CN120447079A - Method for acquiring accurate aviation magnetic measurement data based on total horizontal gradient method - Google Patents
Method for acquiring accurate aviation magnetic measurement data based on total horizontal gradient methodInfo
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Abstract
The invention discloses a method for acquiring accurate aeromagnetic measurement data based on a total horizontal gradient method, which comprises the steps of acquiring aeromagnetic measurement data T actually measured in a test area, and calculating horizontal gradient of the aeromagnetic measurement data T in the x directionAnd the aeromagnetic data T is horizontally graded in the y directionHorizontal gradient in x-direction according to the aeromagnetic data TThe aeromagnetic data T has a horizontal gradient in the y directionThe method comprises the steps of calculating an original total horizontal gradient H xy, calculating a weak signal enhancement function B according to the original total horizontal gradient H xy, and obtaining accurate aviation magnetic measurement data according to the original total horizontal gradient H xy and the weak signal enhancement function B. The method for acquiring accurate aeromagnetic measurement data based on the total horizontal gradient method can improve the boundary resolution of deeper geologic bodies, thereby improving the quality of aeromagnetic data processing and conversion and the geologic body boundary identification effect.
Description
Technical Field
The invention relates to the technical field of aviation magnetic measurement, in particular to a method for acquiring accurate aviation magnetic measurement data based on a total horizontal gradient method.
Background
The aeromagnetometer (such as an optical pump type, a nuclear rotation type and a fluxgate type) system is installed in an aircraft, and magnetic or magnetic-related ore bodies are searched by observing geomagnetic field parameters (such as total geomagnetic field intensity T or total magnetic field abnormality delta T or gradients thereof) so as to know geological structures, perform magnetic mapping, solve the problems of urban and engineering stability, archaeology and the like.
The aviation magnetic force measurement data are comprehensive reflection of magnetic field information of magnetic bodies with different depths, different forms and different scales on an observation surface. However, due to errors of the measured data or superposition of magnetic fields, the measured data are difficult to distinguish, and difficulty is brought to geological interpretation work.
At present, the resolution of aeromagnetic anomalies can be improved by a total horizontal gradient method NSTD.
The total horizontal gradient method has the advantage that the influence of magnetization direction and magnetic abnormal component is less than the influence of vertical vector processing result when detecting the boundary of aeromagnetic data geologic body. But this approach has the disadvantage that linear structures for small scales are easily masked by larger structures and cannot be identified. In other words, the total horizontal gradient method can only give the boundary of shallower geologic bodies, but the boundary resolution of deeper geologic bodies is lower, and false aeromagnetic data geologic body boundaries are easy to generate, so that the practical application effect is affected.
Therefore, in order to improve the quality of aeromagnetic data processing and conversion and the identification effect of geologic body boundary, it is necessary to research and improve the technology of the total horizontal gradient method in actually detecting the aeromagnetic data geologic body boundary.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art.
Disclosure of Invention
In order to solve the above problems, an object of the embodiments of the present invention is to provide a method for obtaining accurate aeromagnetic data based on a total horizontal gradient method, so as to improve the boundary resolution of deeper geologic bodies, thereby improving the quality of aeromagnetic data processing and conversion and the geologic body boundary identification effect.
The invention provides a method for acquiring accurate aeromagnetic measurement data based on a total horizontal gradient method, which comprises the steps of acquiring aeromagnetic measurement data T actually measured in a test area, and calculating horizontal gradient of the aeromagnetic measurement data T in the x directionAnd the aeromagnetic data T is horizontally graded in the y directionHorizontal gradient in x-direction according to the aeromagnetic data TThe aeromagnetic data T has a horizontal gradient in the y directionThe method comprises the steps of calculating an original total horizontal gradient H xy, calculating a weak signal enhancement function B according to the original total horizontal gradient H xy, and obtaining accurate aviation magnetic measurement data according to the original total horizontal gradient H xy and the weak signal enhancement function B.
In one embodiment, after acquiring the aero-magnetic data measured in the test area, the T calculates the horizontal gradient of the aero-magnetic data T in the x-directionAnd the aeromagnetic data T is horizontally graded in the y directionThe method further comprises the step of preprocessing the acquired aeromagnetic measurement data T actually measured in the test area.
In one embodiment, the preprocessing includes one or more of coordinate conversion, normal field correction, daily correction, hysteresis correction, and magnetic field level adjustment.
