An automatic delineation method, device and electronic equipment for aeromagnetic anomalies

Abstract

The application provides a kind of aeromagnetic anomaly automatic delineation method, device and electronic equipment, wherein the method comprises: carrying out continuous wavelet transform to any data in grid aeromagnetic data to obtain wavelet coefficient;Calculate the instantaneous frequency and convert the wavelet coefficient from the time scale domain to the time-frequency domain;The wavelet coefficient is squeezed and rearranged to obtain the two-dimensional synchronous squeezing transformation value;The two-dimensional synchronous squeezing transformation value of each data is stored to the three-dimensional matrix and sliced to obtain the aeromagnetic data information under different frequency distribution, realize the aeromagnetic anomaly identification delineation of grid aeromagnetic data.Through the aeromagnetic anomaly automatic delineation method, device and electronic equipment provided by the embodiment of the application, the characteristics of the reflection of the underground geological body magnetic anomaly of the aeromagnetic data are fully utilized, the time-frequency analysis method is used to convert the aeromagnetic data from the space-amplitude domain to the space-frequency domain, the extraction of the aeromagnetic anomaly characteristics is effectively completed, and the problems of insufficient resolution and fuzzy boundary of the original data are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic interpretation of airborne magnetic data, in particular to an airborne magnetic anomaly automatic delineation method and device, electronic equipment and a computer readable storage medium. BACKGROUND

[0002] Since the 21st century, with the increasing demand for mineral resources in China, the mineral resources that are easy to find and utilize in the shallow part are decreasing, and the deep blind ore prospecting is one of the important research topics of the current exploration work. Because the magnetism of the ore body is usually obviously different from that of the surrounding rock mass, the magnetic method exploration has a wide application in the search for mineral resources, and the airborne high-precision magnetic method exploration is an effective method. However, the geological conditions in nature are often complex, the shapes of various geological bodies are irregular, the physical property parameters are uneven, and the airborne magnetic method exploration is also disturbed by various factors in the data acquisition process, so that the measurement results become complex and difficult to analyze. How to quickly and automatically identify and delineate the airborne magnetic anomaly, and effectively cope with the influence of various disturbances in the anomaly processing process is a problem to be solved in the current airborne magnetic method exploration. SUMMARY

[0003] To solve the existing technical problems, the embodiments of the present application provide an airborne magnetic anomaly automatic delineation method, device, electronic equipment and computer readable storage medium.

[0004] In a first aspect, the embodiments of the present application provide an airborne magnetic anomaly automatic delineation method, comprising: acquiring gridded airborne magnetic data, performing continuous wavelet transform on any data in the gridded airborne magnetic data to obtain the wavelet coefficient corresponding to the data; calculating the instantaneous frequency corresponding to the data according to the wavelet coefficient corresponding to the data, and converting the wavelet coefficient corresponding to the data from the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data; performing squeezing and rearranging on the wavelet coefficient converted to the time frequency domain to obtain the two-dimensional synchronous squeezing transform value corresponding to the data; storing the two-dimensional synchronous squeezing transform value corresponding to each data in the gridded airborne magnetic data to a three-dimensional matrix, slicing the three-dimensional matrix along the frequency direction to obtain the airborne magnetic data information under different frequency distributions corresponding to the gridded airborne magnetic data; and realizing the airborne magnetic anomaly identification and delineation of the gridded airborne magnetic data based on the airborne magnetic data information under different frequency distributions corresponding to the gridded airborne magnetic data.

[0005] Optionally, the gridded airborne magnetic data is acquired by: acquiring airborne magnetic raw data in a to-be-identified work area, performing reduction-to-pole calculation on the airborne magnetic raw data to obtain airborne magnetic reduction-to-pole data; and gridding the airborne magnetic reduction-to-pole data to obtain the gridded airborne magnetic data.

[0006] Optionally, the continuous wavelet transform is a finite-length wavelet basis function that attenuates; and the wavelet basis function comprises a pulse wavelet, a Gaussian wavelet, or a Bump-on-a-Quadratic wavelet.

[0007] Optionally, when the wavelet basis function is the Bump-on-a-Quadratic wavelet, a ratio between a center frequency and a shape factor preset before the continuous wavelet transform is located in an interval [0.1, 0.35].

[0008] Optionally, the synchronous squeezing module is configured to rearrange the wavelet coefficients converted to the time-frequency domain by squeezing, to obtain a two-dimensional synchronous squeezing transform value corresponding to the data.

