CN111932657B - Method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines - Google Patents
Method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines Download PDFInfo
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Abstract
The invention provides a method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines, which can accurately and automatically mark the positions of three characteristic lines, namely a trapezoidal pole belt, a closed contour line main shaft and a beaded abnormal walking line, in a contour map; a new method is provided for detecting the closed contour main shaft, the problem that the detection ladder pole zone of the Laplace operator is affected by a minimum value is solved, and the method for detecting the beaded abnormality through the generalized Hough transformation is supplemented and perfected.
Description
Technical Field
The invention relates to a detection method of heavy and magnetic anomaly characteristic lines in geophysical exploration, in particular to a qualitative interpretation and quantitative description method for automatic detection and drawing of the heavy and magnetic anomaly characteristic lines.
Background
The heavy and magnetic fields contain information of the distribution and structural background of magnetized substances or density anomalies in the earth crust, and the characteristic lines of the heavy and magnetic fields are important reflections on geological structures. For example, a gradient pole zone (i.e. a gradient maximum value zone) is a strip-shaped area with severe changes of heavy and magnetic anomalies, and often represents the contents of a fracture structure, a field source boundary and the like; the main axis direction of the closed contour is usually closely related to the formation trend; beaded anomalies tend to correspond to fractured structures invaded by the formation.
These characteristic lines have important applications in actual geophysical prospecting. For example, in the east Tianshan region, the earth house and the extra large porphyry type copper-molybdenum deposit of Yangtze east are located on the gradient zone of heavy and magnetic anomalies, and this feature is considered as a geophysical prospecting model to predict other copper-molybdenum deposits in the region (Zhang Jianmin et al, 2019). Aeromagnetic anomaly axial statistical analysis is applied to prospecting ores in the area of Beiliu in Xinjiang and plays an important role (Zhang wen bin bear flourishing blue 1998). In addition, when a magnetic method is adopted to find ores in a certain place in southern Anhui, three groups of fracture structures mainly distributed in a working area are displayed in a series of bead-shaped anomalies in a magnetic anomaly contour map to different degrees (Shehua Hejin spring, 2019).
The traditional method for drawing the characteristic lines is to manually mark on a contour map, which is time-consuming and labor-consuming and is influenced by subjective factors of interpreters. Therefore, some methods for automatically extracting the heavy and magnetic abnormal characteristic lines by using a computer are proposed in succession.
Cordell and Grauch discuss a boundary detection technique based on the position of horizontal gradients, which is further automated by Blakely and Simpson (Cordell and Grauch, 1985. However, the result is a set of discrete maxima that are not satisfactory for mapping into a feature line. The zero-value position of the Laplace operator is widely used for edge detection in the field of computer image processing, and there is also a method for applying the zero-value position to geologic body boundary detection in the geophysical field (wangming et al, 2015). However, the zero value of the second derivative corresponds to a minimum value in addition to the maximum value of the first derivative, and the characteristic line of detecting the gradient maximum value band by directly applying the Laplace zero value point is obviously not accurate enough. The problem is solved by the detection part of the echelon pole belt in the invention.
Liu Yan et al proposed a method to automatically detect and draw an axial map of aeromagnetic anomalies using a discrete Carlo transform (Liu Yan et al, 2002). At present, the detection method of the closed contour main shaft is still less in variety on the whole. The invention provides a detection method by using a least square method, and a new method is supplemented for the main shaft detection problem of the closed contour line.
The idea of applying generalized Hough transform to computer detection of aeromagnetic beaded anomalies is proposed by Hanying and Li Tong Lin, and the idea promotes the detection result of aeromagnetic beaded anomalies to the level of quantitative research (Hanying Li Tong Lin, 2003). However, the above prior art does not explicitly discuss two problems that affect the detection effect: firstly, one 'bead' abnormality may correspond to a closed contour line of multiple rings of phase sets, so that the problem of how to count one 'bead' for multiple times is solved; secondly, there may be two or more lines with similar angles and positions that cross a series of identical "beads", and which line is the most representative of the beaded abnormality.
