WO2016138874A1 - 位场构造格架自动提取方法 - Google Patents
位场构造格架自动提取方法 Download PDFInfo
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Definitions
- the invention relates to an automatic extraction method for a gravity bit field and a magnetic field field structure frame, which is a technology for detecting geological structures based on gravity and magnetic anomaly data. More specifically, the present invention relates to the fields of wavelet analysis, image processing, geophysics, geology, mineral exploration, etc., and the method according to the present invention can be directly applied to the fields of mineral exploration and related geological surveys.
- gravity and magnetic methods (hereinafter also referred to as gravity and magnetic) measurement methods are economical, rapid, and can cover many difficult-to-reach landscape areas, and play an increasingly important role in metal deposit exploration and evaluation.
- the role especially the development of high-precision aeromagnetic measurement technology, makes the geological structure detection method based on magnetic anomaly data to control the formation of deposits, which is of great significance in all stages of metal deposit exploration selection to target location.
- gravity and magnetic exploration methods are commonly applied to the direct detection of mineralized bodies with strong magnetism or high density, as well as geological structure interpretation and inversion with strong anomalies.
- geological structure detection based on gravity field data and magnetic field data to control the formation of deposits is of great significance in the target location of metal deposits.
- the automatic identification and extraction methods of gravity magnetic field structure information mainly include analytical signal method, Euler deconvolution method, and multi-scale edge detection method of bit field.
- the common problem is that it is not sensitive to directional information and cannot be obtained. Complete and accurate abnormal boundary position.
- the invention is entitled "Position Field Multi-Directional Multi-Scale Edge Detection Method", and the patent application No. 200810006676.6 discloses a multi-directional multi-scale edge detection method for a bit field, which is enhanced by a direction wavelet transform.
- the directional information obtains the abnormal source boundary information in different directions, realizes the automatic extraction of the structural grid, and overcomes the analytical signal method, the Euler deconvolution method, the bit field multi-scale edge detection method, etc., which is insensitive to directional information.
- the problem is a technical solution for the rapid inversion of the shallow crust three-dimensional structure based on the bit field data.
- the calculated edge is not a single pixel point width, and the actual geographic range corresponding to the intersection of the edge and the different direction edges is large, resulting in low accuracy of the analysis result; (2) need to be based on different The edge of the scale is artificially vectorized, and the center line of the edge is taken as the abnormal boundary to generate the three-dimensional structure of the shallow crust, resulting in low work efficiency. (3) The three-dimensional structure of the shallow crust can only display structural information of different depths. Reflecting the structural belt and two Lateral lithological changes do not indicate structural deformation and activity intensity; (4) there is no clear definition of scale, that is, no specific geophysical properties are assigned to the scale. Therefore, it is desirable to provide a method capable of extracting a bit field construction grid with high precision based on acquired bit field data.
- TMI Total Magnetic Intensity
- a TMI anomaly can be obtained by performing a geomagnetic normal field correction on the TMI.
- TMI anomalies have problems such as lateral offset, morphological deformation, and positive and negative values. It is often necessary to perform a reduction to pole process on the TMI anomaly data to eliminate the effects of such factors.
- the morphological pole converts the observed TMI anomaly into a perpendicular magnetic anomaly in the case of perpendicular magnetization, which converts the observed TMI anomaly into an anomaly that can be measured at the north magnetic pole, thereby migrating the magnetic anomaly directly above the source region, facilitating the geological interpretation of the magnetic anomaly.
- the object of the present invention is to provide an automatic extraction method for a gravity magnetic field structure grid, which can quickly obtain geological structure information for controlling the formation of a deposit, thereby realizing the target location of the metal deposit.
- the invention further provides an automatic extraction method of a magnetic structure grid in a low latitude region, which can not only obtain linear structures (Lineaments) but also obtain a ring structure.
- the present invention defines the configuration thus obtained as a structural framework.
- the present invention uses a multi-directional multi-scale edge detection method to extract a gravity structure grid and a magnetic structure grid for the measured gravity bit field data and magnetic field data, and each of the obtained morphological skeleton algorithms will be obtained.
- the scale structure grid is refined into a single pixel width, and the texture grids of different scales are superimposed with different color gradients to display different depth structure information, and a comprehensive structure grid map is generated; corresponding to each edge point of the grid structure based on different scales
- the structural strength values of the gradient model extraction are superimposed and displayed on different gradient colors, and the density change and the magnetic change intensity information are highlighted to generate a comprehensive structural strength grid map.
- the gravity and magnetic anomaly information of different depths in the study area can be obtained, Characterize the tectonic grid distribution information of different depth geological structures, the density variation of different depth tectonic frameworks and the magnetic variation intensity information, realize the identification and qualitative interpretation of the geological structure controlling the formation of the deposit, and determine the potential according to the prior knowledge of the research analysis area.
- the type of deposit and the structural properties of the controlled deposits are screened for different types of tectonic grids to achieve the target location of the metal deposit.
- the pre-processing includes performing a polarization calculation on the magnetic data to obtain a pseudo-magnetic anomaly or performing pseudo-gravity calculation to obtain a pseudo-gravity anomaly; and pre-processing the gravity data to obtain Bouguer gravity anomaly data.
- the pre-processed gravity data or the two-dimensional directional wavelet transform of the magnetic data is connected to the edge of the gradient in the vertical direction of the gradient to form an edge.
- the edges calculated in different directions of the same scale are obtained, and the obtained edge is obtained as the edge of the scale, so that the multi-directional edge detection of the potential field at each scale can be realized.
- the obtained structural grids of various scales are superimposed to generate a comprehensive structural grid map reflecting different depth information.
