Magnetic phase gradient-based apparent conductivity rapid imaging method and application thereof

Abstract

The invention relates to a magnetic phase gradient-based apparent conductivity rapid imaging method and application thereof, and the method combines the recognition capability of a magnetic phase and an electromagnetic field gradient to an underground electrical structure, takes the phase gradient of a magnetic field Hz component as an imaging parameter for imaging, and avoids the error interference of magnetic field multi-component collection. The method can be applied to rapid imaging of the underground electrical structure; particularly, the conductivity is far greater than that of a metal mine area with dielectric loss. Compared with a traditional apparent resistivity imaging method, imaging is carried out through the phase gradient of the Hz component of the magnetic field, high adaptability is shown in different burial depths, electrical characteristics and noise environments, background field correction is not needed in the imaging process, the adverse effect of background resistivity calculation errors on the imaging result is avoided, and the imaging accuracy is improved. And meanwhile, the calculation process is simplified, the complexity of the imaging process is reduced, and the working efficiency and practicability of the method are effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of metal exploration, and relates to a ground-air frequency domain electromagnetic detection method, in particular to a fast apparent conductivity imaging method based on magnetic phase gradient and its application. Background Art

[0002] The frequency domain electromagnetic method is a geophysical exploration method for studying the electrical distribution and properties of underground structures. It is based on the principle of electromagnetic induction and obtains underground structure information by measuring the response of underground structures to electromagnetic fields of different frequencies. The frequency domain electromagnetic method has a wide range of applications in underground structure detection, mineral resource exploration, hydrogeological survey, polar research, underground pipeline detection, and other environmental and engineering detection fields. Currently, the frequency domain electromagnetic methods applied to geophysical exploration mainly include the following three: controlled source audio-frequency magnetotelluric method (CSAMT), airborne frequency domain electromagnetic method (AFEM), and ground-air frequency domain electromagnetic method (GAFDEM). CSAMT has a high signal-to-noise ratio and a strong observed signal, so it has the advantages of large detection depth and wide detection range; however, it is necessary to lay out a transmitting loop and multiple receiving devices on the ground, so it is difficult to operate in complex terrain areas, with low work efficiency and high cost. AFEM uses an aircraft to carry electromagnetic exploration equipment, and there is no need for personnel to enter the detection area for exploration work, and it can cover a large area in a short time, so it has the advantages of wide detection range, high efficiency, and the ability to detect in complex terrain and extreme environments; however, due to the high-speed movement of the flight platform and the limitation of the measurement height, the resolution of this method is low, the ability to identify small underground targets is poor, and during the detection process, it is affected by the noise of the surface and near-surface, increasing the complexity of data interpretation. Limited by the transmitter power and the distance between the transmitting coil and the receiving coil, the detection depth of this method is relatively shallow, and the cost is high and the safety is poor. GAFDEM uses a ground-based transmitter loop and a flight platform to carry a receiver to collect airborne magnetic field data. This method combines the advantages of CSAMT and AFEM and has the ability to quickly detect the underground electrical structure with a large range and large depth in complex terrain areas, and has the advantages of high safety and low cost.

[0003] At present, the instrument and equipment of the frequency-domain electromagnetic method already have relatively high performance. However, the data interpretation methods matching them are relatively lagging, seriously restricting the practical application and research development of GAFDEM. There are mainly two data interpretation methods for GAFDEM: the inversion method and the fast imaging method. Among them, the inversion method performs iterative calculations on the initial model with an appropriate inversion algorithm, then compares the differences between the data of the forward model and the measured data, continuously optimizes the parameters of the forward model, and finally realizes the interpretation of the underground structure, with the advantages of high resolution and strong adaptability. However, the inversion method is affected by many factors, such as the selection of the initial model, the geometric configuration of the observation system, etc.; and a large amount of computing resources are consumed during the inversion process, the computing time is very long, the work efficiency is low, and it cannot meet the needs of instrument testing, data quality evaluation, and general investigation of geological structures during actual exploration. It is more suitable for data processing after the exploration work is completed. Therefore, the fast imaging method has become an important means for the rapid interpretation of GAFDEM data. It can meet our needs for instrument calibration, data quality monitoring, and real-time interpretation during exploration, and can better reflect the actual changes in the underground electrical structure, providing a reference for the selection of the initial model for subsequent inversion.

[0004] Currently, the main fast imaging methods include the divergence of the tilt angle imaging method and the apparent resistivity imaging method. The divergence of the tilt angle imaging has obvious advantages in terms of resolution and imaging time. However, when using the divergence of the tilt angle to image the underground electrical structure, the upper and lower boundaries of the abnormal body cannot be accurately identified. By comparing the similarities and differences in the response characteristics of the divergence of the tilt angle in the natural field source and the orthogonal electric field source, it is found that through the deployment of the orthogonal field source, the detection effect of the low resistivity anomaly is improved. However, the divergence of the tilt angle imaging requires an orthogonal excitation source, and the layout of the ground excitation source in complex terrain areas is restricted in terms of space and location selection, making the layout of the excitation source consume more time and resources, reducing the work efficiency and usability of the divergence of the tilt angle imaging.

