Tunnel full-time-domain induced polarization discontinuous inversion method based on multi-physical relation constraint

Abstract

The invention belongs to the technical field of geophysical inversion, and particularly relates to a tunnel full-time-domain induced polarization discontinuous inversion method based on multi-physical relationship constraint, which comprises the following steps of: constructing an induced polarization multi-physical parameter fitting item, and introducing the fitting item into a tunnel time-domain induced polarization discontinuous inversion objective function. The problem that a single physical property parameter is absolutely dominant in an inversion result due to too strong structural constraint can be avoided, the multi-physical relationship constraint and the structural similarity constraint are cooperatively used, a multi-physical relationship constraint intermittent cross gradient joint inversion objective function is established, the multi-parameter inversion imaging precision can be improved, and the multi-parameter inversion imaging precision can be improved. And therefore, multi-parameter high-resolution imaging can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of geophysical inversion, and in particular relates to a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints. Background Art

[0002] Water inrush hazards in tunnel construction seriously impact and restrict safe and efficient tunnel excavation. Proactively identifying the source of water inrush hazards ahead of the tunnel face is crucial for proactive disaster prevention. The key to identifying water inrush sources lies in obtaining information about underground water-bearing structures. The tunnel induced polarization method, which uses the electrical parameter differences between the surrounding rock and water-bearing structures within the tunnel as a physical property, uses electrical signals measured by observation devices to determine the location and distribution of water-bearing structures. This method is an effective method for predicting water inrush hazards in tunnel construction.

[0003] Although the research on time-domain induced polarization inversion has achieved certain results, it still has certain limitations. Specifically, the following problems exist: (1) The credibility of the time-domain induced polarization resistivity parameter inversion is significantly higher than that of the four parameters. During the inversion iteration process, due to the strong structural constraints, the resistivity parameter absolutely dominates the inversion results, and the other three physical parameters will quickly become highly consistent with the resistivity.

[0004] (2) For the multi-property parameters of time-domain induced polarization, the consistency of the physical property structure exists in the case that all four parameters of time-domain induced polarization deviate from the true model, and the physical property relationship of the four parameters of induced polarization is not fully explored, and the correlation between the multi-property parameters cannot be added to the time-domain inversion objective function. Summary of the Invention

[0005] The present invention provides a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints. By constructing induced polarization multi-property parameter fitting terms and introducing them into the tunnel time-domain induced polarization discontinuous inversion objective function, the problem of a single property parameter being absolutely dominant in the inversion result due to excessively strong structural constraints can be avoided. The multi-property relationship constraints and structural similarity constraints are used in synergistic manner to establish a discontinuous cross-gradient joint inversion objective function with multi-property relationship constraints, which can improve the multi-parameter inversion imaging accuracy and thus achieve multi-parameter high-resolution imaging.

[0006] A tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints includes: Based on the selected geological exploration area, a tunnel time-domain induced polarization discontinuous inversion model is constructed and theoretical observation data are obtained; Based on rock samples of different particle size ranges, induced polarization tests are carried out to obtain induced polarization test data, obtain the correlation between multiple physical property parameters, and construct induced polarization multi-property parameter fitting terms based on the multi-property correlation; Based on theoretical observation data and experimental observation data, a discontinuous inversion objective function for tunnel time-domain induced polarization is constructed, and a discontinuous inversion strategy is introduced to solve the discontinuous inversion objective function and update the discontinuous inversion model parameters for tunnel time-domain induced polarization. Based on the discontinuous inversion objective function, the induced polarization multi-property parameter fitting term is introduced to jointly construct the discontinuous cross-gradient inversion objective function with multi-property constraints. Based on the discontinuous cross-gradient inversion objective function with multi-property constraints, the parameters of the tunnel time-domain induced polarization discontinuous inversion model are iteratively updated to obtain the final inversion results.

[0007] By constructing the induced polarization multi-property parameter fitting term and introducing it into the tunnel time domain induced polarization discontinuous inversion objective function, the problem of a single physical property parameter absolutely dominating the inversion result due to excessively strong structural constraints can be avoided. By using the multi-property relationship constraint and the structural similarity constraint in a coordinated manner, a discontinuous cross-gradient joint inversion objective function with multi-property relationship constraint is established, which can improve the multi-parameter inversion imaging accuracy and thus achieve multi-parameter high-resolution imaging.

