Abnormal field calculation method and device, electronic equipment and storage medium

Abstract

The application relates to an abnormal field calculation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring first target amplitude data corresponding to different transmission frequencies in first amplitude data of a preset measuring point, and acquiring second target amplitude data corresponding to different transmission frequencies in second amplitude data of the preset measuring point; performing difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain first correction data; performing correction processing on the second amplitude data according to the first correction data to obtain corrected second amplitude data; generating target difference data according to the corrected second amplitude data and the first amplitude data; determining the minimum value in the target difference data as target calibration data of the preset measuring point; and generating abnormal field data of the preset measuring point according to the target calibration data and the first amplitude data. The method solves the problem of interference such as static displacement in the abnormal field in the prior art.

Description

Technical Field

[0001] This application relates to the field of geophysical electromagnetic exploration, and in particular to methods, apparatus, electronic equipment and storage media for calculating anomalies. Background Technology

[0002] Horizontal well fracturing technology is widely used in the underground extraction of oil and shale gas. It can increase the conductivity and productivity of horizontal wells. Compared with the scale of conventional geological targets, the volume of fracturing fluid injected during horizontal well hydraulic fracturing is small and the burial depth is large. The electromagnetic signal anomalies caused by the injection of fracturing fluid are relatively small. In existing technologies, conventional anomaly field calculation algorithms are greatly affected by interference such as static displacement, making it difficult to extract such weak anomaly field information. This leads to difficulties in discovering, distinguishing and characterizing these weak anomaly targets. Summary of the Invention

[0003] In view of the above problems, embodiments of this application are proposed to provide an anomaly field calculation method, apparatus, electronic device and storage medium that overcomes or at least partially solves the above problems.

[0004] According to a first aspect of this application, an anomaly field calculation method is provided, applied to an anomaly field processing system, the method comprising:

[0005] The first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point are obtained respectively.

[0006] The first target amplitude data and the second target amplitude data, which have the same transmission frequency, are respectively subjected to difference processing to obtain the first correction data;

[0007] The second amplitude data is corrected based on the first correction data to obtain the corrected second amplitude data;

[0008] Target difference data is generated based on the corrected second amplitude data and the first amplitude data;

[0009] The minimum value in the target difference data is determined as the target calibration data of the preset measurement point;

[0010] Abnormal field data for the preset measurement points are generated based on the target calibration data and the first amplitude data.

[0011] Optionally, before the steps of acquiring the first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement points, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement points, the method further includes:

[0012] The first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data collected after the fracturing operation are processed to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

[0013] Optionally, the target difference data is obtained using the following formula:

[0014]

[0015] in, For the target difference data, A 1i The first target amplitude data corresponding to the i-th transmission frequency in the first amplitude data before the pre-set measuring point fracturing operation. The second target amplitude data is the i-th transmission frequency in the corrected second amplitude data, where n is the number of transmission frequencies.

[0016] Optionally, the abnormal field data is obtained using the following formula:

[0017]

[0018] Wherein, diff1 is the abnormal field data of the preset measurement point, B1' is the target calibration data of the preset measurement point, and A1 is the first amplitude data of the preset measurement point.

[0019] Optionally, the step of correcting the second amplitude data based on the first correction data to obtain the corrected second amplitude data includes:

[0020] Based on the first correction data, each of the second target amplitude data in the second amplitude data is corrected to obtain the corrected second amplitude data.

[0021] Optionally, after the step of generating the abnormal field data of the preset measurement point based on the target calibration data and the first amplitude data, the method further includes:

[0022] The abnormal field data corresponding to the target area is generated based on the abnormal field data corresponding to all preset measurement points within the target area.

[0023] According to a second aspect of this application, an anomaly field calculation apparatus is provided, characterized in that the apparatus comprises:

[0024] The acquisition module is used to acquire first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point.

[0025] The difference processing module is used to perform difference processing on the first target amplitude data and the second target amplitude data that have the same transmission frequency, respectively, to obtain the first correction data;

[0026] The correction module is used to correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data;

[0027] The first generation module is used to generate target difference data based on the corrected second amplitude data and the first amplitude data;

[0028] The determination module is used to determine the minimum value in the target difference data as the target calibration data of the preset measurement point;

[0029] The second generation module is used to generate abnormal field data of the preset measurement point based on the target calibration data and the first amplitude data.

