A data processing method for time-lapse high-density electrical prospecting and related equipment

Abstract

The application provides a data processing method for time-lapse high-density electrical prospecting and related equipment. After reading data of time-lapse high-density electrical prospecting and obtaining apparent resistivity information of multiple time sections, correction is performed on each two adjacent time sections to obtain corrected time sections. The multiple corrected time sections are connected to obtain continuous sections. Based on the continuous sections, a target geological body is determined. The apparent resistivity information of a first time section and the apparent resistivity information of a second time section are determined according to the target geological body. The second time section is corrected according to a target correction coefficient to obtain a time-lapse high-density electrical inversion resistivity change distribution map. Through twice correction, interference of internal and external environmental factors is overcome. The time-lapse high-density electrical inversion resistivity change distribution map is beneficial to finding subtle geological changes and discovering new geological disaster sources.

Description

Technical Field

[0001] This invention belongs to the field of geological disaster evolution law analysis and disaster-causing capacity assessment, and particularly relates to a data processing method and related equipment for time-shifted high-density electrical resistivity tomography. Background Technology

[0002] Time-shift high-density electrical resistivity tomography (OTT) is an emerging technology that involves measuring the same geological target multiple times within a certain time interval to obtain information on changes in the physical properties of the geological target. The key to this technology is maintaining consistency, which includes: the same measurement location, the same methods and instruments, the same instrument parameters and settings, and the same data processing procedures and parameters.

[0003] Currently, time-shift high-density electrical resistivity tomography (ETS) is typically used to process a single time section in order to improve the reliability of the results for a single measurement line.

[0004] However, for different time sections, factors such as instruments and environment can still interfere with the results of long-distance measurements. Summary of the Invention

[0005] In view of the above problems, this application proposes a data processing method and related equipment for time-shifted high-density electrical resistivity tomography. To solve the interference caused by instrument and environmental factors on the results of long survey lines, the specific solution is as follows:

[0006] 1. A data processing method for time-shifted high-density electrical resistivity tomography, characterized in that it includes:

[0007] Data from time-shifted high-density electrical resistivity surveys were read to obtain apparent resistivity information for multiple time sections;

[0008] For every two adjacent time segments, the overlapping area is determined and processed to obtain a correction coefficient. Based on the correction coefficient, one time segment is used as a reference to correct the other time segment, resulting in a corrected time segment.

[0009] Multiple corrected time sections are connected to obtain a continuous section.

[0010] Based on the continuous cross sections, the target geological body is determined, and the apparent resistivity information of the first time section and the apparent resistivity information of the second time section are determined according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0011] Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, a target correction coefficient is determined, and the second time section is corrected according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion distribution map.

[0012] Optionally, processing the overlapping region to obtain the correction coefficient includes:

[0013] The apparent resistivity information of the overlapping regions is subjected to ordered grouping and clustering to obtain ordered grouping information;

[0014] Calculate the standard deviation vector and mean of the ordered grouping information;

[0015] The correction coefficient is determined based on the standard deviation vector and the mean of the ordered grouping information.

[0016] Optionally, the step of performing ordered grouping and clustering of the apparent resistivity information of the overlapping regions to obtain ordered grouping information includes:

[0017] The apparent resistivity information of the overlapping region is processed to obtain the grouped diameter matrix;

[0018] Establish a loss function matrix and a split point matrix with the same latitude as the grouping diameter matrix;

[0019] Based on the loss function matrix and the point matrix, a trend graph of the loss function change is plotted, and the ordered grouping information is determined.

[0020] Optionally, the step of connecting multiple corrected time sections to obtain continuous sections includes:

[0021] Determine the Cartesian coordinate system;

[0022] The multiple corrected time sections are projected onto the Cartesian coordinate system to obtain spatial location and mean data;

[0023] The spatial location and the mean data are written into a preset cross-section file according to the rules required by the inversion software to obtain the continuous cross-section.

[0024] Optionally, determining the apparent resistivity information of the first time section and the apparent resistivity information of the second time section based on the target geological body includes:

[0025] Based on the target geological body, determine the boundary line of the target geological body;

[0026] Based on the boundary line of the target geological body, the apparent resistivity information of the target is defined;

[0027] The apparent resistivity information of the first time section and the apparent resistivity information of the second time section are filtered from the target apparent resistivity information.

[0028] Optionally, determining the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section includes:

[0029] Calculate the standard deviation vector and mean of the first time segment;

[0030] Calculate the standard deviation vector and mean of the second time section;

[0031] The target correction coefficient is determined based on the standard deviation vector and mean of the first time segment, and the standard deviation vector and mean of the second time segment.