[0008] Furthermore, based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data is obtained, including: Conduct geological exploration based on the selected geological exploration area and obtain geological exploration results; Based on the geological exploration results, the underground medium is meshed and a preliminary geological model of the tunnel surroundings is constructed. Based on the preliminary geological model, preliminary physical parameters were assigned to the selected rock samples. The initial geological model was simulated using time-domain induced polarization discontinuous inversion simulation using numerical simulation software to construct a tunnel time-domain induced polarization inversion model. Based on the initial model of tunnel time-domain induced polarization inversion, simulation calculations were performed to obtain theoretical observation data.

[0009] Furthermore, based on rock samples of different particle size ranges, induced polarization tests were carried out to obtain actual experimental observation data and obtain correlations between multiple physical parameters, including: Based on rock samples with different particle size ranges, induced polarization tests are carried out, and the changes in the potential difference at both ends of different rock samples are recorded to obtain multiple sets of induced polarization data; Based on the multiple sets of induced polarization data obtained, the physical property parameter values ​​of each physical parameter in different particle size ranges are calculated; Numerical simulation software is used to perform correlation analysis on different physical property parameters, and based on the correlation analysis results, appropriate physical property parameters are selected to construct a regression model to characterize the correlation between different physical property parameters.

[0010] Furthermore, the numerical simulation software is used to perform correlation analysis on different physical property parameters, and based on the correlation analysis results, appropriate physical property parameters are selected to construct a regression model to characterize the correlation between different physical property parameters, including: Use numerical simulation software to plot the physical property values ​​of two physical property parameters and observe the distribution of the physical property parameter value data points; When the data points of the physical property parameters are distributed in a straight line on the graph, it is determined that there is a linear relationship between the two physical property parameters, and a linear regression model is constructed to characterize the relationship between the two physical property parameters; When the data points of the physical property parameter values ​​are distributed non-linearly on the graph, it is determined that there is a nonlinear relationship between the two physical property parameters, and a nonlinear regression model is constructed to characterize the relationship between the two physical property parameters.

[0011] Furthermore, the physical property parameters include relaxation time, resistivity, frequency correlation coefficient and polarizability.

[0012] Furthermore, based on the theoretical observation data and the actual experimental observation data, the objective function of the discontinuous inversion of tunnel time-domain induced polarization is constructed, and the parameters of the discontinuous inversion model of tunnel time-domain induced polarization are solved and updated, including: Based on the theoretical observation data and the actual experimental observation data, a discontinuous inversion objective function of tunnel time domain induced polarization is constructed to reflect the data difference between the theoretical observation data and the actual experimental observation data. Based on the discontinuous inversion objective function of tunnel time-domain induced polarization, a discontinuous inversion strategy is introduced to deal with the discontinuity and complexity of geological structures. An optimization algorithm is used to solve the objective function of the discontinuous inversion of tunnel time-domain induced polarization and update the model parameters of the discontinuous inversion of tunnel time-domain induced polarization.

[0013] Furthermore, the induced polarization multi-property parameter fitting term is constructed based on the correlation between multiple physical property parameters, and is introduced into the discontinuous inversion objective function of tunnel time domain induced polarization, thereby jointly constructing a discontinuous cross-gradient inversion objective function constrained by the multi-property relationship, including: Based on the correlation analysis results, the induced polarization multi-property parameter fitting term is constructed to reflect the variation pattern and correlation relationship of the physical property parameters between rock samples in different particle size ranges. The induced polarization multi-property parameter fitting term is introduced into the discontinuous inversion objective function of tunnel time domain induced polarization, and the discontinuous cross-gradient inversion objective function constrained by multi-property relations is jointly constructed. The expression of the objective function of the multi-property constrained discontinuous cross gradient inversion is: ; Where, The objective function value of the discontinuous cross gradient inversion representing the physical property constraints; represents the data fitting term; represents the minimum gradient support model term; represents the weight coefficient of the minimum gradient support model item; represents the discontinuous cross gradient term, Represents the discontinuity parameter, that is, when the inversion process is an odd number of iterations, , for even number of iterations, ; Represents the physical property parameter fitting term, and its expression is: , Represents the physical property parameter fitting item; represents the physical constraint vector, Represents the covariance matrix corresponding to the physical constraint vector; Expressed as partial.

