A global view resistivity iterative initial value setting method, system, device and product

Abstract

The application discloses a global apparent resistivity iterative initial value setting method, device, medium and product, relates to the electromagnetic detection technical field, and the method comprises the following steps: firstly, a plurality of rough estimated resistivity values are selected in a predetermined resistivity range according to logarithmic equal intervals, and a corresponding rough estimation resistivity model is constructed accordingly. Then, the transient electromagnetic response of each rough estimation model on different time channels is calculated, and compared with the actually measured transient electromagnetic response, so that the response deviation value of the model is obtained. According to this, the preliminary resistivity initial value is selected. Subsequently, the transient electromagnetic response of several time channels of the shallow layer is fitted, and a more accurate resistivity estimation value is obtained. Based on these fine estimation resistivity values, the fine estimation resistivity initial value of each time channel is further calculated. Finally, for any one time channel, the transient electromagnetic response thereof is fitted, and the final resistivity initial value of the time channel is determined by taking minimizing the difference between the actual measured value and the predicted value as the target.

Description

Technical Field

[0001] The present application relates to the field of electromagnetic detection technology, and in particular to a method, device, medium and product for setting an initial value of global apparent resistivity iteration. Background Art

[0002] The transient electromagnetic method (TEM) is a core branch of active source time-domain electromagnetic exploration technology. This method uses transient pulsed currents to induce eddy current fields in the subsurface medium and observes the decay response of the secondary field to infer the electrical structure of the subsurface medium. Based on the electromagnetic diffusion principle described by Maxwell's equations and leveraging the fact that electromagnetic field signals at different times correspond to different detection depths, TEM enables three-dimensional detection of subsurface electrical parameters. Its key advantages lie in its highly sensitive response to low-resistance objects and its ability to resolve multi-scale geological targets using wide time window data. Currently, TEM has been widely used in deep mineral exploration, geothermal resource assessment, and geological disaster investigation and remediation. In transient electromagnetic exploration, apparent resistivity definition techniques are often used to convert transient electromagnetic responses into the apparent resistivity of the earth, which can be visually analyzed to analyze the electrical distribution of the subsurface medium.

[0003] Apparent resistivity definition methods, with their advantages of computational simplicity and unique results, are currently one of the most fundamental and important techniques for transient electromagnetic (TEM) data processing and interpretation. Due to the complexity of the TEM field, traditional apparent resistivity definitions require distinguishing between near and far zones, or between early and late stages, and suffer from the inability to effectively define the transition period and transition zone. The TEM global apparent resistivity definition uses an iterative technique to establish a mapping relationship between the TEM field response and the electrical properties of the subsurface medium. This effectively eliminates the influence of geometric diffusion effects of the field source, eliminates the need for zoning and staged apparent resistivity definition, and addresses the difficulty of defining the apparent resistivity during and within the transition period. However, current TEM global apparent resistivity definitions face significant multi-solution issues in practical applications. This is particularly evident when the initial resistivity value is incorrectly chosen, leading to the iteration branching into an incorrect branch. This results in apparent resistivity values ​​that, while valid, fit the data but are significantly irrational, resulting in jumps in the global apparent resistivity curve. This multi-solution issue is particularly pronounced in laterally heterogeneous geological bodies, ultimately manifesting as lateral discontinuities or pseudo-anomalous beaded distributions in the global apparent resistivity profile, severely limiting the ability to accurately characterize geological structures such as faults and lithologic boundaries. To solve this problem, the initial value of the apparent resistivity iteration must be set as close to the true value as possible. However, since the electrical characteristics of the underground medium are unknown quantities that need to be detected and interpreted, it is difficult to make an effective and accurate estimate. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, medium and product for setting the iterative initial value of the global apparent resistivity, which can improve the accuracy of the iterative resistivity initial value setting and thus obtain an accurate global apparent resistivity value.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for setting an initial value of global apparent resistivity iteration, comprising the following steps:

[0007] A number of rough-estimated resistivities are selected within a preset resistivity range at equal logarithmic intervals, and a number of rough-estimated resistivity models are constructed.