[0032] Optionally, the second time section is corrected according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion distribution map, including:

[0033] The second time section is corrected according to the target correction coefficient to obtain the corrected second time section;

[0034] Two-dimensional high-density electrical resistivity tomography is performed on the first time section and the corrected second time section to obtain the difference section.

[0035] Based on the first time section and the difference section, a time-shifted high-density electrical resistivity inversion distribution map is plotted.

[0036] A data processing device for time-shifted high-density electrical resistivity tomography includes:

[0037] The reading unit is used to read data from time-shifted high-density electrical resistivity exploration to obtain apparent resistivity information for multiple time sections;

[0038] The first correction unit is used to determine the overlapping area for every two adjacent time sections, process the overlapping area to obtain a correction coefficient, and correct another time section based on the correction coefficient, so as to obtain the corrected time section.

[0039] The connecting unit is used to connect multiple corrected time sections to obtain a continuous section;

[0040] The determining unit is used to determine the target geological body based on the continuous cross section, and to determine the apparent resistivity information of the first time section and the apparent resistivity information of the second time section according to the target geological body, wherein the first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0041] The second correction unit is used to determine the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, and to correct the second time section according to the target correction coefficient to obtain the time-shifted high-density electrical resistivity inversion distribution map.

[0042] A data processing device for time-shifted high-density electrical resistivity tomography includes a memory and a processor;

[0043] The memory is used to store programs;

[0044] The processor is used to execute the program to implement each step of the data processing method for time-shifted high-density electrical resistivity tomography as described in any of the preceding claims.

[0045] A readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the various steps of the data processing method for time-shifted high-density electrical resistivity tomography as described in any of the preceding claims.

[0046] Based on the above technical solution, the present invention provides a data processing method and related equipment for time-shifted high-density electrical resistivity prospecting. After reading the data from the time-shifted high-density electrical resistivity prospecting and obtaining the apparent resistivity information of multiple time sections, for every two adjacent time sections, an overlapping region is determined, and the overlapping region is processed to obtain a correction coefficient. Based on the correction coefficient, one time section is used as a reference to correct another time section, resulting in a corrected time section. Multiple corrected time sections are connected to obtain a continuous section. Based on the continuous section, the target geological body is determined, and the data is then processed according to the target geological body. Apparent resistivity information of the first time section and the second time section are determined. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold. Based on the apparent resistivity information of the first time section and the second time section, the target correction coefficient is determined. According to the target correction coefficient, the second time section is corrected to obtain the resistivity change distribution map obtained by time-shifting high-density electrical resistivity inversion. The two corrections overcome the interference of internal and external environmental factors. Moreover, the resistivity change distribution map obtained by time-shifting high-density electrical resistivity inversion is conducive to discovering subtle geological changes and new sources of geological hazards. Attached Figure Description

[0047] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0048] Figure 1This is a schematic flowchart of a data processing method for time-shifted high-density electrical resistivity tomography disclosed in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of a multiple overlapping region disclosed in an embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram illustrating a method for processing overlapping regions to obtain correction coefficients, as disclosed in an embodiment of the present invention.

[0051] Figure 4 This is a schematic diagram illustrating a method for processing overlapping regions to obtain correction coefficients, as disclosed in an embodiment of the present invention.

[0052] Figure 5 This is a trend graph of the loss function disclosed in an embodiment of the present invention;

[0053] Figure 6 This is a schematic diagram of a method for connecting multiple corrected time sections to obtain a continuous section, as disclosed in an embodiment of the present invention.

[0054] Figure 7 This is an inversion diagram of an uncorrected continuous cross-section disclosed in an embodiment of the present invention;

[0055] Figure 8 This is an inversion diagram of a corrected continuous cross-section disclosed in an embodiment of the present invention;

[0056] Figure 9 This is a schematic diagram illustrating the process of a method for determining the apparent resistivity information of a first time section and the apparent resistivity information of a second time section of a target geological body, as disclosed in an embodiment of the present invention.

[0057] Figure 10 This is a schematic diagram of a method for determining a target correction coefficient based on apparent resistivity information of a first time section and apparent resistivity information of a second time section, as disclosed in an embodiment of the present invention.

[0058] Figure 11 This is a schematic diagram of a method for correcting a second time section according to a target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion resistivity variation distribution map according to an embodiment of the present invention.