[0014] A system for a tunnel full-time-domain induced polarization discontinuous inversion method based on multi-property relationship constraints, comprising: The first module is used to construct a tunnel time-domain induced polarization inversion model based on the selected geological exploration area and obtain theoretical observation data; The second module is used to conduct induced polarization experiments based on rock samples of different particle size ranges to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; The third module is used to construct the objective function of the discontinuous inversion of tunnel time-domain induced polarization based on theoretical observation data and actual experimental observation data, and to solve and update the parameters of the discontinuous inversion model of tunnel time-domain induced polarization; The fourth module is used to construct the induced polarization multi-property parameter fitting term based on the correlation between multiple physical property parameters, and introduce it into the discontinuous inversion objective function of tunnel time domain induced polarization, jointly constructing the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship; The fifth module is used to iteratively update the parameters of the tunnel time-domain induced polarization discontinuous inversion model based on the objective function of the discontinuous cross-gradient inversion constrained by multiple physical property relationships to obtain the final inversion results.

[0015] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0016] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0017] The beneficial effects of the present invention are: The present invention constructs an induced polarization multi-property parameter fitting term and introduces it into the tunnel time-domain induced polarization discontinuous inversion objective function. This can avoid the problem of a single physical property parameter absolutely dominating the inversion result due to excessively strong structural constraints. The multi-property relationship constraint and the structural similarity constraint are used in synergistic manner to establish a discontinuous cross-gradient joint inversion objective function with multi-property relationship constraints. This can improve the multi-parameter inversion imaging accuracy and thus achieve multi-parameter high-resolution imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the present invention; Figure 2 This is a schematic diagram of the geological model; Figure 3 Schematic diagram of the final inversion result; Figure 4 is a flow chart of the inversion method of the present invention; Figure 5 Schematic diagram of the system structure of the present invention; Figure 6 It is a structural diagram of the computer device in the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this apparatus and / or practice this method.

[0021] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood in specific situations.

[0022] Example 1 Figure 1 The method is a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints. By constructing induced polarization multi-property parameter fitting terms and introducing them into the tunnel time-domain induced polarization discontinuous inversion objective function, it can avoid the problem of a single physical property parameter being absolutely dominant in the inversion result due to excessive structural constraints. By using multi-property relationship constraints and structural similarity constraints in a coordinated manner, a discontinuous cross-gradient joint inversion objective function with multi-property relationship constraints is established, which can improve the accuracy of multi-parameter inversion imaging and thus achieve multi-parameter high-resolution imaging. The specific steps include the following: S1: Based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data are obtained; S11: Perform geological exploration based on the selected geological exploration area and obtain geological exploration results; S12: Based on the geological exploration results, the underground medium is meshed and a preliminary geological model around the tunnel is constructed; Figure 2 Shown is a schematic diagram of the geological model.

[0023] S13: Based on the preliminary geological model, preliminary physical parameters are assigned to the selected rock samples. The initial geological model is simulated using time-domain induced polarization discontinuous inversion simulation using numerical simulation software to construct a tunnel time-domain induced polarization inversion model. In this embodiment, the selected inversion area is 30m×30m; the divided inversion grid size is 1m×1m; the background resistivity is 1000Ω•m; the resistivity of the rectangular low-resistivity body is 500Ω•m; and the resistivity of the rectangular high-resistivity body is 1500Ω•m.

[0024] In this embodiment, natural sandstone is selected as the rock sample, which can ensure that the rock sample selected is representative of most engineering surrounding rock environments, making the correlation between multiple physical parameters obtained from the induced polarization test representative, thereby providing an accurate physical property basis for improving the accuracy of multi-parameter inversion.

[0025] In this embodiment, the physical property parameters include relaxation time, resistivity, frequency-dependent coefficient, and polarizability.

[0026] S14: Tunnel-based time-domain induced polarization inversion model , and perform simulation calculations to obtain theoretical observation data.

