Gravity data separation method, device and equipment for metal mine area and medium

Abstract

The invention discloses a gravity data separation method, device and equipment for a metal mine area and a medium, and relates to the technical field of gravity anomaly data processing.The method comprises the steps that gravity data of each measurement point in a target area is obtained through measurement, and Bouguer gravity anomaly data of each measurement point in the target area is obtained through preprocessing; calculating a radial logarithmic power spectrum of the Bouguer gravity anomaly data, dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and respectively extracting the Bouguer gravity anomaly data of each characteristic frequency band; and performing physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain an underground space density distribution result of the target area. According to the method, the inversion result approaches to the prior information in the constraint iteration process, and the gravity potential field inversion result, with the clear prior information, of the metal mine area is strictly constrained in the minimum interval with the known prior information, so that the accuracy of underground ore body position inversion is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of gravity anomaly data processing, and in particular to a gravity data separation method, device, equipment and medium for metal mining areas. Background Art

[0002] Gravity anomalies include the gravity effects caused by all physical inhomogeneities from the surface to the depths. Therefore, to use gravity anomalies to study potential ore bodies, it is necessary to first eliminate the influence of factors other than potential ore bodies and decompose the superimposed coupled geological anomaly signals.

[0003] At present, geological body position field response extraction methods can be mainly divided into two categories: spatial domain and wavenumber domain methods. Spatial domain methods extract target anomalies based on mathematical assumptions or morphological approximations of different anomalies, while wavenumber domain methods extract target anomalies based on the differences in spectral characteristics of different anomalies. The existing gravity response extraction methods each have their own characteristics and advantages.

[0004] However, in complex geological conditions such as metal mining areas, the surface terrain is usually undulating, the geological structure is complex, and the scale of the ore bodies varies. The gravity responses of ore bodies of different scales and interference signals are often highly mixed, resulting in limited accuracy of traditional methods and difficulty in meeting high-precision exploration needs.

[0005] The information disclosed in this background technology section is only intended to enhance understanding of the overall background of the invention and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the Invention

[0006] The present application provides a method, device, equipment, and medium for separating gravity data in metal mining areas to address the deficiencies of the above-mentioned related technologies. The technical solution is as follows:

[0007] In a first aspect, an embodiment of the present application provides a gravity data separation method for a metal mining area, characterized by comprising the following steps:

[0008] Measure and obtain gravity data of each measuring point in the target area;

[0009] Preprocessing the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area;

[0010] Calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data, dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extracting the Bouguer gravity anomaly data of each characteristic frequency band respectively;

[0011] Physical property inversion calculation is performed based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

[0012] In an optional solution of the first aspect, preprocessing the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area includes:

[0013] Performing terrain correction, obtaining high-precision terrain data of the target area, and calculating the influence of terrain parameters at each measuring point on gravity observations based on the high-precision terrain data to obtain terrain correction terms;

[0014] Perform normal field correction and use the international gravity formula to calculate the theoretical gravity value at each measuring point to obtain the normal field correction term;

[0015] Perform Bouguer correction and calculate the Bouguer correction term based on the elevation of each measurement point and the density of the intermediate layer;

[0016] Bouguer gravity anomaly data of each measuring point in the target area is calculated based on the gravity data, the terrain correction term, the normal field correction term, and the Bouguer correction term.

[0017] In an optional solution of the first aspect, calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data includes:

[0018] The radial logarithmic power spectrum is calculated based on the Bouguer gravity anomaly data, and the formula is applied:

[0019] ;

[0020] The step of dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands includes:

[0021] Determining power spectrum curve characteristics of the radial logarithmic power spectrum, and dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands based on geological data of the target area;

[0022] Determine the upper and lower limits of the spatial frequency of each characteristic frequency band, obtain the characteristic frequency band, and apply the formula:

[0023] ;

[0024] in, is the radial logarithmic power spectrum, is the Bouguer gravity anomaly data, represents the two-dimensional Fourier transform, is the spatial frequency in the radial logarithmic power spectrum, Indicates the i-th characteristic frequency band, i is the sequence number of the characteristic frequency band, and N is the total number of characteristic frequency bands.