[0059] Figure 12 This is a schematic diagram illustrating the resistivity variation of a target geological body as disclosed in an embodiment of the present invention;

[0060] Figure 13 This is a schematic diagram of the structure of a data processing device for time-shifted high-density electrical resistivity tomography disclosed in an embodiment of the present invention;

[0061] Figure 14This is a hardware structure block diagram of a data processing device for time-shifted high-density electrical resistivity tomography disclosed in an embodiment of the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the description of embodiments of the invention. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of units is not necessarily limited to those units, but may include other units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0064] To address the interference caused by instrument and environmental factors on the results of long survey lines, this invention provides a data processing method for time-shifted high-density electrical resistivity tomography. The data processing method for time-shifted high-density electrical resistivity tomography provided by this invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0065] Please see the appendix Figure 1 , Figure 1 This is a flowchart illustrating a data processing method for time-shifted high-density electrical resistivity tomography (EDT) according to an embodiment of the present invention. The method may include the following steps:

[0066] Step S101: Read the data from time-shifted high-density electrical resistivity survey to obtain the apparent resistivity information of multiple time sections.

[0067] For ease of understanding, the following example illustrates this: assume there are multiple time sections C. s1 C s2 ...C sn .

[0068] Step S102: For every two adjacent time sections, determine the overlapping area, process the overlapping area to obtain the correction coefficient, and based on the correction coefficient, use one time section as a reference to correct the other time section to obtain the corrected time section.

[0069] In this application, the overlapping region can be processed according to the least squares method to obtain the scaling factor and offset factor. Based on the selected time section, the time sections that are connected to it and overlap in the same way are corrected to obtain the corrected time section.

[0070] For ease of understanding, the following are examples of these time cross-sections C. s1 C s2 ...C sn Distributed from left to right and overlapping in the same way, with C s1 Based on this, the remaining cross-sections are corrected according to the following steps:

[0071] 3.1 Let k = 1, C1 = C sk C2 = C s(k+1) ;

[0072] 3.2 Find the overlapping region C of C1 and C2. L and C R Obtain the corresponding grouping information and establish the standard deviation vector M. σL M σR Calculate the mean μ of the overlapping region. R μ L Calculate the correction coefficients a and b according to the formula;

[0073] 3.3 According to the formula Find the correction value for C2. make Let k = k + 1, and let C2 = C s(k+1) ;

[0074] 3.4 If k <= n, jump to 3.2; otherwise, continue with the series obtained in step 3.3. That is, C s2 ...C sn The program will exit once the correction value is found.

[0075] Step S103: Connect multiple corrected time sections to obtain a continuous section.

[0076] In this application, if the overlap method is 3 / 4 overlap, please refer to... Figure 2 , Figure 2 A schematic diagram of multiple overlapping regions is disclosed. As can be seen from the figure, there are four types of overlapping regions in the detection profile, which represent the number of times the measurement data is repeated in these regions. Although these data have been corrected in step S102, they are still not completely the same. Therefore, when splicing individual time sections into a continuous section, it is necessary to perform a position-based averaging operation on the data in the overlapping regions, and then use the average value to replace the original value.

[0077] Step S104: Based on the continuous cross-section, determine the target geological body, and determine the apparent resistivity information of the first time section and the apparent resistivity information of the second time section according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0078] In this application, the layered apparent resistivity information of the first time section is geological cross-section information obtained at an earlier time, denoted as C. B The layered apparent resistivity information of the second time section is geological section information obtained at a later time, denoted as C. F .

[0079] Step S105: Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, determine the target correction coefficient, and correct the second time section according to the target correction coefficient to obtain the time-shifted high-density electrical resistivity inversion resistivity variation distribution map.

[0080] In this application, the data, after undergoing two correction processes, were inverted and then processed by calculating the difference, the relative rate of change, and normalization, and a time-shifted high-density electrical resistivity inversion resistivity variation distribution map was plotted. The details will be explained in detail through the following embodiments, and will not be elaborated here.

[0081] In summary, the data processing method for time-lapse high-density electrical resistivity prospecting provided by this invention involves reading the data and obtaining the apparent resistivity information of multiple time sections. For every two adjacent time sections, an overlapping region is identified and processed to obtain a correction coefficient. Based on this correction coefficient, another time section is corrected using one time section as a reference to obtain a corrected time section. Multiple corrected time sections are then connected to obtain a continuous section. Based on the continuous section, the target geological body is identified, and a first time section is determined according to the target geological body. The apparent resistivity information of the first time section and the apparent resistivity information of the second time section are obtained. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold. Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, the target correction coefficient is determined. According to the target correction coefficient, the second time section is corrected to obtain the resistivity change distribution map obtained by time-shifting high-density electrical resistivity inversion. The interference of internal and external environmental factors is overcome by the two corrections. Moreover, the resistivity change distribution map obtained by time-shifting high-density electrical resistivity inversion is conducive to discovering subtle geological changes and new geological hazard sources.

[0082] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation method of processing the overlapping region in step S102 to obtain the correction coefficient is described in detail.

[0083] As one possible implementation method, please refer to the appendix. Figure 3 This is a schematic diagram illustrating a method for processing overlapping regions to obtain correction coefficients, as disclosed in this invention. The method may include the following steps:

[0084] Step S201: Perform ordered grouping and clustering of the apparent resistivity information of the overlapping regions to obtain ordered grouping information.

