CN111968231B - Three-dimensional stratum modeling method based on geological map cutting section - Google Patents
Three-dimensional stratum modeling method based on geological map cutting section Download PDFInfo
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Abstract
The invention discloses a three-dimensional stratum modeling method based on geological map cutting section, which comprises the following steps: s1, editing a graph cut section to finish setting basic parameters required by modeling; s2, performing discrete sampling on the stratum boundary and the inner and outer areas to obtain the discrete distribution of stratum attributes in space; s3, carrying out interpolation calculation on the stratum three-dimensional space discrete points to generate a three-dimensional space stratum attribute data field; s4, performing iso-surface extraction from the three-dimensional space stratum attribute data field to obtain a three-dimensional contour surface of the stratum; s5, repeating the steps S2-S4 to obtain three-dimensional contour surfaces of all stratum; and S6, performing space splicing on the three-dimensional contour surfaces of all stratum to complete three-dimensional stratum modeling. The invention not only avoids the problems of complex contour matching, bifurcation, corresponding triangle network connection and the like in the two-dimensional contour reconstruction method, but also can obtain a three-dimensional vector geological model with higher precision; the method is suitable for stratum modeling under any complex condition, and has high modeling efficiency and wide application range.
Description
Technical Field
The invention relates to the fields of geology, mineral products and engineering, in particular to a three-dimensional stratum modeling method based on geological map cutting sections.
Background
Three-dimensional geologic modeling has been a technical hotspot and difficulty in engineering, geology and mineral industry research. The method reduces the underground geological structure morphology and petrophysical parameters through limited geological data, and has very important roles in engineering geological analysis, oil gas and mineral exploration and development. Due to the multiple nature and multiple solutions of geological data and the limitation of data acquisition means, the three-dimensional geological modeling is difficult and the implementation process is complex. Three-dimensional geologic modeling by adopting geologic map cutting sections is a common modeling mode.
The graph cut section modeling is to draw a series of parallel (or approximately parallel) section lines on a geological map, divide a three-dimensional geological target into a series of two-dimensional geological sections by adopting a geological analysis method, and then construct a three-dimensional target geological body model by adopting a three-dimensional reconstruction means. The technology of modeling by using graph cut sections mainly comprises two modes, namely a three-dimensional reconstruction technology based on two-dimensional contours; one is a three-dimensional grid modeling technique that rasterizes a two-dimensional profile.
The basic realization thinking of the three-dimensional surface reconstruction technology based on the two-dimensional contour is to intercept a series of two-dimensional parallel cross sections from a three-dimensional object, then extract boundary contour lines of each cross section aiming at a specific target, match adjacent contour lines in a three-dimensional space and connect corresponding triangles, thereby completing modeling of the surface of the three-dimensional object. Gridding modeling based on two-dimensional section is to grid the two-dimensional section according to attribute classification of geologic body, and then map to three-dimensional space to generate three-dimensional gridding geologic model. Compared with a gridded three-dimensional geological model, the three-dimensional surface reconstruction method based on the two-dimensional contour generates a three-dimensional vector data model, has high model precision and good visualization effect, and is the most commonly used three-dimensional modeling technology.
In studies based on parallel contour reconstruction of three-dimensional surfaces, only the contour reconstruction problem on two adjacent parallel planes is generally considered. Because the reconstruction problem of multi-layer contours can be reduced to the superposition of multiple adjacent parallel contour reconstruction surfaces, the connection of contours of adjacent sections is critical to complete the modeling. The connection of the contour lines mainly comprises three problems of contour correspondence, contour stitching and bifurcation, wherein the problems of contour correspondence and bifurcation are difficult problems. The existing algorithms have a plurality of limitations on adjacent contour lines, such as small spacing between adjacent tangent planes, high coverage degree between corresponding contour lines, similar shape and the like, and the algorithms related to the branching problem focus on solving the problem of correct connection between one contour line and a plurality of contour lines.
If the number of contours on the same layer exceeds one, then a correspondence problem for the contours (which contours on different layers belong to the same surface) must be determined. If the layer-to-layer distance is particularly small, the correspondence problem can be solved by the degree of coincidence of the contour lines [1] The method comprises the steps of carrying out a first treatment on the surface of the However, when the distance is large and the overlapping degree cannot obtain a correct result, the corresponding problem becomes a difficult problem. Even if the correspondence problem is solved, the branching problem needs to be solved (whether one contour line on one layer and a plurality of contour lines on the other layer belong to the same surface is determined by checking and analyzing the correspondence problem of the contour lines, and one contour line and a plurality of contour lines are connected into the object surface through a triangular patch by a branching structure). Numerous documents have discussed the branch and corresponding problems, but no satisfactory solution has been found to date [2][3][4] . Barequest proposes an optimized triangulation strategy based on dynamic programming algorithm, i.e. BPLI (Barequetps Piecewise Linear Interpolation) method [5][6] . For the input two-layer contour line, the method is not directly aimed at solving the branching problem and the corresponding problem, but is provided withThe method connects them into a three-dimensional surface that does not exhibit self-intersection. The method can obtain the accurate subdivision result of the topological structure for the complex surface, thereby skillfully bypassing the corresponding problem and the branch problem.
How to determine a desired combination from a plurality of acceptable surface combinations, the methods currently employed are: method for maximizing volume of three-dimensional body after reconstruction [7] Surface area minimization method [8] Short-side length method [9] Shortest diagonal method [10] Method for synchronously advancing adjacent contour lines [11] Construction algorithm based on domain knowledge [12] Incision-suture method [13] Etc. For solving the problem of reconstruction of adjacent contour lines with large difference between the shape and the number of vertexes, the methods have limitations in the aspects of adaptability, connection effect and efficiency.
