Highly magnetic body aviation magnetic anomaly efficient calculation method considering demagnetization influence

Abstract

The invention relates to a demagnetization influence-considered high-efficiency calculation method and device for aerial magnetic anomaly of a ferromagnetic body, computer equipment and a storage medium. The method comprises the following steps: respectively establishing discrete grids for a field source region and an underground observation region, and correspondingly obtaining a field source grid and an observation grid; and according to the field source grid and the observation grid, constructing an arc tangent function and a logarithmic function related to the cuboid units of the field source and the observation point, and according to the arc tangent function, the logarithmic function and the three-dimensional difference operator, determining the unit integral coefficient of each cuboid of the observation grid. And three components of the abnormal magnetic field of the observation grid are calculated through two-dimensional compression discrete convolution, and then the airborne magnetic anomaly value of the ferromagnetic body is solved through a loop iteration mode. The method has the advantages of high flexibility, high calculation precision and high efficiency, solves the problem of low iteration efficiency of an existing ferromagnetic body model method, and can meet the requirements of ferromagnetic body aviation exploration.

Description

Technical Field

[0001] This application relates to the field of airborne geophysical exploration technology, and in particular to an efficient calculation method, apparatus, computer equipment, and storage medium for airborne magnetic anomalies of strongly magnetic bodies that take into account the effects of demagnetization. Background Technology

[0002] The magnetization state of an object depends not only on the excitation of an external magnetic field but also on the combined influence of its own generated magnetic field and the magnetic fields of other surrounding objects. This complex coupling phenomenon is commonly referred to as the "self-demagnetization" effect. The strength of this effect is closely related to the object's magnetic susceptibility. At low magnetic susceptibility, it is usually negligible, meaning that classical magnetic anomaly interpretation methods typically do not consider the demagnetization effect. However, as the magnetic susceptibility increases, the self-demagnetization effect significantly strengthens, becoming a key factor affecting the magnetic field distribution. As an important characteristic of magnetic fields, the demagnetization effect must be fully considered in the interpretation of magnetic survey data. This is especially true in the field of mineral exploration, where known mineral deposits are becoming increasingly scarce, and the difficulty of prospecting is constantly increasing. Iron ore, as an important mineral resource in my country, has a large difference in magnetic susceptibility from the surrounding rock, allowing for direct prospecting using magnetic methods. The self-demagnetization effect of polymetallic iron ore is particularly significant. If this factor is ignored during modeling, it will lead to systematic deviations in the inference of the spatial location, geometry, and magnetization intensity of the magnet, seriously affecting the reliability of the exploration results.

[0003] However, the accurate calculation of the self-demagnetizing effect involves complex nonlinear coupling relationships, making the calculation process extremely resource-intensive and placing high demands on computing memory and processor performance. This computational bottleneck severely restricts the practical application of high-precision magnetic field modeling. Therefore, existing numerical simulation techniques for three-dimensional strong magnetic bodies suffer from problems such as large memory consumption and low iteration efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, and storage medium for efficient calculation of aero-magnetic anomalies of strongly magnetic bodies that takes into account both computational efficiency and modeling accuracy and considers the effects of demagnetization, in order to address the above-mentioned technical problems.

[0005] An efficient calculation method for aero-magnetic anomalies of strongly magnetic bodies considering demagnetization effects, the method comprising:

[0006] Based on the information of the exploration target area and the distribution information of strong magnetic geological bodies, the source area and the underground observation area are discretized into several cuboid units along the x, y, and z directions, respectively, to obtain the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size;

[0007] The magnetic susceptibility of each cuboid unit in the field source grid is assigned a value to establish a complex strong magnetic body model with arbitrary magnetic susceptibility distribution;

[0008] Based on the source grid and the observation grid, construct the arctangent function and logarithmic function related to the cuboid elements of the source and observation points. Based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, determine the element integral coefficient of each cuboid in the observation grid. The value of the element integral coefficient can be determined by the cuboid element number of the source grid, the cuboid element number of the observation grid, and the grid size.

[0009] Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expression for the three components of the abnormal magnetic field of the observation grid is determined by vertically accumulating multiple two-dimensional discrete convolutions.

[0010] The three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution, and then the aeromagnetic anomaly value of the strong magnetic body is solved by iterative loop.

