A method and system for constructing a mapping relationship between acoustic wave velocity and surrounding rock stress

Abstract

This invention belongs to the fields of rock mechanics, geological engineering, and geophysical exploration technology. Specifically, it discloses a method and system for constructing a mapping relationship between acoustic wave velocity and surrounding rock stress. The method includes: performing uniaxial graded loading on a standard sandstone sample and simultaneously measuring the P-wave velocity and S-wave velocity under each stress level; then fitting a linear mapping relationship between the P-wave / S-wave velocity ratio and the axial stress of the surrounding rock; introducing joint correction coefficients and water content correction coefficients to optimize the linear mapping relationship and constructing an acoustoelastic model; and using the acoustoelastic model and field-measured wave velocity data to invert the stress state of the actual surrounding rock, thus completing the construction of the acoustic wave velocity-surround rock stress mapping relationship. This invention solves the problems of traditional wave velocity-stress relationships, which, when describing the nonlinear response of rocks at different stress stages, are not sensitive enough to subtle stress changes and lack a complete, high-precision, and interference-resistant stress inversion calculation method, making them difficult to directly apply to complex actual engineering environments.

Description

Technical Field

[0001] This invention belongs to the fields of rock mechanics, geological engineering and geophysical exploration technology, and specifically relates to a method and system for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress. Background Technology

[0002] Accurate assessment of the stress state of underground rock masses, especially deep surrounding rocks, is crucial for stability evaluation of underground engineering projects, pressure prediction of oil and gas reservoirs, and prevention of geological hazards. Currently, traditional stress measurement methods mainly rely on a single wave velocity-stress relationship model, but this has significant limitations in practical engineering applications.

[0003] Traditional wave velocity-stress relationships are not highly sensitive in describing the nonlinear response of rocks at different stress stages, especially for subtle stress variations. Factors such as joint (fracture) density and water saturation, prevalent in rock masses, significantly influence sound wave propagation speed, severely interfering with the accuracy and adaptability of stress inversion methods. The lack of a complete, high-precision, and interference-resistant stress inversion calculation method makes it difficult to directly apply to complex real-world engineering environments. Summary of the Invention

[0004] The purpose of this invention is to address the problems that traditional wave velocity-stress relationships are not sensitive to subtle stress changes when describing the nonlinear response of rocks at different stress stages, and lack a complete, high-precision, and interference-resistant stress inversion calculation method, making it difficult to directly apply to complex practical engineering environments. This invention proposes a method and system for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress.

[0005] The technical solution of the present invention is as follows: Firstly, a method for constructing the mapping relationship between sound wave velocity and surrounding rock stress, comprising the following steps: Standard sandstone samples were subjected to uniaxial graded loading, and the longitudinal wave velocity and transverse wave velocity under each stress level were measured simultaneously. A linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock was obtained by fitting the P-wave velocity and S-wave velocity. By introducing joint correction coefficients and water content correction coefficients, the linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock is optimized using multiple parameters, resulting in the optimized linear mapping relationship. Based on the optimized linear mapping relationship, an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters is constructed. Using an acoustoelastic model that includes second-order Lamé parameters and third-order elastic parameters, as well as field-measured wave velocity data, the stress state of the actual surrounding rock is inverted, and the mapping relationship between acoustic wave velocity and surrounding rock stress is constructed.

[0006] Preferably, the linear mapping relationship between the P-wave and S-wave velocity ratio and the axial stress of the surrounding rock is as follows:

[0007] in, Indicates the axial stress of the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and This represents the material correlation constant coefficients obtained by fitting experimental data.

[0008] As a preferred option, the joint correction coefficient The specific calculation method is as follows: identify the first deceleration point in the S-wave velocity versus stress curve, which corresponds to the critical stress state of joint closure. According to the critical stress state Introducing joint correction coefficient :

[0009] in, This represents the measured stress.

[0010] As a preferred option, the water content correction factor The calculation formula is:

[0011] in, The water sensitivity coefficient, Indicates water saturation.

[0012] As a preferred option, the optimized linear mapping relationship is as follows:

[0013] in, This represents the actual axial stress of the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and These represent the material-related constant coefficients obtained by fitting experimental data. This represents the joint correction factor. This represents the water content correction factor.

[0014] As a preferred option, the formula for the acoustic elasticity model is:

[0015] in, This represents the density of sandstone under zero stress. and For second-order Lamé parameters, and For third-order elastic parameters, For wave speed, This represents the actual axial stress in the surrounding rock.