[0030] Optionally, the device further includes:

[0031] The third generation module is used to process the first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data after the fracturing operation to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

[0032] According to a third aspect of this application, an electronic device is provided, 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.

[0033] Memory, used to store computer programs;

[0034] A processor is used to execute programs stored in memory.

[0035] According to a fourth aspect of this application, a computer-readable storage medium is provided on which a computer program is stored.

[0036] This application obtains first target amplitude data corresponding to different transmission frequencies from the first amplitude data of the preset measuring point, and second target amplitude data corresponding to different transmission frequencies from the second amplitude data of the preset measuring point; performs difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain first correction data; performs correction processing on the second amplitude data based on the first correction data to obtain corrected second amplitude data; generates target difference data based on the corrected second amplitude data and the first amplitude data; determines the minimum value in the target difference data as the target calibration data of the preset measuring point; and generates abnormal field data of the preset measuring point based on the target calibration data and the first amplitude data. By minimizing the root mean square error to correct the data after fracturing, and then generating the abnormal field of data before and after fracturing, the method of calculating the abnormal field of electromagnetic fracturing monitoring data in this application effectively suppresses problems such as static displacement in electromagnetic data, highlights the weak anomalies caused by fracturing fluid injection, and rapidly acquires the abnormal field, improving anti-interference ability and the efficiency of abnormal field data generation.

[0037] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0038] 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.

[0039] Figure 1 This is a flowchart illustrating an anomaly field calculation method according to an exemplary embodiment;

[0040] Figure 2 This is a schematic diagram illustrating the effect of calculating anomaly fields using existing technology, according to an exemplary embodiment.

[0041] Figure 3 This is a schematic diagram illustrating the effect of anomaly field calculation according to an exemplary embodiment;

[0042] Figure 4 This is a flowchart illustrating another method for calculating anomaly fields according to an exemplary embodiment;

[0043] Figure 5 This is a flowchart illustrating another method for calculating anomaly fields according to an exemplary embodiment;

[0044] Figure 6 A block diagram of an anomaly field calculation device is shown according to an exemplary embodiment. Detailed Implementation

[0045] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application 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 application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0046] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0047] The following description, in conjunction with the accompanying drawings, details the method, apparatus, electronic device, and storage medium for irregular data reconstruction provided in this application through specific embodiments and application scenarios.

[0048] The first embodiment of this application relates to an anomaly field calculation method. Figure 1 This is a flowchart illustrating an anomaly field calculation method according to an exemplary embodiment, such as... Figure 1 As shown, it includes the following steps:

[0049] Step 101: Obtain the first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point.

[0050] It should be noted that, in this embodiment of the application, for example, in an oil or shale gas extraction area, resource acquisition is carried out using horizontal well hydraulic fracturing technology. Fourier transforms are performed on the raw electromagnetic time series data collected before and after fracturing operations to obtain amplitude data corresponding to each measuring point before and after fracturing. Logarithmic operations are performed on the two sets of amplitude data obtained from a preset measuring point. The amplitude data before fracturing is recorded as the first amplitude data, and the amplitude data after fracturing is recorded as the second amplitude data. The preset measuring point refers to multiple measuring points within a target area. A measuring point is set at a certain interval along a line, with each line also spaced at a preset distance. For example, a measuring point is set at a 20m interval along a line, and each line is 90m apart. m measuring points can be set within a target area according to the specific needs of the target area. It should be noted that the interval data is set according to the actual situation of the target area, and no specific limitation is made on the interval data in this embodiment of the application.

[0051] Furthermore, each measuring point receives signal data at different transmission frequencies. Based on the different transmission frequencies, the first amplitude data at a preset measuring point can be divided into multiple first target amplitude data according to the transmission frequency. Similarly, the second amplitude data can also be divided into multiple second target amplitude data according to the transmission frequency. When a preset measuring point has n transmission frequencies, the transmission frequency corresponding to the first signal data transmitted to the measuring point is taken as the first transmission frequency. And so on, a preset measuring point can include 1, 2, 3, 4, ..., n transmission frequencies, which also correspond to n target amplitude data.

[0052] It should be noted that for each measuring point in a target work area, the transmission frequency received by the measuring point before fracturing operations is the same as the transmission frequency received after fracturing operations.