Disclosure of Invention
The present invention aims to provide a method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines in view of the above shortcomings of the prior art.
The invention provides a method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines, which comprises the following steps:
a. reading in two-dimensional heavy and magnetic position field grid point data to be detected, drawing a planar contour map according to the data, and recording information of all closed contours;
b. fitting a straight line to each equivalence point on each closed contour line corresponding to the interested abnormal value on the plane contour line in the step a) by using a least square method to obtain parameters of the fitted straight line, and intercepting a line segment of the straight line near the closed contour line as a main axis of the closed contour line; (the outlier means a place on the plane contour map that is convex (higher altitude) or concave (lower altitude) compared to the surroundings;)
c. Based on the planar contour map in the step a), performing low-pass filtering on discrete heavy and magnetic data by using a mask method, calculating Laplace derivatives, drawing zero contour lines of the Laplace derivatives, setting a first derivative which influences the detection accuracy of a echelon band to be a minimum value or a first derivative to be a zero constant, and intercepting adjacent equivalue points which are too far away after screening;
d. screening closed contour lines based on the planar contour map in the step a), enabling one bead to only keep one closed contour line corresponding to the closed contour line, traversing grid points at certain intervals according to generalized Hough transformation, traversing all directions at certain angle intervals at all traversed grid points, constructing straight lines with different slopes and different intercepts, and judging and selecting the optimal straight line passing through enough beads as a trend line of the beaded abnormality;
e. obtaining a heavy and magnetic abnormal characteristic line image or a layer file based on the data in the steps a) to d). The heavy and magnetic abnormal characteristic line image or image layer comprises: the base map is an original abnormal contour map, and a layer on which a closed contour main shaft is drawn, a layer of a ladder pole belt and a layer of a beaded abnormal trend line are respectively arranged on the base map.
Wherein the fitted linear equation in the step b) is y = M 1 +M 2 x; wherein M is 1 ，M 2 Representing the parameters of the linear equation.
Wherein, in the step b), M 1 And M 2 The solution is solved by the following equation:
Xβ＝Y
β＝(X T X) -1 X T Y
wherein X stores the independent variable (X) of discrete data in the equation i ) Beta stores the parameters of the equation of the straight line (M) 1 ,M 2 ) Y store the dependent variable of the discrete data in the equation (y) i )；x i And y i Respectively the horizontal and vertical coordinates of each point participating in the least square method; m1 and M2 are the slope and intercept, respectively, of the line fitted by the least squares method.
And C), setting a first derivative which influences the detection accuracy of the echelon pole belt to be a minimum value or setting the first derivative to be a zero constant, and performing truncation processing on adjacent equivalue points which are too far away after screening.
Wherein, the truncation principle in step C) is to truncate the selected zero contour line if there are two adjacent points whose distance is greater than the truncation threshold value on the zero contour line, that is, not connecting the part between the two points. The cutoff critical value is 1/6-1/3 of the total length of the plane contour map; in the specific operation process, the truncation critical value is converted into the grid number and substituted into the calculation.
Wherein the closed contour screening method in step d) comprises:
i, if A contains B, removing the closed contour line A;
II, if B comprises A, removing the closed contour line B;
III, if A does not contain B, B does not contain A either, then A and B are adjacent and are not removed;
where a, B represent any two closed contour lines.
In the step d), the closed contours recorded in the step a) are arranged in an array according to the sequence determined during contour tracing, and from the second closed contour, the judgment and the removal are respectively carried out on the second closed contour (A) and each closed contour (B) arranged in front of the second closed contour until the end, so that the screening of redundant closed contours is realized.
In the step d), the judgment standard of the optimal straight line is as follows: firstly, defining a central point and an average radius of a closed contour; defining the average X and Y of all equivalent points on the closed contour line as the horizontal and vertical coordinates of the central point; defining the average distance from each equivalent point to the central point as the average radius of the closed contour line; a straight line can be considered to pass through the "bead" when the distance from the central point to the straight line is less than the average radius of the closed contour; for several lines with similar angles and positions which pass through the same 'bead string', the distance from the central point of each 'bead' on the 'bead string' to the line and the minimum line are taken as the optimal solution.
