A method and system for removing outliers from three-dimensional high-density electrical data

Abstract

A method for removing outliers of three-dimensional high-density electrical data, comprising: arranging high-density original data in columns, respectively, coordinates of electrodes A, B, M and N, natural electric potential SP, voltage VP, current IP and resistivity RO; calculating electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized electric potential LOGUI and normalized electric potential and distance ratio LOGUIMNAB according to the high-density original data; establishing a mapping relationship between the spatial positions of data points and each measurement value according to the calculated values of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized electric potential LOGUI and normalized electric potential and distance ratio LOGUIMNAB, and drawing scatter plots of different dimensions; removing outlier data in the scatter plots according to the drawn scatter plots of different dimensions, and saving the data after removing outliers. The present application considers the spatial relationship of each data point and the physical relationship of each measurement value, and has the advantages of high efficiency and high precision.

Description

Technical Field

[0001] This invention relates to the field of electrical resistivity tomography, and in particular to a method and system for removing flying points in three-dimensional high-density electrical resistivity tomography data. Background Technology

[0002] High-density electrical resistivity tomography (ERT) is one of the most commonly used methods in electrical exploration. It involves deploying multiple sets of electrodes at once and automatically moving the electrodes through a controller, simultaneously achieving resistivity depth measurement and profile measurement. It features high measurement efficiency and high data density, especially in three-dimensional high-density electrical resistivity tomography, where the data density increases exponentially and the amount of data is extremely large.

[0003] During the acquisition of high-density electrical resistivity tomography (EPT) data, distorted and skipped points, known as "flying points," are unavoidable due to factors such as the surrounding environment, grounding conditions, and equipment instability. After data acquisition, these "flying points" must be removed before proceeding to the next processing step.

[0004] High-density electrical resistivity tomography (EPM) raw data typically includes four measurements: self-electricity SP (mV), voltage VP (mV), current IP (mA), and resistivity RO (Ω·m). Conventional "flying point" rejection uses a threshold method, which removes data points that fall outside a given range. This method does not consider the spatial relationships between data points or the physical relationships between measurements, which may lead to "missed rejections" or "excessive rejections." Furthermore, it is inefficient and inaccurate, failing to meet the needs of quality evaluation and processing of massive amounts of data from 3D high-density EPM exploration, resulting in poor processing results. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method and system for three-dimensional high-density electrical resistivity tomography (EDT) data flypoint removal that overcomes or at least partially solves the above problems.

[0006] To address the aforementioned technical problems, the embodiments of this application disclose the following technical solutions:

[0007] A method for removing flying points in three-dimensional high-density electrical resistivity tomography (OTT) data includes:

[0008] S100. The high-density raw data is sorted and arranged into columns, namely the coordinates of electrodes A, B, M, and N, the natural potential SP (mV), the voltage VP (mV), the current IP (mA), and the resistivity RO (Ω·m);

[0009] S200. Based on the high-density raw data, calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB;

[0010] S300. Based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, establish the mapping relationship between the spatial location of the data points and each measured value, and draw scatter plots in different dimensions.

[0011] S400. Based on the scatter plots drawn in different dimensions, remove outlier data from the scatter plots and save the data after removing outliers for user use.

[0012] Furthermore, in S200, the formula for calculating the distance between electrode AB and electrode AB is: AB = BA; if B is infinitely far away, then: AB = A - (M + N) / 2; if A is infinitely far away, then: AB = B - (M + N) / 2; where A, B, M, and N are their respective coordinate values.

[0013] Furthermore, in S200, the distance XAB between the midpoints of electrode AB is calculated using the formula: XAB=((A+B) / 2+(M+N) / 2) / 2; if B is infinitely far away, then: XAB=(A+(M+N) / 2) / 2; if A is infinitely far away, then XAB=(B+(M+N) / 2) / 2, where A, B, M, and N are their respective coordinate values.

[0014] Furthermore, in S200, the formula for calculating the distance MN from electrode MN is MN=abs(MN); the formula for calculating the distance XMN from the midpoint of electrode MN is XMN=(M+N) / 2; where M and N are their respective coordinate values.

[0015] Furthermore, in S200, the formula for calculating the normalized potential LOGUI is: LOGUI=real(lg(VP / IP)), where VP is the voltage value and IP is the current value.

[0016] Furthermore, in S200, the normalized potential to distance ratio LOGUIMNAB is calculated as follows: LOGUIMNAB=real(log10(VP / IP / MN / AB)), where VP is the voltage value, IP is the current value, MN is the distance between electrodes MN, and AB is the distance between electrodes AB.