In one embodiment, the aeromagnetic data T is calculated from the aeromagnetic data T as a horizontal gradient in the x-directionAnd the aeromagnetic data T is horizontally graded in the y directionThe method comprises the steps of calling geologic body characteristic distribution data of a test area in a networking mode, evaluating the test area according to the geologic body characteristic distribution data, decomposing the test area according to the evaluation result in a level mode to obtain M level scale areas, wherein the M level scale areas have M level complexity mean value identifications, referencing aviation magnetic measurement data T after decomposition pretreatment of the M level scale areas to obtain M level magnetic measurement data T, and determining M horizontal gradients of the M level magnetic measurement data T in the x direction according to the corresponding relation between two-dimensional Fourier transformation and Hilbert transformation in a frequency domainAnd M horizontal gradients in the y-directionM horizontal gradients in the x-direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the x-directionM horizontal gradients in the y direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the Y direction
In one embodiment, the method comprises the steps of evaluating the test area according to the geologic body characteristic distribution data, decomposing the test area according to the evaluation result in a hierarchical mode to obtain M hierarchical scale areas, wherein the step of dividing the test area into a plurality of grid areas based on a preset grid scale and then dividing the geologic body characteristic distribution data by the plurality of grid areas to obtain a plurality of grid geologic body characteristic data, the step of evaluating the geographic complexity according to the plurality of grid geologic body characteristic data and outputting a plurality of area geographic complexity of the plurality of grid areas, the step of presetting a complexity threshold, and the step of mapping and combining the plurality of grid areas for multiple times according to whether adjacent difference values of the geographic complexity of the plurality of areas meet the complexity threshold to obtain the M hierarchical scale areas.
In one embodiment, the obtaining accurate aeromagnetic data according to the original total horizontal gradient H xy and the weak signal enhancement function B includes:
obtaining accurate airborne magnetic measurement data according to the following formula, wherein the formula comprises:
wherein Max (H xy) represents the maximum value of the total horizontal gradient H Xy, T is the actually measured aeromagnetic data, x and y are two directions of space coordinates, delta is an adjusting parameter, and the range of the delta is 0-1.
In one embodiment, the method further comprises the step of measuring M according to a horizontal gradient in the x-directionCalculating and outputting a first horizontal mean value and a first horizontal variance, and arranging M horizontal gradients in the x direction in ascending orderTo extract the first horizontal extremum, and so on, performing a horizontal gradient M in the y-directionAfter the average burial depth of the test area is obtained interactively, inputting the average burial depth, the first horizontal mean value, the first horizontal variance, the first horizontal extremum, the second horizontal mean value, the second horizontal variance and the second horizontal extremum into a pre-built adjusting parameter disturbance model for disturbance analysis, and outputting real-time adjusting parameters.
In one embodiment, the method further comprises the steps of calling a plurality of groups of sample disturbance variables and a plurality of sample adjustment parameters in a networking mode, wherein each group of sample disturbance variables comprises a sample burial depth, a first sample mean value, a first sample variance, a first sample extreme value, a second sample mean value, a second sample variance and a second sample extreme value, storing the plurality of groups of sample disturbance variables and the plurality of sample adjustment parameters based on knowledge graph association to complete construction of an adjustment parameter disturbance model, inputting the average burial depth, the first horizontal mean value, the first horizontal variance, the first horizontal extreme value, the second horizontal mean value, the second horizontal variance and the second horizontal extreme value into the adjustment parameter disturbance model, carrying out data similarity evaluation on the plurality of groups of sample disturbance variables based on Euclidean distance comparison, and extracting sample adjustment parameters corresponding to the similarity extreme values as real-time adjustment parameters.
The invention also provides a device for acquiring accurate aeromagnetic measurement data based on the total horizontal gradient method, which comprises an acquisition module, a gradient calculation module and a control module, wherein the acquisition module is used for acquiring the aeromagnetic measurement data T actually measured in a test area, and the gradient calculation module is used for calculating the horizontal gradient of the aeromagnetic measurement data T in the x directionAnd the aeromagnetic data T is horizontally graded in the y directionThe original total horizontal gradient calculation module is used for horizontally gradient in the x direction according to the aeromagnetic measurement data TThe aeromagnetic data T has a horizontal gradient in the y directionThe system comprises an original total horizontal gradient H Xy, a weak signal enhancement function calculation module, an accurate aviation magnetic measurement data acquisition module and an accurate aviation magnetic measurement data acquisition module, wherein the weak signal enhancement function calculation module is used for calculating a weak signal enhancement function B according to the original total horizontal gradient H x y, and the accurate aviation magnetic measurement data acquisition module is used for acquiring accurate aviation magnetic measurement data according to the original total horizontal gradient H xy and the weak signal enhancement function B.