[0009] Optionally, the identification and delineation module is configured to: determine whether a lowest frequency slice in the aeromagnetic data information corresponding to different frequency distributions of the gridded aeromagnetic data corresponds to an aeromagnetic anomaly distribution; if yes, output a frequency slice corresponding to the aeromagnetic anomaly distribution, and identify and delineate an aeromagnetic anomaly region where a magnetic body exists based on a concentration of high-energy groups in the frequency slice.

[0010] In a second aspect, the embodiments of the present application further provide an aeromagnetic anomaly automatic delineation device, comprising: a continuous wavelet transform module, a frequency domain conversion module, a synchronous squeezing module, a slicing module, and an identification and delineation module; the continuous wavelet transform module is configured to obtain gridded aeromagnetic data, and perform continuous wavelet transform on any one of the gridded aeromagnetic data to obtain wavelet coefficients corresponding to the data; the frequency domain conversion module is configured to calculate an instantaneous frequency corresponding to the data according to the wavelet coefficients corresponding to the data, and convert the wavelet coefficients corresponding to the data from a time scale domain to a time-frequency domain based on the instantaneous frequency corresponding to the data; the synchronous squeezing module is configured to rearrange the wavelet coefficients converted to the time-frequency domain by squeezing to obtain a two-dimensional synchronous squeezing transform value corresponding to the data; the slicing module is configured to store the two-dimensional synchronous squeezing transform value corresponding to each of the gridded aeromagnetic data to a three-dimensional matrix, and slice the three-dimensional matrix along a frequency direction to obtain aeromagnetic data information corresponding to different frequency distributions of the gridded aeromagnetic data; and the identification and delineation module is configured to realize identification and delineation of aeromagnetic anomalies of the gridded aeromagnetic data based on the aeromagnetic data information corresponding to different frequency distributions of the gridded aeromagnetic data.

[0011] In a third aspect, an electronic device is provided, including a processor and a memory, and the memory stores a computer program. The processor executes the computer program stored in the memory, and the computer program, when executed by the processor, implements the aeromagnetic anomaly automatic delineation method of the first aspect.

[0012] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program, when executed by a processor, implements the aeromagnetic anomaly automatic delineation method of the first aspect.

[0013] In a fifth aspect, a computer program product is provided, and the computer program product includes a computer program. When the computer program is executed, the aeromagnetic anomaly automatic delineation method of the first aspect or any possible design of the first aspect can be implemented.

[0014] The aeromagnetic anomaly automatic delineation method, device, electronic device, and computer readable storage medium provided by the embodiments of the present application make full use of the characteristics of the reflection of the magnetic anomaly of the underground geological body by the aeromagnetic data, convert the aeromagnetic data from the space-amplitude domain to the space-frequency domain by using the time-frequency analysis method, effectively extract the characteristics of the aeromagnetic anomaly in the process, solve the problems of insufficient resolution and fuzzy boundary of the original aeromagnetic data, and the method has good stability and anti-interference ability. The prediction result can be provided to a geological interpreter as an objective basis for aeromagnetic anomaly identification and delineation. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background art, the drawings needed to be used in the embodiments of the present application or the background art will be described below.

[0016] Figure 1 A flowchart of an aeromagnetic anomaly automatic delineation method provided by an embodiment of the present application is shown;

[0017] Figure 2 An aeromagnetic reduction-to-pole data schematic diagram obtained after reduction-to-pole in the aeromagnetic anomaly automatic delineation method provided by an embodiment of the present application is shown;

[0018] Figure 3 An aeromagnetic anomaly delineation diagram finally output in the aeromagnetic anomaly automatic delineation method provided by an embodiment of the present application is shown;

[0019] Figure 4 A detailed flowchart of an aeromagnetic anomaly automatic delineation method provided by an embodiment of the present application is shown;

[0020] Figure 5 A structure schematic diagram of an aeromagnetic anomaly automatic delineation device provided by an embodiment of the present application is shown;

[0021] Figure 6 Fig. 1 shows a structural schematic diagram of an electronic device for performing the method for automatically delineating aeromagnetic anomalies provided by the embodiment of the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application will be described below with reference to the accompanying drawings.

[0023] It can be understood that the aeromagnetic anomaly mentioned in the embodiments of the present application is the superposition of the potential field from different depth and scale geological bodies, the high-frequency signal mainly reflects the high-frequency magnetic anomaly information generated by the shallow magnetic body, and the low-frequency signal mainly reflects the low-frequency magnetic anomaly information generated by the deep magnetic body. In order to better achieve the important exploration target of blind ore prospecting in deep part, the embodiment of the present application proposes a method for automatically delineating aeromagnetic anomalies which can better process low-frequency signals.

