Rapid imaging positioning method for magnetization intensity vector of magnetic target body

Abstract

The invention provides a magnetic target body magnetization intensity vector rapid imaging positioning method, and relates to the field of geophysical exploration, and the method comprises the steps: obtaining the geophysical magnetic measurement data of an underground magnetic body; converting geophysical magnetic measurement data into a magnetic anomaly modulus TMA and a normalized magnetic source intensity NSS, and obtaining a magnetic anomaly modulus imaging field by combining a magnetic anomaly conversion modulus imaging method; according to the magnetic anomaly modulus imaging field, geophysical magnetic measurement data are fitted, and magnetization intensity vector parameters are calculated; updating the magnetization intensity vector model according to the magnetization intensity vector parameters; compressing the magnetization intensity vector model through a compression function; and calculating a data fitting error of the compressed magnetization intensity vector model, if the data fitting error is smaller than a preset threshold value, stopping iteration, and outputting a magnetic source distribution condition and a magnetization direction result of the underground magnetic body. According to the technical scheme, the influence of residual magnetism and oblique magnetization is effectively reduced, and rapid and accurate imaging positioning of the magnetic target body is achieved.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration, and in particular to a method for rapid imaging and positioning of a magnetic target body's magnetization intensity vector. Background Art

[0002] Magnetic exploration is a fast and efficient geophysical method that plays an important role in geological surveys, metal mine exploration, engineering surveys, etc. Underground magnetic geological bodies or target bodies generally have residual magnetism, and its direction is generally different from the contemporary geomagnetic field. In the case of widespread residual magnetism and demagnetization in geological bodies or target bodies, the form of magnetic anomaly data will become more complicated.

[0003] The currently widely used magnetic anomaly inversion method is to divide the underground space into several discrete units, assume that the magnetism of these discrete units is uniform, and obtain the magnetic body model through inversion calculation. This method usually ignores the influence of remanence and demagnetization, which can easily lead to inaccurate imaging positioning and low precision, and low efficiency of inversion calculation. Summary of the invention

[0004] The purpose of the present invention is to provide a method for rapid imaging and positioning of the magnetization intensity vector of a magnetic target body in order to solve the problem that the existing magnetic anomaly inversion method ignores the influence of remanence and demagnetization, which easily leads to inaccurate imaging and positioning, low precision, and low efficiency of inversion calculation.

[0005] The above-mentioned purpose of the present application is achieved through the following technical solutions: S1: Obtain geophysical magnetic survey data of underground magnetic bodies; S2: converting the geophysical magnetic survey data into magnetic anomaly modulus TMA and normalized magnetic source intensity NSS, and combining the magnetic anomaly conversion modulus imaging method to obtain a magnetic anomaly modulus imaging field; S3: According to the magnetic anomaly modulus imaging field, the geophysical magnetic survey data is fitted to calculate the magnetization intensity vector parameters; S4: updating the magnetization intensity vector model according to the magnetization intensity vector parameter; compressing the magnetization intensity vector model by a compression function; S5: Calculate the data fitting error of the compressed magnetization intensity vector model. If the data fitting error is less than a preset threshold, stop the iteration and output the magnetic source distribution and magnetization direction results of the underground magnetic body.

[0006] Optionally, step S1 includes: The geophysical magnetic survey data generated by simulating underground magnetic bodies is simulated by analytical forward modeling; the geophysical magnetic survey data includes: the coordinates of the measuring points and magnetic anomaly data.

[0007] Optionally, step S2 includes: The calculation formulas of magnetic anomaly modulus TMA and normalized magnetic source intensity NSS are as follows: Geophysical magnetic data , calculate the magnetic gradient tensor:

[0008] in, Geophysical magnetic survey data The calculated three components of magnetic anomaly are calculated as follows:

[0009]

[0010]

[0011]

[0012] in, denote the two-dimensional Fourier transform and its inverse transform, respectively. is an imaginary unit, After Fourier transformation, and The wave number of the direction, is the frequency domain direction conversion factor, are the geomagnetic inclination and declination, respectively, which are Subscript the direction indicated; The magnetic anomaly modulus TMA is calculated through the three components of magnetic anomaly as follows:

[0013] Through the magnetic gradient tensor , calculate the normalized magnetic source strength NSS as follows: Magnetic gradient tensor is a symmetric matrix containing only six independent components, then It is expressed as:

[0014]

[0015] in, Symmetrical array The characteristic value of is the eigenvalue The corresponding eigenvectors arrange the eigenvalues ​​of the magnetic gradient tensor in monotonically decreasing order: , the normalized magnetic source intensity NSS is expressed as: ; The magnetic anomaly modulus TMA and the normalized magnetic source intensity NSS are used as the initial fields of the potential field imaging method, and the magnetic anomaly modulus imaging field is calculated.