- the lateral offset of the different scale edges on the map reflects the occurrence information of the structural grid.
- edges extracted after the height of the bit field are extended to different heights correspond to the structures of different depths, and the depth is half of the height after the upward extension (see the author is Jacobsen, BH, titled A case for upward continuation as a standard separation filter for potential- Field maps, journal name Geophysics, issue number v.52no.8, time 1987), can be used to characterize the texture grids at different depths.
- the modulus of the gradient at each edge point on the calculated edge is taken as the intensity value at the edge point in the construction grid.
- the intensity value of the edge points on the structural grid with intensity values reflects the lithological changes of the structural belt and both sides, reflecting the deformation and activity intensity of the structure.
- the total horizontal derivative and the analytical signal of the Tilt derivative (TDR) of the TMI abnormal data are not affected by the magnetic dip angle, and the calculation result is independent of the magnitude of the magnetic dip value, and can be directly
- the TMI anomaly data is used to calculate the total horizontal derivative of TDR and the analytical signal without performing polarization processing.
- the calculation result of the analytical signal method will increase the magnetic anomaly range, loss of geological structure occurrence information and structural division information, and is not sensitive to the identification of geological structures.
- the results of the total horizontal derivative of the current oblique derivative are expressed in the form of grid images or contour maps.
- the traditional horizontal gradient-based edge detection method cannot obtain complete and accurate source bodies of magnetic anomalies because it does not consider the directional information of the data.
- the invention can effectively identify and establish a magnetic tectonic framework in a low latitude region by performing multi-directional edge detection based on the total horizontal derivative of the oblique derivative at multiple scales on the pre-processed TMI anomaly data. Therefore, the automatic extraction method of the structural grid according to the present invention is particularly suitable for automatic extraction of the structural grid of magnetic measurement data in low latitude regions.
- a method for automatically extracting a bit field structure grid comprising the steps of:
- the preprocessed bit field data is extended upward by a plurality of predetermined heights to obtain a plurality of bit field data of corresponding scales;
- the morphological skeletal algorithm is used to refine the calculated bit field edges of each scale into single pixel widths, and obtain a structural grid map of multiple corresponding scales.
- the method further comprises overlaying the calculated structural grid maps of the plurality of respective scales to generate a comprehensive texture grid map.
- the method further comprises using a mode of the gradient at each edge point on each scale structure grid map as the intensity value at the edge point in the scale structure grid map, and obtaining a plurality of structural scales of the corresponding scales Frame map.
- the method further comprises overlaying the plurality of respective scales of structural strength grid maps to generate a composite structural strength grid map.
- the bit field data is gravity bit field data or magnetic method bit field data
- the preprocessing further comprises performing polarization calculation on the magnetic method data to obtain a polar magnetic abnormality or performing pseudo gravity calculation to obtain a pseudo Gravity anomaly; or preprocessing the gravity data to obtain a Bouguer gravity anomaly.
- multi-directional edge detection is performed for the bit field data of each scale, including the following steps:
- k(x, y, z) is the Green's function
- the wavelet function in direction ⁇ is defined as:
- the position (x, y), scale s and orientation ⁇ , f 0 (x, y ) in the direction of the two-dimensional wavelet transform W [f 0] (x, y, s, ⁇ ) and f z (x, y) of gradient Proportional, f 0 (x, y) in the direction of the two-dimensional wavelet transform W [f 0] (x, y, s, ⁇ ) may be f z (x, y) of the gradient To characterize.
- the corresponding angular angle in the horizontal direction of the gradient is:
- the edge point is the point where the modulo M[f z ](x, y, ⁇ ) has a local maximum along the radial direction Af z (x, y, ⁇ ),
- the local maximum point of the gradient mode is connected along the vertical direction of the gradient to form an edge.
- the edges are calculated in a plurality of different directions ⁇ , and the calculated edges are summed to obtain the edges of the height.
- the edge field is extended to a plurality of predetermined heights and the extracted edges correspond to different depth configurations, and the obtained structural grid maps of each scale are superimposed to obtain a comprehensive structural grid map reflecting different depth information.
- the height of the height is characterized by a gradation color to form the integrated texture grid map.
- the magnitude of the intensity value is characterized by a gradation color to form the integrated structural strength grid map.
- a method for automatically extracting a texture grid comprising the steps of:
- TMI anomaly data or Bouguer gravity anomaly data Grid the obtained TMI anomaly data or Bouguer gravity anomaly data, and extend the meshed TMI anomaly data or Bouguer gravity anomaly data to a plurality of predetermined heights to obtain gridded TMI anomalies of multiple scales.
- Data or Bouguer gravity anomaly data T h , h is the height after upward extension;
- the TMI anomaly data of each scale or the tilt derivative TDR h of the Bouguer gravity anomaly data are calculated by using the meshed TMI anomaly data or the Bouguer gravity anomaly data T h of each scale respectively;
- the horizontal gradient-based multi-directional edge detection is performed for each scale of the meshed TMI anomaly data or the oblique derivative of the Bouguer gravity anomaly data, and the magnetic or gravity anomaly source edge of each scale is obtained;
- the morphological skeletal algorithm is used to refine the edge of the magnetic or gravity anomaly source of each scale to a single pixel width, and a structural grid map with multiple scales is obtained.
- the method further comprises superimposing the calculated texture grid maps of the plurality of scales to generate a comprehensive structure grid map.
- the method further comprises: extending the TMI anomaly data or the Bouguer gravity anomaly data to the plurality of predetermined heights and extracting the edges corresponding to the different depths, and superimposing the obtained structural grid maps of the respective depths to reflect different A comprehensive structural grid diagram of cutting depth information.
