the kernel function captures the smoothness of the response. The kernel function specifies the covariance between pairs of random variables: where . In other words, the covariance function determines the similarity between data points and .

[0073] Different types of covariance functions (kernel functions) and their mathematical forms are summarized as follows: (1) Squared Exponential Kernel (Squared Exponential Kernel): also known as Radial Basis Function (RBF) kernel, the formula is where and are input data points, is the distance between two points, l is the length scale parameter, which controls the smoothness of the function and the range of correlation, l the larger the function, the smoother the data points, and the correlation between the data points still exists at a larger distance.

[0074] ​​​​​(2) Exponential Kernel: It is the Matern kernel function. v =0.5, the formula is .here and The same input data points, is the distance between two points, l It is a parameter that controls the decay rate of correlation. Compared with the square exponential kernel function, it captures lower correlation and is suitable for situations where data changes do not need to be too smooth and may have mutations.

[0075] (3) Matern kernel function: It is a generalized form of RBF kernel, which provides more flexible control over smoothness. The formula is .in and is the input data point, Indicates distance, l is the length scale parameter, v is a parameter that controls the smoothness, is the gamma function, is a modified Bessel function. Commonly used ones are Matern32 and Matern52: Matern32 kernel function: when v =1.5, the formula can be written as: It should be understood that the corresponding function has a certain smoothness and allows for faster changes than the square exponential kernel function; Matern52 kernel function: when v =2.5, the formula is: It is smoother than Matern32 and is suitable for scenes that require higher smoothness.

[0076] After constructing the Gaussian process regression model, the wave velocity values ​​of the samples in the sample set can be used as the input values ​​of the Gaussian process regression model, and the static elastic modulus test values ​​can be used as the output values ​​of the Gaussian process regression model. The constructed Gaussian process regression model is then trained to obtain a prediction model.

[0077] It should be understood that one or more covariance functions (kernel functions) can be used to construct a Gaussian process regression model. The following will be explained using the construction of multiple Gaussian process regression models as an example: S31: Based on the mean function, different types of kernel functions are used to construct multiple Gaussian process regression models.

[0078] Different types of kernel functions include a squared exponential kernel function, an exponential kernel function, and a Matern kernel function, wherein the Matern kernel function can include Matern32 and Matern52.

[0079] The plurality of Gaussian process regression models constructed can be continuously trained by subsequent steps, and the model with the minimum error is selected from the plurality of Gaussian process regression models by cross-validation.

[0080] After the Gaussian process regression model is established, the performance of the model is evaluated by cross-validation. The basic idea of cross-validation is to divide the data set into multiple subsets (folds), and then train and validate the model multiple times.

[0081] S32: Divide the samples in the sample set into a training set and a validation set, wherein the wave velocity values of the samples in the training set are input values of the Gaussian process regression model, and the static elastic modulus test values are output values of the Gaussian process regression model.

[0082] The samples in the sample set can be used to train the Gaussian process regression model and to evaluate the trained Gaussian process regression model. Specifically, the cross-validation method can be used for verification, wherein the cross-validation method includes: (1) K-fold cross-validation: divide the sample set into K subsets, use K-1 subsets for training each time, and use the remaining 1 subset for validation. This process is repeated K times, and the final performance evaluation is the average of the K validation results.

[0083] (2) Leave-one-out cross-validation: leave only one sample as the validation set each time, and use the remaining samples as the training set. This method is suitable for small data sets.

[0084] S33: Train each Gaussian process regression model using the training set to obtain a trained Gaussian process regression model.

[0085] The samples in the training set can be used to train each Gaussian process regression model constructed. During training, the wave velocity values of the samples in the training set are used as input values of the Gaussian process regression model, and the static elastic modulus test values are used as output values of the Gaussian process regression model, so as to train the Gaussian process regression model to map the wave velocity values in the same sample to the static elastic modulus test values, thereby learning the mapping relationship. In this way, a plurality of trained Gaussian process regression models can be obtained.

