Exploration data processing method and abnormal data filtering method
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA NAT PETROLEUM CORP
- Filing Date
- 2024-12-05
- Publication Date
- 2026-06-05
AI Technical Summary
In existing technologies, the filtering and processing of geophysical exploration data suffers from problems such as over-filtering, poor fine-tuning effect, inability to handle irregular graphic areas, poor real-time performance, and limited operability for large data volumes.
The system employs a drawing-based mouse-based selection method. By setting transition coefficients and aspect ratios, the cursor selection range is determined, the filtering area is expanded, and the geological data within the expanded area is filtered using preset filtering methods. Distortion points are also removed, enabling flexible and precise data processing.
It enables fine-grained data processing of irregular areas, avoids over-filtering, improves processing efficiency and real-time performance, and retains more geological information, making it suitable for gravity, magnetic and electrical exploration data processing.
Smart Images
Figure CN122151244A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of geophysical exploration technology, and in particular to an exploration data processing method and anomaly data filtering method, electronic equipment and storage medium. Background Technology
[0002] Data collected during geophysical exploration operations often contains instrument noise or human-induced noise interference, resulting in interference points or severely distorted data. Conventional filtering methods typically filter the data as a whole or within a specific range. However, this approach has several drawbacks: poor fine-tuning of localized areas, inability to handle data with irregular shapes (e.g., when processing along structural directions or close to a curve), susceptibility to over-filtering, poor real-time performance, and limited operability for large datasets. Therefore, a data processing method is urgently needed to avoid over-filtering and achieve more flexible and refined data processing.
[0003] The product of the picking range and the transition coefficient is determined as the extended region; Summary of the Invention
[0004] This application provides an exploration data processing method, an anomaly data filtering method, electronic device, and storage medium to solve the problems existing in related technologies in data filtering processing, such as over-filtering, poor fine processing effect, and inability to process data with irregular graphic ranges. It realizes more flexible data filtering range and fine data processing, and removes distortion points while filtering data in irregular graphic regions.
[0005] In a first aspect, this application provides an exploration data processing method, which includes: acquiring exploration data collected by a geophysical exploration mission and processing parameters of the exploration data; wherein the processing parameters include a transition coefficient, and the exploration data includes data nodes and geological data corresponding to the data nodes; determining the cursor's picking range in response to a cursor picking action; changing the cursor's picking range according to the transition coefficient, and using the changed picking range as an extended region; filtering the geological data corresponding to the data nodes located within the extended region using a preset filtering method; and replacing the geological data corresponding to the data nodes within the picking range with the filtered data as the processed exploration data.
[0006] As an optional implementation, the processing parameters include aspect ratio and cursor length. Determining the cursor picking range in response to a cursor picking action includes: using the product of the aspect ratio and the cursor length as the vertical index range of the cursor, using the cursor length as the horizontal index range of the cursor, and determining the cursor index range based on the vertical index range and the horizontal index range; and determining the cursor index range at the time the picking action occurs as the cursor picking range in response to a cursor picking action.
[0007] As an optional implementation, before replacing the geological data corresponding to the data nodes within the picking range with the filtered data, the method further includes determining the data nodes within the picking range, including: obtaining the canvas coordinates corresponding to the data nodes and the cursor, calculating the distance between the canvas coordinates corresponding to the data nodes and the canvas coordinates of the cursor; and determining the data nodes as data nodes within the picking range if the horizontal axis length of the distance is less than the horizontal index range and the vertical axis length of the distance is less than the vertical index range.
[0008] As an optional implementation, the processing parameters include relative error, and the method further includes: for data nodes within the picking range, calculating a first ratio based on the geological data corresponding to the data nodes; if the first ratio is not less than the relative error, identifying the data nodes as distortion points and removing the distortion points.
[0009] As an optional implementation, the first ratio is expressed by the following formula: |Z'-Z| / |Z'+Z|; where Z represents the geological data corresponding to the data node before filtering, and Z' represents the geological data corresponding to the data node after filtering.
[0010] As an optional implementation, the method further includes ensuring that the geological data corresponding to the data nodes in the area outside the picking range within the extended area remain unchanged before and after filtering.
[0011] As an optional implementation, the preset filtering method includes at least one of the following: spatial filtering, median filtering, sliding window averaging filtering, distance-weighted filtering, inverse distance filtering, Gaussian filtering, and low-pass filtering.