[0027] S2: Based on rock samples of different particle size ranges, induced polarization tests are carried out to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; S21: Conduct induced polarization tests on rock samples with different particle size ranges, record the potential difference changes at both ends of different rock samples, and obtain multiple sets of induced polarization data; S22: calculating the physical property parameter value of each physical property parameter in different particle size ranges based on the multiple sets of induced polarization data obtained; S23: Use numerical simulation software to perform correlation analysis on different physical property parameters, and select appropriate physical property parameters based on the correlation analysis results to construct a regression model to characterize the correlation between different physical property parameters; S231: plotting the physical property values ​​of two physical property parameters using numerical simulation software; S232: Observe and determine the distribution of physical property parameter value data points; Among them, the correlation expression between the two physical property parameters is set to characterize the correlation between the two physical property parameters. The expression is: ; Where, Indicates the physical property parameters; Indicates the physical property parameters; ; Expressed as physical properties and the The correlation coefficient of the physical parameters.

[0028] S2321: When the data points of the physical property parameters are distributed in a straight line on the graph, it is determined that there is a linear relationship between the two physical property parameters, and a linear regression model is constructed to characterize the relationship between the two physical property parameters; S2322: When the physical property parameter value data points are distributed non-linearly on the graph, it is determined that there is a nonlinear relationship between the two physical property parameters, and a nonlinear regression model is constructed to characterize the relationship between the two physical property parameters.

[0029] It should be noted that in this embodiment, when constructing a regression model, a model evaluation is required to improve the accuracy of the model construction. This includes using the residual sum of squares and the coefficient of determination method to evaluate the fitting effect of the regression model, and using the t-test or F-test to test the significance of the regression coefficient to determine whether there is a significant effect between two physical property parameters.

[0030] S3: Based on theoretical observation data and experimental observation data, the objective function of the discontinuous inversion of tunnel time-domain induced polarization is constructed, and the parameters of the discontinuous inversion model of tunnel time-domain induced polarization are solved and updated; S31: Based on the theoretical observation data and the actual experimental observation data, a discontinuous inversion objective function of the tunnel time domain induced polarization is constructed to reflect the data difference between the theoretical observation data and the actual experimental observation data; The objective function of the discontinuous inversion of tunnel time-domain induced polarization is expressed as follows: ; Where, The objective function of discontinuous inversion representing the tunnel time-domain induced polarization; Represents the data fitting term, which is used to represent the difference between theoretical observation data and actual experimental observation data; represents the minimum gradient support model term, which is used to maintain the smoothness of the model; represents the minimum gradient support model term weight factor; represents the cross gradient term; Represents the discontinuity parameter, that is, when the inversion process is an odd number of iterations, , for even number of iterations, , which is used to realize discontinuous inversion and solve the problem that the resistivity parameter is absolutely dominant in the inversion process.

[0031] S32: Based on the discontinuous inversion objective function of tunnel time-domain induced polarization, a discontinuous inversion strategy is introduced to deal with the discontinuity and complexity of geological structures; S33: Using an optimization algorithm to solve the objective function of the discontinuous inversion of tunnel time-domain induced polarization, and updating the parameters of the discontinuous inversion model of tunnel time-domain induced polarization.

[0032] In this embodiment, the optimization algorithm may use a gradient descent method or a genetic algorithm to solve the objective function of the discontinuous inversion of tunnel time-domain induced polarization and update the parameters of the discontinuous inversion model of tunnel time-domain induced polarization.

[0033] S4: Based on the correlation between multiple physical property parameters, the multi-property parameter fitting term of induced polarization is constructed and introduced into the discontinuous inversion objective function of tunnel time domain induced polarization, and the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship is jointly constructed; S41: Based on the correlation analysis results, construct the induced polarization multi-property parameter fitting term to reflect the variation pattern and correlation relationship of the physical property parameters between rock samples in different particle size ranges; The expression of the fitting term of the induced polarization multi-property parameter is: ; Where, represents the physical property parameter fitting term, Indicates physical property parameters; represents the physical constraint vector; Represents the covariance matrix corresponding to the physical property constraint vector.

[0034] S42: Introducing the induced polarization multi-property parameter fitting term into the discontinuous inversion objective function of tunnel time domain induced polarization, and jointly constructing the discontinuous cross-gradient inversion objective function constrained by multi-property relations; Among them, the expression of the objective function of the discontinuous cross-gradient inversion with multi-property constraints is: ; Where, The objective function value of the discontinuous cross gradient inversion representing the physical property constraints; It is expressed as a partial division; Represents the cross-gradient weight factor. By setting the cross-gradient function weight factor, the cross-gradient constraint strategy is refined to each inversion iteration, so that the other three physical properties will not immediately be highly consistent with the resistivity, and the contribution of the four physical properties to the inversion results is balanced.