[0008] For any rough-estimated resistivity model, the transient electromagnetic response of the rough-estimated resistivity model at different time channels is calculated and compared with the measured transient electromagnetic response of the corresponding time channels to obtain the response deviation value of the rough-estimated resistivity model.

[0009] The rough-estimated resistivity model with the lowest response deviation is used as the initial resistivity value. The transient electromagnetic responses of several shallow time channels are fitted to minimize the difference between the measured transient electromagnetic responses and the predicted transient electromagnetic responses of the corresponding time channels, and the refined resistivity value is obtained.

[0010] Based on the refined resistivity value, the initial refined resistivity value of each time channel is calculated.

[0011] For any time channel, the transient electromagnetic response of the time channel is fitted, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, and the final selected initial resistivity value of the time channel is obtained.

[0012] Optionally, a number of rough-estimated resistivities are selected at equal logarithmic intervals within a preset resistivity range, and a number of rough-estimated resistivity models are constructed, specifically including:

[0013] A number of rough estimated resistivities are selected within a preset resistivity range at equal logarithmic intervals.

[0014] For any rough-estimated resistivity, according to transient electromagnetic theory, a uniform half-space with a resistivity equal to the rough-estimated resistivity is taken as the rough-estimated resistivity model of the corresponding rough-estimated resistivity.

[0015] Optionally, the transient electromagnetic response of the rough resistivity model at different time channels is calculated according to the following formula:

[0016] .

[0017] Among them, the superscript est represents the transient electromagnetic response of the rough resistivity model, For the jA rough resistivity model is i The transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road, ρ j For the j A rough resistivity model.

[0018] The response deviation value of the rough resistivity model is calculated according to the following formula:

[0019] .

[0020] in, For the j A rough estimate of the response deviation of the resistivity model, m is the number of time channels, d i For the i The measured transient electromagnetic response of a time channel.

[0021] Optionally, a detailed resistivity estimate is obtained by minimizing the following equation:

[0022] .

[0023] in, is the objective function value for estimating the resistivity value, l is the number of shallow time channels, l < m , d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

[0024] Optionally, the initial value of the detailed resistivity of each time channel can be calculated according to the following formula:

[0025] .

[0026] in, ρ si For the i The initial resistivity value of the time channel is estimated. ρ r To estimate the resistivity value, d i For the i The measured transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For thei A time road.

[0027] Optionally, the final selected initial resistivity value of the time channel is obtained by minimizing the following formula:

[0028] .

[0029] in, For the i The objective function value of the time channel, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

[0030] Optionally, the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain a refined resistivity value; the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel as the target to obtain the final selected resistivity initial value of the time channel.

[0031] In a second aspect, the present application provides a global apparent resistivity iterative initial value setting system, comprising the following functional modules:

[0032] The rough-estimated resistivity model construction module is used to select a number of rough-estimated resistivities within a preset resistivity range at equal logarithmic intervals and construct a number of rough-estimated resistivity models.

[0033] The response deviation value determination module is used to calculate the transient electromagnetic response of the rough estimated resistivity model at different time channels for any rough estimated resistivity model, and compare it with the measured transient electromagnetic response of the corresponding time channel to obtain the response deviation value of the rough estimated resistivity model.

[0034] The refined resistivity determination module is used to use the rough resistivity model with the lowest response deviation value as the initial resistivity value, fit the transient electromagnetic response of several shallow time channels, and minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain the refined resistivity value.

[0035] The module for determining the initial value of the fine-estimated resistivity is used to calculate the initial value of the fine-estimated resistivity of each time channel based on the fine-estimated resistivity value.

[0036] The final selected resistivity initial value determination module is used to fit the transient electromagnetic response of any time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the final selected resistivity initial value of the time channel.

[0037] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for setting the initial value of the global apparent resistivity iteration described above.

[0038] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method for setting the initial value of the global apparent resistivity iteration described above.

