Aeromagnetic anomaly automatic delineation method and device and electronic equipment

Abstract

The invention provides an aeromagnetic anomaly automatic delineation method and device and electronic equipment, and the method comprises the steps: carrying out the continuous wavelet transformation of any data in grid aeromagnetic data, and obtaining a wavelet coefficient; calculating an instantaneous frequency and converting the wavelet coefficient from a time scale domain to a time frequency domain; carrying out extrusion rearrangement on the wavelet coefficient to obtain a two-dimensional synchronous extrusion transformation quantity value; and storing the two-dimensional synchronous extrusion transformation quantity value of each channel of data into a three-dimensional matrix and slicing to obtain aeromagnetic data information under different frequency distributions, thereby realizing aeromagnetic anomaly identification delineation of the gridding aeromagnetic data. According to the aeromagnetic anomaly automatic delineation method and device and the electronic equipment provided by the embodiment of the invention, the characteristics of the aeromagnetic data for reflecting the magnetic anomaly of the underground geologic body are fully utilized, and the aeromagnetic data are converted from a space-amplitude domain to a space-frequency domain by using a time-frequency analysis method, so that the extraction of the aeromagnetic anomaly characteristics is effectively completed, and the accuracy of the aeromagnetic anomaly detection is improved. And the problems of insufficient resolution and fuzzy boundary of the original data are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic interpretation of aeromagnetic data, and in particular to an aeromagnetic anomaly automatic delineation method, device, electronic equipment and computer-readable storage medium. Background Art

[0002] Since the 21st century, as my country's demand for mineral resources has continued to increase, the mineral resources that are easy to discover and utilize in shallow areas have become increasingly scarce. Finding blind mines in deep areas is one of the important research topics in current exploration work. Since the magnetic properties of ore bodies are usually significantly different from those of the surrounding rock bodies, magnetic exploration has been widely used in the search for mineral resources, among which high-precision aerial magnetic exploration is an effective method. However, geological conditions in nature are often complex, with irregular shapes and varying physical parameters of various geological bodies. In addition, aeromagnetic exploration is also interfered by various factors during the data acquisition process, making the measurement results complex and difficult to analyze. How to quickly and automatically identify and delineate aeromagnetic anomalies, and how to effectively deal with the influence of various interferences during the anomaly processing process, is an urgent problem to be solved in current aeromagnetic exploration. Summary of the invention

[0003] In order to solve the existing technical problems, the embodiments of the present invention provide a method, a device, an electronic device and a computer-readable storage medium for automatically delineating aeromagnetic anomalies.

[0004] In a first aspect, an embodiment of the present invention provides a method for automatically delineating aeromagnetic anomalies, comprising: acquiring gridded aeromagnetic data, performing continuous wavelet transform on any data in the gridded aeromagnetic data, and obtaining wavelet coefficients corresponding to the data; calculating the instantaneous frequency corresponding to the data according to the wavelet coefficients corresponding to the data, and converting 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; performing extrusion and rearrangement on the wavelet coefficients converted to the time frequency domain to obtain two-dimensional synchronous extrusion transformation values ​​corresponding to the data; storing the two-dimensional synchronous extrusion transformation values ​​corresponding to each data in the gridded aeromagnetic data into a three-dimensional matrix, slicing the three-dimensional matrix along the frequency direction, and obtaining 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, realizing identification and delineation of aeromagnetic anomalies in the gridded aeromagnetic data.

[0005] Optionally, obtaining gridded aeromagnetic data includes: obtaining raw aeromagnetic data in the work area to be identified, performing polarization calculation on the raw aeromagnetic data to obtain aeromagnetic polarization data; and gridding the aeromagnetic polarization data to obtain the gridded aeromagnetic data.

[0006] Optionally, the continuous wavelet transform is a wavelet basis function of finite length that decays; the wavelet basis function includes: an impulse wavelet, a Gaussian wavelet or a concave-convex wavelet.