[0017] Furthermore, in S300, a mapping relationship between the spatial location of data points and each measured value is established, and scatter plots of different dimensions are drawn, specifically including scatter plots of XAB-LOGUI, XAB-LOGUIMNAB, XMN-LOGUI, XMN-LOGUIMNAB, AB-LOGUI, AB-LOGUIMNAB, MN-LOGUI, and MN-LOGUIMNAB.

[0018] Furthermore, in S400, based on the scatter plots drawn in different dimensions, outlier data in the scatter plots are removed. Specifically, this includes: based on the scatter plots drawn in different dimensions, obtaining the distance between a point in the scatter plot and a standard point, comparing the obtained distance with a preset distance, and removing the point as an outlier when the obtained distance is greater than the preset distance.

[0019] This invention also discloses a system for removing flying points from three-dimensional high-density electrical resistivity tomography (EDT) data, comprising: a high-density raw data acquisition unit, a high-density raw data calculation unit, a scatter plot drawing unit for different dimensions, and a flying point data removal unit; wherein:

[0020] The high-density raw data acquisition unit is used to sort and organize the high-density raw data, which are the coordinates of electrodes A, B, M, and N, natural potential SP (mV), voltage VP (mV), current IP (mA), and resistivity RO (Ω·m).

[0021] The high-density raw data calculation unit is used to calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB based on high-density raw data.

[0022] The scatter plotting unit of different dimensions is used to establish the mapping relationship between the spatial location of data points and each measured value based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, and to plot scatter plots of different dimensions.

[0023] The Flying Point Data Removal Unit is used to remove flying point data from scatter plots of different dimensions and save the data after removing flying points for user use.

[0024] The present invention also discloses an electronic device, comprising:

[0025] Memory is used to store instructions that can be executed by the processor;

[0026] A processor for executing instructions to implement a method for flying point removal of three-dimensional high-density electrical resistivity data.

[0027] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0028] This invention discloses a method for removing flying points from three-dimensional high-density electrical resistivity tomography (EMT) data, comprising: S100. Organizing the high-density raw data into columns, namely the coordinates of electrodes A, B, M, and N, the natural potential SP (mV), the voltage VP (mV), the current IP (mA), and the resistivity RO (Ω·m); S200. Calculating the values ​​of the distance AB between electrodes AB, the distance XAB between the midpoints of electrodes AB, the distance MN between electrodes MN, the distance XMN between the midpoints of electrodes MN, the normalized potential LOGUI, and the normalized potential-to-distance ratio LOGUIMNAB based on the high-density raw data; S300. Establishing a mapping relationship between the spatial location of data points and each measured value based on the calculated values ​​of the distance AB between electrodes AB, the distance XAB between the midpoints of electrodes AB, the distance MN between electrodes MN, the distance XMN between the midpoints of electrodes MN, the normalized potential LOGUI, and the normalized potential-to-distance ratio LOGUIMNAB, and drawing scatter plots of different dimensions; S400. Removing flying point data from the scatter plots of different dimensions and saving the data after removing flying points for user use.

[0029] This invention establishes a mapping relationship between the spatial location of data points and each measured value. By drawing a scatter plot, the distribution of each data point can be seen intuitively in multiple dimensions, thereby eliminating some "flying points" that are far from the distribution area, achieving the goal of quickly and efficiently eliminating "flying points", and also providing an intuitive evaluation of data quality.

[0030] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0031] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0032] Figure 1 This is a flowchart of a method for removing flying points in three-dimensional high-density electrical resistivity data in Embodiment 1 of the present invention;

[0033] Figures 2(1)-2(8) This is a schematic diagram of drawing scatter plots in different dimensions in Embodiment 1 of the present invention. Detailed Implementation

[0034] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0035] To address the problems existing in the prior art, embodiments of the present invention provide a method and system for removing flying points from three-dimensional high-density electrical resistivity data.

[0036] Example 1

[0037] This embodiment discloses a method for removing flying points in three-dimensional high-density electrical resistivity data, such as... Figure 1 ,include:

[0038] S100. The high-density raw data is organized and divided into sections, including the coordinates of electrodes A, B, M, and N, the natural potential SP (mV), voltage VP (mV), current IP (mA), and resistivity RO (Ω·m). Specifically, the high-density electrical resistivity tomography (EDT) electrode spacing includes the power supply electrode spacing and the measurement electrode spacing. The power supply electrode spacing directly affects the detection depth, while the measurement electrode spacing affects the lateral resolution. Therefore, when designing the electrode spacing, both the detection depth and lateral resolution must be fully considered. In this embodiment, electrodes A and B are power supply electrodes, and electrodes M and N are measurement electrodes; natural potential is the electrode potential of a metal in a corrosive system without the influence of external current. Based on the detection results, the corrosivity of the soil through which the metal pipeline passes can be determined, and the general situation of corrosion under different soil environments can be understood. This is one of the main factors in evaluating the environment surrounding the pipeline.