[0086] S34: Use the validation set and evaluate the trained Gaussian process regression model using the mean absolute error, the root mean square error, the mean absolute percentage error, and / or the determination coefficient. The trained Gaussian process regression model with the minimum error is used as the prediction model.

[0087] The samples in the verification set can be used to evaluate each trained Gaussian process regression model. During evaluation, the wave velocity values of the samples in the verification set are taken as input values of the trained Gaussian process regression model, and then a static elastic modulus value can be output by the trained Gaussian process regression model. By comparing the output static elastic modulus value with the static elastic modulus test value of the sample in the verification set, the error value of the trained Gaussian process regression model can be obtained.

[0088] During the evaluation process, the mean absolute error, root mean square error, mean absolute percentage error, and / or determination coefficient can be used to evaluate the trained Gaussian process regression model, wherein the smaller the mean absolute error, root mean square error, and mean absolute percentage error, the better, and the larger the determination coefficient, the better.

[0089] From the plurality of trained Gaussian process regression models, the trained Gaussian process regression model with the smallest error is selected as the prediction model.

[0090] Based on the prediction model, the wave velocity measured value of the prediction point, together with its depth and horizontal direction angle, can be taken as variables to invert the static elastic modulus prediction value of the prediction point. The confidence interval for the inverted static elastic modulus prediction value is calculated to show the uncertainty of the model. The confidence interval and the prediction interval are calculated to show the possible range predicted by the prediction model under a given input.

[0091] The borehole 110 includes an orifice section and a body section that are sequentially connected in the depth direction, and a plurality of test points 111 are distributed in the orifice section and the body section. When obtaining the test data, considering that the orifice section of the rock mass borehole 110 has a blind area, it is usually difficult to directly obtain the effective wave velocity value of this section. The reasons are as follows: (1) due to the size limitation of the instrument, when the orifice section of the test hole is smaller than the test distance (the distance between the transmitting end and the receiving end), the transducer cannot complete the transmitting and receiving work; (2) affected by factors such as blasting excavation and stress relaxation, the degree of fragmentation of the orifice section is usually greater than that of other sections (body section) in the hole depth, which often leads to rapid loss of coupling medium during acoustic testing of the orifice section, resulting in distortion of the acoustic data of the orifice section. Based on this, the wave velocity values of the orifice section and the body section are obtained by the following methods: The wave velocity value of the orifice section is obtained (this method can be applied to the rock mass in-situ static elastic modulus inversion method, and can also be used alone to obtain the wave velocity value of the orifice section, so it should not be limited): S11: Obtain image information of the orifice section.

[0092] The orifice section is photographed by using the camera technology of the borehole 110, so as to obtain the image information.

[0093] S12: Divide the orifice section into at least one interval section along the borehole axis direction.

[0094] As needed, the borehole section may be divided into at least one interval section along the axial direction of the borehole 110 (ie, the depth direction of the borehole 110 ).

[0095] S13: Obtaining characteristic angles and the number of structural surfaces in each interval according to the image information of the borehole segment. The characteristic angle of the structural surface is the angle between the structural surface and the borehole axis direction.

[0096] By image information recognition (grayscale and enhance the image, then extract the outline of the structural surface through threshold segmentation, edge detection and morphological processing techniques. The characteristics of the broken rock mass, open joints and closed joints on the inner wall of the borehole 110 are distinguished. In this way, the joint density and crack distribution information on the continuous aperture can be obtained) the structural surface distribution on the inner wall of the borehole 110 is obtained, and the number of structural surfaces of the rock mass in each interval segment is counted. Jv And the characteristic angle of each structural surface, the characteristic angle of the structural surface is the angle between the structural surface and the axial direction of the drill hole 110.

[0097] S14: Based on the empirical mapping relationship between the rock mass integrity coefficient and the number of structural surfaces, the average wave velocity in each interval segment is obtained.