He Jinguo [14] (2003) The BPLI is improved and tried to be researched, and a contour line segmentation matching algorithm and a new algorithm for solving the triangulation of the space polygon are provided so as to eliminate the degradation area and improve the matching effect; qi Weili [15] (2007) And the like, a method for inserting a new contour line in the middle layer is provided, so that the problem of branch pair under the simple condition can be solved; what aversion to light [16] (2010) Based on the minimum surface area and maximum volume method, an Optimal Path (OP) algorithm is provided, and optimization attempts are carried out on contour connection; chen Xiaoqing [17] (2011) And the like, a polygon curve evolution method is provided, and the vertex matching and connection problems of adjacent contour lines are realized by simplifying the polygon and extracting the characteristic points of the polygon. However, this method is also aimed at the problem of connection corresponding to a single contour, and an elongated triangle may appear for a more complex contour; gao Shijuan [18] (2015) Introducing the realization of three-dimensional morphological reconstruction of a geological body with a single contour by a Discrete Smooth Interpolation (DSI) algorithm by means of GOCAD software; yang Yang [19] (2015) And the like, a mode of inserting transition contour lines between the contour lines is provided to improve modeling quality. Jing Yongbin [20] (2016) And the like, a contour line veneering algorithm is proposed, and a wavelet filter bank is utilized to simplify the contour line into low resolution similar to the current situation of the original contour lineThe low resolution contours are then optimally overlaid, and then connected triangles between the contours are constructed. The algorithm reduces the complexity of the directed loop graph algorithm to a certain extent, but similar veneers are difficult to obtain by filtering for adjacent contour lines with large differences.
Because the BPLI method models a complex topological structure, for complex contour construction, and particularly for certain complex contour data with relatively large slice distances, intersecting three-dimensional surface models are likely to appear, and correct three-dimensional model results are not obtained. These problems can be avoided by using a rasterized modeling approach.
The implementation technology of the rasterization modeling is simple, only the two-dimensional section is required to be rasterized, then a grid model of a three-dimensional space is generated through a three-dimensional interpolation algorithm, and finally the required stratum grid is extracted from the grid model. The three-dimensional geologic body in the grid model is expressed by adopting a block model, and the three-dimensional geologic body is discretized into regular geometric shapes (such as a hexahedral model, a tetrahedral model, a prismatic model and the like) in space. The modeling method does not need to consider a complex topological structure and triangle connection in space, is simple in implementation method, and is commonly used for mineral modeling, reserve estimation and the like. However, the method needs a large number of two-dimensional profile sections, the working amount of the profile sections is large, and the visualization effect of the three-dimensional model generated by the method is poor.
Wang Dan [21] (2012) The method has the advantages that the two-dimensional section is utilized, the two-dimensional section is rasterized and mapped into a three-dimensional space, and a three-dimensional grid model is generated by adopting octree; zhou Liangchen [22] (2013) And the method of combining cubic spline fitting and manual repair and editing is adopted to treat complex structures such as folds and the like so as to improve the quality of the grid model; zhang Baoyi [23] (2017) Et al describe the process of constructing a three-dimensional mesh model by rasterizing a cut section using a large number of parallel cut sections; li Chen [24] (2108) The method comprises the steps of generating a distance field of a two-dimensional section by adopting a distance function, then generating a three-dimensional attribute field by adopting a B spline interpolation method, and generating a place by adopting a method of extracting a physical equivalent surface by adopting a Maring cube algorithmThe contoured surface of the body. The method avoids the corresponding connection problem of complex contour lines and can be suitable for geological modeling under various complex conditions. However, the method is difficult to find an accurate boundary value through the three-dimensional physical property equivalent surface generated by the distance field, so that the boundary error of the constructed three-dimensional model is larger, and the result is inaccurate. Second, since the section distance field is a uniformly split grid, the grid data amount of the section will be large. If global interpolation is used to calculate the three-dimensional attribute field, a large amount of computer memory is required. The grid is divided into 20 sections according to 200 multiplied by 200, and the distance matrix is calculated by inverse distance weighted interpolation calculation, so that the memory consumption of the computer can reach 2384G
While the use of local interpolation algorithms can avoid this, the local interpolation method (or linear interpolation method) has significant limitations. The local interpolation method does not take into account the overall relevance of the space of the data distribution. Under the condition of sparse two-dimensional contour lines, fracture of modeling results can occur among contours, and the spatial distribution is discontinuous.
In summary, in the existing method for performing three-dimensional modeling based on the two-dimensional contour, the three-dimensional geological model with higher quality can be obtained by the three-dimensional surface reconstruction method based on the two-dimensional contour. However, the implementation technology is complex, and the requirement on the two-dimensional contour line is high. The corresponding contour line requires a simple convex polygon, and the non-simple polygon requires polygon simplification processing, so that modeling workload is increased. However, for the corresponding problems of complex multi-contours, the connection problems of triangle intersection, long and narrow trilateral shapes and the like of the contours with larger difference and far distance can occur, and the prior art still has no good solution. The cross-section grid modeling method based on rasterization can avoid the problems, and is simple in implementation technology. However, the grid mesh model is affected by subdivision, so that the model precision is low, the visualization effect is poor, and the grid mesh model has certain limitation in application. The method for extracting the equivalent surface modeling based on the three-dimensional attribute field has less research. The existing method has the problems of low section sampling precision, large sampling data volume, difficult three-dimensional attribute field interpolation, inaccurate contour extraction and the like.
Reference is made to:
[1]Meyers D,Skinner S.Surfaces from Contours[J].ACM Transactions on Graphics.1992,11(3):228～258.
[2]Klein R,Schilling A,StraBer W.Reconstruction and Simplification of Surfaces from Contours[J].Graphical Models.2000,62:429～443.