[0085] In this application, the apparent resistivity information of overlapping regions is grouped and clustered in an orderly manner to obtain the optimal grouping. The details will be explained in detail through the following embodiments, and will not be elaborated here.

[0086] Step S202: Calculate the standard deviation vector and mean of the ordered group information.

[0087] In this application, based on the ordered grouping information, the standard deviation σ of each hierarchical group is calculated, and a standard deviation vector M is established. σL M σR And determine the mean μ R μ L :

[0088]

[0089] Step S203: Determine the correction coefficients based on the standard deviation vector and mean of the ordered grouping information.

[0090] In this application, the scaling factor a and the offset factor b can be obtained using the following formula based on the least squares method:

[0091]

[0092] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation method of step S201, which performs ordered grouping and clustering of the apparent resistivity information of the overlapping regions to obtain ordered grouping information, is described in detail.

[0093] As one possible implementation method, please refer to the appendix. Figure 4 This is a schematic diagram illustrating a method for processing overlapping regions to obtain correction coefficients, as disclosed in this invention. The method may include the following steps:

[0094] Step S301: Process the apparent resistivity information of the overlapping region to obtain the grouped diameter matrix.

[0095] In this application, the stratigraphic data point set L for obtaining apparent resistivity information of the overlapping region is first obtained. n , The median of the point set is given if the number of data points in the point set is n. t , respectively Then L nThe sum of squared deviations is S n : If the overlapping region has l t For each level, for natural numbers i and j, 1 ≤ i ≤ j ≤ l t Using group G ij This represents the data from layer i to layer j. G represents ij The mean of the sum of squared deviations of the data in each layer is used to establish l. t line l t A matrix of all zeros in columns, according to the formula Rearrange the matrix at row i and column j to D(i,j) to obtain matrix M. D This is called the grouped diameter matrix.

[0096] Step S302: Establish the loss function matrix and the split point matrix at the same latitude as the grouping diameter matrix.

[0097] In this application, L(n,k) can be used to represent the loss function when n data points are divided into k groups, and we have

[0098]

[0099] Use M L Let M represent the loss function matrix corresponding to L(n,k). P This represents the partition matrix corresponding to L(n,k). The row numbers of these two matrices both represent the number of data points n, and the column numbers both represent the grouping k. M L The content of the element in M ​​represents the loss value when n data points are divided into k groups. P The element in the array represents the first data number of the last group when n data are divided into k groups.

[0100] According to M D Based on equation (1), matrix M is constructed using the following steps. L and M P :

[0101] 1.1 Enter M D Establish with M D A zero matrix M of the same dimension L and M P .

[0102] 1.2 Let k = 2, then transfer 2 to l t Assign natural numbers to n in sequence. For any value of n, list the possible ways to divide all the first n data into two groups: {1,j-1} and {j,n}. Query M. D Obtain the diameters D(1,j-1) and D(j,n) of each group, and calculate the sum of the diameters of these groups, D(1,j-1)+D(j,n). Write the minimum sum of diameters into M. LAt row n, column 2, and write the starting point j of the group D(j,n) with the smallest diameter into M. P At the position in row n, column 2.

[0103] 1.3 Let k = k + 1, then transfer k + 1 to l t Assign natural numbers to n in sequence. For any value of n, list the possible ways to divide all the first n data into two groups: {1,j-1} and {j,n}. For the group {1,j-1}, query M. L To obtain the loss function L(j-1,k-1) when the data is divided into k-1 groups, for group {j,n}, query M. D Obtain D(j,n), calculate L(j-1,k-1)+D(j,n), and write the minimum value of L(j-1,k-1)+D(j,n) into M. L At row n, column k, and write the starting point j of the group D(j,n) where L(j-1,k-1)+D(j,n) reaches its minimum value into M. P At row n, column k.

[0104] 1.4 If k <l t Enter 1.3, otherwise the program will exit.

[0105] Step S303: Based on the loss function matrix and the split point matrix, plot the trend of the loss function change and determine the ordered grouping information.

[0106] In this application, M can be taken. L The last line discards the first data point, resulting in the n data points being divided into numbers 2 to l. t The loss value of the group, with the loss value on the ordinate, and plotted from 2 to l. t Using the x-axis as the horizontal axis, plot the trend of the loss function, identify the inflection point of the trend, and, following the principle of minimizing grouping, select the x-axis of data points that are close to the inflection point and have relatively small values ​​to obtain the ordered grouping information k. c .

[0107] Please refer to [the website / reference] for easier understanding. Figure 5 , Figure 5 This is a trend graph of a loss function, where the horizontal axis represents the number of classes and the vertical axis represents the loss.