[0025] In an optional solution of the first aspect, extracting the Bouguer gravity anomaly data of each characteristic frequency band separately includes:

[0026] Each characteristic frequency band is extracted through multiple iterative cycles. The corresponding filter operator is defined in each iteration and the formula is applied:

[0027] ;

[0028] in, is the filtering operator of the kth iteration, k represents the number of iterations, The characteristic frequency band selected for the kth iteration;

[0029] In the kth iteration, the corresponding filter operator For the selected characteristic frequency band Extract features for each spatial frequency in the Bouguer gravity anomaly data;

[0030] The Bouguer gravity anomaly data of each characteristic frequency band is extracted through multiple iterative cycles.

[0031] In an optional solution of the first aspect, the method further includes:

[0032] During the kth iteration, the sequence number of the selected characteristic frequency band is calculated based on the number of iterations k and the total number of characteristic frequency bands to dynamically select the characteristic frequency band. The formula is applied:

[0033] ;

[0034] in, is the serial number of the selected characteristic frequency band, and the mod function is a remainder function, which is used to obtain the remainder after the division operation of two values.

[0035] In an optional solution of the first aspect, performing physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground spatial density distribution result of the target area includes:

[0036] Construct the inversion objective equation and obtain:

[0037] ;

[0038] Substituting the Bouguer gravity anomaly data of each characteristic frequency band into the inversion target equation, solving the inversion target equation, and obtaining the inversion result of each characteristic frequency band;

[0039] The underground spatial density distribution results of the target area based on the inversion results;

[0040] in, is the data fitting term, is the regularization term, The regularization parameter is used to balance the relative weights of the data fitting term and the regularization term;

[0041] In the data fitting term, is the data weighting matrix, is the gravity observation data vector composed of the Bouguer gravity anomaly data of each characteristic frequency band, G is the forward kernel matrix, and m is the target parameter to be solved. represents the two-norm;

[0042] In the regularization term, W is the model weight matrix, is the prior model vector.

[0043] In an optional solution of the first aspect, after obtaining the inversion result of each characteristic frequency band, the method further includes:

[0044] Calculate the relative error between the inversion result of each characteristic frequency band and the prior constraint information, and apply the formula:

[0045] ;

[0046] in, is the matrix formed by the inversion results of the i-th characteristic frequency band, is the prior constraint information, is the relative error between the inversion result of the i-th characteristic frequency band and the prior constraint information;

[0047] If the relative error When the preset relative error threshold is exceeded, the characteristic frequency band is dynamically adjusted and the formula is applied:

[0048] ;

[0049] in, Adjust the step size for the preset frequency band, is the characteristic frequency band after adjustment;

[0050] Updating the filter operator based on the updated characteristic frequency band, and switching to the step of calculating the Bouguer gravity anomaly data of each characteristic frequency band and subsequent steps based on the updated filter operator, until the calculated inversion result converges to the prior information constraint interval;

[0051] Among them, the prior information constraint interval is ;

[0052] like , then determine that the inversion result converges to the prior information constraint interval and output the corresponding inversion result;

[0053] in, is the preset deviation parameter.

[0054] In a second aspect, an embodiment of the present application further provides a gravity data separation device for a metal mining area, comprising:

[0055] A data measurement unit, used to measure and obtain gravity data of each measurement point in the target area;

[0056] A data preprocessing unit, configured to preprocess the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area;

[0057] a calculation unit, configured to calculate a radial logarithmic power spectrum of the Bouguer gravity anomaly data, divide the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extract the Bouguer gravity anomaly data of each characteristic frequency band;

[0058] The calculation unit is further configured to perform physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

[0059] In a third aspect, an embodiment of the present application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the embodiment of the present application or any one of the implementations of the first aspect is implemented.

[0060] In a fourth aspect, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the method provided by the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect.