[0024] Figure 1 Fig. 2 shows a flow chart of the method for automatically delineating aeromagnetic anomalies provided by the embodiment of the present application. As shown in Fig. 2, the method comprises the following steps 101-105. Figure 1

[0025] Step 101: acquiring the gridded aeromagnetic data, performing continuous wavelet transform on any one of the data in the gridded aeromagnetic data to obtain the wavelet coefficient corresponding to the data.

[0026] The aeromagnetic data refers to the geomagnetic field data acquired through the airborne magnetic survey (referred to as aeromagnetic survey). The embodiment of the present application needs to perform continuous wavelet transform on the gridded aeromagnetic data (i.e. gridded aeromagnetic data) based on the idea of wavelet multi-scale decomposition. Specifically, the gridded aeromagnetic data is a matrix form data composed of multiple rows and multiple columns of data. The embodiment of the present application can perform continuous wavelet transform on any one of the data (such as any one row or any one column) in the gridded aeromagnetic data, thereby obtaining the wavelet coefficient corresponding to the data (such as the row data or the column data).

[0027] Specifically ， The formula of the continuous wavelet transform can be seen from the following formula (1):

[0028]

[0029] Wherein, W x (a, b) is the wavelet coefficient, a is the scale factor, b is the translation factor, and ψ(t) is the wavelet base function.

[0030] ​Step 102: Calculate the instantaneous frequency of the data based on the wavelet coefficients corresponding to the data, and transform the wavelet coefficients of the data from the time scale domain to the time frequency domain based on the instantaneous frequency of the data.

[0031] Specifically, the instantaneous frequency is calculated based on the wavelet coefficients corresponding to any data obtained in step 101 above. Based on the above equation (1), it can be seen that for any (a,b) value, if the wavelet coefficient W x If (a,b)≠0, then the instantaneous frequency of the signal x(t) can be expressed as follows (2):

[0032]

[0033] In other words, the instantaneous frequency of the signal x(t) can be obtained by differentiating the wavelet coefficients in the time domain, i.e., equation (2). Furthermore, based on the instantaneous frequency obtained from equation (2), the transition from (b,a) to (b,ω) is established. x The mapping of (a,b) can be used to map the wavelet coefficients ω x (a,b) Transformation from the time-scale domain to the time-frequency domain (it should be noted that in aeromagnetics, a spatial direction is usually regarded as a time direction), i.e., ω x (a,b) transformed to W x (ω x (a,b),b).

[0034] Step 103: Perform compression and rearrangement on the wavelet coefficients transformed to the time-frequency domain to obtain the two-dimensional synchronous compression transformation value corresponding to the data.

[0035] Based on step 102 above, after obtaining the time-frequency spectrum distribution of the instantaneous frequency (i.e., the center frequency), the interval near any center frequency ωl is... The wavelet coefficients are simultaneously compressed and rearranged to obtain the two-dimensional synchronous compression transform value T corresponding to the data. x (ω,b). As shown in equation (3):

[0036]

[0037] In practical applications, due to the presence of noise or interference signals, W x When (a,b)=0, the two-dimensional synchronous extrusion transformation value T will be affected. x (ω l b) is unstable. Therefore, it is necessary to consider |W x The threshold (a, b)| is used to limit the range of A(b). That is, A(b) = {a; W} x (a,b)≠0},Δw=w l -wl-1 It can be understood that step 103 involves adjusting the wavelet coefficients W in the frequency direction, i.e., the scale direction. x (ω x Compression and recombination of (a,b),b) focuses its energy, thereby improving the ambiguity in the scale direction.

[0038] Step 104: Store the two-dimensional synchronous compression transformation value corresponding to each data point in the gridded aeromagnetic data into a three-dimensional matrix, slice the three-dimensional matrix along the frequency direction, and obtain aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data.

[0039] Based on the process described in steps 101-103 above, each data point in the gridded aeromagnetic data is processed as described above to obtain the two-dimensional synchronous compression transformation value corresponding to each data point. Further, the two-dimensional synchronous compression transformation value corresponding to each data point is stored in a three-dimensional matrix, and then the three-dimensional matrix is ​​sliced ​​along the frequency direction to extract aeromagnetic data information (such as slices) under different frequency distributions of the gridded aeromagnetic data.

[0040] Step 105: Based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, the aeromagnetic anomalies in the gridded aeromagnetic data are identified and delineated.

