Method and device for correcting controllable source magnetotelluric data, electronic equipment and medium

Abstract

The application discloses a controllable source magnetotelluric data correction method and device, electronic equipment and medium. The method can include: calculating the Cagniard apparent resistivity, obtaining the Cagniard apparent resistivity curve; according to the Cagniard apparent resistivity curve, determining the near-field area frequency point range, identifying the frequency points falling into the near-field area frequency point range; determining the one-dimensional inversion frequency range according to the maximum frequency point value in the near-field area frequency point range; one-dimensional inversion is carried out for the apparent resistivity data in the one-dimensional inversion frequency range, and a one-dimensional electrical structure model is obtained; the frequency points in the near-field area frequency point range are corrected according to the one-dimensional electrical structure model, and the near-field corrected apparent resistivity curve is obtained. The electrical structure model obtained by inversion has better forward result and actual data, which is beneficial to reduce the uncertainty of the correction of the near-field data, and then improve the inversion accuracy after correction.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration data processing technology, and more specifically, to a method, apparatus, electronic device, and medium for correcting controlled-source magnetotelluric data. Background Technology

[0002] Currently, the main near-field correction methods include:

[0003] ① Full-frequency domain apparent resistivity method. The full-frequency domain apparent resistivity method (also known as the wide-domain apparent resistivity method) is a novel frequency domain depth sounding method based on the controlled-source audio method. This method does not simplify the process; it uses a precise apparent resistivity calculation formula to calculate a rigorous solution for the apparent resistivity. This solution is accurate at any location within the survey area, thus eliminating near-field problems and enabling the acquisition of greater exploration depths. It has been successfully applied in oil and gas exploration and deep mineral exploration. However, due to its relatively high cost, the application scope of the full-frequency domain apparent resistivity method is far less than that of the controlled-source audio method. Furthermore, current mainstream commercial acquisition software uses the Caniah apparent resistivity calculation formula to obtain the initial frequency domain apparent resistivity, which is not yet implemented in such software. Therefore, the calculation requires data conversion between various software programs, making the process cumbersome.

[0004] ② Correction method for non-artificial source electromagnetic sounding (magnetic sounding, transient electromagnetic sounding). The correction method for non-artificial source electromagnetic sounding requires the simultaneous acquisition of non-artificial source data at nearby locations. When there are significant changes in topography and structure, multiple non-artificial source data channels need to be acquired simultaneously, resulting in higher acquisition costs. Furthermore, non-artificial source electromagnetic sounding is greatly affected by the environment, has a low signal-to-noise ratio, and is not very practical.

[0005] ③ Frequency Truncation Method. The frequency truncation method is currently the most commonly used near-field correction method. In practical exploration applications, most researchers using magnetotelluric 2D and 3D inversion software can only invert wave zone data. Therefore, it is necessary to discard near-field data, excluding it from subsequent processing and inversion, thus trunculating the inversion frequency at a frequency point before entering the near field. However, this method, due to the lack of low-frequency data, significantly reduces the exploration depth of the controlled-source audio method.

[0006] Near-field effects can severely distort the apparent resistivity of the Carnia data, making it unable to accurately reflect the geoelectric structure. Directly using this data for inversion will lead to errors in the interpretation of electrical data. Therefore, it is necessary to develop a method, device, electronic equipment, and medium for correcting magnetotelluric data from a controllable audio source.

[0007] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0008] This invention proposes a method, device, electronic equipment, and medium for correcting controllable source magnetotelluric data. The electrical structure model obtained through inversion has a better match with the actual data in forward modeling, which helps to reduce the uncertainty of near-field data correction and thus improve the accuracy of the corrected inversion.

[0009] In a first aspect, embodiments of this disclosure provide a method for correcting controllable source magnetotelluric data, including:

[0010] Calculate the apparent resistivity of Carnia and obtain the apparent resistivity curve of Carnia.

[0011] Based on the Kania apparent resistivity curve, determine the near-field frequency range and identify the frequency points falling within the near-field frequency range;

[0012] The one-dimensional inversion frequency range is determined based on the maximum frequency value within the near-field frequency range.