[0011] In one embodiment, the method further includes: constructing an arctangent function related to the cuboid elements of the field source and observation points based on the source grid and the observation grid as follows:

[0012]

[0013] The logarithmic function associated with the cuboid elements of the field source and observation point is constructed as follows:

[0014]

[0015] in, , , It is the arctangent function. Indicates the arctangent operation; , , It is a logarithmic function. Represents logarithmic operations; , , , , , , , ; Indicates the number is The center coordinates of the cuboid cells in the observation grid. Indicates the number is The center coordinates of the cuboid elements of the field source mesh. , and These represent the dimensions of the discrete cuboid element in the x, y, and z directions, respectively; , , , The number of grid cells in the x, y, and z directions of the observation grid; , , , The number of grid cells in the x, y, and z directions of the field source grid.

[0016] In one embodiment, the method further includes: determining the element integral coefficients of each cuboid in the observation grid based on the arctangent function, the logarithmic function, and the three-dimensional difference operator.

[0017]

[0018] in, , , , , , This represents the integral coefficient of each cuboid element. Represents a three-dimensional difference operator. It represents pi (π).

[0019] In one embodiment, the method further includes: determining the expression for the three components of the observed grid's anomalous magnetic field by vertically summing multiple two-dimensional discrete convolutions based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0020]

[0021]

[0022]

[0023] in, , , For the number The observed grid cuboid unit anomaly magnetic field The three components, , , In the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the number is... The three components of the effective magnetization of the cuboid unit.

[0024] In one embodiment, the method further includes: constructing a compression matrix based on the unit integral coefficients as follows:

[0025]

[0026] In this matrix, the superscript represents the cuboid number of the field source, and the subscript represents the cuboid element number of the observation point.

[0027] Constructing and compressing matrices Field source matrices of the same size for:

[0028]

[0029] in, They represent dimensions as follows: , , A two-dimensional zero matrix;

[0030] The three components of the anomalous magnetic field of the observed grid are calculated using two-dimensional compressed discrete convolution:

[0031]

[0032] in, and These represent two-dimensional forward and inverse Fourier transforms, respectively. Indicates the first part of the extracted matrix lines and Column elements.

[0033] In one embodiment, it further includes: based on the three components of the observed grid's anomalous magnetic field. The magnetic field value at any observation height is calculated by multi-level accumulation:

[0034]

[0035] Based on the magnetic field value at the arbitrary observation altitude The total magnetic field value is obtained by iteration:

[0036]

[0037] in, The background magnetic field value. For the first The magnetic anomaly value of the sub-forward modeling Through compact operator iteration The total magnetic field value of the second forward modeling It is the magnetic susceptibility;

[0038] Once the preset iteration convergence condition is met, the iteration stops, and the total magnetic field value is output as the aero-magnetic anomaly value of the strong magnetic body in the target area.

[0039] In one embodiment, the number of grids for the source grid and the observation grid can be set to be the same or different.

[0040] A high-efficiency computing device for aero-magnetic anomalies of strongly magnetic bodies considering the effects of demagnetization, the device comprising:

[0041] The grid construction module is used to discretize the source area and the underground observation area into several cuboid units along the x, y, and z directions, respectively, based on the exploration target area information and the distribution information of strongly magnetic geological bodies, thereby obtaining the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size;

[0042] The complex strong magnetic body model building module is used to assign a value to the magnetic susceptibility of each cuboid unit of the field source grid and build a complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0043] The unit integral coefficient determination module is used to construct arctangent and logarithmic functions related to the cuboid units of the field source and observation points based on the field source grid and the observation grid, and to determine the unit integral coefficients of each cuboid of the observation grid based on the arctangent and logarithmic functions and the three-dimensional difference operator; the value of the unit integral coefficients can be determined by the cuboid unit number of the field source grid, the cuboid unit number of the observation grid, and the grid size;

[0044] The discrete convolution module is used to determine the expression of the three components of the anomalous magnetic field of the observation grid by vertically accumulating multiple two-dimensional discrete convolutions based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0045] The results output module is used to calculate the three components of the anomalous magnetic field of the observation grid through two-dimensional compressed discrete convolution, and then solve for the aeromagnetic anomaly value of the strong magnetic body through a cyclic iterative method.