[0061] The beneficial effects of the technical solutions provided by some embodiments of the present application include at least:

[0062] The embodiment of the present application provides a gravity data separation method, device, equipment and medium for metal mining areas, which innovatively adopts nonlinear inversion technology, integrates multi-source geological constraint information to improve solution reliability, and adopts dynamic frequency selection to construct a filter operator to optimize the filter parameters, thereby achieving high-precision separation and enhancement of the geological gravity response of the deep and shallow parts of the metal mining area. In addition, in the process of constraint iteration, the inversion results are approached to the prior information, and the gravity potential field inversion results of the metal mining area with clear prior information are strictly constrained within the minimum interval of the known prior information, thereby improving the accuracy of the inversion of the underground ore body position, and can extract anomalies of different source bodies in the underground space. Based on the above decoupling cycle framework, the effective extraction of the gravity response of specific targets in the mining area under the constraints of geological prior information can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in this application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1 This is a flow chart of a gravity data separation method for metal mining areas provided in an embodiment of the present application;

[0065] Figure 2 This is a structural diagram of a gravity data separation device for metal mining areas provided by an embodiment of the present application;

[0066] Figure 3 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0068] The terms "including" and "having," and any variations thereof, in the specification and claims of this application and the accompanying drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to the process, method, product, or apparatus.

[0069] It should be noted that the terms "first" and "second" used in this application are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that the terms "first" and "second" may interchangeably represent a specific order or precedence, where permitted. It should be understood that the objects distinguished by "first" and "second" may interchangeably represent a specific order or precedence, where appropriate, such that the embodiments of the present application described herein can be implemented in an order other than that described or illustrated herein.

[0070] The present application is described in detail below with reference to specific embodiments.

[0071] Next, combine Figure 1 , introduces a gravity data separation method for metal mining areas provided by the embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0072] S101, measuring and obtaining gravity data of each measuring point in the target area;

[0073] S102, preprocessing the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area;

[0074] S103, calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data, dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extracting the Bouguer gravity anomaly data of each characteristic frequency band respectively;

[0075] S104: Performing physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

[0076] It is understandable that the gravity data in S101 can be measured by instruments such as a gravimeter, and this embodiment of the present application does not limit this.

[0077] In some embodiments, in S102, preprocessing the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area includes:

[0078] Perform terrain correction, obtain high-precision terrain data of the target area, calculate the influence of terrain parameters at each measurement point on the gravity observation value based on the high-precision terrain data, and obtain the terrain correction term ,include:

[0079] ;

[0080] in, is the gravitational constant, is the surface rock density (usually taken as 2.67g / cm³);

[0081] Perform normal field correction and use the international gravity formula to calculate the theoretical gravity value at each measuring point to obtain the normal field correction term ,include:

[0082] ;

[0083] in, is the latitude of the measurement point.

[0084] Perform Bouguer correction and calculate the Bouguer correction term based on the elevation of each measurement point and the density of the intermediate layer ,include:

[0085] ;

[0086] in, is the elevation of the measuring point, is the middle layer density.

[0087] The Bouguer gravity anomaly data of each measuring point in the target area is calculated based on the gravity data, the terrain correction term, the normal field correction term, and the Bouguer correction term, including:

[0088] ;

[0089] in, is the Bouguer gravity anomaly data of the measurement point, and g is the gravitational acceleration of the target area.

[0090] In some embodiments, in S103, calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data includes:

[0091] The radial logarithmic power spectrum is calculated based on the Bouguer gravity anomaly data, and the formula is applied:

[0092] ;

[0093] The step of dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands includes:

[0094] Determining power spectrum curve characteristics of the radial logarithmic power spectrum, and dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands in combination with geological data of the target area (such as drilling data, seismic exploration results, etc.);

[0095] Determine the upper and lower limits of the spatial frequency of each characteristic frequency band, obtain the characteristic frequency band, and apply the formula:

[0096] ;

[0097] in, is the radial logarithmic power spectrum, is the Bouguer gravity anomaly data, represents the two-dimensional Fourier transform, is the spatial frequency in the radial logarithmic power spectrum, Indicates the i-th characteristic frequency band, i is the sequence number of the characteristic frequency band, and N is the total number of characteristic frequency bands.