[0013] A one-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model;

[0014] Based on the one-dimensional electrical structure model, near-field effect correction is performed on the frequency points within the near-field region to obtain the near-field corrected apparent resistivity curve.

[0015] Preferably, the calculation of the apparent resistivity of the cannia includes:

[0016] Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

[0017] Preferably, the apparent resistivity of the Cania is calculated using formula (1):

[0018]

[0019] Where, ρ α Let V be the Carnia apparent resistivity, μ be the permeability of the medium, f be the sampling frequency, and E be the frequency. y For electric field data perpendicular to the construction direction, H x This refers to the magnetic track data perpendicular to the direction of the electric track.

[0020] Preferably, determining the near-field frequency range based on the Carnia apparent resistivity curve includes:

[0021] If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptotes of the last two frequency points with the Kania apparent resistivity curve.

[0022] Preferably, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency collected to the maximum frequency value in the near-field region frequency range.

[0023] Preferably, near-field effect correction of frequencies within the near-field region based on the one-dimensional electrical structure model includes:

[0024] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was superimposed and displayed with the Kania apparent resistivity curve;

[0025] Adjust the apparent resistivity values ​​of the frequencies within the near-field frequency range to the frequency values ​​corresponding to the forward model curve.

[0026] Preferably, it further includes:

[0027] Two-dimensional inversion is performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0028] As one specific implementation of this disclosure,

[0029] Secondly, embodiments of this disclosure also provide a correction device for controllable source magnetotelluric data, comprising:

[0030] The calculation module calculates the apparent resistivity of Kania and obtains the apparent resistivity curve of Kania.

[0031] The identification module determines the near-field frequency range based on the Kania apparent resistivity curve and identifies the frequency points that fall within the near-field frequency range.

[0032] The one-dimensional inversion frequency range determination module determines the one-dimensional inversion frequency range based on the maximum frequency value within the near-field frequency range.

[0033] The one-dimensional inversion module performs one-dimensional inversion on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model.

[0034] The near-field effect correction module performs near-field effect correction on the frequency points within the near-field region based on the one-dimensional electrical structure model, and obtains the near-field corrected apparent resistivity curve.

[0035] Preferably, the calculation of the apparent resistivity of the cannia includes:

[0036] Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

[0037] Preferably, the apparent resistivity of the Cania is calculated using formula (1):

[0038]

[0039] Where, ρ α Let V be the Carnia apparent resistivity, μ be the permeability of the medium, f be the sampling frequency, and E be the frequency. y For electric field data perpendicular to the construction direction, H x This refers to the magnetic track data perpendicular to the direction of the electric track.

[0040] Preferably, determining the near-field frequency range based on the Carnia apparent resistivity curve includes:

[0041] If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptotes of the last two frequency points with the Kania apparent resistivity curve.

[0042] Preferably, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency collected to the maximum frequency value in the near-field region frequency range.

[0043] Preferably, near-field effect correction of frequencies within the near-field region based on the one-dimensional electrical structure model includes:

[0044] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was superimposed and displayed with the Kania apparent resistivity curve;

[0045] Adjust the apparent resistivity values ​​of the frequencies within the near-field frequency range to the frequency values ​​corresponding to the forward model curve.

[0046] Preferably, it further includes:

[0047] Two-dimensional inversion is performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0048] Thirdly, embodiments of this disclosure also provide an electronic device, the electronic device comprising:

[0049] Memory, which stores executable instructions;

[0050] A processor that executes the executable instructions in the memory to implement the method for correcting controlled-source magnetotelluric data.

[0051] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for correcting controllable source magnetotelluric data.

[0052] Its beneficial effects are as follows:

[0053] 1. Compared with the frequency truncation method, it increases the number of effective frequency points and improves the depth of inversion sounding.

[0054] The frequency truncation method directly discards near-field data, excluding it from subsequent processing and inversion. Due to the lack of low-frequency data, the final inversion depth is shallower than the full-band inversion depth. The near-field correction method based on the one-dimensional inversion method retains full-band data, solving the problem that the actual depth measurement cannot reach the design depth.