[3]Barequet G,Shapiro D,Tal A.Multilevel Sensitive Reconstruction of Polyhedral Surfaces from Parallel Slices[J].The Visual Computer.2000,16:116～133.
[4]Levin D.Multidimensional Reconstruction by Set 2valued Approximation[J].IMA J Numer Anal.1986,6:173～184.
[5]Barequet G,SharirM.Piecewise-linear Interpolation between Polygonal Slices[C].Proc 10th Ann ACM Symp onComputational Geometry(SoCG).1994.
[6]Barequet G,SharirM.Piecewise-linear Interpolation between Polygonal Slices[C].ComputerVision ImageUnderstanding.1996.63:251～272.
[7]Keppel E.Approximating complex surfaces by triangulationof contour lines[J].IBM Journal of Research and Development.1975,19(1):2-11.
[8]Fuchs H,Kedem Z M,Uselton S P.Optimal surfaces reconstruction from planar contours[J].Communication of the A CM.1977,20(10):693-702.
[9]Christiansen H N,Sederberg T W.Conversion of complex contour line definitions into polygonal element mosaics[J].Computer Graphics.1978,12(3):187-192.
[10] liu Gang, hu Yuan, deng Lin. Algorithm for surface reconstruction of layered three-dimensional bodies, J. University of Chengdu university, natl Science edition,2003,30 (5): 537-540 (Liu Gang, hu Yuan2lai, deng Lin. Distinguishing on the algorithm of reconstructing the superposition D surface J. Journal of Chengdu University of Technology, science & Technology Edition,2003,30 (5): 537-540).
[11] Tang Zesheng three-dimensional data field visualization [ M ]. Beijing: university of Qinghua Press 2000.
[12] Wang Ende, li Yan, bao Yu mineral three-dimensional visual modeling technique [ J ]. University of northeast university journal of Nature science edition 2005,26 (9): 890-892.
[13] Ma Hongbin, guo Jiateng A new multi-profile reconstruction three-dimensional shape algorithm, cutting-stitching method [ J ]. University of northeast university journal 2007,1.Vol 28) No.1.
[14] He Jinguo, cha Gongbin new algorithm for reconstructing three-dimensional surfaces from two-dimensional parallel contours based on BPLI [ J ]. University of Beijing (Nature science edition). 2003 (03)
[15] Qi Weili, qin Xinjiang, wang Xi, song Liping. Algorithm research on reconstructing three-dimensional surfaces based on two-dimensional parallel contours [ C ]. National 18 th computer technology and application (CACIS) academy of sciences, 2007.8, p891-895.
[16] And (5) aversion, wu Wenli. Based on the cross section contour line human-computer interaction three-dimensional geologic body modeling [ J ], a geophysical prospecting calculation technology, 2010,32 (4): P433-436.
[17] Chen Xiaoqing, ren Fengyu, zhang Guojian, but navigation, a complex mineral body adjacent section matching algorithm [ J ]. University of northeast university (Nature science edition), 2011,32 (4): 579-582.
[18] Gao Shijuan, mao Xiancheng, zhang Bao, et cetera. Three-dimensional modeling of geologic volumes based on planar geologic maps [ J ]. Geological prospecting forum, 2015,30 (4): 594-601.
[19] Yang Yang, pan, wu Gengyu, etc. A new contour three-dimensional geologic surface reconstruction method [ J ]. Scientific journal of earth information, 2015, 17 (3): 253-259.
[20] Jing Yongbin in the King of Sun Guang A two-dimensional contour reconstruction method for three-dimensional models of complex ore bodies [ J ]. Metal mine, 2016,285 (11): 124-127.
[21] Wang Dan three-dimensional geologic modeling method based on planar geologic map research [ D ].2012, university of Nanjing's master paper.
[22] Zhou Liangchen, lin Bingxian, wang Dan. Three-dimensional geologic body modeling methods for planar geologic maps research [ J ]. Scientific journal of Earth information 2013,15 (1): 46-54.
[23] Zhang Baoyi, yang Li, chen Xiaoyang. Three-dimensional modeling of regional mineralogical geologic bodies based on map-cut geologic profiles-taking the university of Gui southwest as example [ J ]. Jilin university journal (earth science edition), 2017,47 (3): 933-948.
[24] Li Chen Li Chen three-dimensional complex geologic body modeling technique based on section research [ D ]. University of Chengdu university's Shuoshi, 2018.
[25] Xia Yanhua, bai Shiwei Complex three-dimensional stratum model modeling based on level set and application research in underground engineering [ J ]. Geotechnical mechanics, 2012,33 (5): 1445-1450.
[26] Li Cheng the geological section map based on MT algorithm [ J ]. Digital communication 2014,41 (4): 35-41.
[27] Shuai Renjun, chen Shujing an improved MC three-dimensional reconstruction algorithm [ J ]. Chinese digital medicine, 2016,11 (3): 83-86.
[28] Wang Zheng, li Ruiming. Moving cube algorithm face ambiguity problem study [ J ]. Software engineering, 2017, 20 (9): 6-9.
[29] Wang Zheng three-dimensional surface modeling in profile data field [ J ]. Software engineering 2018,21 (3): 10-15.