Has the beneficial effects that: the heavy and magnetic abnormal characteristic line detection method provided by the invention can accurately and automatically mark the positions of three characteristic lines, namely a gradient pole belt, a closed contour line main shaft and a beaded abnormal walking line, in a contour map. A new method is provided for detecting the closed contour main shaft, the problem that the detection ladder pole zone of the Laplace operator is affected by a minimum value is solved, and the method for detecting the beaded abnormality through the generalized Hough transformation is supplemented and perfected.
The invention not only solves the problem of low efficiency of manual drawing, but also ensures the objectivity of the drawing result and improves the quantitative description level. Vectorized feature lines facilitate comprehensive interpretation with other geoscience data.
Drawings
FIG. 1 is a graph of the detection results of characteristic lines;
FIG. 2 is a diagram of the closed contour principal axis detection results;
FIG. 3 is a graph showing the detection result of the step belt;
FIG. 4 is a diagram showing the detection results of a string-like abnormal trend line;
figure 5 is a schematic diagram of the distribution trend of the closed contour points, (a) the equivalence points tend to be distributed with X
(b) The equivalence points tend to be distributed Y;
FIG. 6 is a diagram showing the relationship between the primary function, the first derivative and the second derivative, (a) the primary function f (t), (b) the first derivative f' (t) and (c) the second derivative f "(t);
FIG. 7 is an illustration of a second derivative zero value correspondence;
fig. 8 is a schematic diagram of a 3 x 3 low pass filter mask;
fig. 9 is a schematic diagram of a 3 x 3laplace mask;
FIG. 10 is a schematic diagram of generalized Hough transform trend line detection;
FIG. 11 shows several closely angled lines through the same "bead string";
FIG. 12 is a flow chart of the detection of the heavy and magnetic anomaly plane data characteristic lines.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
The invention provides a method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines, which comprises the following steps:
a. and reading in two-dimensional original weight and magnetic anomaly data and related parameters, and drawing a plane contour map for the two-dimensional original weight and magnetic anomaly data. And (3) tracking the contour lines, and simultaneously recording the information of all the closed contour lines separately for later drawing the main axes of the closed contour lines and the trend lines of the beaded anomalies.
In the step a, a grid method in thematic map making automation is adopted to draw a contour map, the maximum value and the minimum value of two-dimensional discrete data are extracted, and an equivalence interval and an equivalence range are planned. For a certain equivalence, the grid is traversed first, and all the equivalence point positions of the value are marked on the edges of the sub-grids. Then, the open contours are traced from the boundaries in four directions in sequence, and the remaining closed contours are traced. This is repeated for each contour until the planned contour is completely traced out. The traced contour line can be processed by interpolation to be smooth, and finally, a contour map is drawn or a layer file is output.
b. And selecting interested heavy and magnetic anomaly values, and fitting a straight line to each equivalence point on each closed contour line corresponding to the value by using a least square method. Considering that discrete equivalent points may tend to be distributed in the x or y direction (as shown in fig. 5), the residual sum of squares of y or x is required to be minimized accordingly. And after obtaining the parameters of the fitted straight line, intercepting the line segment of the straight line near the closed contour line as the main axis of the closed contour line.
Step b uses a least squares method which fits a straight line y = M by minimizing the sum of squares of the errors and finding the best functional match of the data 1 +M 2 x。
Xβ＝Y
X stores independent variable (X) of discrete data in equation i ) Beta stores the parameters of the equation of the straight line (M) 1 ,M 2 ) Y store the dependent variable of the discrete data in the equation (y) i )。
β＝(X T X) -1 X T Y
The linear equation parameter M can be calculated according to the formula 1 ，M 2 。
The above is a case where the discrete points tend to be distributed in the x direction, fitting is performed on the condition that the sum of squared residuals of y is minimum, and when the discrete points tend to be distributed in the y direction, fitting is performed on the condition that the sum of squared residuals of x is minimum. In order to omit the step of judging the distribution trend of the discrete equivalent points, two conditions are calculated simultaneously, and the smaller sum of the squares of the residual errors is taken as the final result.