[0055] 2. It has better compatibility with other software than the full-frequency domain apparent resistivity method.

[0056] Currently, mainstream commercial data acquisition software uses the Caniah apparent resistivity calculation formula to obtain the initial frequency domain apparent resistivity. The full-frequency domain apparent resistivity method is not yet implemented in such software. This invention proposes a near-field correction method based on one-dimensional inversion, which can be directly used in mature mainstream software without the need for software platform conversion. Therefore, it has the advantages of directly utilizing existing software and having stronger compatibility.

[0057] 3. Compared with non-artificial field source electromagnetic depth sounding (MT, TEM) correction methods, it is more practical and has a lower cost.

[0058] Traditional electromagnetic sounding correction methods using non-artificial source sources require simultaneous acquisition of non-artificial source data at nearby locations. When terrain and structural changes are significant, multiple non-artificial source data channels need to be acquired simultaneously, increasing acquisition costs. Furthermore, non-artificial source electromagnetic sounding is significantly affected by the environment, resulting in a low signal-to-noise ratio and limited practicality. The near-field correction method based on one-dimensional inversion proposed in this invention can simulate artificial source sounding data during the processing stage using forward modeling, reducing actual acquisition costs and enhancing practicality.

[0059] The methods and apparatus of the present invention have other features and advantages that will be apparent from or will be set forth in detail in the accompanying drawings and following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0060] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts.

[0061] Figure 1 A flowchart illustrating the steps of a method for correcting controlled-source magnetotelluric data according to an embodiment of the present invention is shown.

[0062] Figure 2 A schematic diagram of the original Carnia apparent resistivity curve at measuring point site09 according to an embodiment of the present invention is shown.

[0063] Figure 3A schematic diagram of the preprocessed Carnia apparent resistivity curve of measuring point site09 according to an embodiment of the present invention is shown.

[0064] Figure 4 A schematic diagram of the near-field frequency range of measurement point site09 according to an embodiment of the present invention is shown.

[0065] Figure 5 A schematic diagram of a one-dimensional inverted apparent resistivity curve at measurement point site09 according to an embodiment of the present invention is shown.

[0066] Figure 6 A schematic diagram of the MT forward modeling curve of measurement point site09 according to an embodiment of the present invention is shown.

[0067] Figure 7 A schematic diagram of the near-field corrected apparent resistivity curve of measuring point site09 according to an embodiment of the present invention is shown.

[0068] Figure 8 A block diagram of a controllable source magnetotelluric data correction device according to an embodiment of the present invention is shown.

[0069] Explanation of reference numerals in the attached figures:

[0070] 201. Calculation module; 202. Identification module; 203. One-dimensional inversion frequency range determination module; 204. One-dimensional inversion module; 205. Near-field effect correction module. Detailed Implementation

[0071] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0072] This invention provides a method for correcting controllable source magnetotelluric data, comprising:

[0073] Calculate the apparent resistivity of Carnia and obtain the apparent resistivity curve of Carnia.

[0074] Based on the Kania apparent resistivity curve, determine the frequency range of the near-field region and identify the frequency points that fall within the frequency range of the near-field region;

[0075] The one-dimensional inversion frequency range is determined based on the maximum frequency value within the near-field frequency range.

[0076] One-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model;

[0077] The near-field effect is corrected for frequencies within the near-field region based on a one-dimensional electrical structure model, and the apparent resistivity curve after near-field correction is obtained.

[0078] In one example, calculating the apparent resistivity of Cania includes:

[0079] Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

[0080] In one example, the apparent resistivity of the Cania is calculated using formula (1):

[0081]

[0082] Where, ρ α Let V be the Carnia apparent resistivity, μ be the permeability of the medium, f be the sampling frequency, and E be the frequency. y For electric field data perpendicular to the construction direction, H x For magnetic track data perpendicular to the direction of the electric track, measurements are taken in the mid-to-far range. I is the current value, r is the transmit / receive distance, and dL is the distance between the two electrodes AB of the transmitter. The angle between the line connecting the measuring point and the midpoint of the AB polar distance and the X direction.