- the horizontal gradient-based multi-directional edge detection is performed on the tilted derivative of the meshed TMI abnormal data or the Bouguer gravity abnormal data for each scale, respectively, including the following steps:
- Tilt derivative TDR h in direction ⁇ and The directional derivatives are defined as:
- the angle of the horizontal gradient is:
- the edges are calculated in a plurality of different directions ⁇ , and the calculated edges are summed to obtain the edge of the magnetic or gravity abnormal source body of the corresponding scale.
- the method further comprises characterizing the horizontal gradient of each edge point on each scale structure grid map to characterize the structural burial depth at the edge point of the scale structure grid map, to obtain a plurality of scale representation structures A structural grid map of buried depth.
- the method further comprises overlaying the plurality of scales of the constructed burial depth of the constructed grid map to generate an integrated buried depth structure grid map.
- the method further comprises calculating the three-dimensional analytical signal AS h based on the meshed TMI abnormality data or the Bouguer gravity abnormality data T h of each scale, respectively, and obtaining the AS h value of each edge point, thereby obtaining multiple scales.
- a structural grid diagram that characterizes the magnetic or density at the edge points.
- the method further comprises superimposing the plurality of scales of the structural lattice patterns characterizing the edge points of the magnetic points or the density to form an integrated magnetic strength structure grid diagram or a comprehensive density strength structure grid diagram.
- the method further comprises performing a process of removing noise from the calculated oblique derivative before performing edge detection.
- the method is suitable for automatic extraction of magnetic structure grids in low latitude regions; preferably, the method is applicable to magnetic measurement data of a region with a magnetic inclination angle of ⁇ 30°; further preferably, the method is applicable to magnetic Magnetic measurement data for an area with an inclination of ⁇ 20°.
- the gravity and magnetic anomaly information at different depths of the study area can be obtained, and the control of deposit formation is realized.
- the identification and qualitative interpretation of the geological structure according to the prior knowledge of the study area to determine the potential type of deposit and control the formation properties of the deposit, and screen the different types of tectonic grids to achieve the target location of the metal deposit.
- the method for automatically extracting the structural grid by using the magnetic method measurement data in the low latitude region solves the problem that it is difficult to accurately obtain the structural information by using the magnetic method measurement data in the low latitude region in the prior art.
- the structural grid diagram obtained according to the present invention visually characterizes the depth of construction, the depth of burial, the primary-secondary relationship, the delivery relationship, the magnetic strength, etc. for the geological solution compared to the existing grid image or contour map. Interpretation and prospecting have important information.
- the automatic extraction method of the magnetic structure grid in the low latitude region proposed by the invention is also suitable for the automatic extraction of the magnetic structure grid in the middle and high latitude regions, and is also suitable for the automatic extraction of the gravity field structure grid.
- the magnetic method is used to analyze and acquire the region of the structural grid, and the accuracy of automatically extracting the structural grid is improved, and the identification and qualitative interpretation of the geological structure for controlling the formation of the deposit can be realized, according to the research area.
- the knowledge is used to determine the type of potential deposits and to control the structural properties of the deposits.
- the different types of structural frameworks are screened to achieve the target location of the metal deposits.
- FIG. 1 is a flow chart of a method for automatically extracting a bit field structure grid according to a first embodiment of the present invention
- FIG. 2 is a block diagram of a single pixel width structure according to a first example of the present invention
- Figure 3 is a diagram showing a comprehensive structure grid according to a first example of the present invention.
- Figure 4 is a structural strength grid diagram in accordance with a first example of the present invention.
- Figure 5 is a comprehensive structural strength grid diagram according to a first example of the present invention.
- FIG. 6 is a flow chart of a method for automatically extracting a magnetic structure grid in a low latitude region according to a second embodiment of the present invention
- FIG. 7 is a block diagram of a single pixel width structure according to a second example of the present invention.
- Figure 8 is a diagram showing a comprehensive structure grid according to a second example of the present invention.
- Figure 9 is a structural grid diagram reflecting the burial depth according to a second example of the present invention.
- Figure 10 is a diagram showing a comprehensive buried depth structure grid according to a second example of the present invention.
- Figure 11 is a diagram showing a grid structure reflecting magnetic strength according to a second example of the present invention.
- Figure 12 is a diagram showing an integrated magnetic strength structure grid according to a second example of the present invention.
- FIG. 1 is a flow chart of a method for automatically extracting a bit field structure grid according to a first embodiment of the present invention.
- Figure 1 As shown, the method includes the following steps:
- Step 101 Preprocess the measured gravity bit field data or magnetic field data.
- the pseudo-magnetic anomaly is obtained by calculating the magnetic pole data to obtain a pseudo-magnetic anomaly or pseudo-gravity calculation.
- the gravity data is preprocessed to obtain a Bouguer gravity anomaly.
- step 102 the pre-processed gravity bit field data or the magnetic field data is processed by using a multi-directional edge multi-directional edge detection method at multiple scales to obtain edges of multiple scales.
- the multi-directional multi-scale edge detection method of the bit field comprises extending the pre-processed gravity bit field data or the magnetic method bit field data to a plurality of predetermined heights to obtain a plurality of corresponding scale bit field data and a bit field for each scale respectively.
- a method for calculating multi-directional edge detection for each scale field including the following steps:
- k(x, y, z) is the Green's function.
- the wavelet function in direction ⁇ can be defined as:
- the two-dimensional directional wavelet transform of f 0 (x, y) can be represented by a gradient:
- the position (x, y), scale s and orientation ⁇ , f 0 (x, y ) in the direction of the two-dimensional wavelet transform W [f 0] (x, y, s, ⁇ ) and f z (x, y) of gradient Proportional, f 0 (x, y) in the direction of the two-dimensional wavelet transform W [f 0] (x, y, s, ⁇ ) may be f z (x, y) of the gradient To characterize.