[0046] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0047] Based on the information of the exploration target area and the distribution information of strong magnetic geological bodies, the source area and the underground observation area are discretized into several cuboid units along the x, y, and z directions, respectively, to obtain the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size;

[0048] The magnetic susceptibility of each cuboid unit in the field source grid is assigned a value to establish a complex strong magnetic body model with arbitrary magnetic susceptibility distribution;

[0049] Based on the source grid and the observation grid, construct the arctangent function and logarithmic function related to the cuboid elements of the source and observation points. Based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, determine the element integral coefficients of each cuboid in the observation grid.

[0050] Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expression for the three components of the abnormal magnetic field of the observation grid is determined by vertically accumulating multiple two-dimensional discrete convolutions.

[0051] The three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution, and then the aeromagnetic anomaly value of the strong magnetic body is solved by iterative loop.

[0052] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0053] Based on the information of the exploration target area and the distribution information of strong magnetic geological bodies, the source area and the underground observation area are discretized into several cuboid units along the x, y, and z directions, respectively, to obtain the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size;

[0054] The magnetic susceptibility of each cuboid unit in the field source grid is assigned a value to establish a complex strong magnetic body model with arbitrary magnetic susceptibility distribution;

[0055] Based on the source grid and the observation grid, construct the arctangent function and logarithmic function related to the cuboid elements of the source and observation points. Based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, determine the element integral coefficient of each cuboid in the observation grid. The value of the element integral coefficient can be determined by the cuboid element number of the source grid, the cuboid element number of the observation grid, and the grid size.

[0056] Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expression for the three components of the abnormal magnetic field of the observation grid is determined by vertically accumulating multiple two-dimensional discrete convolutions.

[0057] The three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution, and then the aeromagnetic anomaly value of the strong magnetic body is solved by iterative loop.

[0058] The aforementioned efficient calculation method, apparatus, computer equipment, and storage medium for aero-magnetic anomalies of strongly magnetic bodies considering demagnetization effects are presented in this invention. Discrete grids are established for the source region and the underground observation region, respectively, resulting in source grids and observation grids, allowing for more flexible grid discretization. Based on the source and observation grids, arctangent and logarithmic functions related to the cuboid elements of the source and observation points are constructed. The element integral coefficients of each cuboid in the observation grid are determined based on the arctangent and logarithmic functions, as well as the three-dimensional difference operator. These element integral coefficients can be directly merged using the subtraction theorem of the arctangent and logarithmic functions, effectively reducing the number of arctangent and logarithmic functions in the integral of a single cuboid element. This significantly improves the computational efficiency of element integral coefficients while ensuring analytical solution accuracy in forward modeling. The three components of the anomalous magnetic field in the observation grid are calculated using two-dimensional compressed discrete convolution, and then the aero-magnetic anomaly value of the strongly magnetic body is solved through iterative iteration. Two-dimensional compressed discrete convolution can quickly solve the three-dimensional integral equation satisfied by the strongly magnetic body, obtaining the magnetic field of the observation area. This invention has the advantages of high flexibility, high computational accuracy and high efficiency, and solves the problem of low iteration efficiency of existing strong magnetic body model methods, and can meet the needs of airborne exploration of strong magnetic bodies. Attached Figure Description

[0059] Figure 1 This is a flowchart illustrating an efficient calculation method for aero-magnetic anomalies of strongly magnetic bodies that takes into account the effects of demagnetization in one embodiment.

[0060] Figure 2 This is a schematic diagram of a uniformly discrete underground observation grid in one embodiment;

[0061] Figure 3 This is a schematic diagram of the vertical non-uniform discretization of the underground observation grid in one embodiment;

[0062] Figure 4 This is a model of a strongly magnetic sphere in a specific embodiment;

[0063] Figure 5 This is a schematic diagram comparing the analytical and numerical solutions of magnetic anomalies in a specific embodiment, where (a), (b), and (c) are schematic diagrams of the numerical solution, analytical solution, and absolute error in the x-direction, respectively; (d), (e), and (f) are schematic diagrams of the numerical solution, analytical solution, and absolute error in the y-direction, respectively; and (g), (h), and (i) are schematic diagrams of the numerical solution, analytical solution, and absolute error in the z-direction, respectively.

[0064] Figure 6 This is a structural block diagram of an efficient computing device for aero-magnetic anomalies of strongly magnetic bodies that takes into account the effects of demagnetization in one embodiment.

