A discontinuous inversion method for tunnel full-time induced polarization based on multi-property relationship constraints

Abstract

The present invention belongs to the technical field of geophysical inversion, and specifically relates to a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints. By constructing induced polarization multi-property parameter fitting items and introducing them into the tunnel time-domain induced polarization discontinuous inversion objective function, the problem that a single property parameter absolutely dominates the inversion result due to excessive structural constraints can be avoided. The multi-property relationship constraints and structural similarity constraints are used in coordination 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 realize multi-parameter high-resolution imaging.

Description

Technical Field

[0001] The 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 disasters in tunnel engineering seriously affect and restrict the safe and efficient excavation of tunnels. It is the key and requirement to proactively prevent water inrush disasters by exploring the source of water inrush disasters in front of the tunnel face in advance. The key to exploring the source of water inrush disasters is how to obtain information about underground water-bearing structures. The tunnel induced polarization method uses the difference in electrical parameters between the surrounding rock and water-bearing structures in the tunnel as the physical property basis, and uses the electrical signals measured by the observation device to obtain the location and distribution of water-bearing structures. It is one of the effective methods for predicting water inrush disasters in tunnel engineering.

[0003] At present, although the research on time-domain induced polarization inversion has achieved certain results, it still has certain limitations. Specifically, there are the following problems:

[0004] (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.

[0005] (2) For the multi-property parameters of time-domain induced polarization, the physical property structure consistency exists in the case that the 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

[0006] 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 items 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 excessive structural constraints can be avoided. The multi-property relationship constraints and the structural similarity constraints are used in coordination 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 realize multi-parameter high-resolution imaging.

[0007] A tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints, comprising:

[0008] Based on the selected geological exploration area, a tunnel time-domain induced polarization discontinuous inversion model is constructed and theoretical observation data are obtained;

[0009] Based on rock samples with 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-physical property parameter fitting items based on the multi-physical property correlation;

[0010] 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 strategy is introduced to solve the discontinuous inversion objective function and update the discontinuous inversion model parameters of tunnel time domain induced polarization.

[0011] 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.

[0012] 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 result.

[0013] 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 excessive structural constraints can be avoided. The multi-property relationship constraints and structural similarity constraints are used in coordination to establish a discontinuous cross-gradient joint inversion objective function with multi-property relationship constraints, which can improve the accuracy of multi-parameter inversion imaging and thus achieve multi-parameter high-resolution imaging.

[0014] 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:

[0015] Conduct geological exploration based on the selected geological exploration area and obtain geological exploration results;

[0016] Based on the geological exploration results obtained, the underground medium is gridded and a preliminary geological model around the tunnel is constructed;

[0017] 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.

[0018] Based on the initial model of tunnel time-domain induced polarization inversion, simulation calculations were performed to obtain theoretical observation data.

[0019] Furthermore, 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:

[0020] 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;

[0021] 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;

[0022] 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.

[0023] Furthermore, the use of 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, including:

[0024] 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;

[0025] 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;

[0026] 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.

[0027] Furthermore, the physical property parameters include relaxation time, resistivity, frequency correlation coefficient and polarizability.

[0028] Furthermore, based on 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:

[0029] 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;

[0030] 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.

[0031] 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.

[0032] 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, and the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship is jointly constructed, including:

[0033] 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.

[0034] 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.

[0035] The expression of the objective function of the discontinuous cross gradient inversion with multi-property constraints is:

[0036] ;

[0037] 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.

[0038] A system for a tunnel full-time domain induced polarization discontinuous inversion method based on multi-property relationship constraints, comprising:

[0039] 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;

[0040] 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;

[0041] 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;

[0042] 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.

[0043] 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.

[0044] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0045] 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.

[0046] The beneficial effects of the present invention are:

[0047] The present invention constructs induced polarization multi-property parameter fitting terms and introduces them into the tunnel time domain induced polarization discontinuous inversion objective function, thereby avoiding the problem that a single property parameter absolutely dominates the inversion result due to excessive structural constraints. The multi-property relationship constraints and the structural similarity constraints are used in a coordinated 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 further realize multi-parameter high-resolution imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of the present invention;

[0049] Figure 2 is a schematic diagram of the geological model;

[0050] Figure 3 This is a schematic diagram of the final inversion result;

[0051] Figure 4 is a flow chart of the inversion method of the present invention;

[0052] Figure 5 It is a schematic diagram of the system structure in the present invention;

[0053] Figure 6 It is a schematic diagram of the structure of the computer device in the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0055] 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 the present 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 the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0056] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples, and a person of ordinary skill in the art can understand the specific meanings of the above terms in this application under specific circumstances.