[0053] Step 102: Perform difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain the first correction data.

[0054] It should be noted that, for the sake of understanding this application, the following examples will use the calculation of the abnormal field value of the first preset measuring point in the target work area as an example, but this does not mean that there is only one preset measuring point in the target work area in this application.

[0055] In step 102, the first amplitude data and the second amplitude data before and after fracturing at the first measuring point are selected. The first amplitude data can be represented as A1, and the second amplitude data can be represented as B1. The difference Δ11 between the amplitude data B11 and A11 corresponding to the first transmission frequency f1 of these two sets of data is calculated as a trial correction quantity, as shown in Formula 1.

[0056] Δ11=B11-A11(Formula 1)

[0057] Wherein, Δ11 is the first correction data, i.e. the trial correction amount, B11 is the second target amplitude data corresponding to the first transmission frequency, and A11 is the first target amplitude data corresponding to the first transmission frequency.

[0058] It should be noted that the first correction data is generated from the target amplitude data corresponding to the first transmission frequency. Therefore, by analogy, when there are n transmission frequencies, there are also n correction data. Thus, the generation of the first correction data corresponding to the first transmission frequency, as expressed in Formula 1, can be further transformed into Formula 2, as shown below:

[0059] Δ1n=B1n-A1n (Formula 2)

[0060] Where Δ1n represents the nth correction data, i.e. the nth trial correction value, B1n is the second target amplitude data corresponding to the nth transmission frequency, and A1n is the first target amplitude data corresponding to the nth transmission frequency.

[0061] Step 103: Correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data.

[0062] The first correction data has been obtained in step 102. Therefore, in step 103, the second amplitude data is corrected based on the first correction data. It should be noted that, as previously explained, the second amplitude data includes n second target amplitude data corresponding to n transmission frequencies. Therefore, the correction processing of the second amplitude data by the first correction data is actually to correct multiple second target amplitude data in the second amplitude data separately. The final collection of multiple corrected second target amplitude data is combined into the corrected second amplitude data.

[0063] The correction process is achieved through Formula 3, which is shown below:

[0064]

[0065] in, The second amplitude data is the corrected data after correction based on the first correction data. B1 is the second amplitude data in the first measuring point, and Δ11 is the first correction data.

[0066] It should be noted that, as explained in step 102, when there are n transmission frequencies, there are also n correction data. Therefore, when there are n correction data, the second amplitude data needs to be corrected with each correction data to output n corrected second amplitude data.

[0067] Therefore, Formula 3 can be transformed into Formula 4, as shown below:

[0068]

[0069] in, B1 is the second amplitude data after correction based on the nth correction data, and Δ1n is the nth correction data.

[0070] Step 104: Generate target difference data based on the corrected second amplitude data and the first amplitude data;

[0071] In step 103, the corrected second amplitude data was generated. Therefore, in step 104, the target difference data is generated based on the corrected second amplitude data and the first amplitude data. Specifically, the target difference data is generated according to formula 5, which is shown below:

[0072]

[0073] in, For the target difference data, A 1i The first target amplitude data corresponding to the i-th transmission frequency in the first amplitude data before the pre-set measuring point fracturing operation. The second target amplitude data is the i-th transmission frequency in the second amplitude data after the preset measurement point is corrected, where n is the number of transmission frequencies. At this time, the preset measurement point refers to the first measurement point set in advance in the target area.

[0074] It should be noted that, as previously explained, the first amplitude data is divided into multiple first target amplitude data based on different transmission frequencies. Similarly, the second amplitude data is divided into multiple second target amplitude data based on different transmission frequencies. For the second amplitude data, it is necessary to perform correction processing with each correction data, outputting n corrected second amplitude data. Therefore, further, the n second amplitude data after fracturing after trial correction are calculated separately. n root mean square errors between the first amplitude data before fracturing

[0075] Step 105: Determine the minimum value in the target difference data as the target calibration data of the preset measurement point.

[0076] In step 104, the root mean square error between each corrected second amplitude data and each first amplitude data is obtained, which is a number of target difference data. Therefore, in step 105, the smallest difference data is selected from the multiple target difference data as the target calibration data of the first measuring point, which is the final correction value.