[0083] In one example, the near-field frequency range is determined based on the Kania apparent resistivity curve, including:

[0084] If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptotes of the last two frequency points with the Kania apparent resistivity curve.

[0085] In one example, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency acquired to the maximum frequency value in the near-field region.

[0086] In one example, near-field effect correction for frequencies within the near-field region based on a one-dimensional electrical structure model includes:

[0087] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was overlaid with the Carnia apparent resistivity curve for display.

[0088] Adjust the apparent resistivity values ​​of frequencies within the near-field frequency range to the frequency values ​​corresponding to the forward model curve.

[0089] In one example, it also includes:

[0090] Two-dimensional inversion was performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0091] Specifically, the current, current, and magnetic data of the controllable audio source magnetotelluric data collected in the field are obtained, and then the apparent resistivity of each measuring point is calculated by formula (1). For some frequency points with abnormal apparent resistivity values, the process of smoothing and deleting jump points is carried out to obtain the apparent resistivity curve of Kania.

[0092] Based on the Kania apparent resistivity curve, determine the frequency range of the near-field region. If the Kania apparent resistivity curve rises at 45°, then the frequency range of the near-field region is defined by the intersection of the 45° asymptote of the last two frequency points and the Kania apparent resistivity curve, and the frequency points falling within the frequency range of the near-field region are identified.

[0093] The one-dimensional inversion frequency range is determined by the maximum frequency value within the near-field frequency range, which is the range from the maximum frequency acquired to the maximum frequency value within the near-field frequency range.

[0094] One-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model; full-band MT forward modeling is performed on the one-dimensional electrical structure model, and the forward modeling curve is superimposed on the Kania apparent resistivity curve for display; the apparent resistivity values ​​of the frequencies within the near-field frequency range are adjusted to the corresponding frequency values ​​of the forward modeling curve to obtain the near-field corrected apparent resistivity curve.

[0095] Two-dimensional inversion was performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0096] The present invention also provides a controllable source magnetotelluric data correction device, comprising:

[0097] The calculation module calculates the apparent resistivity of Kania and obtains the apparent resistivity curve of Kania.

[0098] The identification module determines the near-field frequency range based on the Kania apparent resistivity curve and identifies frequencies that fall within the near-field frequency range.

[0099] The one-dimensional inversion frequency range determination module determines the one-dimensional inversion frequency range based on the maximum frequency value within the near-field frequency range.

[0100] The one-dimensional inversion module performs one-dimensional inversion on apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model.

[0101] The near-field effect correction module performs near-field effect correction on frequencies within the near-field region based on a one-dimensional electrical structure model, and obtains the near-field corrected apparent resistivity curve.

[0102] In one example, calculating the apparent resistivity of Cania includes:

[0103] Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

[0104] In one example, the apparent resistivity of the Cania is calculated using formula (1):

[0105]

[0106] Where, ρ α Let V be the Carnia apparent resistivity, μ be the permeability of the medium, f be the sampling frequency, and E be the frequency. y For electric field data perpendicular to the construction direction, H x This refers to the magnetic track data perpendicular to the direction of the electric track.

[0107] In one example, the near-field frequency range is determined based on the Kania apparent resistivity curve, including:

[0108] If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptotes of the last two frequency points with the Kania apparent resistivity curve.

[0109] In one example, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency acquired to the maximum frequency value in the near-field region.

[0110] In one example, near-field effect correction for frequencies within the near-field region based on a one-dimensional electrical structure model includes:

[0111] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was overlaid with the Carnia apparent resistivity curve for display.

[0112] Adjust the apparent resistivity values ​​of frequencies within the near-field frequency range to the frequency values ​​corresponding to the forward model curve.