[0039] S200. Based on the high-density raw data, calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB;

[0040] In S200 of this embodiment, the formula for calculating the distance AB from electrode AB is: AB = BA; if B is infinitely far away, then: AB = A - (M + N) / 2; if A is infinitely far away, then: AB = B - (M + N) / 2; where A, B, M, and N are their respective coordinate values.

[0041] In S200 of this embodiment, the distance XAB between the midpoints of electrodes AB is calculated using the formula: XAB=((A+B) / 2+(M+N) / 2) / 2; if B is infinitely far away, then: XAB=(A+(M+N) / 2) / 2; if A is infinitely far away, then XAB=(B+(M+N) / 2) / 2, where A, B, M, and N are their respective coordinate values.

[0042] In S200 of this embodiment, the formula for calculating the distance MN from electrode MN is MN=abs(MN); the formula for calculating the distance XMN from the midpoint of electrode MN is XMN=(M+N) / 2; where M and N are their respective coordinate values.

[0043] In S200 of this embodiment, the formula for calculating the normalized potential LOGUI is: LOGUI=real(lg(VP / IP)), where VP is the voltage value and IP is the current value.

[0044] In S200 of this embodiment, the normalized potential to distance ratio LOGUIMNAB is calculated as follows: LOGUIMNAB = real(log10(VP / IP / MN / AB)), where VP is the voltage value, IP is the current value, MN is the distance between electrodes MN, and AB is the distance between electrodes AB.

[0045] S300. Based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, establish the mapping relationship between the spatial location of the data points and each measured value, and draw scatter plots in different dimensions.

[0046] In S300 of this embodiment, a mapping relationship between the spatial location of data points and each measured value is established, and scatter plots of different dimensions are drawn, such as... Figures 2(1)-2(8) As shown, the scatter plots specifically include XAB-LOGUI, XAB-LOGUIMNAB, XMN-LOGUI, XMN-LOGUIMNAB, AB-LOGUI, AB-LOGUIMNAB, MN-LOGUI, and MN-LOGUIMNAB.

[0047] S400. Based on the scatter plots drawn in different dimensions, remove outlier data from the scatter plots and save the data after removing outliers for user use.

[0048] In S400 of this embodiment, the process of removing outlier data from scatter plots of different dimensions includes: obtaining the distance between a point in the scatter plot and a standard point, comparing the obtained distance with a preset distance, and removing the point as an outlier when the obtained distance is greater than the preset distance.

[0049] This embodiment discloses a method for removing flying points from three-dimensional high-density electrical resistivity tomography (EMT) data, including: S100. Organizing the high-density raw data into columns, namely the coordinates of electrodes A, B, M, and N, the natural potential SP (mV), voltage VP (mV), current IP (mA), and resistivity RO (Ω·m); S200. Calculating the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB based on the high-density raw data; S300. Establishing a mapping relationship between the spatial location of data points and each measured value based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, and drawing scatter plots of different dimensions; S400. Removing flying point data from the drawn scatter plots of different dimensions and saving the data after removing flying points for user use.

[0050] This embodiment establishes a mapping relationship between the spatial location of data points and each measured value. By drawing a scatter plot, the distribution of each data point can be seen intuitively in multiple dimensions, thereby eliminating some "flying points" that are far from the distribution area, achieving the goal of quickly and efficiently eliminating "flying points", and also allowing for an intuitive evaluation of data quality.

[0051] Example 2

[0052] Based on the method for removing flying points from three-dimensional high-density electrical resistivity tomography (ED tomography) data in Embodiment 1, this embodiment discloses a system for removing flying points from three-dimensional high-density EDM data, including: a high-density raw data acquisition unit, a high-density raw data calculation unit, a scatter plot drawing unit for different dimensions, and a flying point data removal unit; wherein:

[0053] The high-density raw data acquisition unit is used to sort and organize the high-density raw data, which are the coordinates of electrodes A, B, M, and N, natural potential SP (mV), voltage VP (mV), current IP (mA), and resistivity RO (Ω·m).

[0054] The high-density raw data calculation unit is used to calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB based on high-density raw data.

[0055] The specific calculation methods for the distance AB between electrodes AB, the distance XAB between the midpoints of electrodes AB and MN, the distance XMN between the midpoints of electrodes MN and MN, the normalized potential LOGUI, and the ratio of normalized potential to distance LOGUIMNAB have been described in detail in Example 1, and will not be repeated here.

[0056] The scatter plotting unit of different dimensions is used to establish the mapping relationship between the spatial location of data points and each measured value based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, and to plot scatter plots of different dimensions.