[0016] As a preferred method, the second-order Lamé parameters are calculated by measuring the P-wave velocity and S-wave velocity under zero stress. The specific calculation formula is as follows:

[0017] in, This represents the transverse wave velocity under zero stress. This represents the longitudinal wave velocity under zero stress. The third-order elasticity parameter is obtained by using the second-order Lamé parameter. and The equations were obtained by combining two sets of different data into the formula of the acoustic elasticity model and solving the system of equations.

[0018] The beneficial effects of this invention are: This invention effectively offsets common errors such as anisotropy and temperature by introducing the P-wave and S-wave velocity ratio parameter, significantly improving the sensitivity to stress changes. It not only considers the ideal elastic state, but also makes coefficient corrections for joints and water that are commonly found in rock masses, making the method adaptable to complex geological conditions. By using the relative parameter of wave velocity ratio, it reduces the errors caused by equipment coupling differences in single wave velocity measurement.

[0019] Secondly, a system for constructing a mapping relationship between acoustic wave velocity and surrounding rock stress includes: The first module is used to perform uniaxial graded loading on standard sandstone samples and simultaneously measure the longitudinal wave velocity and transverse wave velocity under each stress level. The second module is used to obtain a linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock by fitting the P-wave velocity and the S-wave velocity. The third module is used to introduce joint correction coefficients and water content correction coefficients to optimize the linear mapping relationship between the longitudinal and transverse wave velocity ratio and the axial stress of the surrounding rock using multiple parameters, and to obtain the optimized linear mapping relationship. The fourth module is used to construct an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters based on the optimized linear mapping relationship. The fifth module is used to invert the stress state of the actual surrounding rock using an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters, as well as field-measured wave velocity data, and to complete the construction of the mapping relationship between acoustic wave velocity and surrounding rock stress.

[0020] Thirdly, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method as described in the first aspect.

[0021] Fourthly, a non-transitory computer-readable storage medium is provided that stores computer instructions for causing a computer to perform the method as described in the first aspect. Attached Figure Description

[0022] Figure 1 The diagram shows a flowchart of a method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress.

[0023] Figure 2 The figure shows the ratio of longitudinal and transverse wave speeds. A schematic diagram showing the linear fitting relationship between the stress and the axial stress of the surrounding rock.

[0024] Figure 3 The diagram shows the wave velocity variation with stress and the characteristics of the S-wave inflection point in a uniaxial pressure test of sandstone.

[0025] Figure 4 The figure shows a three-dimensional surface diagram illustrating the relationship between wave velocity attenuation and confining pressure under different water saturation levels.

[0026] Figure 5 The diagram shown is a block diagram of the acoustic wave velocity-surrounding rock stress inversion system. Detailed Implementation

[0027] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, and are not intended to limit the scope of the invention.

[0028] Example 1: like Figure 1 As shown, a method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress includes the following steps: S1. The standard sandstone sample was subjected to uniaxial graded loading, and the longitudinal wave velocity and transverse wave velocity under each stress level were measured simultaneously. S2. The linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock is obtained by fitting the P-wave velocity and the S-wave velocity. S3. By introducing joint correction coefficient and water content correction coefficient, the linear mapping relationship between the longitudinal and transverse wave velocity ratio and the axial stress of the surrounding rock is optimized by multiple parameters to obtain the optimized linear mapping relationship. S4. Based on the optimized linear mapping relationship, construct an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters; S5. Using an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters, along with field-measured wave velocity data, the stress state of the actual surrounding rock is inverted, and the mapping relationship between acoustic wave velocity and surrounding rock stress is constructed.

[0029] In this embodiment, as Figure 2 As shown, the linear mapping relationship between the P-wave and S-wave velocity ratio and the axial stress of the surrounding rock is:

[0030] in, Indicates the axial stress of the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and This represents the material correlation constant coefficients obtained by fitting experimental data.

[0031] In this embodiment, the joint correction coefficient The specific calculation method is as follows: identify the first deceleration point in the S-wave velocity versus stress curve, which corresponds to the critical stress state of joint closure. According to the critical stress state Introducing joint correction coefficient :

[0032] in, This represents the measured stress.

[0033] In this embodiment, the water content correction factor The specific calculation method is as follows: for different water saturation levels Comparative tests were conducted on samples to establish a functional relationship between wave velocity and water saturation. Based on this relationship, a water content correction coefficient was established.

[0034] in, This is the water sensitivity coefficient.