[0039] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0040] The present application provides a method, device, medium, and product for iteratively setting initial values ​​for global apparent resistivity. In this method, several roughly estimated resistivity values ​​are first selected at logarithmic intervals within a predetermined resistivity range, and a corresponding rough-estimated resistivity model is constructed based on these values. Next, for each rough-estimated resistivity model, its transient electromagnetic response (TEMR) is calculated for different time channels and compared with the actual measured TEMR to obtain the response deviation value of the model. Based on these deviation values, preliminary initial resistivity values ​​are selected. Subsequently, the transient electromagnetic response of several shallow time channels is fitted, with the goal of minimizing the difference between the actual measured value and the predicted value, thereby obtaining a more accurate resistivity estimate. Based on these refined resistivity values, a refined initial resistivity value is further calculated for each time channel. Finally, for any time channel, the final initial resistivity value for that time channel is determined by fitting its transient electromagnetic response, with the goal of minimizing the difference between the actual measured value and the predicted value. The above-mentioned scheme of the present application first makes a rough estimate of the initial apparent resistivity value based on the data of all time channels of a single measuring point, and then uses multiple time channels to make a detailed estimate of the initial apparent resistivity value, and then calculates the initial resistivity value of each time channel. Finally, the obtained initial resistivity value is used to define the global apparent resistivity, and accurate global apparent resistivity values ​​on different time channels are obtained. This eliminates the problems of uneven curves and jump points caused by unreasonable initial value selection in the traditional global apparent resistivity definition, and provides high-reliability global apparent resistivity data for transient electromagnetic data analysis and interpretation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0042] Figure 1A flowchart of a method for setting the initial value of global apparent resistivity iteration provided in one embodiment of the present application.

[0043] Figure 2 This is a schematic diagram of a comparison curve between measured data and roughly estimated data in a method for setting the iterative initial value of global apparent resistivity provided in one embodiment of the present application.

[0044] Figure 3 A schematic diagram of a curve showing a detailed estimation of the initial resistivity value in a method for setting the initial value of the global apparent resistivity iteration provided in one embodiment of the present application.

[0045] Figure 4 A schematic diagram of a curve of global apparent resistivity in a method for iteratively setting initial values ​​of global apparent resistivity provided in one embodiment of the present application.

[0046] Figure 5 Schematic diagram of comparison curve of global apparent resistivity obtained by using the traditional setting method and the setting method provided by the present application.

[0047] Figure 6 A schematic diagram of the functional modules of a global apparent resistivity iterative initial value setting system provided in one embodiment of the present application.

[0048] Figure 7 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0050] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0051] The embodiment of the present application provides a method for setting the initial value of the global apparent resistivity iteration, such as Figure 1 As shown, the following steps are included:

[0052] A1. Selecting a number of roughly estimated resistivities within a preset resistivity range at equal logarithmic intervals and constructing a number of roughly estimated resistivity models. In this embodiment, step A1 specifically includes:

[0053] A11. Select several rough resistivities at equal logarithmic intervals within the preset resistivity range.

[0054] A12. For any rough-estimated resistivity, according to transient electromagnetic theory, a uniform half-space with a resistivity equal to the rough-estimated resistivity is taken as the rough-estimated resistivity model of the corresponding rough-estimated resistivity.

[0055] A2. For any rough-estimated resistivity model, calculate the transient electromagnetic response of the rough-estimated resistivity model at different time channels and compare it with the measured transient electromagnetic response of the corresponding time channels to obtain the response deviation value of the rough-estimated resistivity model. Calculate the transient electromagnetic response of the rough-estimated resistivity model at different time channels according to the following formula:

[0056] .

[0057] Among them, the superscript est represents the transient electromagnetic response of the rough resistivity model, For the j A rough resistivity model is i The transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road, ρ j For the j A rough resistivity model.

[0058] The response deviation value of the rough resistivity model is calculated according to the following formula:

[0059] .

[0060] in, For the j A rough estimate of the response deviation of the resistivity model, m is the number of time channels, d i For the i The measured transient electromagnetic response of a time channel.

[0061] A3. Using the rough resistivity model with the lowest response deviation as the initial resistivity value, the transient electromagnetic response of several shallow time channels is fitted, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain a refined resistivity value. In this embodiment, the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain a refined resistivity value; specifically, the goal is to minimize the following equation:

[0062] .