[0041] Based on the aeromagnetic data information of the gridded aeromagnetic data obtained in step 104 above under different frequency distributions, the automatic identification and delineation of aeromagnetic anomaly regions is completed according to the frequency characteristics of the aeromagnetic anomaly boundary (such as the high-energy cluster boundary in the low-frequency signal slice).

[0042] The automatic delineation method for aeromagnetic anomalies provided in this invention fully utilizes the characteristics of aeromagnetic data reflecting magnetic anomalies in underground geological bodies. It uses time-frequency analysis to convert aeromagnetic data from the spatial-amplitude domain to the spatial-frequency domain, effectively extracting aeromagnetic anomaly features in the process. This solves the problems of insufficient resolution and blurred boundaries in the original aeromagnetic data. At the same time, the method has good stability and anti-interference ability, and the prediction results can be provided to geological interpreters as an objective basis for the identification and delineation of aeromagnetic anomalies.

[0043] Optionally, the process of "acquiring gridded aeromagnetic data" in step 101 above may include the following steps A1-A2.

[0044] Step A1: Obtain the original aeromagnetic data of the work area to be identified, and perform pole conversion calculation on the original aeromagnetic data to obtain aeromagnetic pole conversion data.

[0045] In this embodiment of the invention, the work area to be identified refers to the geographical area delineated for aeromagnetic anomaly identification. An airborne magnetic field meter is used to acquire the raw aeromagnetic data of this work area. For example, an airborne magnetic field meter and its auxiliary equipment can be mounted on an aircraft, and the geomagnetic field strength or gradient can be measured over the measurement area according to a pre-set survey line and altitude to obtain the raw aeromagnetic data. Further, the raw aeromagnetic data needs to be processed to obtain aeromagnetic pole conversion data, such as... Figure 2 As shown, Figure 2 A schematic diagram of the aeromagnetic polarization data obtained after polarization is shown.

[0046] It should be noted that the process of polarization calculation is a conventional technique in this field, and will not be elaborated here.

[0047] Step A2: Grid the aeromagnetic pole data to obtain gridded aeromagnetic data, i.e., convert it into a text-readable GRD format (grid format). It should be noted that the gridding process is a common technique in this field and will not be elaborated upon here.

[0048] Optionally, the "continuous wavelet transform" in step 101 above is a finite-length, decaying wavelet basis function. That is, a finite-length, decaying wavelet basis function can be used to convolve the signal x(t) along the time direction to obtain the instantaneous frequency of the signal x(t). In addition to obtaining the instantaneous frequency, the time position corresponding to the instantaneous frequency can also be located. Specifically, the wavelet basis function used in the embodiments of the present invention may include: pulse wavelet, Gaussian wavelet, or concave-convex wavelet. Preferably, a concave-convex wavelet is used as the wavelet basis function, and its expression can be found in equation (4).

[0049]

[0050] in, Representing an interval The index function within the wavelet transform is defined by μ, which represents the center frequency and σ, which represents the shape factor and determines the bandwidth of the wavelet. μ and σ together determine the time-frequency resolution of the wavelet transform.

[0051] Optionally, when the wavelet basis function is a concave-convex wavelet, the ratio μ / σ between the preset center frequency μ and shape factor σ before performing continuous wavelet transform is located in the interval [0.1, 0.35].

[0052] The reason why the ratio μ / σ between the center frequency μ and the shape factor σ is defined in the interval [0.1, 0.35] in this embodiment of the invention is that when the value of μ / σ is greater than 0.35, it leads to insufficient spatial resolution, making it impossible to accurately delineate the anomaly range; when the value of μ / σ is less than 0.1, it not only leads to insufficient frequency resolution, making it impossible to determine the relative burial depth of the anomaly, but also severely suppresses wavelet coefficients, making it impossible to obtain an effective time-spectrum diagram. Therefore, selecting the ratio μ / σ between the center frequency μ and the shape factor σ in the interval [0.1, 0.35] results in better processing performance. Figure 2 As shown, Figure 2 The diagram shows the synchronous squeezing wavelet transform performed on the data corresponding to the aeromagnetic pole data after data gridding. The wavelet basis used is concave-convex wavelet with a center frequency of 1 and a shape factor of 1.5π.

[0053] Optionally, step 103 above, "compressing and rearranging the wavelet coefficients converted to the time-frequency domain", may include: rearranging the wavelet coefficients in the frequency direction and reconstructing the gridded aeromagnetic data through inverse transformation.

