CN112562078A - Three-dimensional geological analysis prediction model construction method - Google Patents
Three-dimensional geological analysis prediction model construction method Download PDFInfo
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Abstract
The invention discloses a method for constructing a three-dimensional geological analysis prediction model, which comprises the following steps: s1, obtaining drilling data of the three-dimensional geological model construction area; s2, triangulating and grouping the drilling data to form an initial triangulation network; s3, carrying out pinch-out processing on the initial triangulation network according to the pinch-out processing rule to generate a pinch-out processing triangulation network; s4, carrying out interpolation encryption processing on the pinch-out processing triangular net to generate a self-adaptive interpolation encryption processing triangular net; s5, carrying out staggered lamination on the adaptive interpolation encryption processing triangulation network to form a stratum, obtaining a stratum set, and generating a three-dimensional geological analysis prediction model; and S6, performing precision verification on the three-dimensional geological analysis prediction model, and if the precision is not qualified, jumping to the step S1, otherwise, determining the three-dimensional geological analysis prediction model generated in the step S5 as the final model. The method adopts pinch-out processing and interpolation encryption processing, so that the constructed model can fit a space entity to the maximum extent, and the precision of the model is improved.
Description
Technical Field
The invention relates to the technical field of geological three-dimensional model construction, in particular to a three-dimensional geological analysis prediction model construction method.
Background
At present, the acquisition cost of geological survey data in projects such as electric power and municipal works is high, and due to the limitation of geological survey cost, the whole geological survey data of actual projects are usually difficult to acquire, and the three-dimensional geological model can only be built according to the worst condition of acquired geological information, and the margin is large, so that the building cost is overhigh, and meanwhile, the built three-dimensional geological model has larger difference compared with the real geology. In addition, a 'one-project one-geological survey' mode is usually adopted, so that the historical geological survey data are accumulated more and a recycling way is lacked.
Disclosure of Invention
The invention mainly solves the technical problem that the three-dimensional geological model constructed by the original three-dimensional geological model construction method has larger difference compared with the real geology; the method for constructing the three-dimensional geological analysis prediction model is characterized in that the drilling data are triangulated and grouped, discrete points in the drilling data are associated, the effective utilization rate of the drilling data is improved, pinch-out processing and interpolation encryption processing are adopted, the constructed three-dimensional geological body model can be fitted with a space entity to the maximum extent, and the precision of the model is greatly improved.
The technical problem of the invention is mainly solved by the following technical scheme: the invention comprises the following steps:
s1, obtaining drilling data of the three-dimensional geological model construction area;
s2, triangulating and grouping the drilling data to form an initial triangulation network;
s3, carrying out pinch-out processing on the initial triangulation network according to the pinch-out processing rule to generate a pinch-out processing triangulation network;
s4, carrying out interpolation encryption processing on the pinch-out processing triangular net to generate a self-adaptive interpolation encryption processing triangular net;
s5, carrying out staggered lamination on the adaptive interpolation encryption processing triangulation network to form a stratum, obtaining a stratum set, and generating a three-dimensional geological analysis prediction model;
and S6, performing precision verification on the three-dimensional geological analysis prediction model, and if the precision is not qualified, jumping to the step S1, otherwise, determining the three-dimensional geological analysis prediction model generated in the step S5 as the final model.
Based on the drilling data of the three-dimensional geological model construction area as a modeling basis, triangulating and grouping the drilling data, and associating discrete points in the drilling data, so that the reutilization rate of the drilling data is improved, and the cost of geological survey is reduced; by adopting pinch-out processing and interpolation encryption processing, the constructed three-dimensional geological body model can be fitted with a space entity to the maximum extent, the precision of the model is greatly improved, the design precision of subsequent electric power, municipal works and other projects is improved on the basis, the whole project cost of the electric power, the municipal works and other projects is optimized, and the construction efficiency of the projects is also improved.
Preferably, the step S2 specifically includes:
s21, arranging the discrete points in the drilling data in an ascending order according to X coordinates, and if the X coordinates are equal, arranging the discrete points in the drilling data in an ascending order according to Y coordinates to form a point set;
s22, creating an auxiliary triangle and adding the auxiliary triangle into the working triangulation network, wherein the auxiliary triangle comprises all discrete points;
s23, taking the first point in the point set as an insertion point and deleting the first point from the point set;
s24, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is smaller than the X coordinate of the insertion point, judging that the circumscribed circle of the triangle is positioned on the left side of the insertion point, screening triangles positioned on the left side of the insertion point in the circumscribed circle, screening out triangles without auxiliary triangle vertexes, and moving the screened triangles out of the working triangulation network and then into the result triangulation network;
s25, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is more than or equal to the X coordinate of the insertion point, judging that the circumscribed circle of the triangle comprises the insertion point, putting the side of the triangle of which the circumscribed circle comprises the insertion point into a side set, deleting the side which repeatedly appears in the side set, connecting the insertion point with each side in the side set, forming the triangle and moving the triangle into the working triangulation network;
s26, judging whether the point set is an empty set, if not, jumping to the step S23, otherwise, jumping to the step S27;
and S27, moving the triangles which do not contain the auxiliary triangle vertex in the working triangulation network into the result triangulation network, namely forming the initial base network.