If the automation degree is further improved, the step b can adopt the closed contour screening method in the same step d instead of the method of manually selecting the interested heavy and magnetic abnormal values, and then the main shaft is fitted to the screened closed contour. The purpose of both methods is to avoid the problem of multiple major axes crossing or crowding together as a result of the multiple loop closed contour nesting. The former is more targeted to outliers and the latter is more automated.
c. The two-dimensional discrete weight and magnetic data are low-pass filtered by using a mask method, laplace derivatives are calculated, a 3 x 3-scale mask window (shown in figures 8 and 9) is overlapped on the original abnormal grid, and the mask is moved to traverse the whole abnormal grid. The grid and the data at the corresponding point of the mask are multiplied, and the result obtained by adding the 9 products is the numerical result at the center of the mask window. And drawing a zero contour line according to the calculation result of the Laplace derivative, setting a filtering condition, and eliminating two conditions influencing the detection accuracy of the echelon band so that the corresponding equivalence point does not participate in drawing the contour line. And if the distance between two adjacent points is too far on one isoline after screening, the middle part of the two points is cut off.
In step c, the Laplace derivative is substantially the second derivative of the missing directional information, and a zero value of the second derivative corresponds to a maximum or a minimum of the first derivative (see fig. 6). This feature can be used to detect the position of the ladder strap. Since the operation of the Laplace operator is a kind of high frequency filtering, a large amount of high frequency noise is often generated, which affects the continuity of contour tracing. Therefore, it is necessary to perform a low-pass filtering process on the data before calculating the Laplace derivative.
In step c, the Laplace derivative zero point is sensitive to several other conditions besides the first derivative maximum (see fig. 7):
(a) Maximum of first derivative
(b) First derivative minimum
(c) The first derivative being a non-zero constant whose primary function varies linearly
(d) The first derivative is almost constant and zero, and its primitive function is almost unchanged
Wherein (a) and (c) are interesting, and (b) and (d) interfere with the tracking of the echelon strip, and need to be eliminated. And (b) filtering out the minimum value condition by setting a threshold to eliminate the condition (d) that the gradient amplitude in the zero equivalent point is small and comparing the gradient amplitude at the zero equivalent point with the values at two adjacent points in the gradient direction of the zero equivalent point, so that the screened zero equivalent point does not participate in the drawing of the contour line. The gradient amplitude at a certain point on the grid can be obtained by designing a plurality of masks to respectively calculate the first derivatives in different directions and then approximating the maximum one of the absolute values of the derivatives in each direction.
Considering that a zero contour of the Laplace derivative may be continuously screened by the above processing to remove a plurality of points, in order to ensure the accuracy of the detection of the echelon belt, if two adjacent points with too far distance exist on the screened zero contour, the zero contour is truncated, that is, a part between the two points is not connected.
d. And c, screening the closed contour lines recorded in the step a, so that only one closed contour line is reserved for one 'bead'. Then according to generalized Hough transformation, traversing the grid points at certain intervals, and traversing each direction at each point at certain angle intervals to construct different straight lines. By judgment, the optimal straight line passing through enough "beads" (i.e., the closed contour) is selected as the trend line of the beaded anomaly (see fig. 10).
In step d, considering that a "bead" may correspond to multiple nested closed contours, in order to avoid the problem that a "bead" is counted many times, the closed contours need to be screened first, so that a "bead" corresponds to a closed contour only by one closed contour. The undersized closed contour (almost a point, hard to see from the naked eye on the graph) is first removed. And screening out the closed contour line of the innermost circle from the rest contour lines by the following method.