Disclosure of Invention
Aiming at the problems of the existing modeling method, the invention provides a three-dimensional stratum modeling method based on geological map cut section, which combines the gridding modeling and geological model surface reconstruction together, thereby not only avoiding the problems of complex contour correspondence, triangle network connection and the like, but also obtaining a three-dimensional vector geological model with higher precision; and the problems of sampling precision and data volume in the modeling process, calculation of a three-dimensional data field by a global interpolation method, precision of contour extraction and the like are solved.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a three-dimensional stratum modeling method based on geological map cutting section comprises the following steps:
s1, editing a graph cut section to finish setting basic parameters required by modeling; the process for editing the graph cut section comprises the following steps: (1) Converting the plane coordinates of the section into three-dimensional coordinates of geological space through a calibration space positioning point; (2) obtaining formation parameter information by formation property filling; (3) Obtaining a contour boundary of the stratum through stratum boundary tracking;
s2, performing discrete sampling on the stratum boundary and the inner and outer areas, respectively setting respective sampling point attribute values of the stratum inside, the stratum boundary and the stratum outside, and then converting all the map-cut section sampling points into space three-dimensional coordinate points to form a space discrete point set;
s3, carrying out interpolation calculation on the three-dimensional space discrete points to generate a three-dimensional space stratum attribute data field;
s4, performing iso-surface extraction from the three-dimensional stratum attribute data field to obtain a three-dimensional contour surface of the stratum;
s5, repeating the steps S2-S4 to obtain three-dimensional contour surfaces of all stratum, and then executing the step S6;
and S6, performing space splicing on the three-dimensional contour surfaces of all stratum to complete three-dimensional stratum modeling.
Specifically, in the step S1, a quick flooding filling algorithm based on a linear queue is adopted to fill the stratum, and boundary points of the stratum are recorded to obtain a stratum polygon, so as to obtain stratum parameter information.
Specifically, in the step S1, for tracking the obtained formation boundary points, projection processing is adopted to eliminate the boundary point tracking error caused by the influence of the raster image display resolution, so as to ensure the consistency of the obtained formation contour boundary and the original formation contour boundary.
Further, the projection process includes the steps of:
(1) Simplifying the contour line of stratum, deleting redundant points on the contour line, and forming each two points into a contour line segment { L } k -k=1, 2,..n), the number of contour segments being N;
(2) Selecting a tracked formation boundary point P i (i=1, 2,., M) calculate the set of distances { D) of the point to all contour segments ik }(k＝1，2，..N)；
(3) From the distance set { D ik Find the line segment L of the minimum distance j Boundary point P i Projected to line segment L j Obtaining P ij Will P i Replaced by P ij As a new formation boundary point;
(4) Repeating the steps (2) and (3), and projecting all stratum boundary points onto stratum contour lines;
(5) Simplifying the projected stratum boundary contour line, deleting redundant points on the straight line, and completing stratum boundary tracking.
Specifically, the step S2 includes the steps of:
s2-1, setting a sampling interval step, sampling boundary points along the boundary of the stratum contour line to obtain a stratum boundary point set B1, and setting all point attribute values in the set as 1;
s2-2, setting a subdivision grid M multiplied by N with a specified size, performing two-dimensional grid subdivision on the graph cut section, and recording coordinates of central points of each grid to obtain a subdivision point set B2;
s2-3, judging the inside and outside of the stratum for the point in the set B2, if the point is in the stratum polygon, setting the attribute value of the point to be 1, otherwise, setting the attribute value to be 0;
s2-4, performing space coordinate conversion on all points in the sets B1 and B2, and converting the plane coordinate points into geological space coordinate points;
s2-5, placing the converted space coordinate points and the attribute values thereof into a scattered point data set { p } i (i=1, 2,., N), discrete spatial point data after formation sampling is obtained, completing the sampling.
Preferably, in the step S3, an inverse multi-element quadratic radial basis function is used as an interpolation function, and a radial basis function interpolation algorithm is adopted to perform three-dimensional discrete point spatial interpolation, so as to generate a three-dimensional spatial stratum attribute data field; the radial basis function is of the form:
wherein Z is 0 Is the interpolation point value to be estimated, w i Is the weight of the corresponding point, ||p i -p 0 I is p i And p is as follows 0 A distance therebetween;
the interpolation calculation process is as follows:
(1) Calculating distance matrix { D ij }(i＝1，2，...，N，j＝1，2，...，N)，
(2) An inverse distance matrix D is calculated by combining Gaussian elimination method with OpenCL multithreading acceleration technology -1 ；
(3) A matrix W of weight coefficients is calculated,
Z j is the jth discrete point P j Stratum attribute values of (2);
(4) Calculating field values of attributes and field values of any position in three-dimensional space
Preferably, in the step S4, a MarchingCubes algorithm is adopted to extract an isosurface from the three-dimensional attribute data field of the stratum as a three-dimensional surface contour of the stratum, and the process is as follows:
(1) Selecting 8 adjacent points from the three-dimensional grid data to form a hexahedron;
(2) Giving an isosurface value V0, judging the state value Vi of each node in the hexahedron, and setting the state of the node as 1 if Vi is more than V0; otherwise, setting to 0; i=1, 2, 8;
(3) According to the node state sequence, sequentially combining the node state sequences into binary bytes to obtain a hexahedral cell configuration table index value T i (0≤T i ≤255)；
(4) Index value T according to configuration i The corresponding edge node state combination is retrieved from the configuration table, and the intersection point coordinates P (x, y, z) of the equivalent surfaces with the edge node states of 0 and 1 at the edge are calculated according to the following calculation formula:
p(x，y，z)＝p 1(x，y，z) +(v-v1)/(v2-v1)*(p 2(x，y，z) -p 1(x，y，z) )
wherein p (x, y, z) is the coordinate of the intersection point to be solved, and v is the isosurface value to be calculated; p1 and p2 are coordinates of two nodes of an edge, and v1 and v2 are attribute values of the two nodes;
(5) Index value T according to configuration table i Retrieving corresponding triangle vertexes and connection sequences from the configuration table to form a closed triangle surface;
(6) And (5) traversing all grid cells, and repeating the steps (1) - (5) to obtain all triangular faces of the surface profile of the target stratum.