[0057] Among these steps, establishing the mapping relationship between the spatial location of data points and each measured value, and drawing scatter plots in different dimensions, has already been implemented. Figures 2(1)-2(8) The details in the previous embodiments are described in detail, and will not be repeated here.

[0058] The flying point data removal unit is used to remove flying point data from scatter plots of different dimensions and save the data after removing flying points for user use. Specifically, removing flying point data from scatter plots of different dimensions includes: obtaining the distance between a point in the scatter plot and a standard point; comparing the obtained distance with a preset distance; and removing a point as a flying point if the obtained distance is greater than the preset distance.

[0059] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0060] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0061] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0062] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0063] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0064] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A method for removing flying points in three-dimensional high-density electrical resistivity tomography (ED tomography) data, characterized in that, include: S100. The high-density raw data is sorted and organized into columns, namely the coordinates of electrodes A, B, M, and N, the natural potential SP, the voltage VP, the current IP, and the resistivity RO; S200. Based on the high-density raw data, calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB; In S200, the formula for calculating the distance between electrode AB and electrode AB is: AB = BA; if B is infinitely far away, then: AB = A - (M + N) / 2; if A is infinitely far away, then: AB = B - (M + N) / 2; where A, B, M, and N are their respective coordinate values. In S200, the distance XAB between the midpoints of electrode AB is calculated using the formula: XAB = ((A+B) / 2 + (M+N) / 2) / 2; if B is infinitely far away, then: XAB = (A+(M+N) / 2) / 2; if A is infinitely far away, then XAB = (B+(M+N) / 2) / 2, where A, B, M, and N are their respective coordinate values. In S200, the formula for calculating the distance MN from electrode MN is MN=abs(MN); the formula for calculating the distance XMN from the midpoint of electrode MN is XMN=(M+N) / 2; where M and N are their respective coordinate values; In S200, the formula for calculating the normalized potential LOGUI is: LOGUI=real(lg(VP / IP)), where VP is the voltage value and IP is the current value; In S200, the normalized potential to distance ratio LOGUIMNAB is calculated as follows: LOGUIMNAB=real(log10(VP / IP / MN / AB)), where VP is the voltage value, IP is the current value, MN is the distance between electrodes MN, and AB is the distance between electrodes AB. S300. Based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, establish the mapping relationship between the spatial location of the data points and each measured value, and draw scatter plots in different dimensions. S400. Based on the scatter plots of different dimensions, remove outlier data from the scatter plots and save the data after removing outliers for user use.

2. The method for removing flying points in three-dimensional high-density electrical resistivity tomography data as described in claim 1, characterized in that, In S300, a mapping relationship is established between the spatial location of data points and each measured value, and scatter plots of different dimensions are drawn, specifically including scatter plots of XAB-LOGUI, XAB-LOGUIMNAB, XMN-LOGUI, XMN-LOGUIMNAB, AB-LOGUI, AB-LOGUIMNAB, MN-LOGUI, and MN-LOGUIMNAB.

3. The method for removing flying points in three-dimensional high-density electrical resistivity tomography data as described in claim 1, characterized in that, In S400, based on the scatter plots of different dimensions, outlier data in the scatter plots are removed. Specifically, this includes: obtaining the distance between a point in the scatter plot and a standard point based on the scatter plots of different dimensions; comparing the obtained distance with a preset distance; and removing the point as an outlier when the obtained distance is greater than the preset distance.

4. A system for removing flying points from three-dimensional high-density electrical resistivity tomography (ED tomography) data, employing any one of the methods described in claims 1-3, characterized in that, The system includes a high-density raw data acquisition unit, a high-density raw data calculation unit, a scatter plot plotting unit with different dimensions, and a fly-point data removal unit; among which: The high-density raw data acquisition unit is used to sort and organize the high-density raw data, which are the coordinates of electrodes A, B, M, and N, the natural potential SP, the voltage VP, the current IP, and the resistivity RO. The high-density raw data calculation unit is used to calculate the values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB based on high-density raw data. The scatter plotting unit of different dimensions is used to establish the mapping relationship between the spatial location of data points and each measured value based on the calculated values ​​of electrode AB distance AB, electrode AB midpoint distance XAB, electrode MN distance MN, electrode MN midpoint distance XMN, normalized potential LOGUI, and normalized potential to distance ratio LOGUIMNAB, and to plot scatter plots of different dimensions. The Flying Point Data Removal Unit is used to remove flying point data from scatter plots of different dimensions and save the data after removing flying points for user use.

5. An electronic device, characterized in that, include: Memory is used to store instructions that can be executed by the processor; A processor for executing instructions to implement a method for flying point removal of three-dimensional high-density electrical resistivity data as described in claims 1-3.

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