- the corresponding angular angle in the horizontal direction of the gradient is:
- the edge point is the point at which the modulo M[f z ](x, y, ⁇ ) has a local maximum along the radial direction Af z (x, y, ⁇ ).
- the local maximum point of the gradient's mode is connected along the vertical direction of the gradient to form an edge.
- the edges of the complete coverage of the two-dimensional plane are calculated, and the calculated edges are summed to obtain the edges of the scale.
- step 103 the edge of each scale calculated by the morphological skeletal algorithm is refined into a single pixel width, and a grid map of each scale is obtained.
- the actual geographical extent corresponding to the intersection of edges and edges in different directions is significantly smaller than that of the prior art, so that the resulting bit field structure grid is closer to the characteristics of the actual geological map identification structure.
- the aspect information is clear, enhances readability, and on the other hand facilitates geological interpretation.
- step 104 the calculated scale structures are stacked to generate a comprehensive structure grid map.
- step 105 the edge intensity is reflected by the modulus of the gradient of each edge point on each scale grid.
- the modulo M[f z ](x, y, ⁇ ) of the gradient at each edge point is constant, which is a fixed value, and the modulus of the gradient at the edge point represents the structural intensity value at the edge point.
- Step 106 Stacking the plurality of scale structural strength grid maps to generate a comprehensive structural strength grid map.
- the superimposed display of different gradient colors for the intensity values of the edges or depth edges highlights the magnetic and density variation intensity information.
- the aeromagnetic data is subjected to block-shaped pole processing, and the processed data is spliced into a bit field grid file with a grid size of 500 meters.
- the aeromagnetic data in this example is the aeromagnetic data collected multiple times in history. Data, measuring height in the range of 800-1200 meters.
- the skeletal algorithm is used to refine the calculated edges of each scale to obtain the structural grid map of each scale.
- Fig. 2 is a single-pixel width structure grid of a corresponding scale extracted by the skeletal algorithm for the upper extension edge of 5000 m. It can be seen that the bit field structure grid of the single pixel point width obtained by the automatic extraction according to the present invention is closer to the actual geological map recognition structure feature, and is convenient for geological interpretation. In addition, the information on the surface is clearer, which facilitates the overlay analysis of grids of different scales.
- Figure 3 shows the scales of the scales obtained by extending the bit field upwards by 1000, 1500, 2000, 2500, 3000, 4000, 5000, 10000, 15000, 20000, 25000, and 30000 meters.
- a comprehensive structural grid diagram formed by color gradual superposition. The respective heights after the extension are corresponding to the depth of the corresponding source region, and the comprehensive structure grid map can be used to characterize the structural grid information at different depths of the study area.
- the gradient from gray to black represents the upward continuation height from low to high or the depth from shallow to deep.
- the comprehensive structural grid diagram reflects the structural information at different depths.
- Fig. 4 is the structural strength of the mode of the gradient at the edge point of the upper 5,000-meter elongate height grid, and the structural strength value represented by the mode which reflects the gradient from gray to black gradually increases. This figure reflects the change in structural strength at a corresponding scale.
- Figure 5 is a comprehensive structural strength grid obtained by superimposing the edge strengths obtained by extending the potential fields by 1000, 1500, 2000, 2500, 3000, 4000, 5000, 10000, 15000, 20000, 25000, and 30000 meters.
- Figure. It can be seen from the figure that at different scales, it is reflected that the main tectonic belts show a large structural strength, and the corresponding magnetic anomaly changes obviously, indicating that the main structural belts are all magnetic anomaly, and the corresponding depth is very Large, reflecting the structural belt controlling the deep magma-mineralization.
- the structural grid map with depth and intensity information can clearly reflect the large-depth, long-length backbone structure in the region, and the shallower, relatively short-duration secondary structures, and the mutual The delivery relationship, and thus the structural grid map obtained by the method of the present invention, can help those skilled in the art to recognize the detected regional structural pattern.
- Figures 3 and 5 Comparing Figures 3 and 5 with the surface mapping geological structure of the region, the spatial location and extent are very consistent, illustrating the accuracy and effectiveness of the automated extraction method in accordance with the present invention.
- Figures 3 and 5 of the present invention add information on the three-dimensional extension, strength, structure, etc., which can help identify the concealed structural belt.
- the method according to the present invention can quickly and accurately extract aeromagnetic data and gravity data.
- a magnetic flow measurement data is taken as an example to specifically describe a flow chart of a method for automatically extracting a magnetic structure grid in a low latitude region according to a second embodiment of the present invention.
- the method of the present invention is not limited to magnetic measurement data, but is also applicable to the automatic extraction of construction grids of gravity measurement data.
- FIG. 6 is a flow chart of a method for automatically extracting a magnetic structure grid in a low latitude region according to the present invention. As shown in FIG. 6, the method includes the following steps:
- step 601 the observation value obtained by the magnetic method is preprocessed, and the geomagnetic normal field (IGRF) is corrected to obtain the total magnetic field strength (TMI) abnormal data.
- IGRF geomagnetic normal field
- the TMI anomaly data is meshed.
- the grid size is taken as 1/8 to 1/4 or the minimum dot pitch of the line spacing.
- Step 602 Upward continuation a plurality of predetermined heights on the meshed TMI abnormal data T to obtain a plurality of meshed TMI abnormal data T h of corresponding scales, where h represents the height after the upward extension.