[0012] Secondly, this application provides an anomaly data filtering method, which applies the exploration data processing method described above. The anomaly data filtering method includes: acquiring a region to be processed and exploration data within the region to be processed; wherein the region to be processed includes an irregularly shaped region to be processed, and the exploration data includes anomaly data; according to any one of claims 1 to 7, in response to multiple cursor picking actions at the boundary of the region to be processed, the processed exploration data corresponding to the multiple cursor picking actions is used as the anomaly data filtering result; wherein the anomaly data filtering result includes filtered data excluding the distorted points.
[0013] Thirdly, this application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory is used to store computer programs; and the processor is used to implement the exploration data processing method or the abnormal data filtering method as described above when executing the program stored in the memory.
[0014] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the exploration data processing method or the abnormal data filtering method described above.
[0015] The technical solutions provided in this application have the following advantages compared with the prior art:
[0016] The exploration data processing method provided in this application effectively solves the technical problems of poor fine processing of local areas, inability to process data with irregular shapes, over-filtering, poor real-time performance, and limited operability for large data volumes in related technologies. It effectively avoids changes to unwanted data, enabling more flexible and refined data processing with a wider selection range for data filtering. Employing a drawing-based mouse-based selection method, it performs real-time geological data smoothing filtering on irregular areas in geophysical data mapping. Data is acquired in real-time via mouse movement, making operation simple and allowing for more flexible selection of the filtering range. Selecting the filtering area by mouse movement avoids over-filtering. A transition coefficient increases the data selection range, including more geological data for filtering, thus achieving a smooth transition at the boundaries of the selected area. This results in refined processing and allows data containing more actual geological information to be used in subsequent data processing, achieving the desired refined data processing, improving computational speed, and enhancing processing efficiency. Furthermore, compared to the overall filtering and limited area filtering of related technologies, the exploration data processing method provided in this application has strong interactivity, high filtering efficiency, and low data loss for actual data. It is applicable to the processing of various geological data and has broad application prospects. In particular, it is suitable for widespread use in gravity, magnetic and electric exploration data processing and has high technical and economic value. Attached Figure Description
[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This illustration schematically shows the application environment of the exploration data processing method according to an embodiment of this application;
[0020] Figure 2 This is a flowchart illustrating an exploration data processing method according to an embodiment of this application;
[0021] Figure 3 This is one of the geological data schematic diagrams in an exploration data processing method according to another embodiment of this application;
[0022] Figure 4 This is a second schematic diagram of geological data in an exploration data processing method according to yet another embodiment of this application;
[0023] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation
[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0025] Figure 1 This is a diagram illustrating the application environment of an exploration data processing method in one embodiment. (Refer to...) Figure 1 This exploration data processing method is applied to an exploration data processing system. The system includes a terminal 110 and a server 120. The terminal 110 and server 120 are connected via a network. The terminal 110 or server 120 acquires exploration data collected during geophysical exploration tasks and processing parameters for the exploration data; wherein the processing parameters include a transition coefficient, and the exploration data includes data nodes and corresponding geological data; in response to a cursor picking action, the cursor picking range is determined; the cursor picking range is varied according to the transition coefficient, and the varied range is used as an extended area; a preset filtering method is used to filter the geological data corresponding to the data nodes located within the extended area; the geological data corresponding to the data nodes within the picking range is replaced with the filtered data, which is then used as the processed exploration data.
[0026] Terminal 110 can be a desktop terminal or a mobile terminal, and a mobile terminal can be at least one of a mobile phone, tablet computer, or laptop computer. Server 120 can be implemented using a standalone server or a server cluster consisting of multiple servers. It should be understood that... Figure 1 The number of terminals, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.