[0113] In one example, it also includes:

[0114] Two-dimensional inversion was performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0115] Specifically, the current, current, and magnetic data of the controllable audio source magnetotelluric data collected in the field are obtained, and then the apparent resistivity of each measuring point is calculated by formula (1). For some frequency points with abnormal apparent resistivity values, the process of smoothing and deleting jump points is carried out to obtain the apparent resistivity curve of Kania.

[0116] Based on the Kania apparent resistivity curve, determine the frequency range of the near-field region. If the Kania apparent resistivity curve rises at 45°, then the frequency range of the near-field region is defined by the intersection of the 45° asymptote of the last two frequency points and the Kania apparent resistivity curve, and the frequency points falling within the frequency range of the near-field region are identified.

[0117] The one-dimensional inversion frequency range is determined by the maximum frequency value within the near-field frequency range, which is the range from the maximum frequency acquired to the maximum frequency value within the near-field frequency range.

[0118] One-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model; full-band MT forward modeling is performed on the one-dimensional electrical structure model, and the forward modeling curve is superimposed on the Kania apparent resistivity curve for display; the apparent resistivity values ​​of the frequencies within the near-field frequency range are adjusted to the corresponding frequency values ​​of the forward modeling curve to obtain the near-field corrected apparent resistivity curve.

[0119] Two-dimensional inversion was performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0120] The present invention also provides an electronic device, comprising: a memory storing executable instructions; and a processor that executes the executable instructions in the memory to implement the above-described method for correcting controllable source magnetotelluric data.

[0121] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for correcting controllable source magnetotelluric data.

[0122] To facilitate understanding of the solutions and effects of the embodiments of the present invention, four specific application examples are given below. Those skilled in the art should understand that these examples are merely for the purpose of understanding the present invention, and any specific details therein are not intended to limit the present invention in any way.

[0123] Example 1

[0124] Figure 1 A flowchart illustrating the steps of a method for correcting controlled-source magnetotelluric data according to the present invention is shown.

[0125] like Figure 1 As shown, the correction method for controlled-source magnetotelluric data includes: Step 101, calculating the Carnia apparent resistivity to obtain the Carnia apparent resistivity curve; Step 102, determining the near-field frequency range based on the Carnia apparent resistivity curve, and identifying the frequency points falling within the near-field frequency range; Step 103, determining the one-dimensional inversion frequency range based on the maximum frequency value within the near-field frequency range; Step 104, performing one-dimensional inversion on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model; Step 105, performing near-field effect correction on the frequency points within the near-field frequency range based on the one-dimensional electrical structure model to obtain the near-field corrected apparent resistivity curve.

[0126] Figure 2A schematic diagram of the original Carnia apparent resistivity curve at measuring point site09 according to an embodiment of the present invention is shown.

[0127] Figure 3 A schematic diagram of the preprocessed Carnia apparent resistivity curve of measuring point site09 according to an embodiment of the present invention is shown.

[0128] Controlled-audio-source magnetotelluric sounding was conducted in a certain area, acquiring current, current, and magnetic data from 25 measuring points, numbered Site0-Site25. The apparent resistivity of each measuring point was calculated using formula (1). Taking Site09 as an example, the calculation results are as follows: Figure 2 As shown. For anomalies in apparent resistivity values ​​at certain frequency points, the curve is smoothed and jump points are removed to obtain the Cania apparent resistivity curve. Taking Site09 as an example, the processing result is as follows. Figure 3 As shown.

[0129] Observe whether the Carnia apparent resistivity curve rises at 45°. If the Carnia apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptote of the last two frequency points and the Carnia apparent resistivity curve, and then the frequency points falling into the near-field frequency range are identified.

[0130] Figure 4 A schematic diagram of the near-field frequency range of measurement point site09 according to an embodiment of the present invention is shown.

[0131] Taking Site09 as an example, such as Figure 4 As shown, the intersection of the 45° asymptotes of the last two frequency points and the Carnia apparent resistivity curve is 1 Hz. Therefore, in this embodiment, low-frequency electromagnetic waves below 1 Hz are received in the near field, and their resistivity values ​​do not meet the plane wave assumption, so near-field correction is required.