- Step 603 Calculate the tilt derivative TDR h of the corresponding scale TMI abnormal data by using the meshed TMI abnormal data T h of each scale respectively:
- VDR h and THDR h are the vertical first derivative and total horizontal derivative of the meshed TMI anomaly data T h , respectively:
- Step 604 calculating multi-directional edge detection based on the horizontal gradient for each of the scaled derivatives TDR h of each scale.
- Tilt derivative TDR h in direction ⁇ and The directional derivatives are defined as:
- TDR_THDR The total horizontal derivative of the oblique derivative of the TMI anomaly data
- the magnitude of the amplitude is independent of the magnitude of the magnetic dip.
- edge points of the magnetic source body for the height h and the direction ⁇ are modulo Along the radial direction a point with a local maximum
- the local maximum point of the gradient mode is connected along the vertical direction of the gradient to form an edge
- the edges are calculated in a plurality of different directions ⁇ , and the calculated edges are summed to obtain the edge of the magnetic source body of the corresponding scale.
- the subsequent multi-directional edge detection calculation is sensitive to noise.
- a noise reduction process such as Gaussian filtering on the TDR h data having a large noise before calculating the multi-directional edge detection.
- the calculation result is independent of the magnitude of the magnetic dip value.
- the edge of the magnetic anomaly source obtained by the above steps is not affected by the magnetic dip angle, ie, is not affected by the latitude of the area to be analyzed. The influence of position can accurately characterize the structural lattice in low latitudes frame.
- step 605 the calculated edge of each scale is separately processed into a single pixel width by using a morphological skeleton algorithm to obtain a structural grid map at multiple scales.
- the actual geographical extent corresponding to the intersection of edges and edges in different directions is significantly smaller than that of the prior art, so that the structural grid is closer to the characteristics of the actual geological mapping structure.
- the surface information is clear, the readability is enhanced, and the geological interpretation is facilitated on the other hand.
- Step 606 The calculated structural grid maps of each scale are superposed to generate a comprehensive structural grid map.
- the resulting structural grid maps of various scales are superimposed to generate a comprehensive structural grid map reflecting different depth information.
- the lateral offset of the different scale edges on the graph reflects the occurrence information of the structural grid.
- the meshed TMI anomaly data is extended to different heights and the extracted edges correspond to different depths.
- the depth is half of the height after the upward extension (see the author is Jacobsen, BH, titled A case for upward continuation as a standard).
- Separation filter for potential-field maps, journal name Geophysics, issue number v.52no.8, time 1987) can be used to characterize the texture of different cutting depths.
- the obtained structural grid maps of the respective depths are superimposed to obtain a comprehensive structural grid map reflecting different cutting depth information.
- the burial depth is constructed by using a model of the horizontal gradient of the TDR h at each edge point on the grid, and a structural grid map of the burial depth of the plurality of scales is obtained.
- the mode of the horizontal gradient at each edge point The size does not change and is a fixed value.
- the magnitude of TDR h is limited to between - ⁇ /2 and + ⁇ /2. Therefore, the mode of the horizontal gradient at each edge point
- the size of the TIM has little to do with the magnitude of the TMI.
- This value reflects the depth of the source region. The value is inversely proportional to the depth of the burial. The larger the value, the shallower the burial depth of the source region (see author Bruno Verduzco et al., titled New). Insights into magnetic derivatives for structural mapping, the journal name The Leading Edge, issue v.23no.2, time 2004).
- the structure of the horizontal gradient of the oblique derivative TDR h reflects the thickness of the cover layer on the top of the structural belt, while the different depths corresponding to the upward extension of the plurality of predetermined heights reflect the depth of cut of the structural belt, which represents Construct the depth at which the belt extends downward.
- the modulus of the gradient at the edge point Representing the relative burial depth of the edge at the edge point at the edge point, and establishing a structural grid map of the relative burial depth of the reaction structures of different scales or different depths.
- the change in the magnitude of the modulus of the gradient of the same structural zone reflects the depth of burial of different parts of the structural zone.
- Step 608 stacking the structural grid maps of the plurality of scales to characterize the buried depth to generate a comprehensive buried depth structure grid map.
- modulus values of the TDR h horizontal gradients for each scale or depth edge point are superimposed with different gradient colors, highlighting the burial depth variation information of the structural grids with different cutting depth ranges.
- Step 609 calculating a three-dimensional analysis signal AS h for the meshed TMI abnormal data T h of each height:
- Calculated magnitude of the analytical signal AS h has a strong correlation with the magnitude TMI abnormalities, but magnetic tilt value irrespective of the size, can be used to indicate the position of the source region and the magnetic field strength of the magnetic anomalies.
- step 610 the magnetic strength of the structure is indicated by the AS h value at each edge point on each scale grid.
- the magnitude of the three-dimensional analytical signal AS h indicates the magnetic strength of the magnetic anomaly source, and the strong magnetic structure is usually closely related to mineralization.
- Step 611 stacking the plurality of scale magnetic strength structure grid maps to generate a comprehensive magnetic strength structure grid map.
- the aeromagnetic data used in this example has a measuring scale of 1:25000 and a measuring height of 70-120 meters.
- the observations obtained from the aeromagnetic survey in the study area are preprocessed, and the geomagnetic normal field (IGRF) is corrected to obtain the total magnetic field strength (TMI) anomaly data.
- the TMI abnormal data is meshed, and the grid size is taken as the value. 10 m.
- the gridded TMI anomaly data is separately extended upward to obtain gridded TMI anomaly data T h of multiple scales, and the elevation heights are 100, 200, 300, 400, and 500 meters, respectively.