[0007] Optionally, when the wavelet basis function is the concave-convex wavelet, a ratio between a center frequency and a shape factor preset before performing the continuous wavelet transform is in the interval [0.1, 0.35].

[0008] Optionally, the wavelet coefficients converted to the time-frequency domain are squeezed and rearranged to obtain a two-dimensional synchronous squeeze transformation value corresponding to the data, including: rearranging the wavelet coefficients in the frequency direction, and reconstructing the gridded aeromagnetic data through inverse transformation.

[0009] Optionally, based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, aeromagnetic anomaly identification and delineation of the gridded aeromagnetic data is achieved, including: determining 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, outputting the frequency slice corresponding to the aeromagnetic anomaly distribution, and based on the concentration of high-energy clusters in the frequency slices, identifying and delineating aeromagnetic anomaly areas where magnetic bodies exist.

[0010] In a second aspect, an embodiment of the present invention further provides an automatic delineation device for aeromagnetic anomalies, comprising: a continuous wavelet transform module, a frequency domain conversion module, a synchronous extrusion module, a slicing module and an identification and delineation module; the continuous wavelet transform module is used to obtain gridded aeromagnetic data, and perform a continuous wavelet transform on any data in the gridded aeromagnetic data to obtain the wavelet coefficients corresponding to the data; the frequency domain conversion module is used to calculate the 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 the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data; The synchronous extrusion module is used to extrude and rearrange the wavelet coefficients converted to the time-frequency domain to obtain the two-dimensional synchronous extrusion transformation value corresponding to the data; the slicing module is used to store the two-dimensional synchronous extrusion transformation value corresponding to each data in the gridded aeromagnetic data into a three-dimensional matrix, slice the three-dimensional matrix along the frequency direction, and obtain the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data; the identification and delineation module is used to realize the identification and delineation of aeromagnetic anomalies in the gridded aeromagnetic data based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data.

[0011] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program, and is characterized in that the processor executes the computer program stored in the memory, and when the computer program is executed by the processor, the method for automatic delineation of aeromagnetic anomalies described in the first aspect above is implemented.

[0012] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for automatically delineating aeromagnetic anomalies described in the first aspect above is implemented.

[0013] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed, can implement the method for automatic delineation of aeromagnetic anomalies described in the first aspect or any possible design method of the first aspect.

[0014] The method, device, electronic device and computer-readable storage medium for automatically delineating aeromagnetic anomalies provided by the embodiments of the present invention make full use of the characteristics of aeromagnetic data reflecting magnetic anomalies of underground geological bodies, and use time-frequency analysis methods to convert aeromagnetic data from a space-amplitude domain to a space-frequency domain. In this process, the aeromagnetic anomaly characteristics are effectively extracted, and the problems of insufficient resolution and blurred boundaries of aeromagnetic raw data are solved. At the same time, the method has good stability and anti-interference ability, and the prediction results can be provided to geological interpretation personnel as an objective basis for the identification and delineation of aeromagnetic anomalies. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

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

[0017] Figure 2 The figure shows a schematic diagram of aeromagnetic pole data obtained after polarization in the method for automatically delineating aeromagnetic anomalies provided by an embodiment of the present invention;

[0018] Figure 3 The method for automatically delineating aeromagnetic anomalies provided by an embodiment of the present invention is shown, and the aeromagnetic anomaly delineation map is finally output;

[0019] Figure 4 A detailed schematic diagram of a process for automatically delineating aeromagnetic anomalies provided by an embodiment of the present invention is shown;

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

[0021] Figure 6 A schematic structural diagram of an electronic device for executing an automatic aeromagnetic anomaly delineation method provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0022] The embodiments of the present invention are described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0023] It can be understood that the aeromagnetic anomaly mentioned in the embodiment of the present invention is the superposition of potential fields from geological bodies of different depths and scales. The high-frequency signal mainly reflects the high-frequency magnetic anomaly information generated by shallow magnetic bodies, and the low-frequency signal mainly reflects the low-frequency magnetic anomaly information generated by deep magnetic bodies. In order to better achieve the important exploration goal of deep blind ore exploration, the embodiment of the present invention proposes an automatic delineation method for aeromagnetic anomalies that can better process low-frequency signals.