[0035] S5: Based on the discontinuous cross-gradient inversion objective function constrained by multi-property relationships, the parameters of the tunnel time-domain induced polarization discontinuous inversion model are iteratively updated to obtain the final inversion results.

[0036] The initial tunnel time-domain induced polarization discontinuous inversion model is substituted into the discontinuous cross-gradient inversion objective function, and the discontinuous cross-gradient term and the induced polarization multi-property parameter fitting term are calculated to obtain the updated tunnel time-domain induced polarization discontinuous inversion model parameters. The multi-property constrained discontinuous cross-gradient inversion is performed according to the preset number of iterations until the iterative convergence condition is met. The final inversion result is obtained to evaluate the accuracy and resolution of the multi-property parameter inversion imaging.

[0037] Figure 3 The figure shows the schematic diagram of the results of discontinuous cross-gradient inversion of tunnel time-domain induced polarization based on multi-property relationship constraints.

[0038] Example 2 Based on the same design concept, such as Figure 4 As shown, this embodiment provides a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints, which specifically includes the following steps: T1: Based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data are obtained; T11: Conduct geological exploration based on the selected geological exploration area and obtain geological exploration results; T12: Based on the geological exploration results, the underground medium is meshed and a preliminary geological model of the tunnel surroundings is constructed. T13: Based on the preliminary geological model, preliminary physical parameters are assigned to the selected rock samples. The initial geological model is simulated using time-domain induced polarization discontinuous inversion simulation using numerical simulation software to construct a tunnel time-domain induced polarization inversion model. T14: Tunnel-based time-domain induced polarization inversion model , and perform simulation calculations to obtain theoretical observation data.

[0039] T2: Based on rock samples of different particle size ranges, induced polarization tests are carried out to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; T21: Conduct induced polarization tests on rock samples of different particle size ranges, record the potential difference changes at both ends of different rock samples, and obtain multiple sets of induced polarization data; T22: Based on the multiple sets of induced polarization data obtained, calculate the physical property parameter values ​​of each physical parameter in different particle size ranges; T23: Use numerical simulation software to perform correlation analysis on different physical property parameters, and based on the correlation analysis results, use linear regression model or nonlinear regression model to characterize the relationship between two physical property parameters; T3: Based on theoretical observation data and experimental observation data, the objective function of the discontinuous inversion of tunnel time-domain induced polarization is constructed, and the parameters of the discontinuous inversion model of tunnel time-domain induced polarization are solved and updated; T31: Based on the theoretical observation data and the actual experimental observation data, a discontinuous inversion objective function of the tunnel time domain induced polarization is constructed to reflect the data difference between the theoretical observation data and the actual experimental observation data; T32: Based on the discontinuous inversion objective function of tunnel time-domain induced polarization, a discontinuous inversion strategy is introduced to deal with the discontinuity and complexity of geological structures; T33: Use the optimization algorithm to solve the objective function of the discontinuous inversion of tunnel time-domain induced polarization and update the parameters of the discontinuous inversion model of tunnel time-domain induced polarization.

[0040] T4: Based on the correlation between multiple physical property parameters, the induced polarization multi-property parameter fitting term is constructed and introduced into the discontinuous inversion objective function of tunnel time domain induced polarization, and the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship is jointly constructed; T41: Based on the correlation analysis results, construct the induced polarization multi-property parameter fitting term to reflect the variation pattern and correlation relationship of the physical property parameters between rock samples in different particle size ranges; T42: Introducing the induced polarization multi-property parameter fitting term into the discontinuous inversion objective function of tunnel time-domain induced polarization, and jointly constructing the discontinuous cross-gradient inversion objective function constrained by multi-property relations; T5: Based on the discontinuous cross-gradient inversion objective function constrained by multi-property relations, the parameters of the tunnel time-domain induced polarization discontinuous inversion model are iteratively updated to obtain the final inversion results; T51: When the iterative convergence conditions are met, the final inversion results are output; T52: When the iterative convergence condition is not satisfied, return to T3.

[0041] Example 3 Based on the same technical concept, such as Figure 5 As shown, an embodiment of the present application provides a tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints, including a first module, a second module, a third module, a fourth module and a fifth module.