[0065] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0067] In one embodiment, such as Figure 1 As shown, an efficient calculation method for aero-magnetic anomalies of strongly magnetic bodies considering demagnetization effects is provided, comprising the following steps:

[0068] Step 102: Based on the information of the exploration target area and the distribution information of strong magnetic geological bodies, the source area and the underground observation area are discretized into several cuboid units along the x, y, and z directions, respectively, to obtain the source grid and the observation grid.

[0069] Existing technologies typically establish a grid directly based on the target area, meaning the source and observation grids are integrated. This application, however, establishes separate grids for the source region and the underground observation region, with the source and observation grids being independent and of equal size. This allows the number of discrete grids in the source region and the underground observation region to be the same or different, making grid discretization more flexible. For example, consider a complex underground model where airborne magnetic surveys are highly efficient and have wide coverage, but involve significant computational costs. The method of this invention can refine the grid in the model's distribution area and increase the grid spacing in other areas, thus effectively characterizing the complex model without affecting computational accuracy, while also reducing computational load.

[0070] Step 104: Assign a value to the magnetic susceptibility of each cuboid element in the field source grid to establish a complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0071] The magnetic susceptibility of each cuboid cell in the field source grid is assigned a value based on the magnetic susceptibility distribution characteristics of the exploration area, and the magnetic susceptibility within each cuboid cell is set as a constant. The magnetic susceptibility of each small cuboid cell can be the same or different, thereby simulating a complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0072] Step 106: Construct arctangent and logarithmic functions related to the cuboid elements of the field source and observation points based on the source grid and observation grid. Determine the element integral coefficients of each cuboid in the observation grid based on the arctangent and logarithmic functions and the three-dimensional difference operator.

[0073] Based on the source grid and observation grid, the arctangent function related to the cuboid elements of the source and observation points is constructed as follows:

[0074]

[0075] The logarithmic function associated with the cuboid elements of the field source and observation point is constructed as follows:

[0076]

[0077] in, , , This represents the constructed arctangent function. Indicates the arctangent operation; , , Represents the constructed logarithmic function, Represents logarithmic operations; , , , , , , , ; Indicates the number is The center coordinates of the cuboid cells in the observation grid. Indicates the number is The center coordinates of the cuboid elements of the field source mesh. , and These represent the dimensions of the discrete cuboid element in the x, y, and z directions, respectively; , , , The number of grid cells in the x, y, and z directions for observation; , , , This represents the number of grid cells in the x, y, and z directions of the field source grid.

[0078] Based on the arctangent function, logarithmic function, and three-dimensional difference operator, the element integral coefficients of each cuboid in the observation grid are determined as follows:

[0079]

[0080] in, , , , , , This represents the integral coefficient of each cuboid element. Represents a three-dimensional difference operator. It represents pi (π).

[0081] The values ​​of the element integral coefficients can be determined by the cuboid element numbers of the source grid, the observation grid, and the grid size, as inferred below:

[0082] According to the subtraction theorem of the arctangent function, we can obtain , , It can be represented as:

[0083]

[0084]

[0085]

[0086] The two-dimensional difference operator for the arctangent function can be expressed as:

[0087]

[0088]

[0089]

[0090] According to the recursive relation, , and It can be done , , Calculation, where

[0091]

[0092]

[0093]

[0094] Similarly, , and It can be done , , get:

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] In the formula

[0102]

[0103]

[0104] sign represents the sign function, and its specific expression is:

[0105]

[0106] Similar to the method of combining like terms in the arctangent function, the logarithmic function... , , The specific expressions for the three-dimensional difference operators are as follows:

[0107]

[0108]

[0109]

[0110] The arctangent and logarithmic functions constructed in this invention can be directly combined based on the subtraction theorem of arctangent and logarithmic functions, effectively reducing the number of arctangent and logarithmic functions in a single cuboid unit integral. Since the computational cost of arctangent and logarithmic functions in a computer is far greater than that of addition, subtraction, multiplication, and division, reducing the number of arctangent and logarithmic functions in a single cuboid unit integral effectively improves the efficiency of unit integration.

[0111] The method described in this application can effectively improve the calculation efficiency of the integral coefficients of cuboid elements while ensuring the accuracy of the analytical solution.

[0112] Step 108: Based on the unit integral coefficients, the given information on the Earth's main magnetic field model, and the model of a complex strong magnetic body with arbitrary magnetic susceptibility distribution, the expression for the three components of the anomalous magnetic field of the observation grid is determined by accumulating multiple two-dimensional discrete convolutions vertically.