[0027] like Figure 2 As shown, in one embodiment, a method for processing exploration data is provided. This embodiment mainly applies this method to the above-mentioned... Figure 1 Let's take terminal 110 (or server 120) as an example. Figure 2 This is a flowchart illustrating the exploration data processing method according to an embodiment of this application, with reference to... Figure 2 The method for processing this exploration data specifically includes the following steps:
[0028] S1, acquire the exploration data collected by the geophysical exploration mission and the processing parameters of the exploration data; wherein, the processing parameters include a transition coefficient, and the exploration data includes data nodes and the geological data corresponding to the data nodes;
[0029] S2, in response to the cursor picking action, determines the cursor picking range;
[0030] S3, change the cursor picking range according to the transition coefficient, and use the changed picking range as the extended area;
[0031] S4, use a preset filtering method to filter the geological data corresponding to the data nodes located in the extended area;
[0032] S5, replace the geological data corresponding to the data nodes within the picking range with the filtered data as the processed exploration data.
[0033] Specifically, in S1, the processing parameters obtained may include parameters used for data processing such as aspect ratio, cursor length, transition coefficient, and relative error. The exploration data collected by the geophysical exploration mission may include geological data collected from multiple data acquisition points. The geological data may be magnetic data. The exploration data may include the location coordinates of multiple data nodes, i.e., latitude and longitude information, as well as the geological data collected at that location coordinate, i.e., the geological data corresponding to that node.
[0034] In geophysical exploration, the acquired data inevitably contains instrument noise or human-induced noise interference, resulting in some interfering points or severely distorted points. Filtering is a commonly used method in data processing to remove these interfering or distorted points, allowing for the extraction of accurate subsurface information by eliminating noise. In this embodiment, during geophysical data mapping and imaging, the specific numerical values involved in the existing graphics are smoothed and filtered in real time using a mouse-based selection method.
[0035] In one possible implementation, the processing parameters may include aspect ratio and cursor length. Specifically, S2 may also include the following operations: using the product of the aspect ratio and the cursor length as the vertical index range of the cursor, using the cursor length as the horizontal index range of the cursor, determining the cursor index range based on the vertical index range and the horizontal index range; and in response to a cursor picking action, determining the cursor index range at the time the picking action occurs as the cursor picking range.
[0036] For example, setting the aspect ratio 'a' and the cursor length (also called the index range in some software implementations) to 'R', where 'R' can be the actual length of the cursor on the screen, in units such as cm, allows us to define the cursor's horizontal index range. Using 'R' as the standard for the cursor's horizontal index range, a × R represents the cursor's vertical index range. The cursor index range is the elliptical area formed by the actual coordinates returned by the screen (i.e., the canvas coordinates). When a mouse click occurs, the client or server responds to this click operation—a picking action—and determines the picking range. In other words, the index range of the cursor's location on the canvas coordinates is the picking range.
[0037] Specifically, S3 can be implemented by determining the extended region by multiplying the picking range and the transition coefficient. For example, a transition coefficient λ is set as a real number greater than 1, the picking range is Di, and the extended region is Di×λ. Expanding the cursor picking region according to the transition coefficient results in an extended region that can include more data nodes for subsequent filtering operations. Increasing the picking data range through the transition coefficient achieves a smooth transition at the boundary of the picking region. The data nodes located within the extended region in S4 can be data nodes whose corresponding canvas coordinates fall within the extended region.
[0038] Specifically, as the cursor moves, combined with Figure 3 The graphical interface shown illustrates that within the displayed area, all points correspond to canvas coordinates (also known as actual coordinates). For example, the canvas coordinate position when the cursor picks up can be defined as Li, and the canvas coordinates corresponding to the data nodes in the graph can be defined as Lreali, where R is the cursor length. This is achieved by calculating Di = |Li - Lreali. i |, it can be determined that nodes satisfying Di < R are located within the cursor picking range, where Di includes the distance range in the X and Y directions, that is, the horizontal index range Dx < R, the vertical index range Dy < aR, and the canvas coordinates L real corresponding to the data node and the latitude and longitude information corresponding to i, that is, the geographical location coordinates can be L real.
[0039] It should be noted that during the exploration data processing, the data is presented in image form. Figure 3 This is one of the geological data schematic diagrams in an exploration data processing method according to another embodiment of this application, such as... Figure 3As shown, the image represents exploration data, including the geographical location information of numerous data nodes and the corresponding geological data. It is ground observation point data, a comprehensive reflection of the underground geological bodies, and can reflect the geological conditions collected during the exploration task. In actual exploration data acquisition, due to interference, operational errors, and other factors, the acquired data includes many abnormal interferences. Optionally, these abnormal interferences can be eliminated by first removing distorted points, and then normal interferences can be filtered out. Typically, the area to be processed can be pre-defined before data processing. Generally, if distorted points are not removed before filtering, the filtering effect will be severely affected and the accuracy will be low if there are many distorted points in the actual filtering area. Therefore, the decision to perform distorted point removal should be made based on the specific application scenario.