[0024] Figure 1 FIG. 1 is a flow chart showing a method for automatically delineating aeromagnetic anomalies provided by an embodiment of the present invention. Figure 1 As shown, the method includes the following steps 101-105.

[0025] Step 101: Acquire gridded aeromagnetic data, perform continuous wavelet transform on any data in the gridded aeromagnetic data, and obtain wavelet coefficients corresponding to the data.

[0026] Among them, aeromagnetic data refers to the geomagnetic field data obtained through aerial magnetic measurement (abbreviated as aeromagnetic measurement). The embodiment of the present invention 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, gridded aeromagnetic data, as the name implies, is a matrix form of data formed by a combination of multiple rows and columns of data. The embodiment of the present invention can perform continuous wavelet transform on any data (such as any row or any column) in the gridded aeromagnetic data, so as to obtain the wavelet coefficients corresponding to the data (such as the row of data or the column of data).

[0027] Specifically, the formula of continuous wavelet transform can be shown in the following formula (1):

[0028]

[0029] Among them, W x (a,b) are wavelet coefficients, a is the scale factor, b is the translation factor, and ψ(t) is the wavelet basis function.

[0030] Step 102: Calculate the instantaneous frequency corresponding to the data according to the wavelet coefficient corresponding to the data, and convert 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.

[0031] Specifically, the instantaneous frequency corresponding to any data obtained in step 101 is calculated according to the wavelet coefficient corresponding to the data. Based on the above formula (1), for any (a, b) value, if the wavelet coefficient W x (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 taking the derivative of the wavelet coefficient phase in the time domain, i.e., equation (2). Furthermore, based on the instantaneous frequency obtained from equation (2), (b, a) → (b, ω) can be established. x (a,b)) can be used to map the wavelet coefficient ω x (a, b) is transformed from the time scale domain to the time frequency domain (it should be noted that in aeromagnetics, a certain spatial direction is usually regarded as the time direction), that is, ω x (a,b) converted to W x (ω x (a,b),b).

[0034] Step 103: Squeeze and rearrange the wavelet coefficients converted to the time-frequency domain to obtain a two-dimensional synchronous squeezing transformation value corresponding to the data.

[0035] On the basis of the above step 102, the time-frequency spectrum distribution of the instantaneous frequency (that is, the center frequency) is obtained, and in the interval near any center frequency ωl The wavelet coefficients are synchronously compressed and rearranged to obtain the two-dimensional synchronous compression transformation value T corresponding to the data. x (ω,b). As shown in the following formula (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 x (ω l ,b) is unstable. Therefore, it is necessary to consider |W x (a,b)|, thus using the threshold to limit the range of A(b). That is, A(b)={a; W x (a, b)≠0}, Δw=w l -w l-1 It can be understood that this step 103 is to perform the wavelet coefficient W in the frequency direction, that is, the scale direction. x (ωx (a, b), b) are compressed and reorganized to focus their energy, thereby improving the blurring phenomenon in the scale direction.

[0038] Step 104: storing the two-dimensional synchronous extrusion transformation value corresponding to each data in the gridded aeromagnetic data into a three-dimensional matrix, slicing the three-dimensional matrix along the frequency direction, and obtaining 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 in the gridded aeromagnetic data is processed as above to obtain the two-dimensional synchronous extrusion transformation value corresponding to each data. Further, the two-dimensional synchronous extrusion transformation value corresponding to each data is stored in a three-dimensional matrix, and then the three-dimensional matrix is ​​sliced ​​and extracted along the frequency direction, so as to obtain the aeromagnetic data information (such as slices) of the gridded aeromagnetic data under different frequency distributions.