[0108] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation method of connecting multiple corrected time sections to obtain continuous sections in step S103 is described in detail.

[0109] As one possible implementation method, please refer to the appendix. Figure 6This is a schematic diagram illustrating a method disclosed in this invention for connecting multiple corrected time sections to obtain a continuous section. The method may include the following steps:

[0110] Step S401: Determine the Cartesian coordinate system.

[0111] In this application, section C can be used. s1 The location of the first electrode is taken as the origin of the coordinate system, and the straight line intersecting the plane of the cross section is taken as the abscissa. A Cartesian coordinate system is established.

[0112] Step S402: Project multiple corrected time sections onto a Cartesian coordinate system to obtain spatial location and mean data.

[0113] As one possible implementation method, the overlap is 1 / 2 overlap, using F v C represents the region with an overlap of number v, where v = 1 to 4. d R represents the spatial coordinates of each data point. v (C d ) indicates in C d For the data corresponding to the v-th overlapping section, the operation to calculate the mean is as follows:

[0114] Step S403: Write the spatial location and mean data into the preset cross-section file according to the rules required by the inversion software to obtain continuous cross-sections.

[0115] In this application, all processed data and their spatial locations can be written into a preset cross-section file according to the rules required by the inversion software, thus obtaining cross-section C. s1 C s2 ...C sn Connecting continuous sections C cnt .

[0116] For easier understanding, please refer to Figure 7 and Figure 8 , Figure 7 This is an inversion diagram of an uncorrected continuous cross-section. Figure 8 This is an inversion diagram of a corrected continuous cross-section. As can be seen from the diagram, there are differences between the two, mainly in the subtle changes in the shape of the contour lines.

[0117] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation of step S104, which determines the apparent resistivity information of the first time section and the apparent resistivity information of the second time section according to the target geological body, is described in detail.

[0118] As one possible implementation method, please refer to the appendix. Figure 9This is a schematic diagram illustrating the process of determining the apparent resistivity information of a first time section and a second time section based on a target geological body, as disclosed in this invention. The method may include the following steps:

[0119] Step S501: Determine the boundary line of the target geological body based on the target geological body.

[0120] In this application, based on continuous section C cnt Inversion results and field sampling analysis data yield typical electrical information of rocks, contact surfaces, aquifers, and fracture zones. For stable, dense, and continuous rock masses, different delineation methods are used to determine the boundary between the rock mass and the surrounding medium in the following two scenarios:

[0121] Scenario 1: Detailed geological information has been obtained through geological surveys and other means. There is no gradient zone or the gradient zone is narrow between the rock mass and the surrounding medium. The boundary line can be directly delineated based on the known geological information.

[0122] Scenario 2: When the geological information is insufficient, or although the geological information is known, there is a wide gradient zone between the rock mass and the surrounding medium. Based on the electrical information of the rock mass and the surrounding rocks, strata or structures in contact with it, the boundary value between the rock mass and the surrounding medium is selected using fuzzy clustering method to form the boundary line.

[0123] Step S502: Based on the boundary line of the target geological body, divide the target apparent resistivity information.

[0124] In this application, the apparent resistivity data within the rock mass area, i.e., the target apparent resistivity information, can be delineated using boundary lines, surface lines, or detection boundary lines.

[0125] Step S503: Filter out the apparent resistivity information of the first time section and the apparent resistivity information of the second time section from the target apparent resistivity information.

[0126] In this application, the apparent resistivity information D of the first time section can be filtered from the target apparent resistivity information using the least squares method. B1 D B1 ...D Bn Apparent resistivity information D at the second time section F1 D F1 ...D Fn .

[0127] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation method of determining the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section is described in detail.

[0128] As one possible implementation method, please refer to the appendix. Figure 10 This is a schematic diagram illustrating the process of a method for determining a target correction coefficient based on apparent resistivity information from a first time section and apparent resistivity information from a second time section, as disclosed in this invention. The method may include the following steps:

[0129] Step S601: Calculate the standard deviation vector and mean of the first time section.

[0130] In this application, according to D B1 D B1 ...D Bn Find the boundary line coordinates, calculate the standard deviation σ, and establish the standard deviation vector M. σF and mean μ B :

[0131]

[0132] Where: the character or subscript σ represents the standard deviation, and the numbers 1 to n represent the region number.

[0133] Step S602: Calculate the standard deviation vector and mean of the second time section.

[0134] In this application, according to D F1 D F1 ...D Fn Find the boundary line coordinates, calculate the standard deviation σ, and establish the standard deviation vector M. σF and mean μ F :

[0135]

[0136] Where: the character or subscript σ represents the standard deviation, and the numbers 1 to n represent the region number.