To achieve the above object, the present invention further provides a storage medium storing computer-executable instructions for performing the method for acquiring accurate airborne magnetic data based on the total horizontal gradient method according to any one of the above.
Compared with the prior art, the method, the device and the storage medium for acquiring the accurate aeromagnetic measurement data based on the total horizontal gradient method can better detect the boundary of the aeromagnetic data target geologic body, enable the boundary identification result to be more convergent, solve the problem of low resolution of the traditional total horizontal gradient method, and further improve the quality of aeromagnetic data processing and conversion and the geologic body boundary identification effect.
In addition, the boundary interference of the geologic body which generates false aeromagnetic data is eliminated, the signal to noise ratio is enhanced, the boundary position enhancement and extraction capacity of the geologic body with different burial depths are improved, and the method has higher resolution and precision.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for acquiring accurate airborne magnetic survey data based on a total horizontal gradient method provided by an embodiment of the invention;
fig. 2 shows a schematic structural diagram of an apparatus for acquiring accurate airborne magnetic measurement data based on a total horizontal gradient method according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention is, therefore, to be taken in conjunction with the accompanying drawings, and it is to be understood that the scope of the invention is not limited to the specific embodiments.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Throughout the specification and claims, unless explicitly stated otherwise, the term "comprise" or variations thereof such as "comprises" or "comprising", etc. will be understood to include the stated element or component without excluding other elements or components.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
The flow chart of the method for acquiring accurate aeromagnetic measurement data based on the total horizontal gradient method provided by the embodiment of the invention, referring to fig. 1, comprises the steps of S1-S5.
And step 1, acquiring aviation magnetic measurement data T actually measured in a test area.
The method comprises the steps of carrying out geologic body characteristic analysis, such as burial depth, scale, construction complexity and the like, on a test area to divide the topography complexity of the test area to obtain topography complex distribution, carrying out flight trajectory optimization based on the topography complexity distribution to generate a dynamic flight trajectory, and further collecting original magnetic measurement data based on the dynamic flight trajectory. The space and the flying height of the flying curve change along with the difference of the terrain complexity, and the aviation magnetic measurement data T, namely the aviation magnetic abnormal field, is an additional magnetic field generated by the ferromagnetic geological body in the crust under the action of the geomagnetic field.
In one implementation, the method further comprises preprocessing the obtained aero-magnetic measurement data T measured in the test area after the step S1 and before the step S2 to obtain the preprocessed aero-magnetic measurement data T measured in the test area. The preprocessing includes one or more of coordinate conversion, normal field correction, daily correction, hysteresis correction, and magnetic field level adjustment. By preprocessing, noise and errors in data caused by various factors in aeromagnetic field measurement data can be eliminated.
In one implementation, the pre-processing selection order may be, for example, coordinate transformation, normal field correction, daily correction, hysteresis correction.
Further, the above manner can be used in superposition, such as coordinate conversion and daily correction by configuring two containers for simultaneous processing, and then time-space synchronizing the registered spatial data with the time-corrected magnetic field data to unify the time stamp and the position tag. The efficiency is improved by parallel processing of specific preprocessing steps and by result alignment superposition.
Step 2, calculating the horizontal gradient of the aeromagnetic measurement data T in the x directionAnd the aeromagnetic data T is horizontally graded in the y direction
In one implementation, step S2 may further include:
according to the corresponding relation between the two-dimensional Fourier transform and the Hilbert transform in the frequency domain, determining the horizontal gradient of the preprocessed aeromagnetic data T in the x direction And the pre-processed aeromagnetic data T is horizontally graded in the y direction.