[0016] Optionally, step S3 includes: The magnetic anomaly modulus imaging field is converted into the magnetization intensity vector component, and its equation is as follows:

[0017] in is the modulus imaging field, , and There are three magnetization vector parameters that need to be calculated; Substitute the magnetization vector components into the magnetization vector equation to calculate:

[0018] in , and is the kernel matrix in the magnetization vector equation; The magnetization intensity vector equation is solved by the least square method to obtain the magnetization intensity vector parameters.

[0019] Optionally, step S4 includes: According to the magnetization vector parameters, the magnetization vector model is updated. The magnetization vector model updated for the i-th time is calculated by the following equation:

[0020] Where i is the number of iterations; It is the magnetic modulus imaging field of the residual between geophysical magnetic survey data and predicted data; The magnetization intensity vector model is compressed by the compression function as follows:

[0021] in is the compression function of the i-th iteration, which can be calculated as follows:

[0022] Where p is the compression parameter, is a constant; represents the magnetization vector model of the i-th iteration.

[0023] Optionally, step S5 includes: The calculation formula for calculating the data fitting error is as follows:

[0024] in Represents geophysical magnetic survey data; Represents the geophysical magnetic survey data after fitting.

[0025] An electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method for rapid imaging and positioning of the magnetization intensity vector of a magnetic target.

[0026] A computer-readable storage medium stores instructions. When the instructions are executed, a method for rapid imaging and positioning of a magnetic target magnetization intensity vector is performed.

[0027] The beneficial effects of the technical solution provided by this application are: The observed magnetic anomaly data are converted into magnetic anomaly modulus and normalized magnetic source intensity. The magnetic anomaly modulus eliminates the influence of residual magnetization and oblique magnetization on the magnetic anomaly. By imaging the magnetic anomaly modulus, the influence of magnetization direction on the imaging field is also weakened, eliminating the influence of residual magnetism on the estimation of the center position of the magnetic source.

[0028] The imaging method is used to accurately estimate the azimuth coordinates of the magnetic source. On this basis, the magnetization intensity vector equation is substituted to calculate the vector model, and the magnetization intensity vector distribution of the magnetic target is quickly obtained, thereby achieving rapid and accurate imaging and positioning of the magnetic target. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present application will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 is a step diagram in an embodiment of the present application; Figure 2 It is a three-dimensional diagram of the experimental model in the embodiment of the present application; Figure 3 It is a contour map of the magnetic modulus TMA and the normalized magnetic source intensity NSS obtained by forward modeling magnetic survey anomaly in the embodiment of the present application; Figure 4 It is a three-dimensional model diagram of the magnetization intensity vector in the embodiment of the present application; Figure 5 is a magnetization direction distribution diagram in an embodiment of the present application; Figure 6 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to have a clearer understanding of the technical features, purposes and effects of the present application, the specific implementation methods of the present application are now described in detail with reference to the accompanying drawings.

[0031] The embodiment of the present application provides a method for rapid imaging and positioning of the magnetization intensity vector of a magnetic target.

[0032] Please refer to Figure 1 , Figure 1 This is a step diagram of a method for rapid imaging and positioning of a magnetic target magnetization intensity vector in an embodiment of the present application, comprising: S1: Obtain geophysical magnetic survey data of underground magnetic bodies; S2: converting the geophysical magnetic survey data into magnetic anomaly modulus TMA and normalized magnetic source intensity NSS, and combining the magnetic anomaly conversion modulus imaging method to obtain a magnetic anomaly modulus imaging field; S3: According to the magnetic anomaly modulus imaging field, the geophysical magnetic survey data is fitted to calculate the magnetization intensity vector parameters; S4: updating the magnetization intensity vector model according to the magnetization intensity vector parameter; compressing the magnetization intensity vector model by a compression function; S5: Calculate the data fitting error of the compressed magnetization intensity vector model. If the data fitting error is less than a preset threshold, stop the iteration and output the magnetic source distribution and magnetization direction results of the underground magnetic body.

[0033] As an example, the result of the magnetization intensity vector model is output, such as Figure 4 , Figure 5 shown.

[0034] Step S1 includes: The geophysical magnetic survey data generated by simulating underground magnetic bodies is simulated by analytical forward modeling; the geophysical magnetic survey data includes: the coordinates of the measuring points and magnetic anomaly data.