[0132] The one-dimensional inversion frequency range is determined based on the maximum frequency value within the near-field frequency range. The one-dimensional inversion frequency range for Site09 measurement point in this area is 1000Hz to 1Hz.

[0133] Figure 5 A schematic diagram of a one-dimensional inverted apparent resistivity curve of measuring point site09 according to an embodiment of the present invention is shown, where black dots represent the apparent resistivity values ​​after preprocessing and gray dots represent the inverted apparent resistivity values.

[0134] One-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model, such as... Figure 5 As shown.

[0135] Figure 6A schematic diagram of the MT forward modeling curve of measuring point site09 according to an embodiment of the present invention is shown. The black dots are the apparent resistivity values ​​after preprocessing, and the gray dots are the apparent resistivity values ​​obtained from the forward modeling.

[0136] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the model was overlaid with the Carnia apparent resistivity curve obtained in step 1 for display, as shown below. Figure 6 As shown.

[0137] Figure 7 A schematic diagram of the near-field corrected apparent resistivity curve of measuring point site09 according to an embodiment of the present invention is shown.

[0138] Adjust the apparent resistivity values ​​at near-field frequencies to the frequencies corresponding to the MT forward modeling curve to obtain the near-field corrected apparent resistivity curve, such as... Figure 7 As shown.

[0139] The above steps were performed sequentially on measuring points Site0-Site25 to obtain near-field correction data for the entire profile. Based on the near-field corrected apparent resistivity curve, a two-dimensional inversion was performed to obtain the underground two-dimensional electrical structure.

[0140] Example 2

[0141] Figure 8 A block diagram of a controllable source magnetotelluric data correction device according to an embodiment of the present invention is shown.

[0142] like Figure 8 As shown, the controllable source magnetotelluric data correction device includes:

[0143] Calculation module 201 calculates the apparent resistivity of Carnia and obtains the apparent resistivity curve of Carnia.

[0144] The identification module 202 determines the near-field frequency range based on the Kania apparent resistivity curve and identifies the frequency points that fall within the near-field frequency range.

[0145] The one-dimensional inversion frequency range determination module 203 determines the one-dimensional inversion frequency range based on the maximum frequency value within the near-field frequency range.

[0146] The one-dimensional inversion module 204 performs one-dimensional inversion on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model.

[0147] The near-field effect correction module 205 performs near-field effect correction on the frequency points within the near-field region based on the one-dimensional electrical structure model, and obtains the near-field corrected apparent resistivity curve.

[0148] As an optional approach, the calculation of the apparent resistivity of Cania includes:

[0149] Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

[0150] As an alternative, the apparent resistivity of Cania is calculated using formula (1):

[0151]

[0152] Where, ρ α Let V be the Carnia apparent resistivity, μ be the permeability of the medium, f be the sampling frequency, and E be the frequency. y For electric field data perpendicular to the construction direction, H x This refers to the magnetic track data perpendicular to the direction of the electric track.

[0153] As an optional approach, the near-field frequency range can be determined based on the Kania apparent resistivity curve, including:

[0154] If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptotes of the last two frequency points with the Kania apparent resistivity curve.

[0155] As an optional approach, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency collected to the maximum frequency value in the near-field region.

[0156] As an optional approach, near-field effect correction is performed on frequencies within the near-field region based on a one-dimensional electrical structure model, including:

[0157] A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was overlaid with the Carnia apparent resistivity curve for display.

[0158] Adjust the apparent resistivity values ​​of frequencies within the near-field frequency range to the frequency values ​​corresponding to the forward model curve.

[0159] As an optional solution, the following are also included:

[0160] Two-dimensional inversion was performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

[0161] Example 3

[0162] This disclosure provides an electronic device comprising: a memory storing executable instructions; and a processor executing the executable instructions in the memory to implement the aforementioned method for correcting controllable source magnetotelluric data.

[0163] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0164] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0165] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of this disclosure, the processor is used to execute computer-readable instructions stored in the memory.