[0040] Figure 4 This is a second schematic diagram of geological data in an exploration data processing method according to yet another embodiment of this application, as shown below. Figure 4 As shown, the area enclosed by the red line illustrates the effect of filtering on the region to be processed. Figure 3 In comparison, it is evident that magnetic anomaly data has been eliminated, achieving a smooth transition at the boundary of the picking area and realizing refined processing. Similarly, in practical engineering applications, the method of this embodiment demonstrates excellent filtering effects, especially for exploration methods with low precision, and possesses high application value.
[0041] In one possible implementation, the exploration data processing method according to the embodiments of this application may further include: for data nodes within the picking range, calculating a first ratio based on the geological data corresponding to the data nodes; if the first ratio is not less than the relative error, identifying the data nodes as distortion points and removing the distortion points.
[0042] Specifically, the first ratio can be expressed by the following formula:
[0043] |Z'-Z| / |Z'+Z|;
[0044] Where Z represents the geological data corresponding to the data node before filtering, and Z' represents the geological data corresponding to the data node after filtering.
[0045] For example, taking a node in the diagram as an example, the node's canvas coordinates can be (X, Y), the node's corresponding address data, such as the magnetic field value, can be Z, and the geological data corresponding to the data node before filtering can be represented. Z' can represent the geological data corresponding to the data node after filtering.
[0046] In one example, if the first ratio is less than the relative error, i.e., |filtered - unfiltered| / |filtered + unfiltered| < relative error, the geological data Z corresponding to the data node is retained.
[0047] Specifically, the preset filtering method can be: spatial filtering, median filtering, sliding window averaging filtering, distance-weighted filtering, inverse distance filtering, Gaussian filtering, low-pass filtering, and other filtering methods, without any specific limitation. It should be noted that the more data points filtered using different methods, the better the filtering effect and the smoothing effect. Therefore, for the application scenario of this application embodiment, the exploration data processing method of this application embodiment can achieve refined data processing and obtain better smoothing results.
[0048] Prior to S4, the exploration data processing method in this application embodiment further includes: the geological data corresponding to the data nodes in the area outside the picking range within the extended area remains unchanged before and after filtering.
[0049] Specifically, in conjunction with the above example, the Z data of the original point is replaced with the Z' data of the data points within the Di range. Data located outside the Di range and within the transition coefficient expansion area are not replaced. That is, the geological data corresponding to the data nodes within the expansion area but outside the picking range are not replaced.
[0050] Specifically, the above operations can be performed for each cursor picking action to obtain processed exploration data. For a pre-defined area to be processed, picking actions can be performed multiple times along the boundary of that area. The processed exploration data obtained after all picking is completed can be identified as the processing result and used as output. Understandably, for the same area, the more picking points and the more processing iterations, the more refined the results will theoretically be.
[0051] Based on the above operations, the exploration data processing method provided in this application effectively solves the technical problems in related technologies, such as poor fine processing effect in local areas, inability to process data with irregular shapes, over-filtering, poor real-time performance, and limited operability for large data processing volumes. It effectively avoids changes to unwanted data, achieving more flexible and refined data processing with a wider selection range for data filtering. By employing a drawing-based mouse-based selection method, it performs real-time geological data smoothing filtering on irregular areas in geophysical data mapping images. Data is acquired in real-time via mouse movement, making operation simple and allowing for more flexible selection of the data filtering range. Selecting the filtering area by mouse movement avoids over-filtering. The transition coefficient increases the data selection range, including more geological data for filtering, thus achieving a smooth transition at the boundary of the selection area. This achieves refined processing and allows data containing more actual geological information to be used in subsequent data processing, achieving the desired refined data processing, improving computational speed, and enhancing processing efficiency. Furthermore, compared to the overall filtering and limited area filtering of related technologies, the exploration data processing method provided in this application has strong interactivity, high filtering efficiency, and low data loss for actual data. It is applicable to the processing of various geological data and has broad application prospects. In particular, it is suitable for widespread use in gravity, magnetic and electric exploration data processing and has high technical and economic value.