[0098] In some embodiments, in S103, extracting Bouguer gravity anomaly data of each characteristic frequency band includes:

[0099] Each characteristic frequency band is extracted through multiple iterative cycles. The corresponding filter operator is defined in each iteration and the formula is applied:

[0100] ;

[0101] This formula can be understood as follows: if the corresponding spatial frequency falls into the extracted characteristic frequency band Inside, then =1, that is, a bandpass filter is applied to the data corresponding to the spatial frequency.

[0102] in, is the filtering operator of the kth iteration, k represents the number of iterations, The characteristic frequency band selected for the kth iteration;

[0103] In the kth iteration, the corresponding filter operator For the selected characteristic frequency band Extract features for each spatial frequency in the Bouguer gravity anomaly data;

[0104] The Bouguer gravity anomaly data of each characteristic frequency band is extracted through multiple iterative cycles.

[0105] In some embodiments, in S103, the method further includes:

[0106] During the kth iteration, the sequence number of the selected characteristic frequency band is calculated based on the number of iterations k and the total number of characteristic frequency bands to dynamically select the characteristic frequency band. The formula is applied:

[0107] ;

[0108] in, is the serial number of the selected characteristic frequency band, and the mod function is a remainder function, which is used to obtain the remainder after the division operation of two values.

[0109] In some embodiments, in S104, performing physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground spatial density distribution result of the target area includes:

[0110] Construct the inversion objective equation and obtain:

[0111] ;

[0112] Substituting the Bouguer gravity anomaly data of each characteristic frequency band into the inversion target equation, solving the inversion target equation, and obtaining the inversion result of each characteristic frequency band;

[0113] The underground spatial density distribution results of the target area based on the inversion results;

[0114] in, is the data fitting term, is the regularization term, The regularization parameter is used to balance the relative weights of the data fitting term and the regularization term;

[0115] In the data fitting term, is the data weighting matrix, is the gravity observation data vector composed of the Bouguer gravity anomaly data of each characteristic frequency band, G is the forward kernel matrix, and m is the target parameter to be solved. represents the two-norm;

[0116] In the regularization term, W is the model weight matrix, is the prior model vector.

[0117] In some embodiments, after obtaining the inversion result of each characteristic frequency band, the method further includes:

[0118] Calculate the relative error between the inversion result of each characteristic frequency band and the prior constraint information, and apply the formula:

[0119] ;

[0120] in, is the matrix formed by the inversion results of the i-th characteristic frequency band, is the prior constraint information, is the relative error between the inversion result of the i-th characteristic frequency band and the prior constraint information;

[0121] If the relative error When the preset relative error threshold is exceeded, the characteristic frequency band is dynamically adjusted and the formula is applied:

[0122] ;

[0123] in, Adjust the step size for the preset frequency band. If the step size is set small, the result is expected to be close enough to the prior information. Otherwise, it indicates that the accuracy requirement is reduced. is the characteristic frequency band after adjustment;

[0124] Updating the filter operator based on the updated characteristic frequency band, and switching to the step of calculating the Bouguer gravity anomaly data of each characteristic frequency band and subsequent steps based on the updated filter operator, until the calculated inversion result converges to the prior information constraint interval;

[0125] Among them, the prior information constraint interval is ;

[0126] like , then determine that the inversion result converges to the prior information constraint interval and output the corresponding inversion result;

[0127] in, is the preset deviation parameter.

[0128] Finally, based on the inversion results that converge to the prior information constraint interval, the mineral density distribution of the target area can be extracted.

[0129] In this way, the constrained iteration process can approximate the inversion results to the prior information. The gravity potential field inversion results for metal mining areas with clear prior information can be strictly constrained to a very small range within the known prior information, thereby improving the accuracy of the inversion of underground ore body positions and enabling the extraction of anomalies from different source bodies in the underground space. Based on this decoupled loop framework, the effective extraction of target gravity responses for specific mining areas under the constraints of geological prior information can be achieved.