[0035] In this embodiment, the optimized linear mapping relationship is as follows:

[0036] in, This represents the actual axial stress of the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and These represent the material-related constant coefficients obtained by fitting experimental data. This represents the joint correction factor. This represents the water content correction factor.

[0037] In this embodiment, the formula for the acoustoelastic model is:

[0038] in, This represents the density under zero stress. and For second-order Lamé parameters, and For third-order elastic parameters, For wave speed, The actual axial stress of the surrounding rock is used; the second-order Lamé parameters are calculated by measuring the longitudinal wave velocity and transverse wave velocity under zero stress, and the specific calculation formula is as follows:

[0039] in, This represents the transverse wave velocity under zero stress. This represents the longitudinal wave velocity under zero stress. First, typical sandstone from the target engineering area is selected and processed into standard cylindrical samples with a diameter of 50 mm and a height of 100 mm. The physical properties of the samples are then tested, and their natural density is determined. Porosity and mineral composition; according to the formula of nonlinear acoustic elasticity theory:

[0040] in, For including third-order elastic parameters and The term. Assuming the specimen is under zero stress. Measuring the longitudinal wave velocity transverse wave velocity Calculate the second-order Lamé parameters:

[0041] The third-order elasticity parameter is obtained by using the second-order Lamé parameter. and The equations were obtained by combining two sets of different data into the formula of the acoustic elasticity model and solving the system of equations.

[0042] The sandstone sample was placed in a servo-driven pressure loading device. The loading process consisted of four stages: the crack closure stage (0-30%). The experiment involved three stages: elastic deformation, microcrack propagation, and failure. A self-generating and self-receiving ultrasonic transducer (center frequency 50-100kHz) was used. The longitudinal wave velocity was recorded once for every 2MPa increase in axial load. and transverse wave velocity Calculate the ratio of P-wave to S-wave velocity at each stress point. Experimental data show that as stress increases, rock compaction... Faster growth than This leads to the ratio It exhibits regular changes. The least squares method is used to analyze the stress. Sum and ratio Performing linear regression yields the following relationship:

[0043] The coefficients were determined .

[0044] To address the complexities of actual surrounding rock environments and to correct for the effects of joints and water content, multi-parameter optimization was performed on the linear mapping relationship between the P-wave and S-wave velocity ratio and the axial stress of the surrounding rock. For example... Figure 3 As shown, in the uniaxial test wave velocity curve, the S-wave velocity was observed to reach [value missing] when the stress reached [value missing]. A sudden inflection point in the growth rate occurs, corresponding to a completely closed joint state. A joint correction coefficient is defined. for:

[0045] This step utilizes the "first deceleration point" feature to accurately identify the joint-affected zone.

[0046] For different water saturation Comparative tests were conducted using samples of (0%), (50%), and (100%), and it was found that wave velocity decreases with increasing water content. A correction function was established:

[0047] in The water sensitivity coefficient is determined by... Figure 4 The three-dimensional relationship model of wave velocity attenuation and confining pressure under different water saturation levels is obtained.

[0048] Substituting the correction coefficients into the basic equation yields the final engineering application formula, which is used for on-site calculation of surrounding rock stress.

[0049] In this embodiment, a surrounding rock stress inversion system is provided, such as Figure 5 As shown, it includes an ultrasonic testing unit, a pressure loading unit, and a data processing and inversion unit. The ultrasonic testing unit contains a high-precision acoustic time measurement host and an integrated P-wave and S-wave probe, with an acoustic time accuracy of 0.1 ns, used to excite and receive acoustic wave signals and measure the propagation time of P-waves and S-waves. The pressure loading unit has a maximum load of 100 MPa and a constant load holding function, used for indoor calibration. The data processing and inversion unit has a built-in acoustoelastic model, coefficient optimization algorithm, and inversion program, used to process wave velocity data and output surrounding rock stress results.

[0050] Example 2: Based on Example 1, this embodiment of the invention provides a system for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress, which can be used to implement the method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress as described in the foregoing embodiment. The system includes: The first module is used to perform uniaxial graded loading on standard sandstone samples and simultaneously measure the longitudinal wave velocity and transverse wave velocity under each stress level. The second module is used to obtain a linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock by fitting the P-wave velocity and the S-wave velocity. The third module is used to introduce joint correction coefficients and water content correction coefficients to optimize the linear mapping relationship between the longitudinal and transverse wave velocity ratio and the axial stress of the surrounding rock using multiple parameters, and to obtain the optimized linear mapping relationship. The fourth module is used to construct an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters based on the optimized linear mapping relationship. The fifth module is used to invert the stress state of the actual surrounding rock using an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters, as well as field-measured wave velocity data, and to complete the construction of the mapping relationship between acoustic wave velocity and surrounding rock stress.