[0098] Rock mass integrity coefficient Kv Number of structural noodles Jv Refer to Table 1 for the empirical mapping relationship: Table 1 The average wave velocity in each interval is obtained according to the following formula: Where, is the average wave velocity in the interval, is the wave velocity of intact rock (which can be predicted).

[0099] S15: Conduct a wave velocity test on the core at the orifice section to obtain the first average directional influence factor of each interval segment.

[0100] In order to facilitate anisotropy testing, that is, to obtain wave velocity values ​​in different directions, the first average direction influence factor can be introduced. Considering that the characteristic angles of the structural surface are different (that is, the directions are different), the degree of influence on the wave velocity is different, so the first average direction influence factor is introduced to represent this degree of influence.

[0101] S16: deriving the wave velocity value of each test point in the orifice section according to the distribution relationship between the test points and the interval segments, the first average directional influence factor, and the average wave velocity in each interval segment.

[0102] By dividing the intervals described above, it is possible to determine which interval each test point 111 within the orifice section falls within. The wave velocity value of each test point 111 within the orifice section is obtained by combining the direction of each test point 111, the first average directional influence factor, and the average wave velocity within each interval.

[0103] It should be understood that the above methods S11 to S16 can also be used to measure the wave velocity of the full hole depth of the borehole 110. When understanding, it is only necessary to replace the hole mouth section with the full hole depth. The replaced scheme should be able to be used independently for wave velocity measurement.

[0104] S17: The wave velocity values ​​at each test point in the borehole obtained through ultrasonic testing.

[0105] The ultrasonic test may be the aforementioned scheme using the transmitting hole and the receiving hole 120, or an in-situ single hole scheme (using an acoustic wave testing device).

[0106] S18: Static elastic modulus test values ​​of each test point in the borehole mouth section and the borehole body section obtained through the drilling elastic modulus test.

[0107] Optionally, a wave velocity test is performed on the core 113 at the orifice section to obtain the first average directional influence factor of each interval segment, including: S151: Conduct a wave velocity test on the core at the orifice section to obtain the wave velocity test values ​​corresponding to each structural surface in the orifice section.

[0108] The core 113 taken from the hole section is originally continuous with the inner wall of the hole section, so it can be used for corresponding analysis: Figure 10 As shown, a wave velocity test is performed on the taken out core 113 (generally cylindrical or quasi-cylindrical), wherein the direction of the test wave incident on the core 113 (i.e. Figure 10 The test direction in the figure) is along the axis of the core 113 (that is, the axis of the borehole 110). In addition, the angle between the strike direction of the structural surface and the direction in which the test wave enters the core 113 is defined as: , when the structural surface strike direction is parallel to the direction of the test wave incident on the core 113, =0°. Through the test, the wave velocity test value corresponding to each structural surface can be obtained.

[0109] S152: Based on the maximum wave velocity and the wave velocity test value corresponding to each structural surface, the direction influence factor of each structural surface is obtained. The maximum wave velocity is the wave velocity obtained when the strike direction of the structural surface is parallel to the direction of the test wave incident on the rock core.

[0110] The maximum wave velocity is the wave velocity obtained when the strike direction of the structural plane is parallel to the direction of the test wave incident on the core 113, which can be obtained through a wave velocity test. Then, the directional influence factor of each structural plane is calculated based on the following formula: In the formula, is the directional influence factor of the structural plane constituting the angle , and is the P-wave velocity in the wave velocity test through the structural plane constituting the angle , and is the maximum wave velocity.

[0111] S153: Take the average value of the directional influence factors of the structural planes in the interval segment as the first average directional influence factor in the interval segment.

[0112] Calculate the directional influence factors of all structural planes in each interval segment, and calculate the first average directional influence factor in each interval segment, and the calculation formula is as follows: In the formula, is the first average directional influence factor of the i-th interval segment, is the directional influence factor of the m-th structural plane in the i-th segment, is the number of structural planes in the i-th interval segment.