[0005] The apparent resistivity (ARI) imaging method can achieve rapid imaging of the underground structure only with the magnetic field z-component data under the excitation of a single source. However, this method has poor ability to identify the abnormal boundary and can only roughly identify the central position where the anomaly is located. Due to the shadow effect, the abnormal response will extend to a deeper area, making the size of the abnormal body in the imaging profile much larger than the actual size, and the contour of the abnormal body cannot be accurately identified. At present, some researchers have also proposed a GAFDEM fast imaging method based on the spatial magnetic field gradient anomaly, which can effectively identify the position and contour of the abnormal body only with GAFDEM data, effectively improving the imaging accuracy of underground abnormal bodies; however, this method needs to apply ARIMAD to calculate the apparent resistivity as the background resistivity, and then calculate the background field data; there is a certain gap between the background resistivity estimated by this method and the true value, resulting in the appearance of false anomalies. Summary of the Invention

[0006] In view of the problems existing in the existing GAFDEM data fast imaging method, the present invention proposes a fast imaging method of apparent conductivity based on magnetic phase gradient. This method combines the recognition ability of magnetic phase and electromagnetic field gradient for underground electrical structures, and uses the phase gradient of the magnetic field Hz component as the imaging parameter for imaging, avoiding the error interference of multi-component magnetic field acquisition.

[0007] A fast imaging method of apparent conductivity CMPG based on magnetic phase gradient provided by the present invention has the following calculation formula:

[0008]

[0009] Wherein, CMPG(X,Y,Z) is the apparent conductivity of the magnetic phase gradient, and the spatial position coordinates corresponding to the magnetic phase gradient conductivity CMPG of the measuring points at different frequencies are (X(i),Y(i),Z(i)), H z (i,j) is the magnetic field z component of each measuring point on the measuring line at different frequencies, i = 1, 2... p, p is the total number of measuring points on a measuring line, j = 1, 2... q, q is the total number of transmitting frequencies, μ 0 is the vacuum magnetic permeability, ω(j) is the angular velocity corresponding to each transmitting frequency, j = 1, 2... q, is the phase of the magnetic field component Hz, Re(H z (i,j)) is the real part of the magnetic field component Hz, Im(H z (i,j)) is the imaginary part of the magnetic field component Hz, r(i) is the transmitting-receiving distance of the measuring point, ρ 0 is the background resistivity.

[0010] The fast imaging method of apparent conductivity based on magnetic phase gradient provided by the present invention can be applied to the fast imaging of underground electrical structures; especially in metal mining areas where the conductivity is much greater than the dielectric loss, the propagation of electromagnetic waves is mainly determined by the conductivity, and the influence of the dielectric constant is negligible.

[0011] In the case of no abnormal body, this method can correctly depict the background conductivity distribution; compared with the uniform half-space model, when there is an abnormal body underground, a high-value trap of CMPG appears at the position of the abnormal body.

[0012] Since whether it is a low-resistance anomaly or a high-resistance anomaly, the position of the abnormal body in the imaging result of the above method will show a high-value trap, making it impossible to directly compare the relationship between the resistivity of the abnormal body and the background resistivity. Therefore, the present invention further provides an improved imaging method (ICMPG) of apparent conductivity based on magnetic phase gradient, and the formula definition is as follows:

[0013]

[0014] ICMPG(X, Y, Z) is the apparent conductivity that improves the magnetic phase gradient. The spatial position coordinates corresponding to the magnetic phase gradient conductivity CMPG of the measurement points at different frequencies are (X(i), Y(i), Z(i)), and μ 0 is the magnetic permeability of vacuum, ω(j) is the angular velocity corresponding to each emission frequency, j = 1, 2... q, and q is the total number of emission frequencies. is the phase of the magnetic field component Hz, r(i) is the transceiver distance of the measurement point, i = 1, 2... p, and p is the total number of measurement points on a measurement line. is the phase of the magnetic field component Hz, Re(H z (i, j)) is the real part of the magnetic field component Hz, Im(H z (i, j)) is the imaginary part of the magnetic field component Hz, r(i) is the transceiver distance of the measurement point, and ρ 0 is the background resistivity.

[0015] An improved imaging method for the apparent conductivity based on the magnetic phase gradient provided by the present invention can be applied to the rapid imaging of the underground electrical structure; especially in metal mining areas where the conductivity is much greater than the dielectric loss, the propagation of electromagnetic waves is mainly determined by the conductivity, and the influence of the dielectric constant is negligible.

[0016] When the resistivity of the anomaly is lower than the background resistivity, the location of the anomaly shows a high-value trap, and vice versa for a low-value trap. The improved imaging method for the apparent conductivity based on the magnetic phase gradient is based on the positive and negative differences of the magnetic phase gradient, that is, when the resistivity of the anomaly is lower than the background resistivity, the magnetic phase gradient is positive, and vice versa. Therefore, the improved imaging method for the apparent conductivity based on the magnetic phase gradient can not only indicate the location and boundary contour of the anomaly, but also further reflect the relationship between the resistivity of the anomaly and the background resistivity, providing a more intuitive electrical property characteristic of the anomaly.