[0052] In another embodiment, the exploration data processing method provided in this application is specifically implemented as a data smoothing method based on drawing and mouse movement, which can be achieved through the following steps:
[0053] (1) Set the cursor picking range size through the dialog box. Set the index range to R. Here, the index range R should be the actual length of the mouse on the screen in cm. You can modify the two significant digits after the decimal point.
[0054] (2) Set the aspect ratio a, use R as the standard for the horizontal index range of the mouse, and the vertical index range is a×R. The index range is the elliptical area formed by the actual coordinates returned by the screen.
[0055] (3) Set a transition coefficient λ, which is a real number greater than 1. The transition coefficient is mainly used to increase the range of data to be picked, so as to achieve a smooth transition at the boundary of the picking area.
[0056] (4) Set the filtering method to be used. Select one of the following from the drop-down box: spatial filtering, median filtering, sliding window average filtering, distance-weighted filtering, inverse distance filtering, Gaussian filtering, low-pass filtering, etc., as the filtering method for real-time smoothing.
[0057] (5) Add an operation to remove distorted points. Set a checkbox to enter the operation to remove distorted points. Set the relative error value: |after filtering - before filtering| / |after filtering + before filtering| < relative error.
[0058] (6) Move the mouse within the target graphic and click the mouse to pick up the cursor's position on the canvas in real time, denoted as L. 1，2，3 ...i.
[0059] (7) Define the canvas coordinate position of each point as Lreali. By calculating Di = |Li - Lreali|, obtain the number of grid nodes within the index range in step (1) and the corresponding actual coordinates Ltrue, which is Di < R. Di includes the distance in the X and Y directions. Within the index range, it means Dx < R and Dy < aR.
[0060] (8) Pick the number of grid nodes within the range of Di×λ and the corresponding actual coordinates L.
[0061] (9) The picking coordinates correspond to all the display coordinate points in the canvas. Therefore, by zooming in, the actual filtering range can be reduced, thereby improving the calculation speed.
[0062] (10) Filter the indexed point X, Y, Z data using the filtering method selected in step (2) to obtain the filtered data Z' at positions X and Y.
[0063] (11) Use the Z' data of the data points within the Di range to replace the Z data of the original point. Data outside the Di range and within the transition coefficient expansion area are not replaced.
[0064] (12) If the checkbox for removing distorted points is selected, then determine whether |Z'-Z| / |Z'+Z| < relative error is true. If it is true, then the corresponding data point is retained. If it is not true, then it is considered as a distorted point to be removed.
[0065] (13) Move the cursor position, and use the left mouse button to pick the next cursor position. Repeat steps (6)-(12).
[0066] In one example, corresponding to the steps of the above embodiments, taking a measured magnetic force data as an example, Figure 3 and Figure 4 The magnetic anomalies before and after processing using the exploration data processing method are shown in this example. The specific implementation of the above operations is as follows:
[0067] In step (1), through the dialog box, set the cursor picking range size and set the index range to 1.00. The index range is the actual length of the mouse on the screen, in cm.
[0068] In step (2), the aspect ratio is set to 1. The horizontal index range of the mouse is set to 1cm in step (1), and the vertical index range is also 1cm. The index range is the circular area formed by the actual coordinates returned by the screen.
[0069] Step (3) is executed to set a transition coefficient of 1.2.
[0070] Step (4) sets the filtering method to be used. Select sliding window average filter as the real-time smoothing filtering method from the drop-down box.
[0071] Perform step (5) to add the operation of removing distorted points. Check the checkbox and perform the operation of removing distorted points. Set the relative error size to 0.1.
[0072] Step (6) involves moving the mouse within the target graphic to the area where filtering is required to obtain the mouse position Li.
[0073] In step (7), the canvas coordinate position of each point is defined as Lreali. By calculating Di = |Li - Lreali|, the number of grid nodes within the index range in step (6) and the corresponding actual coordinates Ltrue are obtained. These are the points that satisfy the condition Di < R, where Di includes the distance in the X and Y directions. Within the index range, it means Dx < R and Dy < R.
[0074] Step (8) Pick the number of grid nodes within the range of Di×1.2 and the corresponding actual coordinates L.
[0075] Step (9) narrows the actual screening range by amplification.