[0113] Based on the unit integral coefficients, the given information from the Earth's main magnetic field model, and the model of a complex, strongly magnetic body with arbitrary magnetic susceptibility distribution, the expression for the three components of the observed grid's anomalous magnetic field is determined by vertically summing multiple two-dimensional discrete convolutions:

[0114]

[0115]

[0116]

[0117] in, , , For the number The observed grid cuboid unit anomaly magnetic field The three components, , , In the model of a complex strongly magnetic body with arbitrary magnetic susceptibility distribution, the number is... The three components of the effective magnetization of the cuboid unit.

[0118] like Figure 2 , 3 These are all specific implementation examples of underground observation grid discretization. Traditional methods can only... Figure 2 As shown, uniform discretization is performed. This invention's novel method determines the anomalous magnetic field of the observation grid by vertically accumulating multiple two-dimensional discrete convolutions. This not only allows for... Figure 2 As shown, uniform discretization can also be performed as follows: Figure 3 The non-uniform discretization shown is performed by using a vertically non-uniform grid, which makes the grid discretization more flexible and greatly reduces the amount of computation while ensuring accuracy.

[0119] Step 110: The three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution, and then the aero-magnetic anomaly value of the strong magnetic body is solved by iterative loop.

[0120] Construct a two-dimensional compressed matrix based on the unit integral coefficients. for:

[0121]

[0122] In this matrix, the superscript of the matrix element indicates the number of the cuboid source, and the subscript indicates the number of the cuboid unit of the observation point.

[0123] Given the superscript and subscript numbers, we can use unit integrals. Calculate the corresponding matrix Elements, and matrix By calculating and storing only elements relevant to the field source and observation point, the number of calculations for unit integrals is greatly reduced. Therefore, this technique effectively solves the technical problem that accurate calculations considering self-demagnetization effects are extremely resource-intensive and cannot well characterize complex models.

[0124] Constructing and compressing matrices Field source matrices of the same size for:

[0125]

[0126] in, They represent dimensions as follows: , , A two-dimensional zero matrix;

[0127] Field source matrix This refers to the extended matrix formed by the effective magnetization. The initial effective magnetization is calculated as follows:

[0128] First: Given the initial values ​​of the magnetic field. Setting the Earth's main magnetic field as the initial values ​​for a cuboid model, we can obtain...

[0129]

[0130] Next, the effective magnetization is calculated. The effective magnetization is calculated based on given parameters such as the Earth's main magnetic field and magnetic susceptibility:

[0131]

[0132] in, Indicates the number is The magnetic susceptibility of the cuboid unit cell.

[0133] Determine the compression matrix and the source matrix. Then, the three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution:

[0134]

[0135] in, and These represent two-dimensional forward and inverse Fourier transforms, respectively. Indicates the first part of the extracted matrix lines and Column elements.

[0136] Two-dimensional compressed discrete convolution can quickly solve the three-dimensional integral equations satisfied by strongly magnetic bodies to obtain the magnetic field of the observation area.

[0137] Based on the three components of the observed grid anomalous magnetic field The magnetic field value at any observation height is calculated by multi-level accumulation:

[0138]

[0139] Based on the magnetic field value at any observation altitude The total magnetic field value is obtained by iteration:

[0140]

[0141] in, The background magnetic field value. For the first The magnetic anomaly value of the sub-forward modeling Through compact operator iteration The total magnetic field value of the second forward modeling It is the magnetic susceptibility;

[0142] Once the preset convergence condition is met, the iteration stops, and the total magnetic field value is output as the aeromagnetic anomaly value of the strongly magnetic body in the target region. Otherwise, the effective magnetization is updated, and the cycle restarts.

[0143] In this embodiment, the termination condition for iterative convergence can be expressed as:

[0144]

[0145] if If the convergence condition is met, the result will be output.