[0063] in, is the objective function value for estimating the resistivity value, lis the number of shallow time channels, l < m , d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

[0064] A4. Based on the detailed resistivity value, calculate and obtain the initial detailed resistivity value of each time channel. In this embodiment, the initial detailed resistivity value of each time channel is calculated according to the following formula:

[0065] .

[0066] in, ρ si For the i The initial resistivity value of the time channel is estimated. ρ r To estimate the resistivity value, d i For the i The measured transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road.

[0067] A5. For any time channel, fit the transient electromagnetic response of the time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the final selected initial resistivity value of the time channel. In this embodiment, the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel to obtain the final selected initial resistivity value of the time channel; specifically, the goal is to minimize the following formula:

[0068] .

[0069] in, For the i The objective function value of the time channel, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

[0070] The present invention is further described in detail below with reference to a specific embodiment.

[0071] First, prepare the measured transient electromagnetic response of the three-layer earth model at (-10m, 150m) D=[ d 1, d 2,…, d i ,…, d 31 ], the parameters of the three-layer earth model are shown in Table 1, and the measured transient electromagnetic response is shown in Figure 2 As shown in the measured data, there are 31 time channels in total. d i For the corresponding i Time channel t i The transient electromagnetic response value.

[0072] Table 1 Parameters of the three-layer earth model

[0073]

[0074] B1. Construct a rough resistivity series in the range of 0.1~100000Ω·m according to logarithmic equal intervals. ρ 1, ρ 2,…, ρ j ,…, ρ 60 ], the sequence contains 60 rough resistivity values, according to transient electromagnetic theory, the resistivity is taken as j Rough resistivity ρ j The uniform half space is the first j rough estimated resistivity models, and 60 rough estimated resistivity models were obtained.

[0075] B2. Use the electric dipole transient electromagnetic response analytical solution and the dipole superposition method to calculate the first j A rough estimate of the resistivity model's response at different time channels:

[0076] .

[0077] Among them, the superscript est represents the transient electromagnetic response of the rough resistivity model, For the j A rough resistivity model is i The transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road, ρ j For the j A rough resistivity model.

[0078] The transient electromagnetic responses of all time channels are compared with the measured transient electromagnetic responses of the corresponding time channels, and the response deviation value of the rough resistivity model is calculated according to the following formula:

[0079] .

[0080] in, For the j A rough estimate of the response deviation of the resistivity model, m is the number of time channels, d i For the i The measured transient electromagnetic response of a time channel.

[0081] B3, the response deviation values ​​calculated in step B2 form a response deviation sequence [ δ 1, δ 2,…, δ j ,…, δ 60 ], select the number of the rough resistivity model with the smallest response deviation value in the response deviation sequence k =29, the corresponding rough resistivity value is 85.76Ω·m, the corresponding deviation value is 18.69%, and the rough response is as follows Figure 2 As shown in the rough estimate data; select the rough estimate resistivity model ρ 29 As the initial resistivity value, adjust the resistivity value and fit the transient electromagnetic data of the first three time channels using the following objective function:

[0082] .

[0083] in, is the objective function value for estimating the resistivity value, l is the number of shallow time channels, l < m , d i For the i The measured transient electromagnetic response of the time channel, For the i In this embodiment, the Gauss-Newton method is used to minimize the above objective function to obtain the estimated resistivity value. ρ r =92.73Ω·m.

[0084] B4. Based on the detailed resistivity value, the detailed resistivity initial value of each time channel is calculated. In this embodiment, the detailed resistivity initial value of each time channel is calculated according to the following formula:

[0085] .

[0086] in, ρ si For the i The initial resistivity value of the time channel is estimated. ρ r To estimate the resistivity value, d i For the i The measured transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i The initial resistivity curve is shown in the figure below. Figure 3 shown.

[0087] B5. For any time channel, sequentially fit the transient electromagnetic response of the time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the final selected resistivity initial value of the time channel. Specifically, the goal is to minimize the following formula:

[0088] .