[0137] Step S603: Determine the target correction coefficient based on the standard deviation vector and mean of the first time section and the standard deviation vector and mean of the second time section.

[0138] In this application, the scaling factor a′ and the offset factor b′ can be obtained using the least squares method and the following formula:

[0139]

[0140] Based on the embodiments disclosed in the present invention above, in another embodiment of the present invention, the specific implementation method of step S105, which corrects the second time section according to the target correction coefficient to obtain the time-shifted high-density electrical resistivity inversion distribution map, is described in detail.

[0141] As one possible implementation method, please refer to the appendix. Figure 11This is a schematic diagram illustrating a method disclosed in this invention for correcting a second time section based on a target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion resistivity variation distribution map. The method may include the following steps:

[0142] Step S701: Correct the second time section according to the target correction coefficient to obtain the corrected second time section.

[0143] Step S702: Perform two-dimensional high-density electrical resistivity tomography on the first time section and the corrected second time section to obtain the difference section.

[0144] In this application, the first time section C B and the corrected second time section Two-dimensional high-density electrical resistivity inversion is performed. Based on the inverted cross-sectional resistivity information, a first-time cross-sectional matrix W containing both location and resistivity information is established. B and the corrected second time section matrix W F And obtain the difference cross-sectional matrix W including location information. FB W B and W F All are matrices of the same size, each with 3 columns, W B and W F The first two columns are identical, both being the x and y coordinates of the data points. The third column stores the resistivity of the rock at the corresponding locations in the first two columns.

[0145] Among them, the difference section matrix W FB The method for establishing it is: establish a connection with W B Matrix W with identical content size FB W FB The third column equals W B Subtract W from the third column F The third column.

[0146] Step S703: Based on the first time section and the difference section, plot the resistivity variation distribution map obtained by time-shifted high-density electrical resistivity inversion.

[0147] In this application, based on the difference section matrix W FB The resistivity difference in the first time section matrix W B The resistivity ratios in the matrix are used to derive the resistivity relative change rate matrix W. rlt , for W rlt After normalization, the normalized resistivity relative change rate matrix W is obtained. nrm , matrix W nrmThe data was interpolated using the linear interpolation triangulation method to plot the resistivity changes of the cross-section over a long period of time. The speed and extent of geological changes were determined by the size and density of the contour lines.

[0148] For easier understanding, please refer to Figure 12 , Figure 12 This is a schematic diagram of the resistivity change of a target geological body. The processed inversion results highlight the resistivity change of the geological body over a period of time.

[0149] Among them, the resistivity relative change rate matrix W rlt The method for establishing it is: establish a connection with W B Matrix W with identical content size rlt W rlt The element at any position in the third column is equal to W. FB The element at the same position in the third column divided by W B The elements in the same position of the third column; matrix W nrm The process of establishing W is as follows: rlt The maximum value R in the third column max Minimum value R min The difference between the maximum and minimum values, R diff Establish with W rlt Matrix W with identical content size nrm W nrm Each element in the third column is subtracted from R. min The difference obtained is then divided by R. diff The result overwrites the original value.

[0150] The methods described in the above-disclosed embodiments of the present invention are detailed. The methods of the present invention can be implemented by various forms of devices. Therefore, the present invention also discloses a data processing device for time-shifted high-density electrical resistivity tomography. Specific embodiments are given below for detailed description.

[0151] Please see the appendix Figure 13 , Figure 13 This is a schematic diagram of a data processing apparatus for time-shifted high-density electrical resistivity tomography disclosed in an embodiment of this application. The apparatus includes:

[0152] The reading unit 11 is used to read the data from time-shifted high-density electrical resistivity exploration and obtain the apparent resistivity information of multiple time sections;

[0153] The first correction unit 12 is used to determine the overlapping area for every two adjacent time sections, process the overlapping area to obtain a correction coefficient, and correct another time section based on the correction coefficient to obtain the corrected time section.

[0154] Connection unit 13 is used to connect multiple corrected time sections to obtain a continuous section;

[0155] The determining unit 14 is used to determine the target geological body based on the continuous cross section, and to determine the apparent resistivity information of the first time section and the apparent resistivity information of the second time section according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0156] The second correction unit 15 is used to determine a target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, and to correct the second time section according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion resistivity variation distribution map.

[0157] As one possible implementation, the first correction unit 12 includes:

[0158] The grouping subunit is used to perform ordered grouping and clustering of the apparent resistivity information of the overlapping region to obtain ordered grouping information.

[0159] The calculation subunit is used to calculate the standard deviation vector and mean of the ordered grouping information.

[0160] The first determining subunit is used to determine the correction coefficient based on the standard deviation vector and the mean of the ordered grouping information.