[0077] Step 106: Generate abnormal field data for the preset measurement point based on the target calibration data and the first amplitude data.

[0078] Based on the target calibration data and the first amplitude data obtained in step 105, abnormal field data for preset measurement points is generated. Specifically, the abnormal field data is generated using formula 6, as shown in the figure below:

[0079]

[0080] Wherein, diff1 is the abnormal field data of the preset measurement point, B1' is the target calibration data of the preset measurement point, and A1 is the first amplitude data of the preset measurement point.

[0081] Therefore, the abnormal field data corresponding to the preset measurement points can be obtained according to step 106.

[0082] It should be noted that anomaly fields generally refer to various physical fields generated by the geological body being searched. In the embodiments of this application, the difference between the data collected before and after the fracturing operation in the target work area is the anomaly field in this application.

[0083] Conventional anomaly field calculation algorithms in existing technologies specifically involve resource acquisition within a target area, such as an oil or shale gas extraction area, using horizontal well hydraulic fracturing technology. This involves performing Fourier transforms on the raw electromagnetic time-series data collected before and after fracturing to obtain amplitude data for each measuring point before and after fracturing. The anomaly field value for that measuring point is obtained by subtracting the pre-fracturing amplitude data from the post-fracturing amplitude data, dividing by the pre-fracturing amplitude data, and then multiplying by 100%. However, this anomaly field calculation method is significantly affected by interference such as static displacement and is difficult to extract weak anomaly field information. Figure 2 As shown, Figure 2 This is a schematic diagram illustrating the effect of calculating anomaly fields using existing technology, according to an exemplary embodiment. The vertical axis represents the frequency after taking the logarithm, and the horizontal axis represents the offset distance. The schematic diagram shows the effect of anomaly field values ​​obtained by existing technology calculation methods. It can be clearly seen that there is interference caused by static displacement, etc.

[0084] The anomaly field calculation method in this application involves resource acquisition within the target area, such as an oil or shale gas extraction area in a certain region, using horizontal well hydraulic fracturing technology. The specific steps are as follows:

[0085] (1) Perform Fourier transform on the raw electromagnetic time series data collected before and after the fracturing operation to obtain the amplitude data corresponding to different emission frequencies at each measuring point before and after fracturing.

[0086] (2) Perform logarithmic operations on the two sets of amplitude data obtained in step (1). The amplitude data before fracturing is recorded as data A after logarithmic operation, and the amplitude data after fracturing is recorded as data B after logarithmic operation.

[0087] (3) Select data A1 and B1 before and after fracturing at the first measuring point, and calculate the difference Δ11 between the amplitude data B11 and A11 corresponding to the first emission frequency f1 of these two sets of data as a test correction quantity, where Δ11=B11-A11;

[0088] (4) Use the trial correction amount Δ11 obtained in (3) to perform trial correction on the post-fracturing amplitude data B1 of the first measuring point. The data after trial correction is recorded as the calculated value. in

[0089] (5) Calculate the root mean square error between the data after trial correction and the data A1 before fracturing, as shown in Formula 5 in step 104 above.

[0090] (6) Repeat steps (3)-(5), and calculate the test correction values ​​Δ12, Δ13, Δ14, ..., Δ1n using the amplitude data corresponding to the 2nd, 3rd, 4th, ..., nth emission frequencies of the 1st measuring point, respectively. Then calculate the post-fracturing data after test correction. Root mean square error between the data A1 before fracturing

[0091] (7) Select the option that makes step (6) The final correction value B1' corresponding to the first measurement point when minimized;

[0092] (8) Use the final correction value obtained in step (7) and the pre-fracturing data A1 to calculate the abnormal field value diff1 of the first measuring point. The specific calculation process is shown in formula 6 in step 106.

[0093] (9) Calculate the abnormal field values ​​of the 2nd, 3rd, 4th, ..., mth (m is the total number of measuring points) measuring points in sequence according to steps (3)-(8) to obtain the abnormal field of the fracturing monitoring data of the entire work area.

[0094] like Figure 3 As shown, Figure 3This is a schematic diagram of the abnormal field calculation effect according to an exemplary embodiment, that is, a schematic diagram of the abnormal field effect implemented by the method in this application. It can be clearly seen that the abnormal field data obtained after processing by this application is reliable, and the interference such as static displacement is significantly suppressed. The processing effect is better than the prior art.