[0089] in, For the i The objective function value of the time channel, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

[0090] In this embodiment, the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, and the final selected resistivity initial value of the time channel is obtained. The final global apparent resistivity curve is as follows: Figure 4 As shown, it reflects the shallow resistivity value and deep electrical property change law of the earth more completely and accurately. Figure 5 The global apparent resistivity curve obtained using a traditional iterative initialization method for global apparent resistivity is shown, along with a comparison with the results obtained using this application. It can be seen that the two are generally close, but the curve obtained using the traditional method is less smooth and has some jumps. The global apparent resistivity curve calculated using this application's initialization method is more continuous and accurate, avoiding the jumps found in the traditional method and effectively reflecting the changing patterns of the earth's electrical properties.

[0091] By optimizing the iterative initial value setting method for the global apparent resistivity definition, this application can effectively obtain estimated values ​​of the apparent resistivity of different time channels, making the iterative initial value close to the true value, ensuring the accuracy of the iteration direction, and obtaining the correct global apparent resistivity value; the solution proposed in this application can effectively solve the problems of jump points and unevenness in the global apparent resistivity curve caused by unreasonable iterative initial value setting, improve the reliability of the global apparent resistivity definition, and provide highly reliable global apparent resistivity values ​​for subsequent analysis and interpretation.

[0092] Based on the same inventive concept, the embodiment of the present application also provides a system for implementing the above-mentioned method for iteratively setting the initial value of the global apparent resistivity. The solution provided by the system is similar to the solution described in the above-mentioned method. In an exemplary embodiment, Figure 6 As shown in FIG, a global apparent resistivity iterative initial value setting system is provided, which includes the following functional modules:

[0093] The rough-estimated resistivity model construction module is used to select a number of rough-estimated resistivities within a preset resistivity range at equal logarithmic intervals and construct a number of rough-estimated resistivity models.

[0094] The response deviation value determination module is used to calculate the transient electromagnetic response of the rough estimated resistivity model at different time channels for any rough estimated resistivity model, and compare it with the measured transient electromagnetic response of the corresponding time channel to obtain the response deviation value of the rough estimated resistivity model.

[0095] The refined resistivity determination module is used to use the rough resistivity model with the lowest response deviation value as the initial resistivity value, fit the transient electromagnetic response of several shallow time channels, and minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain the refined resistivity value.

[0096] The module for determining the initial value of the fine-estimated resistivity is used to calculate the initial value of the fine-estimated resistivity of each time channel based on the fine-estimated resistivity value.

[0097] The final selected resistivity initial value determination module is used to fit the transient electromagnetic response of any time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the final selected resistivity initial value of the time channel.

[0098] The above-mentioned solution provided in this application makes a rough estimate of the initial apparent resistivity based on all time channel data of a single measuring point. On this basis, a detailed estimate of the initial apparent resistivity is made using multiple time channels, and then the initial resistivity value of each time channel is calculated. Finally, the obtained initial resistivity value is used to define the global apparent resistivity, and accurate global apparent resistivity values ​​on different time channels are obtained. This eliminates the problems of uneven curves and jump points caused by unreasonable initial value selection in the traditional global apparent resistivity definition, and provides highly reliable global apparent resistivity data for transient electromagnetic data analysis and interpretation.

[0099] certainly, Figure 6 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different functions. Figure 6 One or at least two components of the system shown.

[0100] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, memory and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for setting the initial value of the global apparent resistivity iteration provided in the above embodiment can be implemented.

[0101] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0102] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0103] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0104] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0106] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0107] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0108] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for setting the initial value of global apparent resistivity iteration, characterized in that: include: Selecting a number of rough-estimated resistivities within a preset resistivity range at equal logarithmic intervals, and constructing a number of rough-estimated resistivity models; For any rough-estimated resistivity model, calculating the transient electromagnetic response of the rough-estimated resistivity model at different time channels, and comparing it with the measured transient electromagnetic response of the corresponding time channels to obtain a response deviation value of the rough-estimated resistivity model; The rough resistivity model with the lowest response deviation is used as the initial resistivity value. The transient electromagnetic responses of several shallow time channels are fitted to minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel, and the fine resistivity value is obtained. Based on the refined resistivity value, an initial refined resistivity value of each time channel is calculated; For any time channel, fitting the transient electromagnetic response of the time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the final selected initial resistivity value of the time channel; Several rough resistivities are selected at equal logarithmic intervals within the preset resistivity range, and several rough resistivity models are constructed, including: Select several rough resistivities within the preset resistivity range at equal logarithmic intervals; For any rough-estimated resistivity, according to transient electromagnetic theory, a uniform half-space with a resistivity equal to the rough-estimated resistivity is taken as a rough-estimated resistivity model of the corresponding rough-estimated resistivity; The goal is to minimize the following formula to obtain a detailed resistivity value: ； in, is the objective function value for estimating the resistivity value, l is the number of shallow time channels, l < m , m is the number of time channels, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