[0051] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0052] In an exemplary embodiment, the electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress as described in Embodiment 1 above.

[0053] In an exemplary embodiment, the readable storage medium may be a non-transient computer-readable storage medium storing computer instructions for causing a computer to execute the method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to Embodiment 1 above.

[0054] In an exemplary embodiment, the computer program product includes a computer program that, when executed by a processor, implements the method for constructing the mapping relationship between sound wave velocity and surrounding rock stress as described in Embodiment 1 above.

[0055] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0056] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0057] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0058] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0059] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0060] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for constructing a mapping relationship between acoustic wave velocity and surrounding rock stress, characterized in that, Includes the following steps: Standard sandstone samples were subjected to uniaxial graded loading, and the longitudinal wave velocity and transverse wave velocity under each stress level were measured simultaneously. A linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock was obtained by fitting the P-wave velocity and S-wave velocity. By introducing joint correction coefficients and water content correction coefficients, the linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock is optimized using multiple parameters, resulting in the optimized linear mapping relationship. Based on the optimized linear mapping relationship, an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters is constructed. Using an acoustoelastic model that includes second-order Lamé parameters and third-order elastic parameters, as well as field-measured wave velocity data, the stress state of the actual surrounding rock is inverted, and the mapping relationship between acoustic wave velocity and surrounding rock stress is constructed.

2. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 1, characterized in that, The linear mapping relationship between the P-wave and S-wave velocity ratio and the axial stress of the surrounding rock is as follows: in, Indicates the axial stress of the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and This represents the material correlation constant coefficients obtained by fitting experimental data.

3. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 1, characterized in that, Joint correction factor The specific calculation method is as follows: identify the first deceleration point in the S-wave velocity versus stress curve, which corresponds to the critical stress state of joint closure. According to the critical stress state Introducing joint correction coefficient : in, This represents the measured stress.

4. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 1, characterized in that, Water content correction factor The calculation formula is: in, The water sensitivity coefficient, Indicates water saturation.

5. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 1, characterized in that, The optimized linear mapping relationship is as follows: in, This represents the actual axial stress in the surrounding rock. Indicates the transverse wave velocity. Indicates the longitudinal wave velocity. and These represent the material-related constant coefficients obtained by fitting experimental data. This represents the joint correction factor. This represents the moisture content correction factor.

6. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 1, characterized in that, The formula for the acoustic elasticity model is as follows: in, This represents the density of sandstone under zero stress. and For second-order Lamé parameters, and For third-order elastic parameters, For wave speed, This represents the actual axial stress in the surrounding rock.

7. The method for constructing the mapping relationship between acoustic wave velocity and surrounding rock stress according to claim 6, characterized in that, The second-order Lamé parameters are calculated by measuring the P-wave velocity and S-wave velocity under zero stress. The specific calculation formula is as follows: in, This represents the transverse wave velocity under zero stress. This represents the longitudinal wave velocity under zero stress. The third-order elasticity parameter is obtained by using the second-order Lamé parameter. and The equations were obtained by combining two sets of different data into the formula of the acoustic elasticity model and solving the system of equations.

8. A system for constructing a mapping relationship between acoustic wave velocity and surrounding rock stress, characterized in that, include: The first module is used to perform uniaxial graded loading on standard sandstone samples and simultaneously measure the longitudinal wave velocity and transverse wave velocity under each stress level. The second module is used to obtain a linear mapping relationship between the P-wave velocity ratio and the axial stress of the surrounding rock by fitting the P-wave velocity and the S-wave velocity. The third module is used to introduce joint correction coefficients and water content correction coefficients to optimize the linear mapping relationship between the longitudinal and transverse wave velocity ratio and the axial stress of the surrounding rock using multiple parameters, and to obtain the optimized linear mapping relationship. The fourth module is used to construct an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters based on the optimized linear mapping relationship. The fifth module is used to invert the stress state of the actual surrounding rock using an acoustoelastic model containing second-order Lamé parameters and third-order elastic parameters, as well as field-measured wave velocity data, and to complete the construction of the mapping relationship between acoustic wave velocity and surrounding rock stress.

9. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the method according to any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-7.

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