[0113] Optionally, according to the distribution relationship between the test points 111 and the interval segments, the first average directional influence factor, and the average wave velocity in each interval segment, the wave velocity values of each test point 111 in the borehole segment are obtained, including: S161: According to the characteristic angle of the structural plane, determine the number of structural plane strips in the direction of each test point in the borehole segment.

[0114] As described above, the characteristic angle of each structural plane corresponds to the direction thereof, that is, the angle defined above. Since each test point 111 is in a direction, the number of structural plane strips in the direction of each test point 111 can be determined.

[0115] S162: According to the number of structural plane strips in the direction of each test point and the directional influence factor of each structural plane in the direction, obtain the second average directional influence factor of the direction of each test point 111.

[0116] If a test point 111 is in a direction with one structural plane, the directional influence factor corresponding thereto is directly taken as the second average directional influence factor of the direction of the test point 111.

[0117] According to the average wave velocity a mapping relationship with the first average direction influence factor of the first interval, i.e. the direction of the test point 111, is calculated according to the following formula: In the formula, is the second average direction influence factor of the first direction of the ith interval segment, is the direction influence factor of the mth structural surface of the first direction of the ith segment, is the number of structural surfaces of the first direction of the ith interval segment.

[0118] S163: Obtain the wave velocity value of each test point according to the maximum wave velocity and the second average direction influence factor of the direction of each test point.

[0119] The wave velocity value of the first direction of the ith interval segment is calculated according to the following formula : It should be understood that when the first direction of the ith interval segment has no structural surface, the wave velocity of the direction is .

[0120] This method makes up for the missing wave velocity data caused by the measurement blind area of the traditional single-hole ultrasonic detection in the hole segment, ensuring the continuity and integrity of the P-wave velocity profile. Compared with the prior art, the present method has strong applicability, can be used with existing ultrasonic logging devices, and uses simple statistical and empirical models to estimate the wave velocity of the hole segment (near-hole segment), realizes the complete reconstruction of the near-hole segment ultrasonic wave velocity data, and fills the gap in the prior art.

[0121] For a better understanding of the technical solutions of the present application, the following will be explained in the form of specific examples: Obtain the test data of a plurality of test points 111 through the elastic modulus test and ultrasonic detection test of the drill hole 110, as shown in the following Table 1.

[0122] Table 1 Drill hole test data Process the above data to form the data pair: [depth, horizontal direction angle, wave velocity value, static elastic modulus test value].

[0123] Since the horizontal direction angle is 0°, the data pairs can be simplified as: [0.6, 2985, 5.2], [0.8, 3077, 5.2], [1.8, 2939, 6.8], [2.0, 3202, 6.8], [2.6, 5602, 15.4], [2.8, 4690, 15.4], [3.4, 4919, 15.9], [3.6, 4802, 15.9], [4.8, 4690, 12.8], [5.0, 4802, 12.8], [5.4, 5042, 17.5], [5.6, 4834, 17.5].

[0124] Each data pair corresponds to a test point 111 and is taken as a sample to form a sample set.

[0125] Four Gaussian process regression models are constructed by using the squared exponential kernel function, the exponential kernel function, the Matern32 kernel function and the Matern52 kernel function respectively with the mean function. The leave-one-out cross-validation method is used, that is, 11 samples in the above-mentioned 12 samples are taken as a training set, and the four Gaussian process regression models are trained respectively to obtain four trained Gaussian process regression models. Then, the remaining one sample is used as a validation set to validate and evaluate the four trained Gaussian process regression models, and the mean absolute error, the root mean square error and the mean absolute percentage error are used as evaluation indexes. The results are as follows: In this example, the exponential kernel function is selected as the prediction model.