[0057] Example 1

[0058] 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, the problem of a single property parameter being absolutely dominant in the inversion result due to excessive structural constraints can be avoided. The multi-property relationship constraints and structural similarity constraints are used in coordination 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. The specific steps are as follows:

[0059] S1: Based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data are obtained;

[0060] S11: Perform geological exploration based on the selected geological exploration area to obtain geological exploration results;

[0061] S12: Based on the geological exploration results obtained, the underground medium is meshed and a preliminary geological model around the tunnel is constructed;

[0062] Figure 2 Shown is a schematic diagram of the geological model.

[0063] S13: Based on the initially constructed geological model, preliminary physical property parameters are assigned to the selected rock samples, and 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;

[0064] 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-resistance body is 500Ω•m; and the resistivity of the rectangular high-resistance body is 1500Ω•m.

[0065] In this embodiment, natural sandstone is selected as the rock sample, which can ensure that the rock sample selected represents most of the surrounding rock environment of the project, so that the correlation between multiple physical parameters obtained from the induced polarization test is representative, thereby providing an accurate physical property basis for improving the accuracy of multi-parameter inversion.

[0066] In this embodiment, the physical property parameters include relaxation time, resistivity, frequency correlation coefficient and polarizability.

[0067] S14: Tunneling time-domain induced polarization inversion model , and perform simulation calculations to obtain theoretical observation data.

[0068] S2: Based on rock samples with 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;

[0069] S21: Based on rock samples with different particle size ranges, carry out induced polarization tests and record the changes in potential difference at both ends of different rock samples to obtain multiple sets of induced polarization data;

[0070] S22: calculating the physical property parameter value of each physical property parameter in different particle size ranges based on the obtained multiple sets of induced polarization data;

[0071] 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;

[0072] S231: plotting the physical parameter values ​​of two physical parameters using numerical simulation software;

[0073] S232: Observe and determine the distribution of physical property parameter value data points;

[0074] 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:

[0075] ;

[0076] In the formula, Indicates Physical property parameters; Indicates Physical property parameters; ; Expressed as The physical parameters and The correlation coefficient of the physical property parameters.

[0077] S2321: 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;

[0078] S2322: When the data points of the physical property parameter values ​​are distributed non-linearly on the view, 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.

[0079] It should be noted that in this embodiment, when constructing a regression model, it is necessary to perform a model evaluation to improve the accuracy of model construction, including using the residual sum of squares and determination coefficient method to evaluate the fitting effect of the regression model, using the t test or F test to test the significance of the regression coefficient to determine whether there is a significant impact between two physical property parameters, etc.

[0080] S3: Based on the theoretical observation data and the actual experimental observation data, the discontinuous inversion objective function of the tunnel time domain induced polarization is constructed, and the discontinuous inversion model parameters of the tunnel time domain induced polarization are solved and updated;

[0081] S31: 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;

[0082] Among them, the expression of the discontinuous inversion objective function of tunnel time domain induced polarization is:

[0083] ;

[0084] In the formula, The objective function of discontinuous inversion representing the induced polarization in the tunnel time domain; 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 parameters are absolutely dominant in the inversion process.

[0085] 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 in geological structures;

[0086] S33: using an optimization algorithm to solve the discontinuous inversion objective function of tunnel time-domain induced polarization, and updating the discontinuous inversion model parameters of tunnel time-domain induced polarization.

[0087] In this embodiment, the optimization algorithm may use a gradient descent method or a genetic algorithm to solve the discontinuous inversion objective function of tunnel time-domain induced polarization and update the discontinuous inversion model parameters of tunnel time-domain induced polarization.

[0088] S4: 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 multi-property relationship is jointly constructed;

[0089] S41: Based on the correlation analysis results, construct the induced polarization multi-physical property parameter fitting items to reflect the variation law and correlation relationship of physical property parameters between rock samples in different particle size ranges;

[0090] Among them, the expression of the fitting term of the induced polarization multi-property parameter is:

[0091] ;

[0092] In the formula, 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.