Specifically, the original total horizontal gradient H xy can be calculated according to the following formula;
Specifically, the two-dimensional hilbert transform can be directly calculated in frequency, and its fourier domain transform factor is:
DH(u,v)=-i·sign(u,v),
Wherein i 2 = -1, u, v are the number of circles in x and y directions. The components of the Hilbert transform in the x and y directions can be expressed as:
Wherein F < - > and F -1 < - > represent the Fourier forward and inverse transforms, respectively, and H x and H y represent the components of the two-dimensional Hilbert transform in the x and y directions, respectively.
Thus, the x-direction horizontal gradientHorizontal gradient in y directionCan be calculated by using Hilbert transform, and the two have equivalent relationship:
And directly using Hilbert instead of using Fourier transform to obtain xyz three-direction gradients by utilizing the corresponding relation between Hilbert and Fourier transform. The application of the equivalence relation, namely the use of the Hilbert transform instead of the Fourier transform, has the advantage that the direct Hilbert transform does not amplify noise interference in the aeromagnetic data.
In one implementation, step S2 may further include:
the method comprises the steps of calling geologic body characteristic distribution data of a test area in a networking mode, evaluating the test area according to the geologic body characteristic distribution data, decomposing the test area according to an evaluation result level to obtain M level scale areas, wherein the M level scale areas have M level complexity mean value marks, referencing aviation magnetic measurement data T after decomposing and preprocessing the M level scale areas to obtain M level magnetic measurement data T, and determining M horizontal gradients of the M level magnetic measurement data T in the x direction according to the corresponding relation between two-dimensional Fourier transform and Hilbert transform in a frequency domain And M horizontal gradients in the y-directionM horizontal gradients in the x-direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the x-directionM horizontal gradients in the y direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the Y direction
In one implementation manner, the evaluating the test area according to the geologic body feature distribution data, and decomposing the test area according to the evaluation result hierarchy, where obtaining M hierarchy scale areas includes:
Dividing the test area into a plurality of grid areas based on a preset grid scale, dividing the geologic body characteristic distribution data by the plurality of grid areas to obtain a plurality of grid geologic body characteristic data, evaluating the terrain complexity according to the plurality of grid geologic body characteristic data, outputting a plurality of area terrain complexity of the plurality of grid areas, presetting a complexity threshold, and mapping and combining the plurality of grid areas for a plurality of times according to whether adjacent difference values of the terrain complexity of the plurality of areas meet the complexity threshold or not to obtain the M level scale areas.
It should be appreciated that in complex geologic structure scenarios, single-scale gradient computation may have the problem that the gradient values of the strong magnetic anomaly regions are too high, resulting in deep weak gradients being ignored, based on which the present embodiment multi-scale decomposes the magnetic data, obtaining geologic body signals corresponding to different burial depths, then performing the horizontal gradient calculation on each scale layer to obtain the horizontal gradient of each scale layer, and further adopting weight superposition to perform multi-scale gradient fusion.
Specifically, in this embodiment, the geologic body feature data covering the test area is called from the geologic information platform, where the geologic body feature data includes, but is not limited to, geologic structure density information, lithology distribution information, burial depth feature information, and historical geomagnetic data, and the geologic body feature distribution data provides basic geologic background support for subsequent area evaluation and hierarchical decomposition.
Dividing the test area into a plurality of grid areas according to a preset grid scale (such as 1km multiplied by 1 km), and dividing the obtained geologic body characteristic distribution data according to the grid area division to obtain a plurality of grid geologic body characteristic data.
The terrain complexity of each grid is calculated by inputting the plurality of grid ground physique feature data into a quantization model, and evaluation indexes of the quantization model comprise construction density (distribution density based on fracture zones or folds), lithology complexity (reflecting distribution heterogeneity of different lithology), burial depth variation coefficient (representing the spatial variation degree of burial depth of a geological body), and magnetic anomaly gradient (calculating the first derivative of magnetic field intensity by combining historical geomagnetic data and describing the boundary characteristics of a magnetic body).
Setting a complexity threshold, taking the complexity threshold as a judging condition of whether adjacent grid areas can be combined, combining the adjacent grids into the same-level scale area if the complexity difference value of the adjacent grids is lower than the threshold, and otherwise, reserving the adjacent grids as independent areas. And carrying out dynamic iterative adjustment on the adjacent grid areas through a multi-pass merging algorithm to finally obtain M hierarchical scale areas.
And extracting a plurality of corresponding terrain complexity according to the grid region constitution of each hierarchical scale region, carrying out mean value calculation, and marking the corresponding hierarchical scale region.