Specifically, the step S6 includes the steps of:
(1) Combining all vertexes, and removing repeated points to obtain a new vertex set;
(2) And modifying the triangular patch indexes of all models according to the new vertex set to finish three-dimensional stratum modeling.
Compared with the prior art, the invention has the following technical effects:
1. the method is applicable to stratum or geologic body modeling under any complex condition, and has wider application range compared with the existing modeling method based on two-dimensional contour lines, and the reason is that:
(1) The existing three-dimensional modeling method based on two-dimensional contour lines mostly adopts a modeling method for connecting the surfaces of the adjacent contours in space, has parallel or approximately parallel requirements on the graph cut section, and has higher manufacturing requirements on the graph cut section. The invention has no special requirement on the manufacture of the graph cut section, can model the graph cut section in any direction and any angle, and can even adopt the graph cut section which is not straight line (broken line).
(2) Because the global interpolation algorithm is adopted to carry out interpolation calculation on the stratum discrete sampling points, the method has no requirement on the spacing (or density) of the two-dimensional graph cut section. The profile may be a sparse contour line as long as it can control the spatial morphology of the three-dimensional geologic volume of the model to be built. In the invention, the inverse multi-element secondary radial basis function is used as an interpolation function, and the radial basis function interpolation algorithm is adopted to perform three-dimensional discrete point spatial interpolation, so that better model smoothness and spatial continuity can be obtained.
2. The modeling efficiency of the invention is higher, and the invention is mainly expressed in that:
(1) The graph cut section in any direction can be used for modeling, so that the workload of the graph cut section is greatly reduced, and the accuracy of the model is easier to control.
(2) The existing graph cut profile line is almost not required to be subjected to additional work such as splitting, simplifying, editing and modifying, and the like, and only the stratum is required to be filled and assigned with the attribute.
(3) A quick flooding algorithm based on a linear queue is adopted, a kernel function based on threads is created, and stratum boundaries are filled in a multithreading mode, so that the filling efficiency is improved.
3. The modeling accuracy of the invention is higher, and the invention is mainly expressed in that:
(1) Since the filling process is affected by the display resolution of the contour lines, the higher the graphic display resolution, the closer the tracked boundary points are to the true formation boundary. In the process of filling and detecting the stratum boundary, the invention carries out projection processing on the boundary points and the stratum contour lines, and automatically converts the tracked stratum boundary points into contour line boundary points so as to realize the consistency of the stratum tracking boundary points and the original stratum contour lines, reduce calculation errors of the stratum boundary points, improve the accuracy of model boundary detection and solve the problem that the edge detection depends on the resolution of display pixels.
(2) The boundary sampling and grid sampling are combined, so that the accuracy of the stratum original model is guaranteed, excessive sampling data volume is not generated, a three-dimensional attribute data field can be generated by using a three-dimensional global interpolation algorithm, an isosurface is extracted from the stratum three-dimensional attribute data field by combining a Marching cube algorithm to serve as the three-dimensional surface contour of the stratum, the accuracy of surface splicing of the three-dimensional contour of the subsequent stratum is fully guaranteed, and the modeling result is more reasonable and accurate.
In conclusion, the method improves the stratum boundary tracking algorithm and improves the precision of stratum boundary tracking based on the thought of the three-dimensional stratum attribute field; the special section sampling mode is adopted, so that the accuracy of stratum boundary sampling is guaranteed, excessive sampling data volume is not generated, and the guarantee is provided for the application of a three-dimensional global interpolation algorithm; the radial basis function and the GPU-based multithreading calculation technology are adopted, so that the spatial continuity and smoothness of the stratum model are guaranteed, and the calculation efficiency is high.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is a schematic drawing of a schematic cross-section of an embodiment of the present invention.
FIG. 3 is a schematic diagram of a straight section and a folded section of a drawing cut section in an embodiment of the present invention.
FIG. 4 is a schematic representation of formation packing in an embodiment of the present invention.
FIG. 5 is a graph showing the result of tracking formation boundary points using a flood fill algorithm in an embodiment of the present invention.
FIG. 6 is a schematic view of the formation boundary point projection and redundant point elimination results according to the embodiment of the present invention.
FIG. 7 is a diagram illustrating the result of layer boundary tracking, boundary point projection and redundant point elimination according to an embodiment of the present invention.
FIG. 8 is a schematic diagram showing the relationship between plane coordinates and space coordinates of a tangential section in an embodiment of the present invention.
FIG. 9 is a graph showing discrete sampling results of the formation boundary and grid in an embodiment of the present invention.
FIG. 10 is a schematic diagram of discrete sampling results of a three-dimensional space stratum of a schematic cut section in an embodiment of the invention.
FIG. 11 is a schematic diagram of the result of generating formation property data fields by three-dimensional interpolation of radial basis functions in accordance with an embodiment of the present invention.
FIG. 12 is a schematic view of a three-dimensional grid of formation boundaries with an attribute value of 1 in an embodiment of the present invention.
FIG. 13 is a schematic diagram showing the results of calculating the three-dimensional contour surface of the formation using the Marching Cubes algorithm in the present invention-example.
FIG. 14 is a schematic view of the results of a three-dimensional geologic model after stitching in an embodiment of the invention.