[0042] Specifically, the first module is used to construct a tunnel time-domain induced polarization inversion model based on the selected geological exploration area and obtain theoretical observation data; Specifically, the second module is used to conduct induced polarization experiments based on rock samples of different particle size ranges to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; Specifically, the third module is used to construct the discontinuous inversion objective function of tunnel time domain induced polarization based on theoretical observation data and actual experimental observation data, and solve and update the discontinuous inversion model parameters of tunnel time domain induced polarization; Specifically, the fourth module is used to construct the induced polarization multi-property parameter fitting term based on the correlation between multiple physical property parameters, and introduce it into the discontinuous inversion objective function of tunnel time domain induced polarization, and jointly construct the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship. Specifically, the fifth module is used to iteratively update the parameters of the tunnel time domain induced polarization discontinuous inversion model based on the discontinuous cross-gradient inversion objective function constrained by multiple physical property relationships to obtain the final inversion results.

[0043] Example 4 Based on the same technical concept, the embodiment of the present application also provides a computer device, including a memory 1 and a processor 2, such as Figure 6 As shown, the memory 1 stores a computer program, and the processor 2 implements any of the above methods when executing the computer program.

[0044] Memory 1 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, memory 1 can be an internal storage unit of the multi-property relation-constrained tunnel full-time-domain induced polarization discontinuous inversion system, such as a hard disk. In other embodiments, memory 1 can also be an external storage device of the multi-property relation-constrained tunnel full-time-domain induced polarization discontinuous inversion system, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Furthermore, memory 1 can include both an internal storage unit and an external storage device of the multi-property relation-constrained tunnel full-time-domain induced polarization discontinuous inversion system. Memory 1 can not only be used to store application software and various data installed in the tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints, such as the code of the tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints, but can also be used to temporarily store data that has been output or is to be output.

[0045] In some embodiments, the processor 2 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip, which is used to run the program code or process data stored in the memory 1, such as executing a tunnel full-time domain induced polarization discontinuous inversion system program based on multi-property relationship constraints.

[0046] The disclosed embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to perform the steps of the method described in the above method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0047] The computer program product of the application page content refresh method provided in the disclosed embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the method described in the above method embodiment. For details, please refer to the above method embodiment and will not be repeated here.

[0048] The disclosed embodiments of the present invention further provide a computer program that, when executed by a processor, implements any of the methods of the aforementioned embodiments. This computer program product can be implemented in hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is embodied as a computer storage medium. In another alternative embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK).

[0049] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0050] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" is at least two.

[0051] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0052] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0053] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0054] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0055] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0056] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0057] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints, characterized in that: include: Based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data are obtained; Based on rock samples with different particle size ranges, induced polarization tests were carried out to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; According to the theoretical observation data and the actual experimental observation data, the discontinuous inversion objective function of tunnel time domain induced polarization is constructed, and the discontinuous inversion model parameters of tunnel time domain induced polarization are solved and updated; Based on the correlation between multiple physical property parameters, the induced polarization multi-property parameter fitting term is constructed, and it is introduced into the discontinuous inversion objective function of tunnel time domain induced polarization, and the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship is jointly constructed; Based on the discontinuous cross-gradient inversion objective function constrained by multi-property relations, the parameters of the tunnel time-domain induced polarization discontinuous inversion model are iteratively updated to obtain the final inversion result.

2. According to claim 1, a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints is characterized by: Based on the selected geological exploration area, a tunnel time domain induced polarization inversion model is constructed, and theoretical observation data are obtained, including: Conduct geological exploration based on the selected geological exploration area and obtain geological exploration results; Based on the geological exploration results obtained, the underground medium is gridded and a preliminary geological model around the tunnel is constructed; Based on the preliminary geological model, preliminary physical parameters are assigned to the selected rock samples. The initial geological model is simulated by time-domain induced polarization discontinuous inversion using numerical simulation software to construct a tunnel time-domain induced polarization inversion model. Based on the initial model of tunnel time-domain induced polarization inversion, simulation calculations were performed to obtain theoretical observation data.

3. The tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints according to claim 1 is characterized in that: Based on rock samples with different particle size ranges, induced polarization tests were carried out to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters, including: Based on rock samples with different particle size ranges, induced polarization tests are carried out to record the changes in the potential difference at both ends of different rock samples to obtain multiple sets of induced polarization data; Based on the obtained multiple sets of induced polarization data, the physical property parameter values ​​of each physical property parameter in different particle size ranges are calculated; Numerical simulation software is used to perform correlation analysis on different physical property parameters, and based on the correlation analysis results, appropriate physical property parameters are selected to construct a regression model to characterize the correlation between different physical property parameters.