[0017] The present invention also provides a rapid imaging method for the underground electrical structure, including the following steps:

[0018] Lay a long wire source on the ground as the excitation source, and pass an alternating current with a fixed frequency into the long wire source to generate electromagnetic waves. When the electromagnetic waves are incident on the earth, eddy currents will be induced inside the earth, and these eddy currents will generate a magnetic field, which will further affect the magnetic field data collected by the magnetic field data acquisition device;

[0019] The magnetic field generated by the eddy currents is related to the conductivity of the underground structure. Therefore, by detecting the phase data of the magnetic field data generated by the eddy currents, the detection of the underground electrical structure can be realized; use a drone to carry the magnetic field data acquisition device and fly along the preset measurement line, maintaining a certain safe height from the ground; through the magnetic field data acquisition device, collect the vertical component Hz of the magnetic field above the measurement line;

[0020] The noise of power frequency interference and human interference is removed from the collected vertical component of the magnetic field through denoising methods such as wavelet transform to obtain high-quality magnetic field data with a high signal-to-noise ratio. The magnetic field data is subjected to Fourier transform to obtain the real and imaginary part data of the detection target frequency point, and the magnetic field phase is calculated.

[0021] According to a fast apparent conductivity imaging method based on magnetic phase gradient provided above, or an improved imaging method of apparent conductivity based on magnetic phase gradient, the apparent conductivity value of the underground structure is calculated based on the magnetic field phase gradient; according to the skin depth formula, the skin depth corresponding to each target frequency point is calculated, and combined with spatial information such as longitude and latitude, an underground apparent conductivity distribution matrix is obtained.

[0022] The interpolation method is applied to plot the apparent conductivity distribution matrix to obtain an underground electrical property structure diagram.

[0023] The beneficial effects of the present invention:

[0024] A fast apparent conductivity imaging method based on magnetic phase gradient provided by the present invention, and an improved imaging method of apparent conductivity based on magnetic phase gradient. Compared with the traditional apparent resistivity imaging method, the present invention performs imaging through the phase gradient of the magnetic field Hz component. During the imaging process, no background field correction is required, avoiding the adverse effect of background resistivity calculation error on the imaging result. At the same time, the calculation process is simplified, the complexity of the imaging process is reduced, and the working efficiency and practicability of the method are effectively improved.

[0025] Through the imaging simulation verification of different electrical anomaly bodies, a fast apparent conductivity imaging method based on magnetic phase gradient provided by the present invention, and an improved imaging method of apparent conductivity based on magnetic phase gradient show strong adaptability under different burial depths, electrical characteristics, and noise environments. Especially the improved imaging method of apparent conductivity based on magnetic phase gradient, ICMPG, can effectively identify the boundary and position of the anomaly body in both a single anomaly body model and a complex model with multiple anomaly bodies coexisting, and has a high imaging accuracy; in a noisy environment, although the Gaussian white noise interference affects the clarity of the boundary, the position and electrical characteristics of the anomaly body can still be accurately identified, demonstrating the excellent anti-noise performance of the method.

[0026] In actual geological exploration applications, the method of the present invention has been successfully compared with the actual geological background data of the Gang cobalt (copper-nickel) deposit in Linjiang City, Baishan City, Jilin Province, verifying the effectiveness of the method in actual exploration. The imaging results accurately reflect the location and distribution of the deposit, especially showing significant advantages in the identification of deep deposits. The ICMPG method provides a new idea for the rapid imaging of underground electrical structures, especially applicable to complex terrain and depth exploration environments, providing reliable technical support for geophysical exploration. Future research can further optimize the imaging accuracy based on this and expand its application potential in fields such as mineral resource exploration and environmental investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is the imaging model of magnetic phase gradient conductivity CMPG in Example 1;

[0028] Among them: (a) Three-dimensional schematic diagram; (b) yz sectional view; (c) xy sectional view;

[0029] Figure 2 It is the imaging result of magnetic phase gradient conductivity CMPG in Example 1;

[0030] Among them: (a) Uniform half-space model; (b) Low-resistance anomaly model; (c) High-resistance anomaly model;

[0031] Figure 3 It is the imaging result of improved magnetic phase gradient conductivity ICMPG in Example 2;

[0032] Among them: (a) Imaging result of low-resistance anomaly model ICMPG; (b) Imaging result of high-resistance anomaly model ICMPG;

[0033] Figure 4 It is the imaging model of ICMPG in Example 2;

[0034] Among them: (a) Three-dimensional schematic diagram; (b) yz sectional view; (c) xy sectional view;

[0035] Figure 5 It is the three-dimensional slice of the imaging result of low-resistance anomaly model ICMPG in Example 3;

[0036] Among them: (a) x = 0m; (b) x = 100m; (c) x = 200m; (d) x = 300m;

[0037] Figure 6 It is the three-dimensional slice of the imaging result of high-resistance anomaly model ICMPG in Example 3;

[0038] Among them: (a) x = 0m; (b) x = 100m; (c) x = 200m; (d) x = 300m;

[0039] Figure 7 Imaging results of different resistivity anomaly models for Example 4;

[0040] Among them: (a) Low-resistivity anomaly ρ 1 = 50 Ωm model; (b) High-resistivity anomaly ρ 1 = 200 Ωm model;

[0041] Figure 8 Imaging models of different buried depths of abnormal bodies for Example 5;

[0042] Among them: (a) Three-dimensional schematic diagram; (b) yz sectional view of different buried depths of abnormal bodies; (c) xy sectional view of different buried depths of abnormal bodies;