Detailed Description
The invention provides a three-dimensional stratum modeling method based on geological map cut sections, which mainly utilizes the geological map cut sections or other two-dimensional contour lines to carry out three-dimensional geological model modeling, wherein the modeling process is shown in figure 1 and mainly comprises the following steps:
s1, editing a graph cut section to finish setting basic parameters required by modeling; the process for editing the graph cut section comprises the following steps: (1) profile space positioning; (2) formation property filling; (3) formation boundary tracking; wherein: converting the plane coordinates of the section into three-dimensional coordinates of geological space through a calibration space positioning point; stratum parameter information is obtained through stratum attribute filling; obtaining a contour boundary of the stratum through stratum boundary tracking;
s2, performing discrete sampling on the stratum boundary and the inner and outer areas, respectively setting respective sampling point attribute values of the stratum inside, the stratum boundary and the stratum outside, and then converting all the map-cut section sampling points into space three-dimensional coordinate points to form a space discrete point set;
s3, carrying out interpolation calculation on the three-dimensional space discrete points to generate a three-dimensional space stratum attribute data field;
s4, performing iso-surface extraction from the three-dimensional stratum attribute data field to obtain a three-dimensional contour surface of the stratum;
s5, repeating the steps S2-S4 to obtain three-dimensional contour surfaces of all stratum, and then executing the step S6;
and S6, performing space splicing on the three-dimensional contour surfaces of all stratum to complete three-dimensional stratum modeling.
The invention will be further illustrated by the following description and examples, which include but are not limited to the following examples.
Examples
1. Editing cut sections
Fig. 2 shows a schematic diagram of a cut-away cross-section, supporting vector graphics formats (e.g., DXF) or raster graphics formats (JPG, GIF, BMP, etc.). The graph cut section editing comprises the following steps:
(1) And loading a DXF graph cut section graph, selecting four corner points (at least 2 positioning points are needed) on the graph cut section, setting three-dimensional space coordinates of the 4 corner points, and mapping the graph cut section to a space coordinate system. The present invention supports a cut-out section that is either a straight section or a folded section. The straight section means that a straight line is used to produce a drawing section, and the folded section means that a broken line is used to produce a drawing section. The space locating points corresponding to the folding sections are marked on the turning points of the folding lines, as shown in fig. 3;
(2) Selecting a stratum, filling the stratum by adopting a flooding filling algorithm, recording stratum boundary points to obtain stratum polygons, and setting the name and attribute value (stratum unique identification number) of the stratum, wherein the figure 4 is shown;
(3) Because the error exists between the stratum boundary point obtained by the tracking of the flooding filling algorithm and the actual stratum contour boundary (as shown in fig. 5), the stratum boundary point needs to be subjected to projection processing to obtain an accurate stratum boundary, and the projection processing steps are as follows:
a. simplifying the stratum contour line and deleting redundant points on the contour line. Every two points are then combined into a contour line segment { L ] k -k=1, 2,..n), the number of contour segments being N;
b. selecting a tracked formation boundary point P i (i=l, 2,., M) calculate the set of distances { D) of the point to all contour segments ik }；
c. From the distance set { D ik Find the line segment L of the minimum distance k Boundary point P i Projected to line segment L k Obtaining P ik Will P i Replaced by P ik As a new formation boundary point;
d. repeating the steps b and c, and projecting all stratum boundary points onto stratum contour lines;
e. simplifying the projected stratum boundary contour line, deleting redundant points on the line, and completing stratum boundary tracking (shown in fig. 6 and 7).
2. Discrete sampling and combination into a set of spatially discrete points
(1) Setting an interval step, sampling boundary points along the boundary of the stratum contour line to obtain a stratum boundary point set B1, and setting all point attribute values in the set to be 1;
(2) Setting a subdivision grid M multiplied by N (for example, M=100, N=80) with a specified size, performing two-dimensional grid subdivision on the graph cut section, and recording the coordinates of the central point of each grid to obtain a subdivision point set B2;
(3) Carrying out stratum inside and outside judgment on the point in the set B2, wherein if the point is in a stratum polygon, the attribute value of the point is 1, otherwise, the attribute value is 0;
(4) Performing space coordinate conversion on all points in the sets B1 and B2, and converting plane coordinate points into geological space coordinate points; the conversion process is as follows (as shown in fig. 8):
wherein P (x, y) is the coordinates of the plane point to be converted, and P' (x, y, z) is the converted space coordinates; p1 and P2 are plane coordinates of a locating point section where the point P is located, V1 (x, y, z), and V2 (x, y, z) are space coordinates corresponding to the point P1 and P2; y1 is the minimum value of the positioning point in the Y direction of the plane, and Y2 is the maximum value of the positioning point in the Y direction of the plane; zmin and Zmax are the corresponding minimum elevation and maximum elevation values in space;
the calculation formula for converting the plane point P (x, y) coordinates into the spatial coordinates P' (x, y, z) is as follows:
p′ x ＝V1 x +(p x -p1 x )*(V2 x -V1 x )/(p 2x -p1 x )
p′ y ＝V1 y +(p x -p1 x )*(V2 y -V1 y )/(p 2x -p1 x )
p′ z ＝Z min +(Z max -Z min )*(p y -Y1)/(Y2-Y1)
the distribution of sampling points after sampling the graph cut section is shown in fig. 9;
(6) And (3) putting the converted space coordinates and attribute values (0 or 1) thereof into a scattered point data set S to obtain scattered space point data (shown in figure 10) after stratum sampling.
3. Generating three-dimensional spatial stratigraphic attribute data fields
And carrying out three-dimensional discrete point spatial interpolation by adopting a radial basis function interpolation algorithm to generate a three-dimensional spatial stratum attribute data field. The radial basis function is of the form:
wherein Z is 0 Is the interpolation point value to be estimated, w i Is the weight of the corresponding point, ||p i -p 0 I is p i And p is as follows 0 Distance between them. The basis function adopts an inverse polynary quadratic function, and the function form is as follows:
the interpolation calculation process is as follows:
(1) Calculating distance matrix { D ij }(i＝1，2，...，N，j＝1，2，...，N)，
(2) An inverse distance matrix D is calculated by combining Gaussian elimination method with OpenCL multithreading acceleration technology -1 ；
(3) A matrix W of weight coefficients is calculated,
Z j is the jth discrete point P j Stratum attribute values of (2);
(4) Calculating field values of attributes and field values of any position in three-dimensional space
The three-dimensional attribute data field after the three-dimensional interpolation is completed is shown in fig. 11, and the grid distribution with the attribute value of 1 is shown in fig. 12.