[0054] During the synchronous compression process, since the wavelet coefficients are rearranged in the frequency direction in this embodiment of the invention, this algorithm is reversible. Therefore, the gridded aeromagnetic data obtained by initially gridding the aeromagnetic pole data can be reconstructed by inverse transformation. Its expression can be found in Equation (5).

[0055]

[0056] Where Re is the operation for taking the real part of a complex number, and C ψ C is the regularization constant. ψ The expression for can be found in equation (6).

[0057]

[0058] Optionally, step 105 above, "based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, realize the identification and delineation of aeromagnetic anomalies in the gridded aeromagnetic data", may include the following steps B1-B2.

[0059] Step B1: Determine whether the lowest frequency slice in the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data corresponds to the aeromagnetic anomaly distribution.

[0060] In this embodiment of the invention, after processing and obtaining aeromagnetic data information (i.e. slices) under different frequency distributions corresponding to the gridded aeromagnetic data, it can be determined whether the lowest frequency slice corresponds to a known aeromagnetic anomaly distribution. By determining whether this condition is met, aeromagnetic data information (i.e. slices) with aeromagnetic anomalies can be selected.

[0061] Step B2: If yes, output the frequency slice corresponding to the aeromagnetic anomaly distribution. Based on the concentration of high-energy clusters in the frequency slice, identify and delineate the aeromagnetic anomaly region where a magnetic body exists.

[0062] If the lowest frequency slice corresponds to a known aeromagnetic anomaly distribution, the aeromagnetic anomaly data information (i.e., slice) at that frequency is output. Based on the low energy distribution in the low frequency slice, the boundary of the aeromagnetic anomaly can be accurately identified, thereby achieving automatic delineation of the aeromagnetic anomaly boundary. Based on the distribution of high energy clusters in the slice, the region where high energy clusters are concentrated is automatically identified and delineated, and it is determined that there is a magnetic body in the region.

[0063] like Figure 3 As shown, Figure 3 The final output aeromagnetic anomaly delineation map is shown. The aeromagnetic anomaly identification and delineation method based on synchronous compression transform can accurately identify the boundaries of aeromagnetic anomalies, thereby achieving automatic delineation of aeromagnetic anomaly boundaries. It can also identify high-energy clusters in low-frequency slices (such as...) Figure 3 The concentration of the clusters (circled in the middle) determines whether there is a magnetic body deep within.

[0064] Please refer to the following. Figure 4 The process shown below provides a detailed understanding of the automatic aeromagnetic anomaly delineation method, which will not be elaborated upon here.

[0065] The automatic delineation method for aeromagnetic anomalies provided by the embodiments of the present invention has been described in detail above. This method can also be implemented by a corresponding device. The automatic delineation device for aeromagnetic anomalies provided by the embodiments of the present invention will be described in detail below.

[0066] Figure 5 A schematic diagram of an automatic aeromagnetic anomaly delineation device provided in an embodiment of the present invention is shown. Figure 5 As shown, the automatic aeromagnetic anomaly delineation device includes a processor. The processor includes: a continuous wavelet transform module 51, a frequency domain conversion module 52, a synchronous compression module 53, a slicing module 54, and an identification and delineation module 55.

[0067] The continuous wavelet transform module 51 is used to acquire gridded aeromagnetic data, perform continuous wavelet transform on any channel of the gridded aeromagnetic data, and obtain the wavelet coefficients corresponding to the data.

[0068] The frequency domain conversion module 52 is used to calculate the instantaneous frequency corresponding to the data based on the wavelet coefficients corresponding to the data, and convert the wavelet coefficients corresponding to the data from the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data.

[0069] The synchronous squeezing module 53 is used to squeeze and rearrange the wavelet coefficients converted to the time frequency domain to obtain the two-dimensional synchronous squeezing transformation value corresponding to the data.

[0070] The slicing module 54 is used to store the two-dimensional synchronous compression transformation value corresponding to each data point in the gridded aeromagnetic data into a three-dimensional matrix, and slice the three-dimensional matrix along the frequency direction to obtain aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data.

[0071] The identification and delineation module 55 is used to identify and delineate aeromagnetic anomalies in the gridded aeromagnetic data based on aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data.

[0072] Optionally, the continuous wavelet transform module 51 includes: a polarization unit and a meshing unit.

[0073] The polarization unit is used to acquire the original aeromagnetic data within the work area to be identified, and to perform polarization calculations on the original aeromagnetic data to obtain aeromagnetic polarization data.

[0074] A gridded cell is used to grid the aeromagnetic pole data to obtain the gridded aeromagnetic data.