[0035] As an example, an analytical forward modeling method is used to simulate the geophysical magnetic survey data generated by underground magnetic bodies, such as Figure 2 As shown, the dimensions of both cubes are 200m×200m×200mm, and the magnetization intensity is 3A / m. The magnetization inclination and declination of model A on the left are 30° and 45°, respectively, and the magnetization inclination of model B on the right is 60° and -35°. Model distributions in different directions are set to simulate the presence of strong remanent magnetization. The inclination and declination of the geomagnetic field are 45° and 0°, respectively. The observation area size is 1200m×1200m, and the grid spacing is 25m. Figure 3 The magnetic anomaly generated by the model is equivalent to the magnetic anomaly data observed in actual work , unit is nT.

[0036] Step S2 includes: As an example, based on the magnetic anomaly data, the magnetic anomaly modulus TMA and the normalized magnetic source intensity NSS are calculated in the frequency domain, such as Figure 3As shown, the data size is a real matrix of 48×48. The corresponding imaging field is calculated for the magnetic anomaly modulus TMA and the normalized magnetic source intensity NSS. Here, the structural index N=3 is used, and the imaging field can be calculated by the above imaging calculation formula.

[0037] The calculation formulas of magnetic anomaly modulus TMA and normalized magnetic source intensity NSS are as follows: Geophysical magnetic data , calculate the magnetic gradient tensor:

[0038] in, Geophysical magnetic survey data The calculated three components of magnetic anomaly are calculated as follows:

[0039]

[0040]

[0041]

[0042] in, denote the two-dimensional Fourier transform and its inverse transform, respectively. is an imaginary unit, After Fourier transformation, and The wave number of the direction, is the frequency domain direction conversion factor, are the geomagnetic inclination and declination, respectively, which are Subscript the direction indicated; The magnetic anomaly modulus TMA is calculated through the three components of magnetic anomaly as follows:

[0043] Through the magnetic gradient tensor , calculate the normalized magnetic source strength NSS as follows: Magnetic gradient tensor is a symmetric matrix containing only six independent components, then It is expressed as:

[0044]

[0045] in, Symmetrical array The characteristic value of is the eigenvalue The corresponding eigenvectors arrange the eigenvalues ​​of the magnetic gradient tensor in monotonically decreasing order: , the normalized magnetic source intensity NSS is expressed as: ; The magnetic anomaly modulus TMA and the normalized magnetic source intensity NSS are used as the initial fields of the potential field imaging method, and the magnetic anomaly modulus imaging field is calculated.

[0046] As an embodiment, the magnetic anomaly conversion modulus imaging method is applicable to potential fields, namely Newton potential fields and any n-th order vertical derivative fields thereof, including gravity fields, magnetic fields, etc.:

[0047] where k is a physical constant related to physical properties, is the source density, and They represent the position vectors of a point P outside the field source and a point Q inside the field source, and n represents the nth-order derivative of the field. Therefore, for the general potential field imaging method, the imaging field is calculated as:

[0048] in are TMA and NSS data at different altitudes, = represents the depth of the i-th layer, x, y, z represent the position coordinates of different observation points, and q is the order of the vertical derivative of the potential field. This method is not only applicable to gravity and magnetic potential fields, but also to high-order vertical derivative fields of the potential field. Before imaging, it is necessary to determine the height of the upward extension. .

[0049] Step S3 includes: The magnetic anomaly modulus imaging field is converted into the magnetization intensity vector component, and its equation is as follows:

[0050] in is the modulus imaging field, , and There are three magnetization vector parameters that need to be calculated; Substitute the magnetization vector components into the magnetization vector equation to calculate:

[0051] in , and is the kernel matrix in the magnetization vector equation; The magnetization intensity vector equation is solved by the least square method to obtain the magnetization intensity vector parameters.

[0052] As an example, the magnetization vector equation is further generalized to the general case in iteration:

[0053] in is the residual magnetic modulus imaging field of geophysical magnetic survey data and predicted data. By solving this equation, the parameters in each iteration can be obtained. , and , and update the magnetization vector model; where Represents geophysical magnetic survey data; Represents the geophysical magnetic survey data after fitting.

[0054] Step S4 includes: According to the magnetization vector parameters, the magnetization vector model is updated. The magnetization vector model updated for the i-th time is calculated by the following equation:

[0055] Where i is the number of iterations; It is the magnetic modulus imaging field of the residual between geophysical magnetic survey data and predicted data; The magnetization intensity vector model is compressed by the compression function as follows:

[0056] in is the compression function of the i-th iteration, which can be calculated as follows:

[0057] Where p is the compression parameter, is a constant; represents the magnetization vector model of the i-th iteration.

[0058] Step S5 includes: The calculation formula for calculating the data fitting error is as follows:

[0059] in Represents geophysical magnetic survey data; Represents the geophysical magnetic survey data after fitting.