[0043] Figure 9 Imaging results of different buried depths of abnormal body models for Example 5;

[0044] Among them: (a) Imaging result of low-resistivity abnormal body buried at 200 m; (b) Imaging result of high-resistivity abnormal body buried at 200 m; (c) Imaging result of low-resistivity abnormal body buried at 600 m; (d) Imaging result of high-resistivity abnormal body buried at 600 m;

[0045] Figure 10 Multi-anomaly model for Example 6;

[0046] Among them: (a) Three-dimensional schematic diagram; (b) yz sectional view; (c) xy sectional view;

[0047] Figure 11 Imaging results of the multi-anomaly model for Example 6;

[0048] Among them: (a) Double low-resistivity anomalies ρ 1 = 10 Ωm, ρ 2 = 10 Ωm; (b) Double high-resistivity anomalies ρ 1 = 1000 Ωm, ρ 2 = 1000 Ωm; (c) Near-source low-resistivity anomaly and far-source high-resistivity anomaly ρ 1 = 10 Ωm, ρ 2 = 1000 Ωm; (d) Near-source high-resistivity anomaly and far-source low-resistivity anomaly ρ 1 = 1000 Ωm, ρ 2 = 10 Ωm;

[0049] Figure 12 Imaging results of data under simulated noise environment for Example 7; (a) Low-resistivity anomaly model; (b) High-resistivity anomaly model;

[0050] Figure 13 Schematic diagram of detection experiment for Example 8;

[0051] Figure 14Geological ICMPG imaging result map of the Shansonggang cobalt (copper-nickel) deposit in Example 8. Detailed implementation mode

[0052] Example 1

[0053] During the propagation of electromagnetic waves, the earth's interior will attenuate the energy of the electromagnetic waves, and the degree of attenuation is determined by the electrical parameters of the underground structure, such as the dielectric constant, conductivity, etc. Therefore, the data can be processed based on the observed attenuated information to understand the distribution information of the electrical parameters of the underground structure.

[0054] In the frequency domain, Maxwell's equations can be written as:

[0055]

[0056] where ω is the angular frequency of the electromagnetic wave, μ is the magnetic permeability of the medium, σ is the conductivity of the medium, ε is the dielectric constant of the medium, E is the electric field strength, H is the magnetic field strength, and i is the imaginary unit;

[0057] By taking the curl of and using the vector identity In a homogeneous medium, we can obtain:

[0058]

[0059] Substituting into it, we can get the wave equation of the electric field strength E:

[0060]

[0061] After simplification, we get:

[0062]

[0063] Similarly, the wave equation of the magnetic field is:

[0064]

[0065] In the far field, assuming that the electromagnetic wave propagates along the z direction in the form of a plane wave, the solution of the magnetic field Hz is:

[0066] Hz = H 0 e ikz (6)

[0067] where k is the complex wave number, and H 0 is the initial amplitude of the magnetic field; e ikz is a complex term, where z is the spatial coordinate representing the distance along the propagation direction.

[0068] Substitute the plane wave solution into the wave equation From this, we can obtain:

[0069]

[0070] Therefore:

[0071] k 2 = μ(σ + iωε)ω 2 (8)

[0072] Then the expression of k at this time is:

[0073]

[0074] Express σ + iωε in polar coordinate form, then we have:

[0075]

[0076] where e is the base of the natural logarithm;

[0077]

[0078] Then the complex wavenumber k is expressed as:

[0079]

[0080] Using the complex square root formula:

[0081]

[0082] where r is the transmitting-receiving distance of the measuring point;

[0083] Divide the wavenumber into the real part (attenuation constant α) and the imaginary part (phase constant β):

[0084]

[0085] where the attenuation constant (describing the attenuation of the amplitude of the electromagnetic wave with distance) is:

[0086]

[0087] The phase constant (describing the change of the phase of the electromagnetic wave with distance) is:

[0088]

[0089] The phase constant can also be written as:

[0090]

[0091] where μ 0 is the vacuum magnetic permeability, ε 0 is the vacuum permittivity, ε ris the relative permittivity of the medium. When the conductivity is much greater than the dielectric loss, i.e., σ >> ωε 0 ε r , the wavenumber is mainly determined by the conductivity, then:

[0092]

[0093] In the metal mining area, due to the very high conductivity of the metal deposit and the very small dielectric term within the geophysical exploration frequency range; in this case, σ >> ωε 0 ε r basically holds. At this time, the propagation of electromagnetic waves is mainly determined by the conductivity, and the influence of the permittivity can be ignored.

[0094] Based on the above formula, the phase relationship between the conductivity of the electromagnetic wave propagation medium and the magnetic field component Hz is derived:

[0095]

[0096] where, is the phase of the magnetic field component Hz;

[0097] The calculation formula of the conductivity imaging method based on the magnetic phase gradient is defined as follows:

[0098]

[0099] where, H z (i, j) is the z-component of the magnetic field at each measurement point on the survey line at different frequencies (i = 1, 2... p, p is the total number of measurement points on a survey line, j = 1, 2... q, q is the total number of transmitting frequencies), ω(j) is the angular velocity corresponding to each transmitting frequency (j = 1, 2... q, q is the total number of transmitting frequencies), μ 0 is the vacuum magnetic permeability; when performing underground structure imaging, the spatial position coordinates corresponding to the CMPG of the measurement points at different frequencies are (X(i), Y(i), Z(i)), ρ 0 is the background resistivity; is the phase of the magnetic field component Hz, Re(H z (i, j)) is the real part of the magnetic field component Hz, Im(H z (i, j)) is the imaginary part of the magnetic field component Hz, and r(i) is the transmitter-receiver distance of the measurement point.