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

[0041] Based on the aeromagnetic data information of the gridded aeromagnetic data obtained by slicing in step 104 under different frequency distributions, the aeromagnetic anomaly area is automatically identified and delineated 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 method for automatically delineating aeromagnetic anomalies provided by the embodiment of the present invention makes full use of the characteristics of aeromagnetic data reflecting magnetic anomalies of underground geological bodies, and uses a time-frequency analysis method to convert aeromagnetic data from a space-amplitude domain to a space-frequency domain. In this process, the aeromagnetic anomaly characteristics are effectively extracted, and the problems of insufficient resolution and blurred boundaries of the original aeromagnetic data are solved. At the same time, the method has good stability and anti-interference ability, and the prediction results can be provided to geological interpretation personnel as an objective basis for the identification and delineation of aeromagnetic anomalies.

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

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

[0045] The work area to be identified mentioned in the embodiment of the present invention is a geographical area that needs to be delineated for aeromagnetic anomaly identification. The aeromagnetic raw data of the work area to be identified is obtained by using an aeromagnetic instrument. For example, the aeromagnetic instrument and its supporting auxiliary equipment can be loaded on an aircraft, and the geomagnetic field strength or gradient is measured over the measurement area according to a pre-set measurement line and height to obtain the aeromagnetic raw data. Furthermore, it is necessary to perform polarization calculation on the aeromagnetic raw data to obtain aeromagnetic polarization data, such as Figure 2 As shown, Figure 2 A schematic diagram of the aeromagnetic pole data obtained after polarization is shown.

[0046] It should be noted that the process of pole calculation is a common technical means in this field and will not be described in detail here.

[0047] Step A2: gridding the aeromagnetic polar data to obtain gridded aeromagnetic data, i.e., converting the data into a text-readable grd format (grid format). It should be noted that the gridding process is a common technical means in the art and will not be described in detail here.

[0048] Optionally, the "continuous wavelet transform" in the above step 101 is a wavelet basis function of finite length that decays. That is to say, a wavelet basis function of finite length that decays 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, 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 embodiment 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 referred to formula (4).

[0049]

[0050] in, Representation interval The index function within; μ represents the center frequency; σ represents the shape factor, which 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, a ratio μ / σ between a preset center frequency μ and a shape factor σ before performing continuous wavelet transform is in an interval of [0.1, 0.35].

[0052] The reason why the embodiment of the present invention determines the range of the ratio μ / σ between the center frequency μ and the shape factor σ to be in the interval [0.1, 0.35] is that when the value of μ / σ is greater than 0.35, it will lead to insufficient spatial resolution, making it impossible to accurately define the abnormal range; when the value of μ / σ is less than 0.1, it will not only lead to insufficient frequency resolution and the inability to determine the relative burial depth of the abnormal body, but also severely suppress the wavelet coefficients and fail to obtain an effective time-frequency spectrum diagram. Therefore, the ratio μ / σ between the center frequency μ and the shape factor σ is selected in the interval [0.1, 0.35], and the processing effect is better. Figure 2 As shown, Figure 2 A schematic diagram is shown in which the data corresponding to the aeromagnetic pole data is gridded and then subjected to synchronous extrusion wavelet transform, the wavelet basis used being a concave-convex wavelet with a center frequency of 1 and a shape factor of 1.5π.

[0053] Optionally, the above step 103 of “squeezing 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] In the process of synchronous extrusion, since the embodiment of the present invention rearranges the wavelet coefficients in the frequency direction, the algorithm is reversible, so the gridded aeromagnetic data obtained by initially gridding the aeromagnetic pole data can be reconstructed by inverse transformation, and its expression can be shown in formula (5).

[0055]

[0056] Among them, Re is the operation of taking the real part of a complex number, C ψ is the regularization constant, C ψ The expression of can be seen in formula (6).