2. The method for setting the initial value of global apparent resistivity iteration according to claim 1, characterized in that: The transient electromagnetic response of the rough resistivity model at different time channels is calculated according to the following formula: ； Among them, the superscript est represents the transient electromagnetic response of the rough resistivity model, For the j A rough resistivity model is i The transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road, ρ j For the j A rough resistivity model; The response deviation value of the rough resistivity model is calculated according to the following formula: ； in, For the j A rough estimate of the response deviation of the resistivity model, m is the number of time channels, d i For the i The measured transient electromagnetic response of a time channel.

3. The method for setting the initial value of global apparent resistivity iteration according to claim 1, characterized in that: The initial value of the detailed resistivity of each time channel is calculated according to the following formula: ； in, ρ si For the i The initial resistivity value of the time channel is estimated. ρ r To estimate the resistivity value, d i For the i The measured transient electromagnetic response of the time channel, F is the transient electromagnetic response function, t i For the i A time road.

4. The method for setting the initial value of global apparent resistivity iteration according to claim 1, characterized in that: The final selected resistivity initial value of the time channel is obtained with the goal of minimizing the following formula: ； in, For the i The objective function value of the time channel, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

5. The method for setting the initial value of global apparent resistivity iteration according to claim 1, characterized in that: The Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the transient electromagnetic response prediction value of the corresponding time channel to obtain a refined resistivity value; the Gauss-Newton method is used to minimize the difference between the measured transient electromagnetic response and the transient electromagnetic response prediction value of the time channel as the target to obtain the final selected resistivity initial value of the time channel.

6. A global apparent resistivity iterative initial value setting system, characterized by: include: A rough resistivity model construction module is used to select a number of rough resistivities within a preset resistivity range at equal logarithmic intervals and construct a number of rough resistivity models; a response deviation value determination module, configured to calculate, for any rough-estimated resistivity model, the transient electromagnetic response of the rough-estimated resistivity model at different time channels, and compare the calculated transient electromagnetic response with the measured transient electromagnetic response of the corresponding time channel to obtain a response deviation value of the rough-estimated resistivity model; The refined resistivity determination module is used to use the rough resistivity model with the lowest response deviation as the initial resistivity value, fit the transient electromagnetic response of several shallow time channels, and minimize the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the corresponding time channel to obtain the refined resistivity value; A module for determining a fine-estimated resistivity initial value is configured to calculate a fine-estimated resistivity initial value for each time channel based on the fine-estimated resistivity value; A module for determining the initial value of the final selected resistivity is used to fit the transient electromagnetic response of any time channel, with the goal of minimizing the difference between the measured transient electromagnetic response and the predicted transient electromagnetic response of the time channel, to obtain the initial value of the final selected resistivity of the time channel; The rough resistivity estimation model construction module is specifically used to: Select several rough resistivities within the preset resistivity range at equal logarithmic intervals; For any rough-estimated resistivity, according to transient electromagnetic theory, a uniform half-space with a resistivity equal to the rough-estimated resistivity is taken as a rough-estimated resistivity model of the corresponding rough-estimated resistivity; The goal is to minimize the following formula to obtain a detailed resistivity value: ； in, is the objective function value for estimating the resistivity value, l is the number of shallow time channels, l < m , m is the number of time channels, d i For the i The measured transient electromagnetic response of the time channel, For the i The predicted value of transient electromagnetic response of each time channel.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for setting the initial value of the global apparent resistivity iteration according to any one of claims 1 to 5.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for setting the initial value of the global apparent resistivity iteration according to any one of claims 1 to 5 is implemented.

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