[0100] Apply the finite element method to Figure 1Forward modeling is performed on the shown model to obtain GAFDEM data. The blue line segment represents a long wire electrical emission source, located at x = 0m, y = -250m to 250m, with a length of 500m. The center position is at the coordinate origin. The emission current amplitude is 40A, and the emission frequency is an equally spaced frequency from 32Hz to 1024Hz, with an interval of 16Hz. The green cuboid represents an anomaly, whose position is as shown, with a size of 400m * 400m * 200m. The center position is at x = 0m, y = 5000m, and the burial depth is 400m. The red dashed line represents the survey line position, located at x = 0m, y = 4000m to 6000m, with a length of 2000m. The earth resistivity, i.e., the background resistivity, is 100Ωm. To ensure that the electromagnetic wave can be regarded as a vertically incident plane wave, the transceiver distance is 4800m. The resistivity of the anomaly is divided into two cases: low resistivity and high resistivity. Among them, the low resistivity anomaly ρ 1 = 10Ωm, and the high resistivity anomaly ρ 1 = 1000Ωm. Since magnetic field data is collected in the air, a straight line at x = 0m, y = 4000m to 6000m, z = 100m is taken as the survey line, and the phase information of the Hz component of the magnetic field on the survey line at different emission frequencies is extracted with a step of 10m. And CMPG is applied to image the data of the homogeneous half-space model and the Figure 1 shown model. The imaging result of the yz section at x = 0 is as Figure 2 shown. The white dashed box is the location of the anomaly.

[0101] As can be seen from Figure 2 , the CMPG imaging result of the homogeneous half-space model is a consistent conductivity distribution, and there is no abnormal area. This is because there is no influence of underground anomalies in this model, verifying that this method can correctly depict the background conductivity distribution in the absence of anomalies.

[0102] Compared with the homogeneous half-space model, when there are underground anomalies, high-value CMPG closures appear at the locations of the anomalies. There is a slight deviation between the closure position and the actual position of the anomaly, but it can still effectively indicate the anomaly area and boundary. Compared with the high resistivity anomaly, the CMPG value corresponding to the low resistivity anomaly is higher.

[0103] Example 2,

[0104] Since both low-resistance anomalies and high-resistance anomalies will appear as high-value traps at the location of the anomaly body in the imaging results, it is impossible to directly compare the relationship between the resistivity of the anomaly body and the background resistivity. The study found that the magnetic phase gradient in the calculation formula of the imaging method in Embodiment 1 has positive and negative differences for the resistivity of the anomaly body being higher and lower than the background resistivity. When the resistivity of the anomaly body is lower than the background resistivity, the magnetic phase gradient is positive, and when the resistivity of the anomaly body is higher than the background resistivity, the magnetic phase gradient is negative.

[0105] Therefore, Embodiment 2 proposes an improved imaging method ICMPG based on CMPG, and the formula is defined as follows:

[0106]

[0107] Applying ICMPG to Figure 1 the model shown in, the imaging result of the yz section at x = 0m is as shown in Figure 3 From the figure, it can be seen that when the resistivity of the anomaly body is lower than the background resistivity, the location of the anomaly body appears as a high-value trap, and vice versa as a low-value trap. The improved magnetic phase gradient apparent conductivity imaging method is based on the positive and negative differences of the magnetic phase gradient, that is, when the resistivity of the anomaly body is lower than the background resistivity, the magnetic phase gradient is positive, and vice versa, it is negative. Therefore, ICMPG can not only indicate the location and boundary contour of the anomaly body, but also further reflect the relationship between the resistivity of the anomaly body and the background resistivity, providing more intuitive electrical characteristics of the anomaly body.

[0108] Embodiment 3,

[0109] In order to verify the 3D imaging ability of this imaging method and analyze the influence of the relative position of the survey line and the anomaly body on the imaging result. Extract the magnetic field component data of multiple survey lines in the model shown in Figure 4 . The red dotted line indicates the position of the survey line. While ensuring that y = 4000m to 6000m and z = 100m remain unchanged, extract the survey line data at x = 0m, 100m, 200m, and 300m respectively, and apply the imaging method in Embodiment 2 to image the survey line data. The results are as shown in Figure 5 and Figure 6 shown. Among them, Figure 5 is the imaging result of the low-resistance anomaly model, Figure 6 is the imaging result of the high-resistance anomaly model.