[0057]

[0058] Optionally, in the above step 105, "based on the aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data, realizing 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 an embodiment of the present invention, after processing the 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 the known aeromagnetic anomaly distribution. By determining whether this condition is met, the aeromagnetic data information (i.e., slices) with aeromagnetic anomalies can be screened out.

[0061] Step B2: If yes, then the frequency slice corresponding to the aeromagnetic anomaly distribution is output, and based on the concentration of high energy clusters in the frequency slice, the aeromagnetic anomaly area where magnetic bodies exist is identified and delineated.

[0062] If the lowest frequency slice can correspond to the known aeromagnetic anomaly distribution, the aeromagnetic anomaly data information (i.e., slice) at this frequency will be output. According to the low energy distribution in the low frequency slice, the boundary of the aeromagnetic anomaly can be accurately identified, thereby realizing the automatic delineation of the boundary of the aeromagnetic anomaly. Based on the distribution of high energy clusters in the slice, the area where the high energy clusters are concentrated can be automatically identified and delineated, and it can be determined that there are magnetic bodies in this area.

[0063] like Figure 3 As shown, Figure 3 The final output of the aeromagnetic anomaly delineation map is shown. The aeromagnetic anomaly identification and delineation method based on synchronous extrusion transformation can accurately identify the boundary of the aeromagnetic anomaly, thereby realizing the automatic delineation of the aeromagnetic anomaly boundary. At the same time, it can also identify the high energy clusters in the low frequency slices (such as Figure 3 The concentration of the particles (as shown by the circled mass in the middle) can be used to determine whether there are magnetic bodies in the deep part.

[0064] Please refer to the following Figure 4 The process shown in the figure provides a detailed understanding of the process of the automatic delineation method of aeromagnetic anomalies, which will not be repeated here.

[0065] The above describes in detail the method for automatic delineation of aeromagnetic anomalies provided by an embodiment of the present invention. The method can also be implemented by a corresponding device. The following describes in detail the device for automatic delineation of aeromagnetic anomalies provided by an embodiment of the present invention.

[0066] Figure 5 FIG. 2 shows a schematic diagram of the structure of an aeromagnetic anomaly automatic delineation device provided by an embodiment of the present invention. Figure 5 As shown, the aeromagnetic anomaly automatic delineation device comprises a processor, which comprises a continuous wavelet transform module 51 , a frequency domain conversion module 52 , a synchronous extrusion module 53 , a slicing module 54 and an identification and delineation module 55 .

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

[0068] The frequency domain conversion module 52 is used to calculate the 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 the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data.

[0069] The synchronous extrusion module 53 is used to perform extrusion and rearrangement on the wavelet coefficients converted to the time-frequency domain to obtain a two-dimensional synchronous extrusion transformation value corresponding to the data.

[0070] The slicing module 54 is used to store the two-dimensional synchronous extrusion 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 the 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 of 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 gridding unit.

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

[0074] The gridding unit is used to grid the aeromagnetic polar data to obtain the gridded aeromagnetic data.

[0075] Optionally, the continuous wavelet transform is a wavelet basis function of finite length that decays; the wavelet basis function includes: an impulse wavelet, a Gaussian wavelet or a concave-convex wavelet.

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

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

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

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

[0080] The judging unit is used to judge 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, and identify and delineate the aeromagnetic anomaly area where magnetic bodies exist based on the concentration of high-energy clusters in the frequency slice.

[0082] The device provided in the embodiment of the present invention makes full use of the characteristics of aeromagnetic data reflecting the magnetic anomaly of underground geological bodies, and uses a time-frequency analysis device to convert the aeromagnetic data from the space-amplitude domain to the space-frequency domain. In this process, the aeromagnetic anomaly characteristics are effectively extracted, and the problems of insufficient resolution and blurred boundaries of the original aeromagnetic data are solved. At the same time, the device has good stability and anti-interference ability, and the prediction results can be provided to geological interpretation personnel as an objective basis for the identification and delineation of aeromagnetic anomalies.