4. Obtaining a three-dimensional contoured surface of a formation
And extracting an isosurface with an attribute value of l from a stratum three-dimensional attribute data field by using a MarchingCubes algorithm as a three-dimensional surface contour of the stratum, and completing three-dimensional modeling of the stratum, as shown in fig. 13.
The MarchingCubes algorithm extracts the iso-surface as follows:
(1) Selecting 8 adjacent points from the three-dimensional grid data to form a hexahedron;
(2) Giving an isosurface value V0, judging the state value Vi of each node in the hexahedron, and setting the state of the node as 1 if Vi is more than V0; otherwise, setting to 0; i=1, 2, 8;
(3) According to the node state sequence, sequentially combining the node state sequences into binary bytes to obtain a hexahedral cell configuration table index value T i (0≤T i ≤255)；
(4) Index value T according to configuration i The corresponding edge node state combination is retrieved from the configuration table, and the intersection point coordinates P (x, y, z) of the equivalent surfaces with the edge node states of 0 and 1 at the edge are calculated according to the following calculation formula:
p(x，y，z)＝p 1(x，y，z) +(v-v1)/(v2-v1)*(p 2(x，y，z) -p 1(x，y，z) )
wherein p (x, y, z) is the coordinate of the intersection point to be solved, and v is the isosurface value to be calculated; p1 and p2 are coordinates of two nodes of the edge, v1 and v2 are attribute values of two nodes (coordinates meet a vector algorithm); in the embodiment, the HashMap linear table is adopted to store the edge intersection points, so that the equivalent surface and each edge intersection point are not repeatedly calculated and repeatedly stored;
(5) Index value T according to configuration table i Retrieving corresponding triangle vertexes and connection sequences from the configuration table to form a closed triangle surface;
(6) And (5) traversing all grid cells, and repeating the steps (1) - (5) to obtain all triangular faces of the surface profile of the target stratum.
5. Repeating the above flow to create three-dimensional surface models of all strata.
6. Completion of three-dimensional formation modeling
All stratum models are spliced in space, and the splicing process is as follows:
(1) Combining all vertexes, and removing repeated points to obtain a new vertex set;
(2) The triangular patch indexes of all models are modified according to the new vertex set.
Thus, a three-dimensional model is generated and output in a three-dimensional graphics format (e.g., obj or ply), thereby completing three-dimensional formation modeling, as shown in fig. 14.
The three-dimensional vector geological model has reasonable and strict design, avoids the problems of complex contour correspondence, triangle network connection and the like, and can obtain a high-precision three-dimensional vector geological model. The invention breaks through the limitation of the prior art well, conforms to the trend of technological development, and well matches the requirement of engineering on three-dimensional geological modeling in the current stage. Therefore, compared with the prior art, the invention has obvious technical progress and outstanding substantive characteristics and remarkable progress.
The above embodiment is only one of the preferred embodiments of the present invention, and should not be used to limit the scope of the present invention, and all the modifications or color changes that are not significant in the spirit and scope of the main body design of the present invention are still consistent with the present invention.
Claims (3)
1. The three-dimensional stratum modeling method based on the geological map cutting section is characterized by comprising the following steps of:
s1, editing a graph cut section to finish setting basic parameters required by modeling; the process for editing the graph cut section comprises the following steps: (1) Converting the plane coordinates of the section into three-dimensional coordinates of geological space through a calibration space positioning point; (2) obtaining formation parameter information by formation property filling; (3) Obtaining a contour boundary of the stratum through stratum boundary tracking; in the step, for tracking the obtained stratum boundary points, projection processing is adopted to eliminate boundary point tracking errors caused by the influence of grid image display resolution, and ensure the consistency of the tracked stratum contour boundaries and the original stratum contour boundaries, wherein the projection processing comprises the following steps:
(a) Simplifying the contour line of stratum, deleting redundant points on the contour line, and forming each two points into a contour line segment { L } k -k=1, 2,..n), the number of contour segments being N;
(b) Selecting a tracked formation boundary point P i (i=1, 2, …, M), the set of distances { D) of the point to all contour segments is calculated ik }(k＝1,2,..N)；
(c) From the distance set { D ik Find the line segment L of the minimum distance j Boundary point P i Projected onto a lineSegment L j Obtaining P ij Will P i Replaced by P ij As a new formation boundary point;
(d) Repeating steps (b) and (c), and projecting all stratum boundary points onto stratum contour lines;
(e) Simplifying the projected stratum boundary contour line, deleting redundant points on a straight line, and completing stratum boundary tracking;
s2, performing discrete sampling on the stratum boundary and the inner and outer areas, respectively setting respective sampling point attribute values of the stratum inside, the stratum boundary and the stratum outside, and then converting all the map-cut section sampling points into space three-dimensional coordinate points to form a space discrete point set; the method comprises the following steps:
s2-1, setting a sampling interval step, sampling boundary points along the boundary of the stratum contour line to obtain a stratum boundary point set B1, and setting all point attribute values in the set as 1;
s2-2, setting a subdivision grid M multiplied by N with a specified size, performing two-dimensional grid subdivision on the graph cut section, and recording coordinates of central points of each grid to obtain a subdivision point set B2;
s2-3, judging the inside and outside of the stratum for the point in the set B2, if the point is in the stratum polygon, setting the attribute value of the point to be 1, otherwise, setting the attribute value to be 0;