[0076] Step (10) is executed to filter the indexed point X, Y, Z data using the sliding window averaging method selected in step (2) to obtain the filtered data Z' at positions X and Y.
[0077] Execute step (12) to determine whether |Z'-Z| / |Z'+Z| < relative error is true. If true, retain the corresponding data point Z. If not true, discard it as a distorted point.
[0078] Execute step (13) to move the cursor position, and click the left mouse button to pick the next cursor position. Repeat steps (6)-(12) to generate the final calculation result as shown. Figure 4 As shown.
[0079] The results show that this method can perform more accurate filtering within the target range, and the resulting filtering range is freely controllable. Compared with previous overall filtering and limited area filtering, this method has strong interactivity, high filtering efficiency, and low data loss for actual data. It is suitable for widespread use in gravity, magnetic and electric exploration data processing and has significant technical and economic value.
[0080] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0081] Based on the same inventive concept, this application also provides an abnormal data filtering method, which applies the exploration data processing method described above. The abnormal data filtering method includes: acquiring a region to be processed and exploration data within the region to be processed; wherein the region to be processed includes an irregularly shaped region to be processed, and the exploration data includes abnormal data; according to any one of claims 1 to 7, in response to multiple cursor picking actions at the boundary of the region to be processed, the processed exploration data corresponding to the multiple cursor picking actions is used as the abnormal data filtering result; wherein the abnormal data filtering result includes filtered data excluding the distorted points.
[0082] The abnormal data filtering method provided in this application effectively solves the technical problems of poor fine processing of local areas, inability to process data with irregular shapes, over-filtering, poor real-time performance, and limited operability for large data volumes in related technologies. It effectively avoids changes to unwanted data, enabling more flexible and refined data filtering. Employing a drawing-based mouse-based selection method, it performs real-time geological data smoothing filtering on irregular areas in geophysical data mapping. Data is acquired in real-time via mouse movement, making operation simple and allowing for more flexible data filtering. Selecting the filtering area by mouse movement avoids over-filtering. A transition coefficient increases the data selection range, including more geological data for filtering, thus achieving a smooth transition at the boundary of the selected area. This achieves refined processing and allows data containing more actual geological information to be used in subsequent data processing, achieving the desired refined data processing, improving computational speed, and enhancing processing efficiency. Furthermore, compared to the overall filtering and limited area filtering of related technologies, the exploration data processing method provided in this application has strong interactivity, high filtering efficiency, and low data loss for actual data. It is applicable to the processing of various geological data and has broad application prospects. In particular, it is suitable for widespread use in gravity, magnetic and electric exploration data processing and has high technical and economic value.
[0083] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0084] Based on the same inventive concept, this application also provides an exploration data processing apparatus, comprising: a data acquisition module for acquiring exploration data collected by a geophysical exploration task and processing parameters of the exploration data; wherein the processing parameters include a transition coefficient, and the exploration data includes data nodes and geological data corresponding to the data nodes; a picking determination module for determining the picking range of the cursor in response to a picking action of the cursor; an expansion determination module for changing the picking range of the cursor according to the transition coefficient, the changed picking range being used as an expansion area; a filtering module for filtering the geological data corresponding to the data nodes located within the expansion area using a preset filtering method; and a replacement module for replacing the geological data corresponding to the data nodes within the picking range with the filtered data, as the processed exploration data.
[0085] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0086] Based on the same inventive concept, embodiments of this application also provide an abnormal data filtering device, comprising: a first module, configured to acquire a region to be processed and exploration data within the region to be processed; wherein the region to be processed includes an irregularly shaped region to be processed, and the exploration data includes abnormal data; a second module, configured to, in response to multiple cursor picking actions at the boundary of the region to be processed, use the processed exploration data corresponding to the multiple cursor picking actions as the abnormal data filtering result according to the aforementioned exploration data processing method; wherein the abnormal data filtering result includes filtered data excluding the distorted points.
[0087] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0088] Any number of the functional modules included in the above-described device can be combined into one module, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. At least one of the functional modules included in the above-described device can be at least partially implemented as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the functional modules included in the device can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.
[0089] Based on the same inventive concept, combined with Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.