[0083] It should be noted that the automatic delineation device for aeromagnetic anomalies provided in the above embodiment only uses the division of the above functional modules as an example to illustrate the corresponding functions. 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 delineation device for aeromagnetic anomalies provided in the above embodiment and the automatic delineation method for aeromagnetic anomalies embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0084] According to one aspect of the present application, an embodiment of the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program comprising a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part. When the computer program is executed by a processor, the method for automatically delineating aeromagnetic anomalies provided in an embodiment of the present application is executed.

[0085] In addition, an embodiment of the present invention further 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 respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned aeromagnetic anomaly automatic delineation method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described 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 an embodiment of the present invention, the electronic device further includes: a computer program stored in the memory 1150 and executable on the processor 1120, and when the computer program is executed by the processor 1120, each process of the above-mentioned aeromagnetic anomaly automatic delineation method embodiment is implemented.

[0088] The transceiver 1130 is configured to receive and send data under the control of the processor 1120 .

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

[0090] Bus 1110 represents one or more of any of several types of bus structures, including a memory bus and memory controller, a peripheral bus, an Accelerate Graphical Port (AGP), a processor, or a local bus using any of a variety of bus architectures. By way of example and not limitation, such architectures include: Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA), Peripheral Component Interconnect (PCI) bus.

[0091] The processor 1120 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment may be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processors include: a general-purpose processor, a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a complex programmable logic device (CPLD), a programmable logic array (PLA), a microcontroller unit (MCU) or other programmable logic devices, discrete gates, transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention may be implemented or executed. For example, the processor may be a single-core processor or a multi-core processor, and the processor may be integrated into a single chip or located in multiple different chips.

[0092] Processor 1120 can be a microprocessor or any conventional processor. The method steps disclosed in conjunction with the embodiments of the present invention can be directly executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a readable storage medium known in the art, such as a random access memory (RAM), a flash memory (FlashMemory), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a register, etc. The readable storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware.

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

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

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

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

[0097] Volatile memory includes: Random Access Memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as: Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Synchronous Link Dynamic Random Access Memory (SLDRAM) and Direct Rambus RAM (DRRAM). The memory 1150 of the electronic device described in the embodiment of the present invention includes but is not limited to the above and any other suitable types of memory.

[0098] In the embodiment of the present invention, the memory 1150 stores the following elements of the operating system 1151 and the application program 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, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 1152 includes various applications, such as a media player (Media Player) and a browser (Browser), which are used to implement various application services. The program for implementing the method of the embodiment of the present invention may be included in the application 1152. The application 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, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned aeromagnetic anomaly automatic delineation method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0101] Computer readable storage media include: permanent and non-permanent, removable and non-removable media, which are tangible devices that can retain and store instructions for use by instruction execution devices. Computer readable storage media include: electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, and any suitable combination of the above. 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 technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassette storage, magnetic tape disk storage or other magnetic storage devices, memory sticks, mechanical encoding devices (such as punched cards or raised structures in grooves with instructions recorded thereon) or any other non-transmission medium that can be used to store information that can be accessed 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 (such as light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

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

[0103] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one location or distributed on multiple network units. Some or all of the units may be selected according to actual needs to solve the problem to be solved by the embodiments of the present invention.

[0104] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0105] If the integrated unit is implemented in the form of 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 embodiment of the present invention is essentially or part of the contribution to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (including: a personal computer, a server, a data center or other network device) to perform all or part of the steps of the method described in each embodiment of the present invention. The above-mentioned storage medium includes various media that can store program codes as listed above.

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

[0107] The above-mentioned computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM), flash memories, optical fibers, compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices or any combination of the above. In an embodiment of the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device, or device.

[0108] The computer program code contained in the above-mentioned computer-readable storage medium can be transmitted using any appropriate medium, including: wireless, wire, optical cable, radio frequency (RF) or any suitable combination thereof.