[0095] This application obtains first target amplitude data corresponding to different transmission frequencies from the first amplitude data of the preset measuring point, and second target amplitude data corresponding to different transmission frequencies from the second amplitude data of the preset measuring point; performs difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain first correction data; performs correction processing on the second amplitude data based on the first correction data to obtain corrected second amplitude data; generates target difference data based on the corrected second amplitude data and the first amplitude data; determines the minimum value in the target difference data as the target calibration data of the preset measuring point; and generates abnormal field data of the preset measuring point based on the target calibration data and the first amplitude data. By minimizing the root mean square error to correct the data after fracturing, and then generating the abnormal field of data before and after fracturing, the method of calculating the abnormal field of electromagnetic fracturing monitoring data in this application effectively suppresses problems such as static displacement in electromagnetic data, highlights the weak anomalies caused by fracturing fluid injection, and rapidly acquires the abnormal field, improving anti-interference ability and the efficiency of abnormal field data generation.

[0096] The second embodiment of this application relates to another method for calculating anomaly fields. Figure 4 This is a flowchart illustrating an anomaly field calculation method according to an exemplary embodiment, such as... Figure 4 As shown, it includes the following steps:

[0097] Step 001 involves processing the first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data collected after the fracturing operation to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

[0098] It should be noted that electromagnetic time series data is the main storage form of collected electromagnetic data. In areas with severe human interference, electromagnetic data collected will inevitably be affected by strong noise, resulting in reduced data quality. In the embodiments of this application, for example, in an oil or shale gas extraction area, resource collection is carried out through horizontal well hydraulic fracturing technology. At this time, the original electromagnetic time series data collected before and after the fracturing operation are processed separately.

[0099] Specifically, Fourier transforms were performed on the raw electromagnetic time series data collected before and after fracturing operations to obtain the amplitude data corresponding to each measuring point before and after fracturing. For the two sets of amplitude data obtained from a preset measuring point, logarithmic operations were performed on them respectively. The amplitude data before fracturing was recorded as the first amplitude data after the logarithmic operation, and the amplitude data after fracturing was recorded as the second amplitude data after the logarithmic operation.

[0100] The amplitude data after Fourier transform is further processed by taking the logarithm. This is done because the logarithmic function is a monotonically increasing function in its domain. Taking the logarithm will not change the relative relationship of the data, which can reduce the absolute value of the data and facilitate subsequent calculations.

[0101] Step 101: Obtain the first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point;

[0102] Step 102: Perform difference processing on the amplitude data of the first target and the amplitude data of the second target, which have the same transmission frequency, respectively, to obtain the first correction data;

[0103] Step 103: Correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data;

[0104] Step 104: Generate target difference data based on the corrected second amplitude data and the first amplitude data;

[0105] Step 105: Determine the minimum value in the target difference data as the target calibration data of the preset measurement point;

[0106] Step 106: Generate abnormal field data for the preset measurement point based on the target calibration data and the first amplitude data.

[0107] Steps 101-106 above are discussed in the preceding paragraphs and will not be repeated here.

[0108] This application obtains first target amplitude data corresponding to different transmission frequencies from the first amplitude data of the preset measuring point, and second target amplitude data corresponding to different transmission frequencies from the second amplitude data of the preset measuring point; performs difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain first correction data; performs correction processing on the second amplitude data based on the first correction data to obtain corrected second amplitude data; generates target difference data based on the corrected second amplitude data and the first amplitude data; determines the minimum value in the target difference data as the target calibration data of the preset measuring point; and generates abnormal field data of the preset measuring point based on the target calibration data and the first amplitude data. By minimizing the root mean square error to correct the data after fracturing, and then generating the abnormal field of data before and after fracturing, the method of calculating the abnormal field of electromagnetic fracturing monitoring data in this application effectively suppresses problems such as static displacement in electromagnetic data, highlights the weak anomalies caused by fracturing fluid injection, and rapidly acquires the abnormal field, improving anti-interference ability and the efficiency of abnormal field data generation.