4. The tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints according to claim 3 is characterized in that: The method of using numerical simulation software to perform correlation analysis on different physical property parameters, and selecting appropriate physical property parameters based on the correlation analysis results to construct a regression model to characterize the correlation between different physical property parameters includes: Use numerical simulation software to plot the physical property parameter values ​​of two physical property parameters and observe the distribution of the physical property parameter value data points; When the data points of the physical property parameter values ​​are distributed in a straight line on the graph, it is determined that there is a linear relationship between the two physical property parameters, and a linear regression model is constructed to characterize the relationship between the two physical property parameters; When the data points of the physical property parameter values ​​are distributed non-linearly on the graph, it is determined that there is a nonlinear relationship between the two physical property parameters, and a nonlinear regression model is constructed to characterize the relationship between the two physical property parameters.

5. The tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints according to claim 3 is characterized in that: The physical property parameters include relaxation time, resistivity, frequency correlation coefficient and polarizability.

6. The tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints according to claim 3 is characterized in that: According to the theoretical observation data and the actual experimental observation data, the discontinuous inversion objective function of tunnel time domain induced polarization is constructed, and the discontinuous inversion model parameters of tunnel time domain induced polarization are solved and updated, including: According to the theoretical observation data and the actual experimental observation data, the discontinuous inversion objective function of tunnel time domain induced polarization is constructed to reflect the data difference between the theoretical observation data and the actual experimental observation data. Based on the discontinuous inversion objective function of tunnel time-domain induced polarization, a discontinuous inversion strategy is introduced to deal with the discontinuity and complexity of geological structures. An optimization algorithm is used to solve the objective function of the discontinuous inversion of tunnel time-domain induced polarization and update the model parameters of the discontinuous inversion of tunnel time-domain induced polarization.

7. The tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints according to claim 3 is characterized in that: The method constructs the induced polarization multi-property parameter fitting term based on the correlation between the multiple property parameters, introduces it into the discontinuous inversion objective function of the tunnel time domain induced polarization, and jointly constructs the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship, including: Based on the correlation analysis results, the induced polarization multi-physical property parameter fitting items are constructed to reflect the variation law and correlation relationship of physical property parameters between rock samples in different particle size ranges. The induced polarization multi-property parameter fitting term is introduced into the discontinuous inversion objective function of induced polarization in tunnel time domain, and the discontinuous cross-gradient inversion objective function constrained by multi-property relations is jointly constructed. The expression of the objective function of the discontinuous cross gradient inversion with multi-property constraints is: ； In the formula, The objective function value of the discontinuous cross gradient inversion representing the physical property constraints; represents the data fitting term; represents the minimum gradient support model term; represents the weight coefficient of the minimum gradient support model term; represents the discontinuous cross gradient term, represents the discontinuity parameter, that is, when the inversion process is an odd number of iterations, , for even number of iterations, ; It represents the physical property parameter fitting term, and its expression is: , Represents the physical property parameter fitting item; represents the physical constraint vector, Represents the covariance matrix corresponding to the physical constraint vector; Expressed as partial.

8. A system for the tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints as claimed in claim 1, characterized in that: include: The first module is used to construct a tunnel time-domain induced polarization inversion model based on the selected geological exploration area and obtain theoretical observation data; The second module is used to carry out induced polarization tests based on rock samples with different particle size ranges to obtain actual experimental observation data and obtain the correlation between multiple physical property parameters; The third module is used to construct the discontinuous inversion objective function of tunnel time domain induced polarization based on theoretical observation data and actual experimental observation data, and to solve and update the discontinuous inversion model parameters of tunnel time domain induced polarization; The fourth module is used to construct the induced polarization multi-property parameter fitting term based on the correlation between multiple physical property parameters, and introduce it into the discontinuous inversion objective function of tunnel time domain induced polarization, and jointly construct the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship; The fifth module is used to iteratively update the discontinuous cross-gradient inversion model parameters in the tunnel time-domain induced polarization based on the objective function of the discontinuous cross-gradient inversion constrained by multiple physical property relationships to obtain the final inversion results.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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