[0093] S42: Introduce the induced polarization multi-property parameter fitting term into the discontinuous inversion objective function of induced polarization in the tunnel time domain, and jointly construct the discontinuous cross-gradient inversion objective function constrained by the multi-property relationship;

[0094] Among them, the expression of the objective function of discontinuous cross gradient inversion with multi-property constraints is:

[0095] ;

[0096] In the formula, The objective function value of the discontinuous cross gradient inversion representing the physical property constraints; It is expressed as a partial score; 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 be immediately highly consistent with the resistivity, and the contribution of the four physical properties to the inversion results is balanced.

[0097] S5: Based on the discontinuous cross-gradient inversion objective function constrained by multiple physical property relationships, the parameters of the tunnel time-domain induced polarization discontinuous inversion model are iteratively updated to obtain the final inversion result.

[0098] 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 terms and induced polarization multi-property parameter fitting terms 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 conditions are met. The final inversion result is obtained to evaluate the accuracy and resolution of the multi-property parameter inversion imaging.

[0099] Figure 3 The figure shows a schematic diagram of the results of discontinuous cross-gradient inversion of tunnel time-domain induced polarization based on multi-property relationship constraints.

[0100] Example 2

[0101] Based on the same design concept, 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:

[0102] T1: Based on the selected geological exploration area, a tunnel time-domain induced polarization inversion model is constructed and theoretical observation data are obtained;

[0103] T11: Conduct geological exploration based on the selected geological exploration area and obtain geological exploration results;

[0104] T12: Based on the geological exploration results obtained, the underground medium is meshed and a preliminary geological model around the tunnel is constructed;

[0105] T13: 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.

[0106] T14: Tunnel-based time-domain induced polarization inversion model , and perform simulation calculations to obtain theoretical observation data.

[0107] T2: Based on rock samples with 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;

[0108] T21: Based on rock samples with different particle size ranges, carry out induced polarization tests and record the changes in the potential difference at both ends of different rock samples to obtain multiple sets of induced polarization data;

[0109] T22: Based on the multiple sets of induced polarization data obtained, calculate the physical property parameter value of each physical property parameter in different particle size ranges;

[0110] 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;

[0111] T3: Based on theoretical observation data and 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;

[0112] T31: Based on 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;

[0113] 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 in geological structures;

[0114] T33: 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.

[0115] T4: 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 multi-property relationship is jointly constructed;

[0116] T41: Based on the correlation analysis results, construct the induced polarization multi-physical property parameter fitting items to reflect the variation law and correlation relationship of physical property parameters between rock samples in different particle size ranges;

[0117] T42: Introduce the induced polarization multi-property parameter fitting term into the discontinuous inversion objective function of induced polarization in the tunnel time domain, and jointly construct the discontinuous cross-gradient inversion objective function constrained by multi-property relations;

[0118] T5: Based on the discontinuous cross-gradient inversion objective function constrained by multi-property relations, the discontinuous inversion model parameters of tunnel time-domain induced polarization are iteratively updated to obtain the final inversion results;

[0119] T51: When the iterative convergence conditions are met, the final inversion results are output;

[0120] T52: When the iteration convergence condition is not met, return to T3.

[0121] Example 3

[0122] Based on the same technical concept, 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.

[0123] 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;

[0124] Specifically, 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;

[0125] 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 experimental actual observation data, and solve and update the discontinuous inversion model parameters of tunnel time domain induced polarization;

[0126] 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;

[0127] 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 result.

[0128] Example 4

[0129] 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-mentioned methods when executing the computer program.

[0130] Among them, the memory 1 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 1 can be an internal storage unit of the tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints, such as a hard disk. In other embodiments, the memory 1 can also be an external storage device of the tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Further, the memory 1 can also include both the internal storage unit and the external storage device of the tunnel full-time domain induced polarization discontinuous inversion system based on multi-property relationship constraints. 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.

[0131] 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.

[0132] The disclosed embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the steps of the method described in the above method embodiment. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0133] 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, and 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, which will not be repeated here.

[0134] The disclosed embodiment of the present invention further provides a computer program, which implements any one of the methods of the aforementioned embodiments when executed by a processor. The computer program product can be implemented in hardware, software, or a combination thereof. In an optional embodiment, the computer program product is specifically embodied as a computer storage medium, and in another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0135] 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.

[0136] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0137] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes 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 not be performed in 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 belong.

[0138] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0139] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0140] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0141] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0142] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0143] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary 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 relationship 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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