Further, referring to the M-level scale region decomposed and preprocessed aviation magnetic measurement data T to obtain M-level magnetic measurement data T, determining M horizontal gradients of the M-level magnetic measurement data T in the x direction according to the corresponding relation between the two-dimensional Fourier transform and the Hilbert transform in the frequency domainAnd M horizontal gradients in the y-directionM horizontal gradients in the x-direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the x-directionM horizontal gradients in the y direction according to the M-level complexity mean weighted fusionOutputting a horizontal gradient in the Y direction
Determining M horizontal gradients of the M layers of magnetic measurement data t in the x direction according to the corresponding relation between the two-dimensional Fourier transform and the Hilbert transform in the frequency domainAnd M horizontal gradients in the y-directionIn the above, the correspondence between the two-dimensional fourier transform and the hilbert transform in the frequency domain may include:
then, M horizontal gradients in the x-direction are weighted and fused according to the M-level complexity average values Outputting horizontal gradient in x directionM horizontal gradients in the y direction according to the M-level complexity mean weighted fusionOutputting a y-direction horizontal gradient
Step 3, horizontally gradient in the x direction according to the aeromagnetic measurement data TThe aeromagnetic data T has a horizontal gradient in the y directionThe original total horizontal gradient H xy was calculated.
Wherein the horizontal gradientCan be M horizontal gradients in the x-direction according to the M level complexity mean weighted fusionPost-output x-direction horizontal gradientHorizontal gradientCan be M horizontal gradients in the y direction according to the M level complexity mean weighted fusionPost-output y-direction horizontal gradient
In this embodiment, M weights of the M hierarchical scale regions are obtained based on the M hierarchical complexity average value calculation, and are used for weighting fusion calculation of the x-direction horizontal gradientHorizontal gradient in y-direction
Specifically, the original total horizontal gradient H xy is calculated according to the following formula;
And 4, calculating a weak signal enhancement function according to the original total horizontal gradient H xy.
Specifically, step 4 may be calculated by the following formula:
The resolution of boundary recognition is improved through a weak signal enhancement function B, and the expression is as follows:
It should be noted that, the original total horizontal gradient H xy and the weak signal enhancement function may be calculated according to the gradient after weighted fusion according to the M-level complexity average, or may be directly calculated according to the gradient without fusion.
And step 5, obtaining accurate aviation magnetic measurement data according to the original total horizontal gradient H xy and the weak signal enhancement function B.
Specifically, accurate airborne magnetic data may be obtained according to the following formula, which includes:
Wherein, max (H xy) represents the maximum value of the total horizontal gradient H xy, T is the actually measured aviation magnetic measurement data, x and y are two directions of space coordinates, delta represents the adjustment parameter, the denominator is prevented from being 0, and the expression is prevented from having 'analytic singular points', and the delta takes the value of 0-1.
In step 5, the gradient values obtained through weighted fusion of the M hierarchical scale regions are used for calculation, so that the obtained magnetic measurement data is more stable in a complex geological structure scene.
In one implementation, the tuning parameters may be obtained by M based on a horizontal gradient in the x-directionCalculating and outputting a first horizontal mean value and a first horizontal variance, and arranging M horizontal gradients in the x direction in ascending orderTo extract the first horizontal extremum, and so on, performing a horizontal gradient M in the y-directionAfter the average burial depth of the test area is obtained interactively, inputting the average burial depth, the first horizontal mean value, the first horizontal variance, the first horizontal extremum, the second horizontal mean value, the second horizontal variance and the second horizontal extremum into a pre-built adjusting parameter disturbance model for disturbance analysis, and outputting real-time adjusting parameters.
In one implementation mode, a plurality of groups of sample disturbance variables and a plurality of sample adjustment parameters are called in a networking mode, wherein each group of sample disturbance variables comprises a sample burial depth, a first sample mean value, a first sample variance, a first sample extremum, a second sample mean value, a second sample variance and a second sample extremum, the plurality of groups of sample disturbance variables and the plurality of sample adjustment parameters are stored in a correlation mode based on a knowledge graph to complete construction of an adjustment parameter disturbance model, the average burial depth, the first horizontal mean value, the first horizontal variance, the first horizontal extremum, the second horizontal mean value, the second horizontal variance and the second horizontal extremum are input into the adjustment parameter disturbance model, data similarity evaluation is conducted on the plurality of groups of sample disturbance variables based on Euclidean distance ratio, and the sample adjustment parameters corresponding to the similarity extremum are extracted to serve as real-time adjustment parameters.