For any two closed contour lines a, B, there are only three cases of their positional relationship: (a) A comprises B; (B) B comprises A; and (c) A is adjacent to B. To determine whether a contains B, it is only necessary to determine whether any point in B is in a, i.e., whether the point is within the polygon. This determination can be realized by referring to a monotonicity and correlation edge-based polygon inner and outer point determination algorithm proposed by lie base extension et al. Similarly, it can be determined whether B contains a. If:
i, A contains B, the closed contour line A is removed
II, B contains A, the closed contour B is removed
III, A does not contain B, B does not contain A, and A and B are not removed adjacently
Starting from the second closed contour, the above determination and removal are carried out respectively for (a) and each of the closed contours (B) preceding it, until the end. Thus, the screening of redundant closed contour lines is realized.
Step d, referring to the line detection method in the generalized Hough transform (as shown in FIG. 10), traversing (or traversing at certain intervals) each grid point, and marking each point (as x) 0 ,y 0 ) Traversing all directions at certain angle intervals (recording the positive included angle alpha with the y axis), and constructing a large number of straight lines with different slopes and different intercepts. Thus, each line may have three parameters (x) 0 ,y 0 And alpha) expression. For each line, the information of its passage through the "bead" is judged and recorded. A threshold is set and a line is considered likely to be the strike line for a beaded anomaly only if the number of "beads" it crosses is greater than the threshold.
As to how to judge whether the "beads" are crossed by straight lines, the following method is adopted: the center point and mean radius of the closed contour are first defined. Defining the average X and Y of all equivalent points on the closed contour line as the horizontal and vertical coordinates of the central point; the average distance of each contour point to the center point is defined as the average radius of the closed contour. A straight line can be considered to pass through the "bead" when the distance from the central point to the straight line is less than the average radius of the closed contour.
For several lines (as shown in fig. 11) with similar angles and positions, which pass through the same "bead string", the optimal solution is taken as the line with the minimum distance from the center point of each "bead" on the "bead string" to the line and the minimum distance.
e. And outputting an image or layer file, and superposing the characteristic line graph on other geological data for comprehensive interpretation. Obtaining a heavy and magnetic abnormal characteristic line image or a layer file based on the data in the steps a) to d). The heavy and magnetic abnormal characteristic line image or image layer comprises: the base map is an original abnormal contour map, and is respectively provided with a layer painted with a closed contour main shaft, a layer painted with a step belt and a layer painted with a beaded abnormal trend line, wherein the layers painted with the closed contour main shaft, the layer painted with the step belt and the layer painted with the beaded abnormal trend line are shown in fig. 2-4, and the combined layers are shown in fig. 1.
The method is different from the method of marking the characteristic lines with geological significance in the gravity-magnetic anomaly contour map in a manual mode, and the positions of the characteristic lines (points) can be quickly and automatically calculated by using a computer algorithm and only manually setting some simple parameters, and the characteristic lines are presented on a screen in a computer image mode.
In addition, it is relevant how to judge whether two straight lines pass through the same "bead string". After the screening of the closed contours is completed previously, all the "beads" on the contour map have been determined to be next in the array loaded with relevant information. Whether a certain straight line passes through each 'bead' is judged in sequence, the character 'a' represents that the straight line passes through the current 'bead', and the character 'b' represents that the straight line does not pass through the current bead. The characters are spliced into a character string, and the character string records the information of the condition that the straight line passes through each 'bead'. And comparing the character strings corresponding to the two straight lines, wherein if the character strings are consistent, the two straight lines pass through the same 'bead string', otherwise, the two straight lines do not pass through the same 'bead string'.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A method for automatically detecting and drawing heavy and magnetic abnormal characteristic lines is characterized by comprising the following steps:
a. reading in two-dimensional heavy and magnetic position field grid point data to be detected, drawing a planar contour map according to the data, and recording information of all closed contours;
b. fitting a straight line by using a least square method for each equivalence point on each closed contour line corresponding to the abnormal value of interest on the plane contour map in the step a) to obtain parameters of the fitted straight line, and intercepting a line segment of the straight line near the closed contour line as a main axis of the closed contour line;
c. based on the planar contour map in the step a), performing low-pass filtering on discrete heavy and magnetic data by using a mask method, calculating Laplace derivatives, drawing zero contour lines of the Laplace derivatives, setting a first derivative which influences the detection accuracy of a echelon band to be a minimum value or setting the first derivative to be a zero constant, and performing truncation processing on adjacent equivalue points which are too far away after screening;
d. screening closed contour lines based on the planar contour map in the step a), enabling one bead to only keep one closed contour line corresponding to the closed contour line, traversing grid points at certain intervals according to generalized Hough transformation, traversing all directions at certain angle intervals at all traversed grid points, constructing straight lines with different slopes and different intercepts, and judging and selecting the optimal straight line passing through enough beads as a trend line of the beaded abnormality;
e. and obtaining a heavy and magnetic abnormal characteristic line image or a layer file based on the data in the steps a) to d).