[0109] The third embodiment of this application relates to another method for calculating anomaly fields. Figure 5 This is a flowchart illustrating an anomaly field calculation method according to an exemplary embodiment, such as... Figure 5 As shown, it includes the following steps:

[0110] Step 101: Obtain the first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point;

[0111] Step 102: Perform difference processing on the amplitude data of the first target and the amplitude data of the second target, which have the same transmission frequency, respectively, to obtain the first correction data;

[0112] Step 103: Correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data;

[0113] Step 104: Generate target difference data based on the corrected second amplitude data and the first amplitude data;

[0114] Step 105: Determine the minimum value in the target difference data as the target calibration data of the preset measurement point;

[0115] Step 106: Generate abnormal field data for the preset measurement point based on the target calibration data and the first amplitude data.

[0116] Steps 101-106 above are discussed in the preceding paragraphs and will not be repeated here.

[0117] Step 107: Generate the abnormal field data corresponding to the target area based on the abnormal field data corresponding to all preset measurement points within the target area.

[0118] It should be noted that, as described in the first embodiment, there are multiple preset measuring points within a target mining area. These preset measuring points are arranged according to pre-set rules to achieve effective monitoring of resource mining. Therefore, in steps 101-106, only the anomalous field data corresponding to one preset measuring point is obtained. For an actual resource mining area, one measuring point is not enough. Therefore, it is necessary to process each preset measuring point in steps 101-106 to obtain all the anomalous field data in the entire target area. Only then can the anomalous field data of a target mining area be used in actual production. The anomalous field is a local geophysical field caused by the detection object. The obtained anomalous data can be used as a basis for further detecting the extension range of fracturing fluid.

[0119] The fourth embodiment of this application relates to an anomaly field calculation device, such as... Figure 6 As shown, Figure 6 This is a block diagram of an apparatus for calculating anomaly fields according to an exemplary embodiment. The apparatus includes the following modules:

[0120] The acquisition module 601 is used to acquire first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point.

[0121] The difference processing module 602 is used to perform difference processing on the first target amplitude data and the second target amplitude data that have the same transmission frequency, respectively, to obtain the first correction data;

[0122] The correction module 603 is used to correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data;

[0123] The first generation module 604 is used to generate target difference data based on the corrected second amplitude data and the first amplitude data;

[0124] The determination module 605 is used to determine the minimum value in the target difference data as the target calibration data of the preset measurement point;

[0125] The second generation module 606 is used to generate abnormal field data of the preset measurement point based on the target calibration data and the first amplitude data.

[0126] Furthermore, the device also includes:

[0127] The third generation module is used to process the first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data after the fracturing operation to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

[0128] Furthermore, the correction module includes:

[0129] The correction submodule is used to perform correction processing on each of the second target amplitude data in the second amplitude data according to the first correction data, so as to obtain the corrected second amplitude data.

[0130] Furthermore, the device also includes:

[0131] The fourth generation module is used to generate abnormal field data corresponding to the target area based on the abnormal field data corresponding to all preset measurement points within the target area.

[0132] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0133] Furthermore, based on the same inventive concept, a specific embodiment of this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method steps described in the first, second, or third embodiments.

[0134] Based on the same inventive concept, in specific embodiments of this application, the processor can implement any of the methods in the embodiments of this application when executing the computer program.

[0135] Since the electronic devices described in the specific embodiments of this application are devices used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the devices based on the methods described in the embodiments of this application, and therefore will not be described in detail here. All devices used in the methods of the embodiments of this application fall within the scope of protection of this application.

[0136] Based on the same inventive concept, this application also provides a storage medium corresponding to the method in the embodiment: This embodiment provides a computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the method steps in the first, second, or third embodiment described above.

[0137] In practice, when the computer program is executed by the processor, it can implement any of the methods in the specific embodiments of this application.

[0138] The technical solutions provided in the specific embodiments of this application have at least the following technical effects or advantages:

[0139] This application obtains first target amplitude data corresponding to different transmission frequencies from the first amplitude data of the preset measuring point, and second target amplitude data corresponding to different transmission frequencies from the second amplitude data of the preset measuring point; performs difference processing on the first target amplitude data and the second target amplitude data with the same transmission frequency to obtain first correction data; performs correction processing on the second amplitude data based on the first correction data to obtain corrected second amplitude data; generates target difference data based on the corrected second amplitude data and the first amplitude data; determines the minimum value in the target difference data as the target calibration data of the preset measuring point; and generates abnormal field data of the preset measuring point based on the target calibration data and the first amplitude data. By minimizing the root mean square error to correct the data after fracturing, and then generating the abnormal field of data before and after fracturing, the method of calculating the abnormal field of electromagnetic fracturing monitoring data in this application effectively suppresses problems such as static displacement in electromagnetic data, highlights the weak anomalies caused by fracturing fluid injection, and rapidly acquires the abnormal field, improving anti-interference ability and the efficiency of abnormal field data generation.