[0126] The test point 111 in the foregoing Table 1 is taken as a prediction point, and the depth, the horizontal direction angle and the wave velocity value are input into the prediction model to inversely calculate the static elastic modulus prediction value of the prediction point. The inversion results are shown in Table 2 as follows: Table 2 Inverted static elastic modulus prediction value Figure 3 The static elastic modulus test value and the static elastic modulus prediction value are shown in Table 1. It can be seen that the static elastic modulus prediction value reflects the dynamic change trend of the static elastic modulus test value of the borehole 110 and the longitudinal wave velocity (wave velocity measured value). Thus, the elastic modulus field can be quickly inverted according to the limited static elastic modulus test value and the wave velocity test of the whole hole section.

[0127] In order to provide a range estimation for the prediction results obtained based on the sample set, the uncertainty of the static elastic modulus prediction value is reflected. Figure 4The 95% confidence interval static modulus of elasticity prediction value range is shown, which is calculated based on the distribution and standard deviation of the sample mean. Figure 5 The static modulus of elasticity value range in which the 80% confidence interval static modulus of elasticity prediction value can fall is shown, which not only considers the uncertainty of the estimated parameters, but also considers the random fluctuations of the data itself, i.e. the variability of the prediction value itself.

[0128] The above describes the basic principles of the present application in combination with specific embodiments, but it should be noted that the advantages, advantages, effects, etc. mentioned in the present application are only examples and not limitations, and these advantages, advantages, effects, etc. cannot be considered as necessary for each embodiment of the present application. In addition, the above specific details disclosed are only for the purpose of example and understanding, and are not limited to the above specific details. The above specific details do not limit the present application to be necessarily implemented with the above specific details.

[0129] The block diagrams of the devices, apparatuses, equipment, systems involved in the present application are only illustrative examples and are not intended to require or imply the connection, arrangement, configuration shown in the block diagram. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, which mean "including but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0130] It should also be noted that in the devices, equipment and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of the present application.

[0131] The above description of the disclosed aspects is provided so that any person skilled in the art can make or use the present application. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but is intended to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0132] The above description has been given for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain modifications, alterations, changes, additions and sub-combinations thereof.

Claims

1. A method for in-situ static elastic modulus inversion of rock mass, characterized in that: The method comprises: Acquiring test data, the test data including wave velocity values ​​and static elastic modulus test values ​​at multiple test points in the borehole; The wave velocity value and static elastic modulus test value of a single test point are used to form a sample, and the samples corresponding to the multiple test points are combined to form a sample set; A Gaussian process regression model is used to learn the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample in the sample set to obtain a prediction model, which is used to characterize the relationship between the measured wave velocity value and the static elastic modulus predicted value of each prediction point in the borehole.

2. The rock mass in-situ static elastic modulus inversion method according to claim 1, characterized in that: The sample is a data pair consisting of the position information, wave velocity value and static elastic modulus test value of a single test point.

3. The rock mass in-situ static elastic modulus inversion method according to claim 1, characterized in that: The Gaussian process regression model is used to learn the mapping relationship between the wave velocity value and the static elastic modulus test value of the same sample in the sample set to obtain a prediction model, which includes: Based on the mean function, different types of kernel functions are used to construct multiple Gaussian process regression models; The samples in the sample set are divided into a training set and a validation set, wherein the wave velocity values ​​of the samples in the training set are the input values ​​of the Gaussian process regression model, and the static elastic modulus test values ​​are the output values ​​of the Gaussian process regression model; Using the training set to train each Gaussian process regression model to obtain a trained Gaussian process regression model; The validation set is used to evaluate the trained Gaussian process regression model using mean absolute error, root mean square error, mean absolute percentage error and / or coefficient of determination, and the trained Gaussian process regression model with the smallest error is used as the prediction model.