[0130] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0131] See next Figure 2 , is a schematic diagram of the structure of a gravity data separation device for metal mining areas provided by an exemplary embodiment of the present application. The device can be implemented as all or part of a terminal through software, hardware, or a combination of both, and can also be integrated into a server as an independent module. The gravity data separation device for metal mining areas in the embodiment of the present application can be applied to a terminal or the cloud. The device includes a data measurement unit, a data preprocessing unit, and a computing unit, wherein:

[0132] A data measurement unit, used to measure and obtain gravity data of each measurement point in the target area;

[0133] A data preprocessing unit, configured to preprocess the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area;

[0134] a calculation unit, configured to calculate a radial logarithmic power spectrum of the Bouguer gravity anomaly data, divide the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extract the Bouguer gravity anomaly data of each characteristic frequency band;

[0135] The calculation unit is further configured to perform physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

[0136] It should be noted that the apparatus provided in the above embodiment, when executing the gravity data separation method for metal mining areas, is merely illustrated by the division of the above-mentioned functional modules. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus provided in the above embodiment and the embodiment of the gravity data separation method for metal mining areas are based on the same concept. The implementation process is detailed in the method embodiment and will not be repeated here.

[0137] An embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method of any of the above embodiments are implemented.

[0138] See Figure 3 , is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0139] like Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302 .

[0140] In the embodiment of the present application, the processor 301 is the control center of the computer system and can be the processor of a physical machine or the processor of a virtual machine. The processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 can be implemented in the form of at least one hardware of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array).

[0141] The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state.

[0142] The memory 302 may include one or more computer-readable storage media, which may be non-transitory. The memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments of the present application, the non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, which is used to be executed by the processor 301 to implement the method in the embodiment of the present application.

[0143] In some embodiments, the electronic device 300 further includes a peripheral device interface 303 and at least one peripheral device 304. The processor 301, memory 302, and peripheral device interface 303 may be connected via a bus or signal lines. Each peripheral device 304 may be connected to the peripheral device interface 303 via a bus, signal lines, or circuit boards. Specifically, the peripheral devices 304 include a display screen, a camera, and an audio circuit. The peripheral device interface 303 may be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 301 and memory 302.

[0144] In some embodiments of the present application, the processor 301, the memory 302, and the peripheral device interface 303 are integrated on the same chip or circuit board; in some other embodiments of the present application, any one or two of the processor 301, the memory 302, and the peripheral device interface 303 may be implemented on separate chips or circuit boards. This embodiment of the present application is not specifically limited to this.

[0145] The electronic device structure block diagram shown in the embodiment of the present application does not constitute a limitation on the electronic device 300. The electronic device 300 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0146] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method of any of the aforementioned embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic or optical card, a nanosystem (including a molecular memory IC), or any other type of medium or device suitable for storing instructions and / or data.

[0147] Through the description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the relevant technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0148] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A gravity data separation method for metal mining areas, characterized in that: The following steps are involved: Measure and obtain gravity data of each measuring point in the target area; Preprocessing the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area; Calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data, dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extracting the Bouguer gravity anomaly data of each characteristic frequency band respectively; Physical property inversion calculation is performed based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

2. The gravity data separation method for metal mining areas according to claim 1, characterized in that: The gravity data is preprocessed to obtain Bouguer gravity anomaly data for each measuring point in the target area, including: Performing terrain correction, obtaining high-precision terrain data of the target area, and calculating the influence of terrain parameters at each measuring point on gravity observations based on the high-precision terrain data to obtain terrain correction terms; Perform normal field correction and use the international gravity formula to calculate the theoretical gravity value at each measuring point to obtain the normal field correction term; Perform Bouguer correction and calculate the Bouguer correction term based on the elevation of each measurement point and the density of the intermediate layer; Bouguer gravity anomaly data of each measuring point in the target area is calculated based on the gravity data, the terrain correction term, the normal field correction term, and the Bouguer correction term.