[0110] From Figure 5 and Figure 6From the imaging results, it can be seen that for both the low-resistivity anomaly body and the high-resistivity anomaly body models, the imaging method can accurately identify the location and electrical characteristics of the anomaly body. Especially when there is an anomaly body below the survey line, the imaging results can clearly show high-value or low-value traps, reflecting the conductivity information of the anomaly body. However, when the survey line is at the edge of the anomaly body or far from the anomaly body, the imaging results will show the phenomenon of blurred traps or smooth background, verifying the influence of the relative position between the survey line and the anomaly body on the imaging results. In addition, there is good continuity between the slices, proving that the imaging method has good three-dimensional recognition ability. At different survey line positions, the imaging results all show high stability and consistency, providing strong support for the three-dimensional imaging of the underground electrical structure. These imaging results show the advantages of this method in three-dimensional imaging, which can effectively reflect the location, contour and electrical characteristics of underground anomaly bodies, and can better adapt to different survey line configurations and measurement conditions.

[0111] Example 4

[0112] To verify the recognition ability of ICMPG for anomaly bodies when the resistivity of the anomaly body is close to that of the background, Figure 1 the resistivity of the anomaly body in the model is set to a value closer to that of the background. Among them, the low-resistivity anomaly is set to ρ 1 = 50 Ωm, and the high-resistivity anomaly is set to ρ 1 = 200 Ωm. Apply the improved imaging method ICMPG based on CMPG in Example 2 to image the model, and its imaging results in the yz section at x = 0 m are as shown in Figure 7 shown.

[0113] From Figure 7 the imaging results, it can be seen that when the resistivity of the anomaly body is close to that of the background, the imaging method can still effectively identify the location and main characteristics of the anomaly body. Although due to the influence of low contrast, the boundary of the anomaly body appears to be blurred and distorted to a certain extent, especially in the edge area, but the overall imaging results can still accurately locate the central position and approximate contour of the anomaly body. It verifies the effectiveness of the imaging method under the condition that the resistivity of the anomaly body is close to that of the background, especially in the case of low contrast, and can still maintain good imaging ability and stability. Therefore, the imaging method proposed in the present invention is not only applicable to the detection of anomaly bodies under high-contrast conditions, but also can remain effective under the complex conditions where the resistivity of the anomaly body is close to that of the background, ensuring its application potential in actual exploration.

[0114] Example 5

[0115] To verify the effectiveness of the fast imaging method proposed in the present invention at different burial depths of electrical anomaly bodies, establish as shown in Figure 8The imaging models with different buried depths of the anomaly bodies shown. The green cuboids represent the anomaly bodies, and the buried depths of the anomaly bodies are 200m and 600m respectively. The earth resistivity, i.e., the background resistivity, is 100Ωm. The resistivity of the anomaly bodies is divided into two cases: low resistivity and high resistivity. Among them, for the low-resistivity anomaly ρ 1 = 10Ωm, and for the high-resistivity anomaly ρ 1 = 1000Ωm. Apply the ICMPG in Embodiment 2 to Figure 8 the model in it for imaging, and the imaging results at the yz section where x = 0m are as Figure 9 shown.

[0116] From Figure 9 the imaging results, it can be seen that when the buried depth of the anomaly body is 200m, the trap position of the low-resistivity anomaly body is slightly lower and cannot be completely closed. The reason is the limitation of the detection depth. Since the excitation source emits frequencies in the range of 32Hz - 1024Hzs, according to formula (25), the corresponding detection depth range is 222m to 1257m. Therefore, the underground electrical structure shallower than 222m cannot be detected, resulting in the upper edge of the trap not being closed in the imaging results. The imaging of the high-resistivity anomaly body is relatively clear, and the position of the anomaly body is accurate. As the buried depth increases to 600m, the contour of the anomaly body in the imaging results gradually becomes blurred, and the imaging accuracy decreases. However, even under the condition of relatively deep buried depth, the imaging method can still effectively identify the position of the anomaly body and demonstrate good depth detection ability. The fast imaging method proposed by the present invention still shows strong adaptability for electrical anomaly bodies with different buried depths, can overcome the influence brought by the change of buried depth to a certain extent, accurately locate the spatial position of the anomaly body, and show good depth detection ability. Especially in the case of low contrast and relatively deep buried depth, it can still effectively identify the existence of the anomaly body.

[0117] Embodiment 6,

[0118] In actual detection, there may be multiple electrical anomaly bodies in the ground at the same time. Therefore, it is necessary to verify the identification ability of ICMPG when multiple electrical anomaly bodies exist simultaneously. First, establish a multi-anomaly model as Figure 10 shown. The resistivity of the anomaly bodies is divided into the following four cases: 1. Double low-resistivity anomalies ρ 1 = 10Ωm, ρ 2 = 10Ωm; 2. Double high-resistivity anomalies ρ 1 = 1000Ωm, ρ 2 = 1000Ωm; 3. Near-source low-resistivity anomaly and far-source high-resistivity anomaly ρ 1 = 10Ωm, ρ 2 = 1000Ωm; 4. Near-source high-resistivity anomaly and far-source low-resistivity anomaly ρ 1 = 1000Ωm, ρ 2 = 10Ωm. Apply the ICMPG in Embodiment 2 toFigure 10 The multi - anomaly model is imaged, and the imaging result of its yz section at x = 0m is as follows Figure 11 shown.