[0075] Optionally, the continuous wavelet transform is converted into a finite-length, decaying wavelet basis function; the wavelet basis function includes: pulse wavelet, Gaussian wavelet, or concave-convex wavelet.

[0076] Optionally, when the wavelet basis function is the concave-convex wavelet, the ratio between the preset center frequency and shape factor before performing the continuous wavelet transform is located in the interval [0.1, 0.35].

[0077] Optionally, the synchronous extrusion module 53 includes an inverse transformation unit.

[0078] The inverse transform unit is used to rearrange the wavelet coefficients in the frequency direction and reconstruct the gridded aeromagnetic data through inverse transform.

[0079] Optionally, the identification and delineation module 55 includes: a judgment unit and a delineation unit.

[0080] The judgment unit is used to determine whether the lowest frequency slice in the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data corresponds to the aeromagnetic anomaly distribution.

[0081] The delineation unit is used to output a frequency slice corresponding to the aeromagnetic anomaly distribution if the condition is met, and to identify and delineate the aeromagnetic anomaly region where a magnetic body exists based on the concentration of high-energy clusters in the frequency slice.

[0082] The device provided in this invention fully utilizes the characteristics of aeromagnetic data reflecting magnetic anomalies in underground geological bodies. It uses a time-frequency analysis device to convert aeromagnetic data from the spatial-amplitude domain to the spatial-frequency domain, effectively extracting aeromagnetic anomaly features in the process. This solves the problems of insufficient resolution and blurred boundaries in the original aeromagnetic data. At the same time, the device has good stability and anti-interference ability, and the prediction results can be provided to geological interpreters as an objective basis for the identification and delineation of aeromagnetic anomalies.

[0083] It should be noted that the automatic aeromagnetic anomaly delineation device provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the automatic aeromagnetic anomaly delineation device and the automatic aeromagnetic anomaly delineation method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0084] According to one aspect of this application, embodiments of the present invention also provide a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component. When the computer program is executed by a processor, the automatic aeromagnetic anomaly delineation method provided in embodiments of this application is performed.

[0085] In addition, this invention also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are connected via the bus. When the computer program is executed by the processor, it implements the various processes of the above-described automatic aeromagnetic anomaly identification method embodiment and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0086] For details, see Figure 6 As shown, the electronic device includes a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150, and a user interface 1160.

[0087] In this embodiment of the invention, the electronic device further includes: a computer program stored in a memory 1150 and executable on a processor 1120, wherein the computer program, when executed by the processor 1120, implements the various processes of the above-described automatic aeromagnetic anomaly delineation method embodiment.

[0088] Transceiver 1130 is used to receive and send data under the control of processor 1120.

[0089] In this embodiment of the invention, a bus architecture (represented by bus 1110) is used. Bus 1110 may include any number of interconnected buses and bridges. Bus 1110 connects various circuits, including one or more processors represented by processor 1120 and memory represented by memory 1150.

[0090] Bus 1110 represents one or more of several types of bus architectures, including memory buses and memory controllers, peripheral buses, Accelerated Graphics Port (AGP), processors, or local buses using any bus architecture from various bus architectures. As an example and not a limitation, such architectures include: Industry Standard Architecture (ISA) buses, Micro Channel Architecture (MCA) buses, Enhanced ISA (EISA) buses, Video Electronics Standards Association (VESA) buses, and Peripheral Component Interconnect (PCI) buses.

[0091] The processor 1120 can be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method embodiments can be completed by integrated logic circuits in the processor hardware or by instructions in software form. The processors mentioned above include: general-purpose processors, central processing units (CPUs), network processors (NPs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), programmable logic arrays (PLAs), microcontroller units (MCUs) or other programmable logic devices, discrete gates, transistor logic devices, and discrete hardware components. They can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. For example, the processor can be a single-core processor or a multi-core processor, and the processor can be integrated on a single chip or located on multiple different chips.

[0092] Processor 1120 can be a microprocessor or any conventional processor. The method steps disclosed in the embodiments of the present invention can be directly executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in readable storage media known in the art, such as Random Access Memory (RAM), Flash Memory, Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), registers, etc. The readable storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0093] Bus 1110 can also connect various other circuits, such as peripheral devices, voltage regulators, or power management circuits. Bus interface 1140 provides an interface between bus 1110 and transceiver 1130, all of which are well known in the art. Therefore, embodiments of the present invention will not be described further.