- Multi-directional edge detection based on horizontal gradient is performed on the calculated TDR for each of the upper extension heights.
- FIG. 7 is a single-pixel width magnetic structure grid with a scale of 300 M in the upper limit of the gridded TMI anomaly data, and the edge is refined by the bone algorithm. It can be seen that the structure frame of the single pixel dot width obtained by the automatic extraction according to the present invention is closer to the actual geological map identification structure feature, and is convenient for geological interpretation. In addition, the information on the surface is clearer, which facilitates the overlay analysis of the grids of different scales.
- Fig. 8 is a comprehensive structure of color gradual superposition of structural grids of various scales obtained by extending the gridded TMI anomaly data up to 100, 200, 300, 400, and 500 meters upwards and then detecting the 64 directional edges.
- the respective heights after the extension are corresponding to the depth of the corresponding source region, and the comprehensive structure grid map can be used to characterize the structural grid information at different depths of the study area.
- the gradient from gray to black represents the upward extension height from low to high or the depth of cut from shallow to deep.
- the comprehensive texture grid map reflects the construction information of different cutting depths.
- Figure 9 is a structural burial depth characterized by a gradient of the gradient at the edge of the 300 m upper echelat, and the burial depth represented by the mode that reflects the horizontal gradient from gray to black gradually decreases. This figure reflects the variation of the burial depth of the structure at the corresponding scale.
- Figure 10 is a comprehensive buried depth structure grid diagram obtained by superimposing the gridded TMI anomaly data on the elevation heights of 100, 200, 300, 400, and 500 meters, respectively. . It can be seen from the figure that at different scales, it reflects that the burial depth of the main structural belt varies greatly. Generally, the buried deep structure is thicker, and the corresponding TMI abnormal amplitude is lower, which is a concealed structure. The method contributes to the identification of hidden structures.
- the three-dimensional analysis signal AS h is calculated for the meshed TMI abnormality data T h of each scale.
- the calculated analytical signal AS h value is independent of the magnitude of the magnetic dip value and can be used to indicate the location of the magnetic anomaly source region and the magnetic field strength.
- the AS h value at each edge point on each scale grid is used to indicate the structural magnetic strength.
- Figure 11 is a structural grid diagram showing the magnetic strength using the AS h value at the edge point of the 300 m upper extension grid.
- the gray-white to black gradient color indicates the gradual change of the structural band indicated by the analytical signal AS h value. Enhanced.
- the magnetic scale structure maps of the plurality of scales are superposed to generate a comprehensive magnetic strength and weak structure grid diagram, as shown in FIG. 12, the AS h values of the scales or depth edges are gray-white to black gradient colors.
- Overlay display highlights the magnetic change information of the texture grids in different depth ranges.
- the magnitude of the three-dimensional analytical signal AS h indicates the magnetic strength of the anomalous source.
- the strong magnetic structure is usually closely related to mineralization.
- the structural grid map with the information of cutting depth and burial depth can clearly reflect the main structure with deep and long extension in the region, and the secondary structure with relatively shallow depth and relatively short extension.