[0146] In the aforementioned efficient calculation method for aero-magnetic anomalies of strongly magnetic bodies considering demagnetization effects, this invention establishes discrete grids for the source region and the underground observation region, respectively, resulting in source grids and observation grids, which offer greater flexibility in grid discretization. Based on the source and observation grids, arctangent and logarithmic functions related to the cuboid elements of the source and observation points are constructed. The element integral coefficients of each cuboid in the observation grid are determined using the arctangent and logarithmic functions, along with a three-dimensional difference operator. These element integral coefficients can be directly merged using the subtraction theorem of the arctangent and logarithmic functions, effectively reducing the number of arctangent and logarithmic functions in the integral of a single cuboid element. This ensures that the forward modeling achieves analytical solution accuracy while significantly improving the computational efficiency of the element integral coefficients. The three components of the anomalous magnetic field in the observation grid are calculated using two-dimensional compressed discrete convolution, and then the aero-magnetic anomaly value of the strongly magnetic body is solved through iterative iteration. Two-dimensional compressed discrete convolution can quickly solve the three-dimensional integral equation satisfied by the strongly magnetic body, yielding the magnetic field of the observation region. This invention has the advantages of high flexibility, high computational accuracy and high efficiency, and solves the problem of low iteration efficiency of existing strong magnetic body model methods, and can meet the needs of airborne exploration of strong magnetic bodies.

[0147] In one embodiment, the number of grids for the source grid and the observation grid can be set to be the same or different.

[0148] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed, and they can be performed in other orders. Furthermore, Figure 1At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0149] In another specific embodiment, such as Figure 4 The sphere model shown is described in detail below:

[0150] The target region extends from -100m to 100m in both the x and y directions, and from 0m to 100m in the z direction. The number of prisms in the x and y directions is 200 each, and the number of prisms in the z direction is 100 each. The center coordinates of the spherical shell are (0, -20, 50)m, the outer radius of the shell is 20m, the inner radius is 15m, and the magnetic susceptibility is 100 SI. The source region is uniformly discretized into 25 × 25 × 25 cuboid units. The local geomagnetic field magnitude is 50000 nT, and the geomagnetic tilt angle is... Magnetic declination is .

[0151] The method for calculating aeromagnetic anomalies of strongly magnetic bodies in this embodiment is implemented using Fortran programming language. Figure 5 To compare the analytical and numerical solutions for magnetic anomalies, it was found that the analytical and numerical interpretations are identical in shape. Therefore, the absolute error between the analytical and numerical solutions was calculated. The maximum absolute error is less than two orders of magnitude of the field value, which can effectively measure the numerical accuracy of the present invention.

[0152] In one embodiment, such as Figure 6 As shown, a high-efficiency computing device for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects is provided, comprising: a mesh construction module 602, a complex strongly magnetic body model establishment module 604, a unit integral coefficient determination module 606, a discrete convolution module 608, and a result output module 610, wherein:

[0153] The grid construction module 602 is used to discretize the source area and the underground observation area into several cuboid units along the x, y, and z directions, respectively, based on the exploration target area information and the distribution information of strong magnetic geological bodies, thereby obtaining the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size;

[0154] The complex strong magnetic body model building module 604 is used to assign the magnetic susceptibility of each cuboid element of the field source grid and build a complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0155] The unit integral coefficient determination module 606 is used to construct arctangent and logarithmic functions related to the cuboid units of the field source and observation points based on the field source grid and the observation grid, and to determine the unit integral coefficients of each cuboid of the observation grid based on the arctangent and logarithmic functions and the three-dimensional difference operator; the value of the unit integral coefficients can be determined by the cuboid unit number of the field source grid, the cuboid unit number of the observation grid, and the grid size;

[0156] Discrete convolution module 608 is used to determine the expression of the three components of the anomalous magnetic field of the observation grid by vertically accumulating multiple two-dimensional discrete convolutions based on the unit integral coefficients, the given information of the Earth's main magnetic field model, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution.

[0157] The result output module 610 is used to calculate the three components of the anomalous magnetic field of the observation grid through two-dimensional compressed discrete convolution, and then solve the aeromagnetic anomaly value of the strong magnetic body through a cyclic iterative method.

[0158] The element integral coefficient determination module 606 is also used to construct the arctangent function related to the cuboid elements of the field source and observation points based on the source grid and observation grid:

[0159]

[0160] The logarithmic function associated with the cuboid elements of the field source and observation point is constructed as follows:

[0161]

[0162] in, , , It is the arctangent function. Indicates the arctangent operation; , , It is a logarithmic function. Represents logarithmic operations; , , , , , , , ; Indicates the number is The center coordinates of the cuboid cells in the observation grid. Indicates the number is The center coordinates of the cuboid elements of the field source mesh. , and These represent the dimensions of the discrete cuboid element in the x, y, and z directions, respectively; , , , The number of grid cells in the x, y, and z directions for observation; , , , This represents the number of grid cells in the x, y, and z directions of the field source grid.