[0060] The present application also discloses an electronic device. Figure 6 , Figure 6The electronic device 500 may include: at least one processor 501 , at least one network interface 504 , a user interface 503 , a memory 505 , and at least one communication bus 502 .

[0061] The communication bus 502 is used to realize the connection and communication between these components.

[0062] The user interface 503 may include a display screen, and the optional user interface 503 may also include a standard wired interface or a wireless interface.

[0063] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0064] The present application also discloses a computer-readable storage medium storing a plurality of instructions suitable for loading by a processor to execute the above-mentioned method for rapid imaging and positioning of the magnetization intensity vector of a magnetic target.

[0065] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure.

[0066] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for rapid imaging and positioning of magnetic target magnetization intensity vector, characterized in that: The method comprises the following steps: S1: Obtain geophysical magnetic survey data of underground magnetic bodies; S2: converting the geophysical magnetic survey data into magnetic anomaly modulus TMA and normalized magnetic source intensity NSS, and combining the magnetic anomaly conversion modulus imaging method to obtain a magnetic anomaly modulus imaging field; S3: According to the magnetic anomaly modulus imaging field, the geophysical magnetic survey data is fitted to calculate the magnetization intensity vector parameters; S4: updating the magnetization intensity vector model according to the magnetization intensity vector parameter; compressing the magnetization intensity vector model by a compression function; S5: Calculate the data fitting error of the compressed magnetization intensity vector model. If the data fitting error is less than a preset threshold, stop the iteration and output the magnetic source distribution and magnetization direction results of the underground magnetic body.

2. A magnetic target object magnetization intensity vector rapid imaging positioning method as claimed in claim 1, characterized in that: Step S1 includes: The geophysical magnetic survey data generated by underground magnetic bodies are simulated by analytical forward modeling; the geophysical magnetic survey data include: the coordinates of the measuring points and magnetic anomaly data.

3. A magnetic target object magnetization intensity vector rapid imaging positioning method as claimed in claim 1, characterized in that: Step S2 includes: The calculation formulas of magnetic anomaly modulus TMA and normalized magnetic source intensity NSS are as follows: Geophysical magnetic data , calculate the magnetic gradient tensor as follows: in, Geophysical magnetic survey data The calculated three components of magnetic anomaly are calculated as follows: in, denote the two-dimensional Fourier transform and its inverse transform, respectively. is an imaginary unit, After Fourier transformation, and The wave number of the direction, is the frequency domain direction conversion factor, are the geomagnetic inclination and declination, respectively, which are Subscript the direction indicated; The magnetic anomaly modulus TMA is calculated through the three components of magnetic anomaly as follows: Through the magnetic gradient tensor , calculate the normalized magnetic source strength NSS as follows: Magnetic gradient tensor is a symmetric matrix containing only six independent components, then It is expressed as: in, Symmetrical array The characteristic value of is the eigenvalue The corresponding eigenvectors arrange the eigenvalues ​​of the magnetic gradient tensor in monotonically decreasing order: , the normalized magnetic source intensity NSS is expressed as: ； The magnetic anomaly modulus TMA and the normalized magnetic source intensity NSS are used as the initial fields of the potential field imaging method, and the magnetic anomaly modulus imaging field is calculated.

4. A magnetic target object magnetization intensity vector rapid imaging positioning method as claimed in claim 1, characterized in that: Step S3 includes: The magnetic anomaly modulus imaging field is converted into the magnetization intensity vector component, and its equation is as follows: in is the modulus imaging field, , and There are three magnetization vector parameters that need to be calculated; Substitute the magnetization vector components into the magnetization vector equation to calculate: in , and is the kernel matrix in the magnetization vector equation; The magnetization intensity vector equation is solved by the least square method to obtain the magnetization intensity vector parameters.

5. A magnetic target object magnetization intensity vector rapid imaging positioning method as claimed in claim 1, characterized in that: Step S4 includes: According to the magnetization vector parameters, the magnetization vector model is updated. The magnetization vector model updated for the i-th time is calculated by the following equation: Where i is the number of iterations; It is the magnetic modulus imaging field of the residual between geophysical magnetic survey data and predicted data; The magnetization vector model is compressed by the compression function as follows: in is the compression function of the i-th iteration, which can be calculated as follows: Where p is the compression parameter, is a constant; represents the magnetization vector model of the i-th iteration.

6. A magnetic target object magnetization intensity vector rapid imaging positioning method as claimed in claim 1, characterized in that: Step S5 includes: The calculation formula for calculating the data fitting error is as follows: in Represents geophysical magnetic survey data; Represents the geophysical magnetic survey data after fitting.

7. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 6 is executed.

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