- the cover thickness of each configuration and the mutual delivery relationship, and thus the structural grid map obtained by the method of the present invention can help those skilled in the art to recognize the detected regional structural pattern.
- the intersections along the magnetically strong, deeper structural belts, the different directions, and the transitional bends of the structural belts are important locations for the discovery of potential metal deposits.
- the method according to the present invention can quickly and accurately extract and cut with magnetic measurement data.
- Structural grid maps of depth, burial depth, magnetic strength, primary and secondary relationships, and delivery relationships help prospectors accurately and quickly identify potential metal deposits.
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Abstract
Description
Claims (20)
- 一种位场构造格架自动提取方法,包括以下步骤:对来自待研究区域的位场数据进行预处理;将经预处理的位场数据向上延拓多个预定高度得到多个相应尺度的位场数据;分别针对每一尺度的位场数据进行多方向边缘检测,得到多个相应尺度的位场边缘;采用形态学骨骼算法将计算得到的各尺度的位场边缘分别细化为单像素宽度,得到多个相应尺度的构造格架图。
- 如权利要求1所述的位场构造格架自动提取方法,其特征在于,该方法进一步包括将计算得到的所述多个相应尺度的构造格架图叠置生成综合构造格架图。
- 如权利要求1所述的位场构造格架自动提取方法,其特征在于,该方法进一步包括:将各尺度构造格架图上的每一边缘点处的梯度的模作为该尺度构造格架图中该边缘点处的强度值,得到多个相应尺度的构造强度格架图。
- 如权利要求3所述的位场构造格架自动提取方法,其特征在于,该方法进一步包括将所述多个相应尺度的构造强度格架图叠置生成综合构造强度格架图。
- 如权利要求1所述的位场构造格架自动提取方法,其特征在于,所述位场数据为重力位场数据或磁法位场数据,所述预处理进一步包括对重力数据进行预处理得到布格重力异常;或对磁法数据进行化极计算得到化极磁异常或进行伪重力计算得到伪重力异常。
- 如权利要求1所述的位场构造格架自动提取方法,其特征在于,针对每一尺度的位场数据进行多方向边缘检测,包括以下步骤:设尺度s=z/z0,且z>z0,z0代表测量高度,z代表向上延拓后的高度,定义高度为零的位置(x,y)处的重力异常或磁异常为f0(x,y),尺度s的平滑函数定义为:在方向α的小波函数定义为:其中,D表示一阶导数;在尺度s和位置(x,y)的情况下,重力异常或磁异常f0(x,y)在方向α的小波变换定义为:其中,*表示卷积运算,因此,Wα[f0](x,y,s)=sDαfz(x,y)=(z/z0)Dαfz(x,y);则,f0(x,y)的二维方向小波变换用梯度表示为:W[f0](x,y,s,α)=(z/z0)▽fz(x,y,α)其中▽为二维梯度,对于高度z,定义梯度▽fz(x,y,α)的模为:该梯度相应的沿水平方向的辐角为:边缘点为模M[fz](x,y,α)沿辐角方向Afz(x,y,α)有局部极大值的点,针对每一方向α,梯度的模的局部极大值点沿梯度的垂直方向连接得到的曲线构成边缘,针对同一高度,以多个不同的方向α计算边缘,对计算得到的各边缘求并集得到相应尺度的位场边缘。
- 如权利要求6所述的位场构造格架自动提取方法,其特征在于,针对同一高度以多个不同的方向α计算边缘的步骤进一步包括,各方向α取值为kπ/(2n-1),其中k=0,1,2,…,(2n-1),n为大于或等于2的整数,以完整覆盖二维平面。
- 如权利要求6所述的位场构造格架自动提取方法,其特征在于,位场向上延拓多个预定高度后提取的边缘对应于不同深度的构造,对得到的各尺度的构造格架图进行叠加得到反映不同深度信息的综合构造格架图。
- 如权利要求2或8所述的位场构造格架自动提取方法,其特征在于,以渐变颜色表征高度的高低,来形成所述综合构造格架图。
- 如权利要求4所述的位场构造格架自动提取方法,其特征在于,以渐变颜色表征强度值的大小,来形成所述综合构造强度格架图。
- 一种构造格架自动提取方法,该方法包括以下步骤:对来自待研究区域的磁法或重力测量数据进行预处理,得到总磁场强度(TMI)异常数据或布格重力异常数据;将所得到的TMI异常数据或布格重力异常数据网格化,并将网格化的TMI异常数据或布格重力异常数据向上延拓多个预定高度,得到多个尺度的网格化TMI异常数据或布格重力异常数据Th,h为向上延拓后的高度;分别利用每一尺度的网格化TMI异常数据或布格重力异常数据Th计算各尺度的TMI异常数据或布格重力异常数据的倾斜导数TDRh;分别针对每一尺度的网格化TMI异常数据或布格重力异常数据的倾斜导数,进行基于水平梯度的多方向边缘检测,得到各尺度的磁或重力异常源体边缘;采用形态学骨骼算法将计算得到的各尺度的磁或重力异常源体边缘分别细化为单像素宽度,得到多个尺度的构造格架图。
- 如权利要求11所述的构造格架自动提取方法,其特征在于,该方法进一步包括,将计算得到的所述多个尺度的构造格架图叠置生成综合构造格 架图。
- 如权利要求12所述的构造格架自动提取方法,其特征在于,该方法进一步包括,将网格化TMI异常数据或布格重力异常数据向上延拓多个预定高度后提取的边缘对应于不同深度的构造,对得到的各深度的构造格架图进行叠加得到反映不同切割深度信息的综合构造格架图。
- 如权利要求11所述的构造格架自动提取方法,其特征在于,所述分别针对每一尺度的网格化TMI异常数据或布格重力异常数据的倾斜导数进行基于水平梯度的多方向边缘检测,包括以下步骤:其中,D表示一阶导数;对于高度h和方向α,倾斜导数TDRh的水平梯度表示为:其中▽为水平梯度;该水平梯度的辐角为:针对每一方向α,将倾斜导数TDRh的水平梯度的模的局部极大值点沿梯度的垂直方向连接,得到的曲线构成边缘;针对同一高度h,以多个不同的方向α计算边缘,对计算得到的各边缘求并集得到相应尺度的磁或重力异常源体边缘,其中,所述多个不同方向α取值为分别kπ/(2n-1),k=0,1,2,…,(2n-1),n为大于或等于2的整数。
- 如权利要求14所述的构造格架自动提取方法,其特征在于,该方法进一步包括:分别将各尺度构造格架图上的每一边缘点处的水平梯度的模表征该尺度构造格架图中该边缘点处的构造埋藏深度,得到多个尺度的表征构造埋藏深度的构造格架图。
- 如权利要求15所述的构造格架自动提取方法,其特征在于,该方法进一步包括将所述多个尺度的表征构造埋藏深度的构造格架图叠置生成综合埋藏深度构造格架图。
- 如权利要求11所述的构造格架自动提取方法,其特征在于,该方法进一步包括,分别基于每一尺度的网格化TMI异常数据或布格重力异常数据Th计算三维解析信号ASh,得到各边缘点的ASh值,由此得到多个尺度的表征边缘点处磁性或密度强弱的构造格架图。
- 如权利要求17所述的构造格架自动提取方法,其特征在于,该方法进一步包括将所述多个尺度的表征边缘点磁性或密度强弱的构造格架图叠置生成综合磁性强弱构造格架图或综合密度强弱构造格架图。
- 如权利要求11所述的构造格架自动提取方法,其特征在于,该方法进一步包括,在进行边缘检测前对计算得到的倾斜导数进行去除噪声的处理。
- 如权利要求11所述的构造格架自动提取方法,其特征在于,该方法适用于低纬度地区的磁构造格架自动提取;优选地,该方法适用于磁倾角为±30°之间的区域的磁法测量数据;进一步优选地,该方法适用于磁倾角为±20°之间的区域的磁法测量数据。
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US11815647B1 (en) * | 2022-04-20 | 2023-11-14 | Chinese Academy Of Geological Sciences | Gravity inversion method and system based on meshfree method |
CN115236755B (zh) * | 2022-07-25 | 2023-10-03 | 中国自然资源航空物探遥感中心 | 基于张量特征值的航磁异常边界检测方法、装置 |