[0161] As one possible implementation, the grouping subunit includes:

[0162] The processing subunit is used to process the apparent resistivity information of the overlapping region to obtain the grouped diameter matrix.

[0163] Establish sub-units to create loss function matrices and point matrices with the same latitude as the grouping diameter matrix.

[0164] The first drawing subunit is used to draw a trend graph of the loss function based on the loss function matrix and the point matrix, and to determine the ordered grouping information.

[0165] As one possible implementation, the connection unit 13 includes:

[0166] The second defining sub-unit is used to define the Cartesian coordinate system.

[0167] The projection subunit is used to project the multiple corrected time sections onto the Cartesian coordinate system to obtain spatial position and mean data.

[0168] The writing sub-unit is used to write the spatial location and the mean data into a preset cross-section file according to the rules required by the inversion software, so as to obtain the continuous cross-section.

[0169] As one possible implementation, the determining unit 14 includes:

[0170] The third determining subunit is used to determine the boundary line of the target geological body based on the target geological body.

[0171] Sub-units are used to divide the apparent resistivity information of the target geological body based on the boundary line of the target geological body.

[0172] The filtering subunit is used to filter out the apparent resistivity information of the first time section and the apparent resistivity information of the second time section from the target apparent resistivity information.

[0173] As one possible implementation, the second correction unit 15 includes:

[0174] The first calculation subunit is used to calculate the standard deviation vector and mean of the first time section.

[0175] The second calculation subunit is used to calculate the standard deviation vector and mean of the second time section.

[0176] The fourth determining subunit is used to determine the target correction coefficient based on the standard deviation vector and mean of the first time section and the standard deviation vector and mean of the second time section.

[0177] As one possible implementation, the second correction unit 15 includes:

[0178] The correction subunit is used to correct the second time section according to the target correction coefficient to obtain the corrected second time section.

[0179] The inversion subunit is used to perform two-dimensional high-density electrical resistivity tomography (EDT) inversion on the first time section and the corrected second time section to obtain the difference section.

[0180] The second plotting subunit is used to plot a time-shifted high-density electrical resistivity inversion distribution map based on the first time section and the difference section.

[0181] Reference Figure 14 , Figure 14 The hardware structure block diagram of the data processing device for time-shifted high-density electrical resistivity tomography provided in this application embodiment may include: at least one processor 1, at least one communication interface 2, at least one memory 3, and at least one communication bus 4.

[0182] In this embodiment, the number of processor 1, communication interface 2, memory 3, and communication bus 4 is at least one, and processor 1, communication interface 2, and memory 3 communicate with each other through communication bus 4.

[0183] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0184] Memory 3 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0185] The memory stores a program, which the processor can call. The program is used for:

[0186] Data from time-shifted high-density electrical resistivity surveys were read to obtain apparent resistivity information for multiple time sections;

[0187] For every two adjacent time segments, the overlapping area is determined and processed to obtain a correction coefficient. Based on the correction coefficient, one time segment is used as a reference to correct the other time segment, resulting in a corrected time segment.

[0188] Multiple corrected time sections are connected to obtain a continuous section.

[0189] Based on the continuous cross sections, the target geological body is determined, and the apparent resistivity information of the first time section and the apparent resistivity information of the second time section are determined according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0190] Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, a target correction coefficient is determined, and the second time section is corrected according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion distribution map.

[0191] Optionally, the refined and extended functions of the program can be found in the description above.

[0192] This application embodiment also provides a readable storage medium that can store a program suitable for execution by a processor, the program being used for:

[0193] Data from time-shifted high-density electrical resistivity surveys were read to obtain apparent resistivity information for multiple time sections;

[0194] For every two adjacent time segments, the overlapping area is determined and processed to obtain a correction coefficient. Based on the correction coefficient, one time segment is used as a reference to correct the other time segment, resulting in a corrected time segment.

[0195] Multiple corrected time sections are connected to obtain a continuous section.

[0196] Based on the continuous cross sections, the target geological body is determined, and the apparent resistivity information of the first time section and the apparent resistivity information of the second time section are determined according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold.

[0197] Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, a target correction coefficient is determined, and the second time section is corrected according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion distribution map.

[0198] Optionally, the refined and extended functions of the program can be found in the description above.