[0090] In one embodiment, this application provides an electronic device including a processor 401, a communication interface 402, a memory 403, and a communication bus 404. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer programs. The processor, when executing the program stored in the memory, implements the method described above. The steps of implementing the exploration data processing method or the abnormal data filtering method in any of the above possible implementations can be equivalent to the exploration data processing device or the abnormal data filtering device described above. Of course, the processor can also be used to process other data or perform calculations. This electronic device can be a PC, server, terminal, or other similar device.
[0091] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0092] Based on the same inventive concept, in one embodiment, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the exploration data processing method or the abnormal data filtering method as described above.
[0093] More details and beneficial effects of this embodiment can be found in the descriptions of the foregoing embodiments, and will not be repeated here.
[0094] It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of this application. Experimental methods in the following embodiments, unless specific conditions are specified, are generally determined according to national standards. If no corresponding national standard exists, then generally accepted international standards, conventional conditions, or conditions recommended by the manufacturer are followed.
[0095] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0096] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.
Claims
1. A method for processing exploration data, characterized in that, include: The exploration data collected by the geophysical exploration mission and the processing parameters of the exploration data are obtained; wherein, the processing parameters include a transition coefficient, and the exploration data includes data nodes and the geological data corresponding to the data nodes; In response to the cursor's picking action, determine the cursor's picking range; The cursor picking range is changed according to the transition coefficient, and the changed picking range is used as the extended area; A preset filtering method is used to filter the geological data corresponding to the data nodes located within the extended area; The geological data corresponding to the data nodes within the picking range are replaced with filtered data to form the processed exploration data.
2. The exploration data processing method according to claim 1, characterized in that, The processing parameters include aspect ratio and cursor length. The process of determining the cursor's picking range in response to the cursor's picking action includes: The product of the aspect ratio and the cursor length is used as the vertical index range of the cursor, and the cursor length is used as the horizontal index range of the cursor. The cursor index range is determined based on the vertical index range and the horizontal index range. In response to a cursor picking action, the cursor index range at the time the picking action occurs is determined as the cursor picking range.
3. The exploration data processing method according to claim 2, characterized in that, Before replacing the geological data corresponding to the data nodes within the picking range with the filtered data, the method further includes determining the data nodes within the picking range, including: Obtain the canvas coordinates corresponding to the data node and the cursor, and calculate the distance between the canvas coordinates corresponding to the data node and the canvas coordinates of the cursor; If the horizontal axis length of the distance is less than the horizontal index range and the vertical axis length of the distance is less than the vertical index range, the data node is determined as a data node within the picking range.
4. The exploration data processing method according to claim 1, characterized in that, The processing parameters include relative error, and the method further includes: For the data nodes within the picking range, a first ratio is calculated based on the geological data corresponding to the data nodes; If the first ratio is not less than the relative error, the data node is identified as a distortion point and the distortion point is removed.
5. The exploration data processing method according to claim 4, characterized in that, The first ratio is expressed by the following formula: |Z'-Z| / |Z'+Z|; Where Z represents the geological data corresponding to the data node before filtering, and Z' represents the geological data corresponding to the data node after filtering.
6. The exploration data processing method according to claim 1, characterized in that, The method further includes ensuring that the geological data corresponding to the data nodes in the area outside the picking range within the extended area remain unchanged before and after filtering.
7. The exploration data processing method according to any one of claims 1 to 6, characterized in that, The preset filtering method includes at least one of the following: spatial filtering, median filtering, sliding window average filtering, distance-weighted filtering, inverse distance filtering, Gaussian filtering, and low-pass filtering.
8. An anomaly data filtering method applying the exploration data processing method as described in any one of claims 1 to 7, characterized in that, include: Acquire the area to be processed and the exploration data within the area to be processed; wherein, the area to be processed includes irregularly shaped areas to be processed, and the exploration data includes abnormal data; According to any one of claims 1 to 7, in response to multiple cursor picking actions at the boundary of the area to be processed, the processed exploration data corresponding to the multiple cursor picking actions is used as the abnormal data filtering result; wherein, the abnormal data filtering result includes filtered data excluding the distorted points.
9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor, when executing a program stored in memory, implements the exploration data processing method according to any one of claims 1 to 7 or the abnormal data filtering method according to claim 8.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the exploration data processing method of any one of claims 1 to 7 or the abnormal data filtering method of claim 8.