4. The in-situ static elastic modulus inversion method of rock mass according to any one of claims 1 to 3, characterized in that: The borehole includes a borehole mouth section and a borehole body section that are sequentially connected along a depth direction, the multiple test points are distributed in the borehole mouth section and the borehole body section, and obtaining the test data includes: acquiring image information of the orifice section; Dividing the orifice section into at least one interval section along the borehole axis direction; Obtaining characteristic angles and the number of structural surfaces within each of the interval segments based on the image information of the orifice segment, wherein the characteristic angle of the structural surface is the angle between the structural surface and the borehole axis direction; Based on the empirical mapping relationship between the rock mass integrity coefficient and the number of structural surfaces, the average wave velocity in each of the intervals is obtained; Conducting a wave velocity test on the core at the orifice section to obtain the first average directional influence factor of each interval section; Determining the wave velocity value of each test point in the orifice section according to the distribution relationship between the test points and the interval sections, the first average directional influence factor, and the average wave velocity in each of the interval sections; Wave velocity values ​​at each of the test points within the bore section obtained through ultrasonic testing; The static elastic modulus test values ​​of each test point in the hole mouth section and the hole body section are obtained through the drilling elastic modulus test.

5. The rock mass in-situ static elastic modulus inversion method according to claim 4, characterized in that: The first average directional influencing factor of each interval obtained by performing a wave velocity test on the core at the orifice section includes: Conducting a wave velocity test on the core at the orifice section to obtain wave velocity test values ​​corresponding to each structural surface in the orifice section; Calculating the direction influence factor of each structural surface based on the maximum wave velocity and the wave velocity test value corresponding to each structural surface, wherein the maximum wave velocity is the wave velocity obtained when the strike direction of the structural surface is parallel to the direction in which the test wave is incident on the core; The average value of the directional influence factors corresponding to the structural surfaces in the interval segment is used as the first average directional influence factor in the interval segment.

6. The rock mass in-situ static elastic modulus inversion method according to claim 5, characterized in that: Determining the wave velocity value of each test point in the orifice section according to the distribution relationship between the test points and the interval segments, the first average directional influence factor, and the average wave velocity in each interval segment includes: Determine the number of structural surfaces in the direction of each test point in the orifice section according to the characteristic angle of the structural surface; deriving a second average directional influence factor in the direction of each test point according to the number of structural planes in the direction of each test point and the directional influence factor of each structural plane in the direction; The wave velocity value of each test point is obtained according to the maximum wave velocity value and the second average direction influence factor of the direction in which each test point is located.

7. The in-situ static elastic modulus inversion method of rock mass according to any one of claims 1 to 3, characterized in that: Among the multiple test points, at least some of the test points are located in different directions and depths.

8. An anisotropic wave velocity testing device, characterized in that: Applied to the in-situ static elastic modulus inversion method of a rock mass according to any one of claims 1 to 7, the anisotropic wave velocity testing device is used to test the wave velocity values ​​of at least some test points in a borehole, the anisotropic wave velocity testing device comprising: a detection head, an air filling and deflation device, and a processor; The detection head comprises: base; A detection rod is fixed to the base, and a sound wave transmitter, a first sound wave receiver and a second sound wave receiver are arranged at intervals along the axis direction of the detection rod; A plurality of inflatable rods are respectively fixed to the base, the plurality of inflatable rods are arranged in parallel with the detection rod, and the plurality of inflatable rods surround the detection rod; A plurality of air bags, each of the inflation rods is wrapped with the air bag, and the inflation rods are connected to the air bags, and the air bags are in contact with the inner wall of the borehole and the detection rod respectively after being inflated; The inflation and deflation device and the plurality of inflation rods are connected via independent air paths, and the inflation and deflation device is used to independently control the inflation and deflation of each airbag; The processor is electrically connected to the sound wave transmitter, the first sound wave receiver, and the second sound wave receiver respectively.

9. The anisotropic wave velocity testing device according to claim 8, characterized in that: A plurality of air flow holes are provided on the inflation rod, and the plurality of air flow holes are arranged in sequence along the length direction of the inflation rod.

10. The anisotropic wave velocity testing device according to claim 8, characterized in that: The adjacent air bags are arranged to fit each other after being inflated.

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