[0199] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0200] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0201] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware, and of course, it can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memory, special components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for the present invention, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, portable hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0202] In summary, the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the above embodiments, or equivalent substitutions can be made to some of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data processing method for time-shifted high-density electrical resistivity tomography, characterized in that, include: Data from time-shifted high-density electrical resistivity surveys were read to obtain apparent resistivity information for multiple time sections; For every two adjacent time segments, the overlapping area is determined and processed to obtain a correction coefficient. Based on the correction coefficient, one time segment is used as a reference to correct the other time segment, resulting in a corrected time segment. Multiple corrected time sections are connected to obtain a continuous section. Based on the continuous cross sections, the target geological body is determined, and the apparent resistivity information of the first time section and the apparent resistivity information of the second time section are determined according to the target geological body. The first time section and the second time section are in the same position and the time interval exceeds a preset threshold. The step of determining the apparent resistivity information of the first time section and the apparent resistivity information of the second time section based on the target geological body includes: Based on the target geological body, determine the boundary line of the target geological body; Based on the boundary line of the target geological body, the apparent resistivity information of the target is defined; The apparent resistivity information of the first time section and the apparent resistivity information of the second time section are filtered from the target apparent resistivity information; Based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, a target correction coefficient is determined, and the second time section is corrected according to the target correction coefficient to obtain a time-shifted high-density electrical resistivity inversion distribution map. The step of determining the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section includes: Calculate the standard deviation vector and mean of the first time segment; Calculate the standard deviation vector and mean of the second time section; The target correction coefficient is determined based on the standard deviation vector and mean of the first time segment, and the standard deviation vector and mean of the second time segment.

2. The method according to claim 1, characterized in that, The process of processing the overlapping region to obtain the correction coefficient includes: The apparent resistivity information of the overlapping regions is subjected to ordered grouping and clustering to obtain ordered grouping information; Calculate the standard deviation vector and mean of the ordered grouping information; The correction coefficient is determined based on the standard deviation vector and the mean of the ordered grouping information.

3. The method according to claim 2, characterized in that, The step of performing ordered grouping and clustering of the apparent resistivity information of the overlapping regions to obtain ordered grouping information includes: The apparent resistivity information of the overlapping region is processed to obtain the grouped diameter matrix; Establish a loss function matrix and a split point matrix with the same latitude as the grouping diameter matrix; Based on the loss function matrix and the point matrix, a trend graph of the loss function change is plotted, and the ordered grouping information is determined.

4. The method according to claim 1, characterized in that, The process of connecting multiple corrected time sections to obtain a continuous section includes: Determine the Cartesian coordinate system; The multiple corrected time sections are projected onto the Cartesian coordinate system to obtain spatial location and mean data; The spatial location and the mean data are written into a preset cross-section file according to the rules required by the inversion software to obtain the continuous cross-section.

5. The method according to claim 1, characterized in that, Based on the target correction coefficient, the second time section is corrected to obtain a time-shifted high-density electrical resistivity inversion distribution map, including: The second time section is corrected according to the target correction coefficient to obtain the corrected second time section; Two-dimensional high-density electrical resistivity tomography is performed on the first time section and the corrected second time section to obtain the difference section. Based on the first time section and the difference section, a time-shifted high-density electrical resistivity inversion distribution map is plotted.

6. A data processing device for time-shifted high-density electrical resistivity tomography, characterized in that, include: The reading unit is used to read data from time-shifted high-density electrical resistivity exploration to obtain apparent resistivity information for multiple time sections; The first correction unit is used to determine the overlapping area for every two adjacent time sections, process the overlapping area to obtain a correction coefficient, and correct another time section based on the correction coefficient, so as to obtain the corrected time section. The connecting unit is used to connect multiple corrected time sections to obtain a continuous section; The determining unit is used to determine the target geological body based on the continuous cross section, and to determine the apparent resistivity information of the first time section and the apparent resistivity information of the second time section according to the target geological body, wherein the first time section and the second time section are in the same position and the time interval exceeds a preset threshold. The step of determining the apparent resistivity information of the first time section and the apparent resistivity information of the second time section based on the target geological body includes: Based on the target geological body, determine the boundary line of the target geological body; Based on the boundary line of the target geological body, the apparent resistivity information of the target is defined; The apparent resistivity information of the first time section and the apparent resistivity information of the second time section are filtered from the target apparent resistivity information; The second correction unit is used to determine the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section, and to correct the second time section according to the target correction coefficient to obtain the time-shifted high-density electrical resistivity inversion resistivity variation distribution map. The step of determining the target correction coefficient based on the apparent resistivity information of the first time section and the apparent resistivity information of the second time section includes: Calculate the standard deviation vector and mean of the first time segment; Calculate the standard deviation vector and mean of the second time section; The target correction coefficient is determined based on the standard deviation vector and mean of the first time segment, and the standard deviation vector and mean of the second time segment.

7. A data processing device for time-shifted high-density electrical resistivity tomography, characterized in that, Including memory and processor; The memory is used to store programs; The processor is configured to execute the program and implement each step of the data processing method for time-shifted high-density electrical resistivity tomography as described in any one of claims 1 to 5.

8. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the data processing method for time-shifted high-density electrical resistivity tomography as described in any one of claims 1 to 5.

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