[0166] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0167] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0168] Example 4

[0169] This disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for correcting controlled-source magnetotelluric data.

[0170] A computer-readable storage medium according to embodiments of the present disclosure stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present disclosure are performed.

[0171] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0172] Those skilled in the art should understand that the above description of the embodiments of the present invention is only intended to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any of the examples given.

[0173] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for correcting controlled-source magnetotelluric data, characterized in that, include: Calculate the apparent resistivity of Carnia and obtain the apparent resistivity curve of Carnia. Based on the Kania apparent resistivity curve, determine the near-field frequency range and identify the frequency points falling within the near-field frequency range; The one-dimensional inversion frequency range is determined based on the maximum frequency value within the near-field frequency range. A one-dimensional inversion is performed on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model; Based on the one-dimensional electrical structure model, near-field effect correction is performed on the frequency points within the near-field region to obtain the near-field corrected apparent resistivity curve; The determination of the near-field frequency range based on the Carnia apparent resistivity curve includes: If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptote of the last two frequency points and the Kania apparent resistivity curve. Wherein, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency collected to the maximum frequency value of the near-field region frequency range; The near-field effect correction for frequencies within the near-field region based on the one-dimensional electrical structure model includes: A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was superimposed and displayed with the Kania apparent resistivity curve; Adjust the apparent resistivity value of the frequency points within the near-field frequency range to the frequency point value corresponding to the forward model curve; This also includes: Two-dimensional inversion is performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

2. The method for correcting controllable source magnetotelluric data according to claim 1, wherein, The calculation of Carnia's apparent resistivity includes: Acquire current, electrical, and magnetic data from a controllable audio source magnetotelluric data collected in the field, and then calculate the apparent resistivity of each measuring point.

3. The method for correcting controllable source magnetotelluric data according to claim 2, wherein, The apparent resistivity of the Cania is calculated using formula (1): （1） in, For the apparent resistivity of Cania, The magnetic permeability of the medium, For the sampling frequency, For circuit data perpendicular to the construction direction, This refers to the magnetic track data perpendicular to the direction of the electric track.

4. A device for correcting controllable source magnetotelluric data, characterized in that, include: The calculation module calculates the apparent resistivity of Kania and obtains the apparent resistivity curve of Kania. The identification module determines the near-field frequency range based on the Kania apparent resistivity curve and identifies the frequency points that fall within the near-field frequency range. The one-dimensional inversion frequency range determination module determines the one-dimensional inversion frequency range based on the maximum frequency value within the near-field frequency range. The one-dimensional inversion module performs one-dimensional inversion on the apparent resistivity data within the one-dimensional inversion frequency range to obtain a one-dimensional electrical structure model. The near-field effect correction module performs near-field effect correction on the frequency points within the near-field region based on the one-dimensional electrical structure model, and obtains the near-field corrected apparent resistivity curve. The determination of the near-field frequency range based on the Carnia apparent resistivity curve includes: If the Kania apparent resistivity curve rises at 45°, then the near-field frequency range is defined by the intersection of the 45° asymptote of the last two frequency points and the Kania apparent resistivity curve. Wherein, the one-dimensional inversion frequency range is the maximum frequency value from the maximum frequency collected to the maximum frequency value of the near-field region frequency range; The near-field effect correction for frequencies within the near-field region based on the one-dimensional electrical structure model includes: A full-band MT forward modeling was performed on the one-dimensional electrical structure model, and the forward modeling curve was superimposed and displayed with the Kania apparent resistivity curve; Adjust the apparent resistivity value of the frequency points within the near-field frequency range to the frequency point value corresponding to the forward model curve; This also includes: Two-dimensional inversion is performed on the near-field corrected apparent resistivity curve to obtain the underground two-dimensional electrical structure.

5. An electronic device, characterized in that, The electronic device includes: Memory, which stores executable instructions; A processor that executes the executable instructions in the memory to implement the method for correcting controlled-source magnetotelluric data according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for correcting controlled-source magnetotelluric data according to any one of claims 1-3.

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