[0119] From Figure 11 the imaging results, it can be seen that when multiple electrical anomalies exist simultaneously, the ICMPG method can effectively identify the positions and contours of each anomaly. For low - resistivity anomalies, the recognition ability of ICMPG is better than that of high - resistivity anomalies, manifested as relatively clear high - value traps. In the case of multiple anomalies existing simultaneously, especially between anomalies with large resistivity differences, the imaging effect will be affected by coupling and mutual influence, resulting in singular points in some areas or a decrease in imaging accuracy. Especially in different electrical combinations of near - source and far - source, ICMPG can better identify the positions of anomalies, but there may be small - scale singular points or distortions during the imaging process. Compared with the single - anomaly model, the imaging effect of ICMPG in the multi - anomaly model is slightly worse, but it can still effectively identify the positions, contours, and electrical characteristics of anomalies, verifying the good recognition ability of the ICMPG method in multi - anomaly situations. This performance shows that the ICMPG method can still provide stable and practical imaging results in actual detection, especially in complex environments where multiple anomalies coexist.

[0120] Example 7

[0121] In actual detection, due to the human - induced noise and electromagnetic interference in the experimental environment, it will have a certain impact on data acquisition and introduce environmental noise into the data. In addition, since the magnetic - field data acquisition device is suspended on a flying platform, the collected magnetic - field data will also introduce motion noise. To verify the anti - noise performance of ICMPG, this example simulates the noisy data in actual detection, adds 10% Gaussian white noise to the magnetic - field data, and images the Figure 1 model in it, and the imaging result of its yz section at x = 0m is as follows Figure 12 shown.

[0122] From Figure 12From the imaging results, it can be seen that although 10% Gaussian white noise is added, the ICMPG method can still effectively identify the location and electrical characteristics of abnormal bodies in a noisy environment. Although the noise causes slight distortion of the trap boundary in the imaging results, the high-value or low-value traps of the abnormal bodies are still clearly visible and accurately located. This verifies the strong noise resistance of the ICMPG method in a noisy environment, enabling it to be applied in complex detection environments. This characteristic provides theoretical support and practical guarantee for the application of the ICMPG method in actual geophysical exploration. Especially under actual measurement conditions with electromagnetic interference and human noise, it can ensure the stability and reliability of the imaging results. Therefore, this method can not only provide accurate imaging results under ideal conditions but also maintain good performance in an environment with severe noise interference and adapt to more complex application scenarios.

[0123] Example 8

[0124] To further verify the actual effectiveness of the ICMPG imaging method, in this example, the Gang cobalt (copper-nickel) deposit in Linjiang City, Baishan City, Jilin Province, China is taken as an example. The actual terrain data of the deposit area is obtained using the BIGEMAP software, and an equivalent model is established in COMSOL. The surrounding rocks of the deposit in this area are mainly composed of phyllitic schist, phyllitic metamorphic siltstone, and thin-layered marble, showing high-resistance characteristics, while the cobalt (copper-nickel) deposit is mainly composed of metal elements, showing low-resistance characteristics. Based on this geological information, we performed ICMPG imaging using the low-resistance characteristics of the cobalt-copper-nickel ore body and evaluated the feasibility and effectiveness of the ICMPG method in actual field detection according to the coincidence between the imaging results and the actual geological data.

[0125] According to the actual detection situation, the transmitter and the survey line are set, and the actual terrain simulation is as Figure 13 shown. In the figure, the red line segment represents the position of the excitation source, and the length of the excitation source is approximately 1000 m; the yellow dashed line represents the position of the survey line, and the length of the survey line is about 2300 m, perpendicular to the trend of the excitation source. The distance of the survey line is about 3.3 km to 5.7 km from the midpoint position of the excitation source, with a total of 249 measurement points, and the measurement point spacing is 10 m. To simulate the actual detection conditions, the excitation source emits a current of 20 A, and the frequencies are set to 32 Hz, 64 Hz, 96 Hz, 128 Hz, 160 Hz, 256 Hz, 512 Hz, 1024 Hz, and 2048 Hz.

[0126] Figure 14The vertical cross-section of the survey line is shown. The horizontal axis represents the shot-receiver distance of each point on the survey line, and the vertical axis represents the altitude. In actual exploration, based on geological data and the results of other physical methods, the ground resistivity of this area is approximately 1000 Ωm. There are two cobalt (copper-nickel) ore deposits below the survey line. Deposit A is located between a shot-receiver distance of 4400 m and 5200 m, with a longitudinal scale of 200 m and a burial depth between an altitude of 400 m and 600 m. Deposit B is located between a shot-receiver distance of 5350 m and 5550 m, with a longitudinal scale of 200 m and a burial depth of approximately 200 m above sea level. The resistivity of the cobalt (copper-nickel) ore body is set to 10 - 36 Ωm. In this embodiment, airborne magnetic field data was obtained at an altitude of approximately 1000 m, and the apparent depth was converted according to the frequency. The ICMPG was used to image the topography and electrical structure, and the imaging results are as Figure 14 shown.