3. The gravity data separation method for metal mining areas according to claim 1, characterized in that: Calculating the radial logarithmic power spectrum of the Bouguer gravity anomaly data includes: The radial logarithmic power spectrum is calculated based on the Bouguer gravity anomaly data, and the formula is applied: ； The step of dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands includes: Determining power spectrum curve characteristics of the radial logarithmic power spectrum, and dividing the radial logarithmic power spectrum into a plurality of characteristic frequency bands based on geological data of the target area; Determine the upper and lower limits of the spatial frequency of each characteristic frequency band, obtain the characteristic frequency band, and apply the formula: ， ； in, is the radial logarithmic power spectrum, is the Bouguer gravity anomaly data, represents the two-dimensional Fourier transform, is the spatial frequency in the radial logarithmic power spectrum, Indicates the i-th characteristic frequency band, i is the sequence number of the characteristic frequency band, and N is the total number of characteristic frequency bands.

4. The gravity data separation method for metal mining areas according to claim 3, characterized in that: The step of extracting Bouguer gravity anomaly data of each characteristic frequency band includes: Each characteristic frequency band is extracted through multiple iterative cycles. The corresponding filter operator is defined in each iteration and the formula is applied: ； in, is the filtering operator of the kth iteration, k represents the number of iterations, The characteristic frequency band selected for the kth iteration; In the kth iteration, the corresponding filter operator For the selected characteristic frequency band Extract features for each spatial frequency in the Bouguer gravity anomaly data; The Bouguer gravity anomaly data of each characteristic frequency band is extracted through multiple iterative cycles.

5. The gravity data separation method for metal mining areas according to claim 4, characterized in that: The method further comprises: During the kth iteration, the sequence number of the selected characteristic frequency band is calculated based on the number of iterations k and the total number of characteristic frequency bands to dynamically select the characteristic frequency band. The formula is applied: ; in, is the serial number of the selected characteristic frequency band, and the mod function is a remainder function, which is used to obtain the remainder after the division operation of two values.

6. The gravity data separation method for metal mining areas according to claim 5, characterized in that: The physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area includes: Construct the inversion objective equation and obtain: ； Substituting the Bouguer gravity anomaly data of each characteristic frequency band into the inversion target equation, solving the inversion target equation, and obtaining the inversion result of each characteristic frequency band; The underground spatial density distribution results of the target area based on the inversion results; in, is the data fitting term, is the regularization term, The regularization parameter is used to balance the relative weights of the data fitting term and the regularization term; In the data fitting term, is the data weighting matrix, is the gravity observation data vector composed of the Bouguer gravity anomaly data of each characteristic frequency band, G is the forward kernel matrix, and m is the target parameter to be solved. represents the two-norm; In the regularization term, W is the model weight matrix, is the prior model vector.

7. The gravity data separation method for metal mining areas according to claim 6, characterized in that: After obtaining the inversion result of each characteristic frequency band, the method further includes: Calculate the relative error between the inversion result of each characteristic frequency band and the prior constraint information, and apply the formula: ； in, is the matrix formed by the inversion results of the i-th characteristic frequency band, is the prior constraint information, is the relative error between the inversion result of the i-th characteristic frequency band and the prior constraint information; If the relative error When the preset relative error threshold is exceeded, the characteristic frequency band is dynamically adjusted and the formula is applied: ; in, Adjust the step size for the preset frequency band, is the characteristic frequency band after adjustment; Updating the filter operator based on the updated characteristic frequency band, and switching to the step of calculating the Bouguer gravity anomaly data of each characteristic frequency band and subsequent steps based on the updated filter operator, until the calculated inversion result converges to the prior information constraint interval; Among them, the prior information constraint interval is ; like , then determine that the inversion result converges to the prior information constraint interval and output the corresponding inversion result; in, is the preset deviation parameter.

8. A gravity data separation device for metal mining areas, characterized in that: include: A data measurement unit, used to measure and obtain gravity data of each measurement point in the target area; A data preprocessing unit, configured to preprocess the gravity data to obtain Bouguer gravity anomaly data for each measuring point in the target area; a calculation unit, configured to calculate a radial logarithmic power spectrum of the Bouguer gravity anomaly data, divide the radial logarithmic power spectrum into a plurality of characteristic frequency bands, and extract the Bouguer gravity anomaly data of each characteristic frequency band; The calculation unit is further configured to perform physical property inversion calculation based on the Bouguer gravity anomaly data of each characteristic frequency band to obtain the underground space density distribution result of the target area.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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