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7079135B2 (en) * | 2002-03-07 | 2006-07-18 | Samsung Electronics Co., Ltd. | Method of wavelets-based multiresolution representation of three-dimensional image object |
CN101256676A (zh) * | 2008-01-31 | 2008-09-03 | 中国地质科学院矿产资源研究所 | 位场多方向多尺度边缘检测方法 |
CN102236108A (zh) * | 2010-05-06 | 2011-11-09 | 中国石油天然气集团公司 | 一种磁性地表三维地形改正方法 |
CN102937725A (zh) * | 2012-11-12 | 2013-02-20 | 中国科学院地质与地球物理研究所 | 一种基于过渡区与相叠合的位场异常边缘增强方法 |
CN104658037A (zh) * | 2015-03-04 | 2015-05-27 | 中国地质科学院矿产资源研究所 | 一种位场构造格架自动提取方法 |
CN104965232A (zh) * | 2015-06-04 | 2015-10-07 | 中国地质科学院矿产资源研究所 | 低纬度地区磁构造格架自动提取方法 |
Family Cites Families (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7486811B2 (en) * | 1996-09-16 | 2009-02-03 | The Research Foundation Of State University Of New York | System and method for performing a three-dimensional virtual examination of objects, such as internal organs |
RU2169384C1 (ru) * | 1999-12-17 | 2001-06-20 | Закрытое акционерное общество "Петербургская геофизическая компания" | Способ поиска нефтегазовых месторождений |
US7127104B2 (en) * | 2004-07-07 | 2006-10-24 | The Regents Of The University Of California | Vectorized image segmentation via trixel agglomeration |
US8041141B2 (en) * | 2006-06-30 | 2011-10-18 | The University Of Louisville Research Foundation, Inc. | Method and software for shape representation with curve skeletons |
CN101520518B (zh) | 2008-02-25 | 2011-01-12 | 中国石油集团东方地球物理勘探有限责任公司 | 一种利用重磁电异常的组合特征识别火成岩岩性的方法 |
RU2401443C2 (ru) * | 2008-03-17 | 2010-10-10 | Общество с ограниченной ответственностью "Научно-производственное предприятие "Нейво" | Способ обнаружения и отображения фигуры газонефтяной лог-трубки |
AU2009234284A1 (en) * | 2008-04-11 | 2009-10-15 | Terraspark Geosciences, Llc | Visulation of geologic features using data representations thereof |
CN102066980B (zh) * | 2008-05-22 | 2015-02-25 | 埃克森美孚上游研究公司 | 地震层位骨架化 |
US8126247B2 (en) * | 2009-05-19 | 2012-02-28 | National Tsing Hua University | Image preprocessing system for 3D image database construction |
WO2014003596A1 (en) * | 2012-06-26 | 2014-01-03 | Schlumberger, Holdings Limited | A method for building a 3d model of a rock sample |
CN103955007A (zh) | 2014-05-20 | 2014-07-30 | 中国石油化工股份有限公司胜利油田分公司西部新区研究院 | 复杂山前构造带的综合建模方法及建立的地质结构模型 |
US10136869B2 (en) * | 2016-03-25 | 2018-11-27 | Perkinelmer Health Sciences, Inc. | Systems and methods for characterizing a central axis of a bone from a 3D anatomical image |
-
2016
- 2016-03-04 AU AU2016228027A patent/AU2016228027B2/en active Active
- 2016-03-04 RU RU2017133223A patent/RU2664488C1/ru active
- 2016-03-04 CA CA2978500A patent/CA2978500C/en active Active
- 2016-03-04 WO PCT/CN2016/075626 patent/WO2016138874A1/zh active Application Filing
- 2016-03-04 US US15/555,153 patent/US10884161B2/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7079135B2 (en) * | 2002-03-07 | 2006-07-18 | Samsung Electronics Co., Ltd. | Method of wavelets-based multiresolution representation of three-dimensional image object |
CN101256676A (zh) * | 2008-01-31 | 2008-09-03 | 中国地质科学院矿产资源研究所 | 位场多方向多尺度边缘检测方法 |
CN102236108A (zh) * | 2010-05-06 | 2011-11-09 | 中国石油天然气集团公司 | 一种磁性地表三维地形改正方法 |
CN102937725A (zh) * | 2012-11-12 | 2013-02-20 | 中国科学院地质与地球物理研究所 | 一种基于过渡区与相叠合的位场异常边缘增强方法 |
CN104658037A (zh) * | 2015-03-04 | 2015-05-27 | 中国地质科学院矿产资源研究所 | 一种位场构造格架自动提取方法 |
CN104965232A (zh) * | 2015-06-04 | 2015-10-07 | 中国地质科学院矿产资源研究所 | 低纬度地区磁构造格架自动提取方法 |
Non-Patent Citations (1)
Title |
---|
CAO, DIANHUA: "Porphyry Copper Deposit Model and Exploration Technique in Zhongdian, Yunnan", CHINA DOCTORAL DISSERTATIONS FULL-TEXT DATABASE (BASIC SCIENCES, 15 February 2008 (2008-02-15), pages 53 - 54, ISSN: 1674-022X * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117312898A (zh) * | 2023-11-27 | 2023-12-29 | 山东省煤田地质规划勘察研究院 | 一种基于多重k均值聚类分析的找矿预测方法及系统 |
CN117312898B (zh) * | 2023-11-27 | 2024-03-15 | 山东省煤田地质规划勘察研究院 | 一种基于多重k均值聚类分析的找矿预测方法及系统 |
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