[0163] The element integral coefficient determination module 606 is also used to determine the element integral coefficients of each cuboid in the observation grid based on the arctangent function, the logarithmic function, and the three-dimensional difference operator:

[0164]

[0165] in, , , , , , This represents the integral coefficient of each cuboid element. Represents a three-dimensional difference operator. It represents pi (π).

[0166] Discrete convolution module 608 is also used to determine the expression for the three components of the observed grid's anomalous magnetic field by vertically summing multiple two-dimensional discrete convolutions, based on the unit integral coefficients, given Earth's main magnetic field model information, and a complex strong magnetic body model with arbitrary magnetic susceptibility distribution:

[0167]

[0168]

[0169]

[0170] in, , , For the number The observed grid cuboid unit anomaly magnetic field The three components, , , In the model of a complex strongly magnetic body with arbitrary magnetic susceptibility distribution, the number is... The three components of the effective magnetization of the cuboid unit.

[0171] The discrete convolution module 608 is also used to construct a compression matrix based on the unit integral coefficients as follows:

[0172]

[0173] In this matrix, the superscript represents the cuboid number of the field source, and the subscript represents the cuboid element number of the observation point.

[0174] Constructing and compressing matrices Field source matrices of the same size for:

[0175]

[0176] in, They represent dimensions as follows: , , A two-dimensional zero matrix;

[0177] The three components of the anomalous magnetic field of the observed grid are calculated using two-dimensional compressed discrete convolution:

[0178]

[0179] in, and These represent two-dimensional forward and inverse Fourier transforms, respectively. Indicates the first part of the extracted matrix lines and Column elements.

[0180] The result output module 610 is also used to analyze the three components of the observed grid's anomalous magnetic field. The magnetic field value at any observation height is calculated by multi-level accumulation:

[0181]

[0182] Based on the magnetic field value at any observation altitude The total magnetic field value is obtained by iteration:

[0183]

[0184] in, The background magnetic field value. For the first The magnetic anomaly value of the sub-forward modeling Through compact operator iteration The total magnetic field value of the second forward modeling The magnetic susceptibility is denoted as ρ. When the preset iteration convergence condition is reached, the iteration stops, and the total magnetic field value is output as the aero-magnetic anomaly value of the strong magnetic body in the target area.

[0185] Specific limitations regarding the efficient computing device for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects can be found in the limitations of the efficient computing method for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects described above, and will not be repeated here. Each module in the aforementioned efficient computing device for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0186] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and the database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores efficient calculation data for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an efficient calculation method for aeromagnetic anomalies of strongly magnetic bodies considering demagnetization effects.

[0187] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0188] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps in the above method embodiment.

[0189] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0190] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0191] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0192] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A highly efficient calculation method for aero-magnetic anomalies of strongly magnetic bodies considering demagnetization effects, characterized in that, The method includes: Based on the information of the exploration target area and the distribution information of strong magnetic geological bodies, the source area and the underground observation area are discretized into several cuboid units along the x, y, and z directions, respectively, to obtain the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size; The magnetic susceptibility of each cuboid unit in the field source grid is assigned a value to establish a complex strong magnetic body model with arbitrary magnetic susceptibility distribution; Based on the source grid and the observation grid, construct the arctangent function and logarithmic function related to the cuboid elements of the source and observation points. Based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, determine the element integral coefficient of each cuboid in the observation grid. The value of the element integral coefficient can be determined by the cuboid element number of the source grid, the cuboid element number of the observation grid, and the grid size. Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expression for the three components of the abnormal magnetic field of the observation grid is determined by vertically accumulating multiple two-dimensional discrete convolutions. The three components of the anomalous magnetic field of the observation grid are calculated by two-dimensional compressed discrete convolution, and then the aeromagnetic anomaly value of the strong magnetic body is solved by iterative loop.

2. The method according to claim 1, characterized in that, Based on the source grid and the observation grid, construct the arctangent function and logarithmic function related to the cuboid elements of the source and observation points, including: Based on the source grid and the observation grid, the arctangent function related to the cuboid elements of the source and observation points is constructed as follows: The logarithmic function associated with the cuboid elements of the field source and observation point is constructed as follows: in, , , This represents the constructed arctangent function. Indicates the arctangent operation; , , Represents the constructed logarithmic function, Represents logarithmic operations; , , , , , , , ; Indicates the number is The center coordinates of the cuboid cells in the observation grid. Indicates the number is The center coordinates of the cuboid elements of the field source mesh. , and These represent the dimensions of the discrete cuboid element in the x, y, and z directions, respectively; , , , The number of grid cells in the x, y, and z directions of the observation grid; , , , The number of grid cells in the x, y, and z directions of the field source grid.