2. The method for automatically detecting and mapping the heavy and magnetic abnormal characteristic line according to claim 1, wherein the fitted linear equation in the step b) is y = M 1 +M 2 x; wherein M is 1 ，M 2 Representing the parameters of the linear equation.
3. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic line according to claim 2, wherein M) in the step b) 1 And M 2 Solving by the following equation:
Xβ＝Y
β＝(X T X) -1 X T Y
wherein X stores the independent variable (X) of discrete data in the equation i ) Beta stores the parameters (M) of the linear equation 1 ,M 2 ) Y store the dependent variable of the discrete data in the equation (y) i )；x i And y i Respectively the horizontal and vertical coordinates of each point participating in the least square method; m1 and M2 are the slope and intercept, respectively, of the line fitted by the least squares method.
4. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic line according to claim 1, wherein the step c) further comprises the steps of setting the first derivative which affects the detection accuracy of the echelon band to be a minimum value or setting the first derivative to be a zero constant, and performing truncation processing on adjacent equivalue points which are too far away after the screening.
5. The method for automatically detecting and drawing a heavy and magnetic abnormal characteristic line according to claim 4, wherein the truncation rule in step c) is to truncate two adjacent points with a distance greater than the truncation threshold value on the zero contour line after screening, i.e. not to connect the parts between the two points.
6. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic line according to claim 1, wherein the closed contour screening method in the step d) comprises the following steps:
i, if A comprises B, removing the closed contour line A;
II, if B comprises A, removing the closed contour line B;
III, if A does not contain B, B does not contain A either, then A and B are adjacent and are not removed;
where a, B represent any two closed contour lines.
7. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic line according to claim 6, wherein in the step d), the closed contour lines recorded in the step a) are arranged in an array according to the sequence determined during contour tracing, and the judgment and the removal are respectively carried out on the closed contour line (A) and each closed contour line (B) arranged in front of the closed contour line from the second closed contour line until the end, so that the screening of redundant closed contour lines is realized.
8. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic lines according to claim 6, wherein in the step d), the judgment criteria of the optimal straight line are as follows: firstly, defining a central point and an average radius of a closed contour; defining the average X and Y of all equivalent points on the closed contour line as the horizontal and vertical coordinates of the central point; defining the average distance from each equivalent point to the central point as the average radius of the closed contour line; a straight line can be considered to pass through the "bead" when the distance from the central point to the straight line is less than the average radius of the closed contour; for several lines with similar angles and positions passing through the same 'bead string', the distance from the center point of each 'bead' on the 'bead string' to the line and the line with the minimum distance are taken as the optimal solution.
9. The method for automatically detecting and drawing the heavy and magnetic abnormal characteristic lines according to any one of claims 1 to 8, wherein the image or the layer of the heavy and magnetic abnormal characteristic lines comprises: the base map is an original abnormal contour map, and a layer on which a closed contour main shaft is drawn, a layer of a ladder pole belt and a layer of a beaded abnormal trend line are respectively arranged on the base map.
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| CN103995944A (en) * | 2014-06-10 | 2014-08-20 | 中国地质大学（武汉） | Space abnormal extreme value unbiased isogram drawing method |
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