s2-4, performing space coordinate conversion on all points in the sets B1 and B2, and converting the plane coordinate points into geological space coordinate points;
s2-5, placing the converted space coordinate points and the attribute values thereof into a scattered point data set { p } i (i=1, 2, …, N), obtaining discrete space point data after stratum sampling, and completing sampling;
s3, carrying out interpolation calculation on the three-dimensional space discrete points to generate a three-dimensional space stratum attribute data field; in the step, an inverse multi-element secondary radial basis function is used as an interpolation function, a radial basis function interpolation algorithm is adopted to conduct three-dimensional discrete point spatial interpolation, and a three-dimensional space stratum attribute data field is generated; the radial basis function is of the form:
wherein Z is 0 Is the interpolation point value to be estimated, w i Is the weight of the corresponding point, ||p i -p 0 I is p i And p is as follows 0 A distance therebetween;
is an inverse multiple quadratic function;
the interpolation calculation process is as follows:
(f) Calculating distance matrix { D ij }(i＝1,2,…,N,j＝1,2,…,N)，
(g) An inverse distance matrix D is calculated by combining Gaussian elimination method with OpenCL multithreading acceleration technology -1 ；
(h) A matrix W of weight coefficients is calculated,
Z j is the jth discrete point P j Stratum attribute values of (2);
(i) Calculating field values of attributes and field values of any position in three-dimensional space
S4, performing iso-surface extraction from the three-dimensional stratum attribute data field to obtain a three-dimensional contour surface of the stratum; in the step, a Marching cube algorithm is adopted to extract an isosurface from a stratum three-dimensional attribute data field as a three-dimensional surface profile of the stratum, and the process is as follows:
(j) Selecting 8 adjacent points from the three-dimensional grid data to form a hexahedron;
(k) Giving an isosurface value V0, judging the state value Vi of each node in the hexahedron, and setting the state of the node to be 1 if Vi is more than V0; otherwise, setting to 0; i=1, 2, …,8;
(l) According to the node state sequence, the binary system is formed by sequential combinationBytes to obtain hexahedral cell configuration table index value T i (0≤T i ≤255)；
(m) indexing value T according to configuration i The corresponding edge node state combination is retrieved from the configuration table, and the intersection point coordinates P (x, y, z) of the equivalent surfaces with the edge node states of 0 and 1 at the edge are calculated according to the following calculation formula:
p(x,y,z)＝p 1(x,y,z) +(v-v1)/(v2-v1)*(p 2(x,y,z) -p 1(x,y,z) )
wherein p (x, y, z) is the coordinate of the intersection point to be solved, and v is the isosurface value to be calculated; p is p 1 、p 2 The coordinates of two nodes of the edge, and v1 and v2 are attribute values of the two nodes;
(n) indexing the value T according to the configuration table i Retrieving corresponding triangle vertexes and connection sequences from the configuration table to form a closed triangle surface;
(o) traversing all grid cells, and repeating the steps (j) - (n) to obtain all triangular faces of the surface profile of the target stratum;
s5, repeating the steps S2-S4 to obtain three-dimensional contour surfaces of all stratum, and then executing the step S6;
and S6, performing space splicing on the three-dimensional contour surfaces of all stratum to complete three-dimensional stratum modeling.
2. The three-dimensional stratum modeling method based on geological map cut sections according to claim 1, wherein in the step S1, a stratum is filled by adopting a quick flooding filling algorithm based on a linear queue, boundary points of the stratum are recorded, stratum polygons are obtained, and stratum parameter information is obtained.
3. The three-dimensional stratum modeling method based on geological map section according to claim 1, wherein the step S6 comprises the steps of:
s6-1, combining all vertexes, and removing repeated points to obtain a new vertex set;
s6-2, modifying the triangular patch indexes of all models according to the new vertex set, and completing three-dimensional stratum modeling.
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| CN117115391B (en) * | 2023-10-24 | 2024-01-12 | 中科云谷科技有限公司 | Model updating method, device, computer equipment and computer readable storage medium |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109326002A (en) * | 2018-11-27 | 2019-02-12 | 中南大学 | Ore-body modeling method, apparatus, system and storage medium based on borehole data |
| CN109584357A (en) * | 2018-11-27 | 2019-04-05 | 中南大学 | Three-dimensional modeling method, device, system and storage medium based on more contour lines |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005010797A2 (en) * | 2003-07-23 | 2005-02-03 | Lee Wook B | Improved 3d veloctiy modeling, with calibration and trend fitting using geostatistical techniques, particularly advantageous for curved-ray prestack time migration and for such migration followed by prestack depth migration |
| CN104715506B (en) * | 2015-04-01 | 2017-08-25 | 中国地质大学（北京） | The construction method of catamaran type geological model |
| CN106709987B (en) * | 2015-11-13 | 2020-01-17 | 星际空间（天津）科技发展有限公司 | Dynamic construction method of three-dimensional geological profile model |
| CN106097448A (en) * | 2016-06-08 | 2016-11-09 | 江西理工大学 | A kind of salt chamber wall rock geology three-dimensional modeling method under multiple features constraint |
| CN109753707B (en) * | 2018-12-25 | 2023-10-24 | 核工业北京地质研究院 | Method for extracting stratum boundary line by utilizing exploration line profile to develop three-dimensional modeling |
| CN110599594B (en) * | 2019-07-29 | 2021-07-20 | 成都理工大学 | Three-dimensional modeling method for rock physical structure |
| CN111415415B (en) * | 2020-03-31 | 2023-05-09 | 南京师范大学 | Automatic construction method of three-dimensional map cutting geological section |
-
2020
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109326002A (en) * | 2018-11-27 | 2019-02-12 | 中南大学 | Ore-body modeling method, apparatus, system and storage medium based on borehole data |
| CN109584357A (en) * | 2018-11-27 | 2019-04-05 | 中南大学 | Three-dimensional modeling method, device, system and storage medium based on more contour lines |
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