[0094] Transceiver 1130 can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. For example, transceiver 1130 receives external data from other devices, and transceiver 1130 is used to send data processed by processor 1120 to other devices. Depending on the nature of the computer system, a user interface 1160 may also be provided, such as a touchscreen, physical keyboard, monitor, mouse, speaker, microphone, trackball, joystick, or stylus.

[0095] It should be understood that, in embodiments of the present invention, memory 1150 may further include memory remotely configured relative to processor 1120, and such remotely configured memory can be connected to a server via a network. One or more portions of the aforementioned network may be an ad hoc network, intranet, extranet, virtual private network (VPN), local area network (LAN), wireless local area network (WLAN), wide area network (WAN), wireless wide area network (WWAN), metropolitan area network (MAN), Internet, public switched telephone network (PSTN), ordinary old-style telephone service (POTS), cellular telephone network, wireless network, Wi-Fi network, and combinations of two or more of the aforementioned networks. For example, cellular telephone networks and wireless networks can be Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), WiMAX, General Packet Radio Service (GPRS), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), Advanced Long Term Evolution (LTE-A), Universal Mobile Telecommunications System (UMTS), Enhanced Mobile Broadband (eMBB), Massive Machine Type Communication (mMTC), Ultra Reliable Low Latency Communications (uRLLC), etc.

[0096] It should be understood that the memory 1150 in the embodiments of the present invention may be volatile memory or non-volatile memory, or may include both volatile memory and non-volatile memory. Non-volatile memory includes: read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0097] Volatile memory includes random access memory (RAM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1150 of the electronic device described in this embodiment includes, but is not limited to, the above-described and any other suitable types of memory.

[0098] In this embodiment of the invention, the memory 1150 stores the following elements of the operating system 1151 and the application 1152: executable modules, data structures, or subsets thereof, or extended sets thereof.

[0099] Specifically, the operating system 1151 includes various system programs, such as a framework layer, a core library layer, and a driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 1152 includes various applications, such as a media player and a browser, used to implement various application functions. Programs implementing the methods of this embodiment of the invention can be included in the application program 1152. The application program 1152 includes applets, objects, components, logic, data structures, and other computer system executable instructions that perform specific tasks or implement specific abstract data types.

[0100] In addition, this embodiment of the invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the various processes of the above-described automatic aeromagnetic anomaly delineation method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0101] Computer-readable storage media include: permanent and non-permanent, removable and non-removable media, which are tangible devices capable of retaining and storing instructions for use by an instruction execution device. Computer-readable storage media include: electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, and any suitable combination thereof. Computer-readable storage media include: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, optical disc read-only memory (CD-ROM), digital versatile optical disc (DVD) or other optical storage, magnetic tape storage, magnetic disk storage or other magnetic storage devices, memory sticks, mechanical encoding devices (e.g., punched cards or raised structures in grooves on which instructions are recorded), or any other non-transfer medium that can be used to store information accessible by a computing device. As defined in the embodiments of the present invention, computer-readable storage media do not include temporary signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0102] In the several embodiments provided in this application, it should be understood that the disclosed apparatus, electronic devices, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0103] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to solve the problems addressed by the embodiments of the present invention, depending on actual needs.

[0104] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0105] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (including: a personal computer, a server, a data center, or other network device) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media listed above that can store program code.

[0106] In the description of the embodiments of the present invention, those skilled in the art should understand that the embodiments of the present invention can be implemented as methods, apparatuses, electronic devices, and computer-readable storage media. Therefore, the embodiments of the present invention can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. Furthermore, in some embodiments, the embodiments of the present invention can also be implemented as a computer program product in one or more computer-readable storage media, the computer-readable storage media containing computer program code.

[0107] The aforementioned computer-readable storage medium may be any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any combination thereof. In embodiments of the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0108] The computer program code contained in the aforementioned computer-readable storage medium may be transmitted using any suitable medium, including wireless, wire, optical fiber, radio frequency (RF), or any suitable combination thereof.

[0109] Computer program code for performing the operations of the embodiments of the present invention can be written in assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, integrated circuit configuration data, or in one or more programming languages ​​or combinations thereof. The programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The computer program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer or an external computer via any type of network, including a local area network (LAN) or a wide area network (WAN).

[0110] The embodiments of the present invention describe the provided methods, apparatus, and electronic devices through flowcharts and / or block diagrams.

[0111] It should be understood that each block of a flowchart and / or block diagram, as well as combinations of blocks in a flowchart and / or block diagram, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine that, when executed by a computer or other programmable data processing apparatus, creates means for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0112] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to function in a particular manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction apparatus product that includes the functions / operations specified in the blocks of a flowchart and / or block diagram.