Illustratively, the knowledge-graph is stored in part as the following 3 sets of sample disturbance variables and corresponding tuning parameters Δ.
Therefore, the method for acquiring accurate aeromagnetic measurement data based on the total horizontal gradient method can better detect the boundary of the aeromagnetic data target geologic body, enables the boundary recognition result to be more convergent, solves the problem of low resolution of the existing total horizontal gradient method, and accordingly improves the quality of aeromagnetic data processing and conversion and the geologic body boundary recognition effect. In addition, the boundary interference of the geologic body which generates false aeromagnetic data is eliminated, the signal to noise ratio is enhanced, the boundary position enhancement and extraction capacity of the geologic body with different burial depths are improved, and the method has higher resolution and precision.
Therefore, the boundary position enhancement and extraction capability of the geologic body with different burial depths is improved, and the resolution and the precision are higher.
The general horizontal gradient method (THDR) expression provided in this example is:
Compared with the existing expression of the total horizontal gradient method:
Aiming at the characteristic that the total horizontal gradient method is insufficient in enhancing the boundary of a larger buried depth field source, the total horizontal gradient method expression provided by the embodiment provides that the maximum value of the total horizontal gradient is utilized to normalize H xy.B, and aims to balance the strong and weak magnetic anomalies by limiting the amplitude of the strong and weak magnetic anomalies within a specific range compared with the amplitude of the large magnetic anomalies, and avoid distortion caused by the fact that the magnetic anomalies are too strong or too weak, so that the stability and noise resistance of the magnetic anomalies are improved.
The expression of the total horizontal gradient method provided by the embodiment introduces a weak signal enhancement function B and Hilbert transformation, establishes a reasonable equalization filter and redefines the total horizontal gradient method. The position of the aeromagnetic data geological target body is obtained by using the total horizontal gradient method provided by the embodiment, so that the boundary, depth, occurrence, scale, field distribution rule, physical property and the like of a structural body field source are further accurately deduced, and the method has important significance for dividing a geodetic structural unit, carrying out structural partition, determining the position of a fracture structural band, distinguishing the distribution of different lithology and stratum, carrying out physical property map filling and the like.
The embodiment of the invention also provides a device for acquiring the accurate aviation magnetic measurement data based on the total horizontal gradient method, which comprises an acquisition module 1, a gradient calculation module 2, an original total horizontal gradient calculation module 3, a weak signal enhancement function calculation module 4 and an accurate aviation magnetic measurement data acquisition module 5.
The acquisition module 1 is used for acquiring aviation magnetic measurement data T actually measured in a test area. The gradient calculation module 2 is used for calculating the horizontal gradient of the aeromagnetic measurement data T in the x direction according to the aeromagnetic measurement data TThe aeromagnetic measurement data T has a horizontal gradient in the y directionAnd the vertical gradient of the aeromagnetic measurement data T in the z directionThe original total horizontal gradient calculation module 3 is used for horizontally gradient in the x direction according to the aeromagnetic measurement data TThe aeromagnetic data T has a horizontal gradient in the y directionThe original total horizontal gradient H xy was calculated. The weak signal enhancement function calculation module 4 is configured to calculate a weak signal enhancement function B according to the original total horizontal gradient H xy. The accurate aviation magnetic measurement data acquisition module 5 is used for acquiring accurate aviation magnetic measurement data according to the original total horizontal gradient H xy and the weak signal enhancement function B.
The embodiment of the invention also provides a storage medium, which stores computer executable instructions, and the storage medium contains a program for executing the method for acquiring accurate aeromagnetic measurement data based on the total horizontal gradient method, and the computer executable instructions can execute the method in any of the method embodiments.
The storage medium may be any available medium or data storage device that can be accessed by a computer, including, but not limited to, magnetic storage (e.g., floppy disks, hard disks, magnetic tape, magneto-optical disks (MOs), etc.), optical storage (e.g., CD, DVD, BD, HVD, etc.), and semiconductor storage (e.g., ROM, EPROM, EEPROM, nonvolatile storage (NAND FLASH), solid State Disk (SSD)), etc.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
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