[0140] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0141] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, storable media, and processors. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] In a typical configuration, the computer device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. Memory may include non-persistent memory in computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media. Computer-readable media includes both permanent and non-persistent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined in this article, computer-readable media do not include transient media, such as modulated data signals and carrier waves.

[0143] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0144] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0146] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0147] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only 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 terminal device 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 terminal device. 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 terminal device that includes said element.

[0148] The above provides a detailed description of the abnormal field calculation method, apparatus, electronic device, and storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An anomaly field calculation method, applied to an anomaly field processing system, characterized in that, The method includes: The first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point are obtained respectively. The amplitude data of the first target and the amplitude data of the second target, which have the same transmission frequency, are respectively subjected to difference processing to obtain the first correction data; The second amplitude data is corrected based on the first correction data to obtain the corrected second amplitude data; Target difference data is generated based on the corrected second amplitude data and the first amplitude data; The minimum value in the target difference data is determined as the target calibration data of the preset measurement point; Based on the target calibration data and the first amplitude data, abnormal field data of the preset measurement point is generated; The target difference data is obtained through the following formula: in, For the target difference data, The first target amplitude data corresponding to the i-th transmission frequency in the first amplitude data before the pre-set measuring point fracturing operation. The second target amplitude data is the i-th transmission frequency in the corrected second amplitude data, where n is the number of transmission frequencies.

2. The method according to claim 1, characterized in that, Before the steps of acquiring the first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement points, and the second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement points, the method further includes: The first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data collected after the fracturing operation are processed to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

3. The method according to claim 1, characterized in that, The abnormal field data is obtained using the following formula: in, The abnormal field data for the preset measurement points, The target calibration data for the preset measurement points. The first amplitude data for the preset measurement point.

4. The method according to claim 1, characterized in that, The step of correcting the second amplitude data based on the first correction data to obtain the corrected second amplitude data includes: Based on the first correction data, each of the second target amplitude data in the second amplitude data is corrected to obtain the corrected second amplitude data.

5. The method according to claim 1, characterized in that, After the step of generating the abnormal field data of the preset measurement point based on the target calibration data and the first amplitude data, the method further includes: The abnormal field data corresponding to the target area is generated based on the abnormal field data corresponding to all preset measurement points within the target area.

6. An anomalous field calculation device, characterized in that, The device includes: The acquisition module is used to acquire first target amplitude data corresponding to different transmission frequencies in the first amplitude data of the preset measurement point, and second target amplitude data corresponding to different transmission frequencies in the second amplitude data of the preset measurement point. The difference processing module is used to perform difference processing on the first target amplitude data and the second target amplitude data that have the same transmission frequency, respectively, to obtain the first correction data; The correction module is used to correct the second amplitude data according to the first correction data to obtain the corrected second amplitude data; The first generation module is used to generate target difference data based on the corrected second amplitude data and the first amplitude data; The determination module is used to determine the minimum value in the target difference data as the target calibration data of the preset measurement point; The second generation module is used to generate abnormal field data of the preset measurement point based on the target calibration data and the first amplitude data. The target difference data is obtained through the following formula: in, For the target difference data, The first target amplitude data corresponding to the i-th transmission frequency in the first amplitude data before the pre-set measuring point fracturing operation. The second target amplitude data is the i-th transmission frequency in the corrected second amplitude data, where n is the number of transmission frequencies.

7. The apparatus according to claim 6, characterized in that, The device further includes: The third generation module is used to process the first electromagnetic time series data collected from preset measuring points within the target area before the fracturing operation and the second electromagnetic time series data after the fracturing operation to generate the first amplitude data before the fracturing operation and the second amplitude data after the fracturing operation at the preset measuring points.

8. 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; A processor, when executing a program stored in memory, implements the method of any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method as described in any one of claims 1 to 5.

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