[0113] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus or other device to produce a computer-implemented process, such that the instructions that execute on the computer or other programmable data processing apparatus provide a process for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0114] The above description is merely a specific implementation of the embodiments of the present invention, but the protection scope of the embodiments of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of the present invention should be included within the protection scope of the embodiments of the present invention. Therefore, the protection scope of the embodiments of the present invention should be determined by the protection scope of the claims.

Claims

1. A method for automatically delineating aeromagnetic anomalies, characterized in that, include: Obtain gridded aeromagnetic data, and perform continuous wavelet transform on any channel of the gridded aeromagnetic data to obtain the wavelet coefficients corresponding to the data; Calculate the instantaneous frequency of the data based on the wavelet coefficients corresponding to the data, and transform the wavelet coefficients of the data from the time scale domain to the time frequency domain based on the instantaneous frequency of the data. The wavelet coefficients transformed to the time-frequency domain are squeezed and rearranged to obtain the two-dimensional synchronous squeezing transformation value corresponding to the data. The two-dimensional synchronous compression transformation value corresponding to each data point in the gridded aeromagnetic data is stored in a three-dimensional matrix. The three-dimensional matrix is ​​sliced ​​along the frequency direction to obtain aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data. Based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, the aeromagnetic anomaly identification and delineation of the gridded aeromagnetic data is realized, including: Determine whether the lowest frequency slice in the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data corresponds to the aeromagnetic anomaly distribution; If so, output the frequency slice corresponding to the aeromagnetic anomaly distribution, and based on the concentration of high-energy clusters in the frequency slice, identify and delineate the aeromagnetic anomaly region where a magnetic body exists.

2. The method according to claim 1, characterized in that, The acquisition of gridded aeromagnetic data includes: Obtain raw aeromagnetic data within the work area to be identified, and perform pole conversion calculation on the raw aeromagnetic data to obtain aeromagnetic pole conversion data; The aeromagnetic pole data is gridded to obtain the gridded aeromagnetic data.

3. The method according to claim 1, characterized in that, The continuous wavelet transform is a finite-length, decaying wavelet basis function; the wavelet basis function includes: pulse wavelet, Gaussian wavelet, or concave-convex wavelet.

4. The method according to claim 3, characterized in that, When the wavelet basis function is the concave-convex wavelet, the ratio between the preset center frequency and shape factor before performing the continuous wavelet transform is located in the interval [0.1, 0.35].

5. The method according to claim 1, characterized in that, The compression and rearrangement of wavelet coefficients converted to the time-frequency domain includes: The wavelet coefficients are rearranged in the frequency direction, and the gridded aeromagnetic data is reconstructed by inverse transformation.

6. An automatic aeromagnetic anomaly delineation device, characterized in that, include: The module includes a continuous wavelet transform module, a frequency domain conversion module, a synchronous compression module, a slicing module, and an identification and delineation module. The continuous wavelet transform module is used to acquire gridded aeromagnetic data, perform continuous wavelet transform on any channel of the gridded aeromagnetic data, and obtain the wavelet coefficients corresponding to the data. The frequency domain conversion module is used to calculate the instantaneous frequency corresponding to the data based on the wavelet coefficients corresponding to the data, and convert the wavelet coefficients corresponding to the data from the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data. The synchronous squeezing module is used to squeeze and rearrange the wavelet coefficients converted to the time frequency domain to obtain the two-dimensional synchronous squeezing transformation value corresponding to the data. The slicing module is used to store the two-dimensional synchronous compression transformation value corresponding to each data in the gridded aeromagnetic data into a three-dimensional matrix, and slice the three-dimensional matrix along the frequency direction to obtain aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data. The identification and delineation module is used to identify and delineate aeromagnetic anomalies in the gridded aeromagnetic data based on aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, including: Determine whether the lowest frequency slice in the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data corresponds to the aeromagnetic anomaly distribution; If so, output the frequency slice corresponding to the aeromagnetic anomaly distribution, and based on the concentration of high-energy clusters in the frequency slice, identify and delineate the aeromagnetic anomaly region where a magnetic body exists.

7. An electronic device comprising a processor and a memory, the memory storing a computer program, characterized in that, The processor executes the computer program stored in the memory to implement the steps in the automatic aeromagnetic anomaly delineation method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the automatic delineation method for aeromagnetic anomalies as described in any one of claims 1 to 5.

9. A computer program product comprising a computer program that, when executed, can implement the steps of the automatic aeromagnetic anomaly delineation method as described in any one of claims 1 to 5.

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