[0127] Figure 14 The ICMPG imaging results of the Shansonggang cobalt (copper-nickel) ore deposit area are shown. The black dashed box represents the location of the low-resistivity ore deposit. The horizontal axis is the shot-receiver distance, the vertical axis is the altitude, and the color bar represents the change in apparent conductivity. The red area represents higher conductivity (low resistivity), and the blue to purple area represents lower conductivity (high resistivity). It can be seen from the figure that: between a shot-receiver distance of approximately 4400 m and 5200 m and an altitude range of approximately 400 m to 600 m, the imaging results show a significant low-resistivity area, and the location highly coincides with the actual location of Deposit A, indicating that the ICMPG method can accurately reflect the distribution characteristics of Deposit A. Between a shot-receiver distance of approximately 5350 m and 5550 m and an altitude of approximately 200 m, a smaller low-resistivity area appears in the imaging results, which also conforms to the actual location of Deposit B. This further verifies the reliability of the detection method. Most of the area below the survey line shows a uniform high-conductivity background, which is consistent with the characteristics of the stable high-resistivity surrounding rock in this area.

[0128] Generally speaking, Figure 14 the imaging results are highly consistent with the actual geological background. The location and scope of the low-resistivity anomaly area accurately reflect the distribution characteristics of the ore deposit, verifying the effectiveness and feasibility of the ICMPG method in ore deposit electrical detection. This method shows good application prospects in the actual complex environment and provides reliable data support for subsequent research.

Claims

1. A method for rapid imaging of apparent conductivity based on magnetic phase gradient, characterized in that: The calculation formula is as follows: Among them, CMPG(X,Y,Z) is the apparent conductivity of the magnetic phase gradient. The spatial coordinates of the magnetic phase gradient conductivity of the measuring point at different frequencies are (X(i), Y(i), Z(i)). z (i,j) is the z component of the magnetic field at each measuring point on the measuring line at different frequencies, i = 1, 2...p, p is the total number of measuring points on a measuring line, j = 1, 2...q, q is the total number of transmitting frequencies, μ0 is the vacuum permeability, ω(j) is the angular velocity corresponding to each transmitting frequency, j = 1, 2...q, is the phase of the magnetic field component Hz, Re(H z (i,j)) is the real part of the magnetic field component Hz, Im(H z (i,j)) is the imaginary part of the magnetic field component Hz, r(i) is the transmitting and receiving distance of the measuring point, and ρ0 is the background resistivity.

2. The method for rapid imaging of apparent conductivity based on magnetic phase gradient according to claim 1, characterized in that: Applied to rapid imaging of underground electrical structures.

3. The method for rapid imaging of apparent conductivity based on magnetic phase gradient according to claim 1 or 2, characterized in that: It is used for rapid imaging of underground electrical structures in metal mining areas where the conductivity is much greater than the dielectric loss, and the influence of the dielectric constant is negligible.

4. An improved imaging method of apparent conductivity based on magnetic phase gradient, characterized in that: The calculation formula is as follows: Among them, ICMPG (X, Y, Z) is the apparent conductivity of the improved magnetic phase gradient, the spatial position coordinates corresponding to the magnetic phase gradient conductivity of the measuring point at different frequencies are (X (i), Y (i), Z (i)), μ0 is the vacuum permeability, ω (j) is the angular velocity corresponding to each transmission frequency, j = 1, 2 ... q, q is the total number of transmission frequencies, is the phase of the magnetic field component Hz, r(i) is the transmitting and receiving distance of the measuring point, i=1,2…p, p is the total number of measuring points on a measuring line, is the phase of the magnetic field component Hz, Re(H z (i,j)) is the real part of the magnetic field component Hz, Im(H z (i,j)) is the imaginary part of the magnetic field component Hz, r(i) is the transmitting and receiving distance of the measuring point, and ρ0 is the background resistivity.

5. The improved imaging method of apparent conductivity based on magnetic phase gradient according to claim 4, characterized in that: Applied to rapid imaging of underground electrical structures.

6. The improved imaging method of apparent conductivity based on magnetic phase gradient according to claim 4 or 5, characterized in that: It is used for rapid imaging of underground electrical structures in metal mining areas where the conductivity is much greater than the dielectric loss, and the influence of the dielectric constant is negligible.

7. A method for rapid imaging of underground electrical structures, characterized in that: The following steps are involved: A long wire source is laid on the ground as an excitation source, and an alternating current of a fixed frequency is passed through the long wire source to generate electromagnetic waves. The electromagnetic waves are incident on the earth, inducing eddy currents inside the earth, and the eddy currents generate magnetic fields; The magnetic field data acquisition device is mounted on a drone and flies along the preset survey line, maintaining a certain safe height above the ground. The vertical component Hz of the magnetic field above the survey line is collected through the magnetic field data acquisition device. The underground electrical structure is detected by detecting the phase data of the magnetic field data generated by the eddy current. The vertical component of the collected magnetic field is de-noised by industrial frequency interference and human interference to obtain high-quality magnetic field data. Perform Fourier transform on the magnetic field data to obtain the real and imaginary data of the detection target frequency point, and calculate the magnetic field phase; According to the method for rapid imaging of apparent conductivity based on magnetic phase gradient according to any one of claims 1 to 3, or the improved method for imaging apparent conductivity based on magnetic phase gradient according to any one of claims 4 to 6, the apparent conductivity value of the underground structure is obtained based on the magnetic field phase gradient calculation; the skin depth corresponding to each target frequency point is calculated according to the skin depth formula, and the underground apparent conductivity distribution matrix is ​​obtained in combination with the spatial information; The interpolation method is used to plot the apparent conductivity distribution matrix and obtain the underground electrical structure map.

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