3. The method according to claim 2, characterized in that, The element integral coefficients of each cuboid in the observation grid are determined based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, including: Based on the arctangent function, the logarithmic function, and the three-dimensional difference operator, the element integral coefficients of each cuboid in the observation grid are determined as follows: in, , , , , , This represents the integral coefficient of each cuboid element. Represents a three-dimensional difference operator. It represents pi (π).

4. The method according to claim 3, characterized in that, Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expressions for the three components of the observed grid's anomalous magnetic field are determined by vertically accumulating multiple two-dimensional discrete convolutions, including: Based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the expression for the three components of the observed grid's anomalous magnetic field is determined by vertically accumulating multiple two-dimensional discrete convolutions: in, , , For the number The observed grid cuboid unit anomaly magnetic field The three components, , , In the complex strong magnetic body model with arbitrary magnetic susceptibility distribution, the number is... The three components of the effective magnetization of the cuboid unit.

5. The method according to claim 4, characterized in that, The three components of the anomalous magnetic field of the observed grid are calculated using two-dimensional compressed discrete convolution, including: The compression matrix is ​​constructed based on the unit integral coefficients as follows: In this matrix, the superscript represents the cuboid number of the field source, and the subscript represents the cuboid element number of the observation point. Constructing and compressing matrices Field source matrices of the same size for: in, They represent dimensions as follows: , , A two-dimensional zero matrix; The three components of the anomalous magnetic field of the observed grid are calculated using two-dimensional compressed discrete convolution: in, and These represent two-dimensional forward and inverse Fourier transforms, respectively. Indicates the first part of the extracted matrix lines and Column elements.

6. The method according to claim 5, characterized in that, The aeromagnetic anomaly values ​​of strongly magnetic bodies are solved using an iterative method, including: Based on the three components of the anomalous magnetic field of the observed grid The magnetic field value at any observation height is calculated by multi-level accumulation: Based on the magnetic field value at the arbitrary observation altitude The total magnetic field value is obtained by iteration: in, The background magnetic field value. For the first The magnetic anomaly value of the sub-forward modeling Through compact operator iteration The total magnetic field value of the second forward modeling It is the magnetic susceptibility; Once the preset iteration convergence condition is met, the iteration stops, and the total magnetic field value is output as the aero-magnetic anomaly value of the strong magnetic body in the target area.

7. The method according to any one of claims 1 to 6, characterized in that, The number of grids in the source grid and the observation grid can be set to be the same or different.

8. A high-efficiency computing device for aero-magnetic anomalies of strongly magnetic bodies considering the effects of demagnetization, characterized in that, The device includes: The grid construction module is used to discretize the source area and the underground observation area into several cuboid units along the x, y, and z directions, respectively, based on the exploration target area information and the distribution information of strongly magnetic geological bodies, thereby obtaining the source grid and the observation grid; the source grid and the observation grid are independent of each other and have the same size; The complex strong magnetic body model building module is used to assign a value to the magnetic susceptibility of each cuboid unit of the field source grid and build a complex strong magnetic body model with arbitrary magnetic susceptibility distribution. The unit integral coefficient determination module is used to construct arctangent and logarithmic functions related to the cuboid units of the field source and observation points based on the field source grid and the observation grid, and to determine the unit integral coefficients of each cuboid of the observation grid based on the arctangent and logarithmic functions and the three-dimensional difference operator; the value of the unit integral coefficients can be determined by the cuboid unit number of the field source grid, the cuboid unit number of the observation grid, and the grid size; The discrete convolution module is used to determine the expression of the three components of the anomalous magnetic field of the observation grid by vertically accumulating multiple two-dimensional discrete convolutions based on the unit integral coefficients, the given Earth's main magnetic field model information, and the complex strong magnetic body model with arbitrary magnetic susceptibility distribution. The results output module is used to calculate the three components of the anomalous magnetic field of the observation grid through two-dimensional compressed discrete convolution, and then solve for the aeromagnetic anomaly value of the strong magnetic body through a cyclic iterative method.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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