[0109] The computer program code for performing the operation of the embodiments of the present invention can be written in assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or in one or more programming languages ​​or a combination thereof, wherein the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as C language or a similar programming language. The computer program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on a remote computer, and completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer or to an external computer through 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, devices, and electronic devices through flowcharts and / or block diagrams.

[0111] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the 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 device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in 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 work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the 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, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0114] The above is only a specific implementation of the embodiment of the present invention, but the protection scope of the embodiment of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the embodiment of the present invention, which should be included in the protection scope of the embodiment of the present invention. Therefore, the protection scope of the embodiment of the present invention should be based on the protection scope of the claims.

Claims

1. A method for automatically delineating aeromagnetic anomalies, characterized in that: include: Acquire gridded aeromagnetic data, and perform continuous wavelet transform on any data in the gridded aeromagnetic data to obtain wavelet coefficients corresponding to the data; Calculating the instantaneous frequency corresponding to the data according to the wavelet coefficients corresponding to the data, and converting 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; Squeeze and rearrange the wavelet coefficients converted to the time-frequency domain to obtain a two-dimensional synchronous squeezing transformation value corresponding to the data; The two-dimensional synchronous extrusion transformation value corresponding to each data in the gridded aeromagnetic data is stored in a three-dimensional matrix, and the three-dimensional matrix is ​​sliced ​​along the frequency direction to obtain the 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 achieved.

2. The method according to claim 1, characterized in that The obtaining of gridded aeromagnetic data comprises: Acquire the original aeromagnetic data in the work area to be identified, perform polarization calculation on the original aeromagnetic data, and obtain aeromagnetic polarization data; The aeromagnetic polar data are gridded to obtain the gridded aeromagnetic data.

3. The method according to claim 1, characterized in that: The continuous wavelet transform is a wavelet basis function of finite length that will decay; the wavelet basis function includes: an impulse wavelet, a Gaussian wavelet or a 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 center frequency and the shape factor preset before performing the continuous wavelet transform is in the interval [0.1, 0.35].

5. The method according to claim 1, characterized in that The squeezing and rearranging of the wavelet coefficients converted to the time-frequency domain comprises: The wavelet coefficients are rearranged in the frequency direction, and the gridded aeromagnetic data are reconstructed through inverse transformation.

6. The method according to claim 1, characterized in that The method of realizing identification and delineation of aeromagnetic anomalies of the gridded aeromagnetic data based on aeromagnetic data information of different frequency distributions corresponding to the gridded aeromagnetic data comprises: Determining 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, the frequency slice corresponding to the aeromagnetic anomaly distribution is output, and based on the concentration of high-energy clusters in the frequency slice, the aeromagnetic anomaly area where magnetic bodies exist is identified and delineated.

7. An automatic aeromagnetic anomaly delineation device, characterized in that: include: Continuous wavelet transform module, frequency domain conversion module, synchronous extrusion module, slicing module and identification and delineation module; The continuous wavelet transform module is used to obtain gridded aeromagnetic data, perform continuous wavelet transform on any data in the gridded aeromagnetic data, and obtain wavelet coefficients corresponding to the data; The frequency domain conversion module is used to calculate the 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 the time scale domain to the time frequency domain based on the instantaneous frequency corresponding to the data; The synchronous extrusion module is used to perform extrusion and rearrangement on the wavelet coefficients converted to the time-frequency domain to obtain a two-dimensional synchronous extrusion transformation value corresponding to the data; The slicing module is used to store the two-dimensional synchronous extrusion 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 the 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 of the gridded aeromagnetic data based on aeromagnetic data information under different frequency distributions corresponding to the gridded aeromagnetic data.

8. An electronic device comprising a processor and a memory, wherein the memory stores a computer program, characterized in that: The processor executes the computer program stored in the memory to implement the steps in the method for automatic delineation of aeromagnetic anomalies according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method for automatic delineation of aeromagnetic anomalies according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, which, when executed, can implement the steps of the method for automatic delineation of aeromagnetic anomalies as claimed in any one of claims 1 to 6.

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