All the discrete points are sequenced according to X coordinates and then inserted in sequence, if the circumscribed circle of the triangle is positioned on the left side of the insertion point, namely the sum of the X coordinate of the center of the circumscribed circle and the X coordinate of the radius is still smaller than that of the insertion point, the circumscribed circle of the triangle does not contain the subsequent insertion point and can be directly placed into a result triangulation network, the test times can be reduced when the insertion test is carried out later, the times for testing whether the discrete points are positioned in the circumscribed circle of the triangle or not are greatly reduced, and the modeling efficiency is improved.
Preferably, the step S3 specifically includes:
and traversing all the triangular edges in the initial triangular network, and constructing a stratum pinch-out treatment virtual borehole at a pinch-out point according to a pinch-out treatment rule.
Preferably, the step S4 specifically includes:
s41, calculating an encryption level:
the encryption factor of each triangle of the pinch-out processing triangular net is
Wherein l is the side length of the longest side of the triangle, h is the height on the longest side, s is the area of the triangle,
the similarity between the shape of the triangle and the regular triangle is defined, alpha is an adjustable weight, the smaller alpha is the more easily the encryption factor is influenced by the area size of the triangle, the larger alpha is the more easily the encryption factor is influenced by the similarity between the shape of the triangle and the regular triangle, and the higher the encryption factor is, the higher the encryption level is;
s42, carrying out encryption processing on the pinch-out processing triangular net to form an encryption triangular net;
s43, calculating the elevation coordinates of each encrypted point by adopting an interpolation algorithm;
and S44, generating the adaptive interpolation encryption processing triangular network.
Because the cost of engineering drilling is high, only a limited number of drilling data can be obtained in a specific research area, the distribution is extremely uneven, the original sampling point data is directly utilized without any processing, and the aim of constructing an accurate and complete entity model cannot be realized. Different encryption levels are determined for each triangle in the triangular net according to the area size and the shape whether to be close to a regular triangle, so that the problem of model data redundancy or excessively harsh distortion of the model is avoided.
Preferably, the interpolation algorithm includes a linear interpolation method, a distance weight method and a spline surface method.
The spline function in the spline surface method has low times and certain smoothness, and is suitable for the condition that drilling data are more uniform and not very sparse in the interpolation of the three-dimensional geological model; the distance weight method is generally used for medium and small scale scattered point simulation in three-dimensional geological modeling; the linear interpolation method is suitable for occasions with huge data volume and low requirement on three-dimensional fidelity.
Preferably, the encryption level of each triangle of the pinch-off processing triangulation network is a power of 2.
And the phenomenon that 'cracks' appear on adjacent edges due to unequal encryption levels of adjacent triangles in the encryption process of pinch-out processing of the triangular network is prevented.
Preferably, in the process of forming the encryption triangulation network in step S42: when the encryption levels of the adjacent triangles are not equal, only the triangles with higher encryption levels need to be encrypted.
And the phenomenon that 'cracks' appear on adjacent edges due to unequal encryption levels of adjacent triangles in the encryption process of pinch-out processing of the triangular network is prevented.
Preferably, the step S5 specifically includes:
s51, constructing a generalized triangular prism set mapped by the triangles in the initial triangular network;
s52, constructing a mapping relation between an edge and a triangle and between an edge and a triangular prism, and setting the initial states of all the generalized triangular prisms in the generalized triangular prism set as successful;
s53, randomly extracting triangles from the initial triangular net, screening out triangular prisms which are in successful and unprocessed states in the generalized triangular prism set mapped by the triangles, obtaining the topmost triangular prism in the successful and unprocessed triangular prisms, performing seed method search on the lower surfaces of the topmost triangular prisms, searching all the lower surfaces of the unprocessed triangular prisms which are in successful states, and obtaining the triangular net belonging to the same geological property;
s54, obtaining the upper surfaces of the generalized triangular prisms where the triangles in the triangular network belong to the same geological attribute by using the topological mapping inertia of the generalized triangular prisms;
s55, sewing and connecting the boundaries of the upper surface and the lower surface to form a stratum;
and S56, repeating the steps S51-S55 to obtain a stratum set, splicing and combining the stratums in the stratum set from top to bottom in sequence according to the formation age from new to old to generate the three-dimensional geological analysis prediction model.
Preferably, the step S6 specifically includes:
s61, calculating the contrast of the real drilling data and the simulated drilling data corresponding to each stratum in the model: when the soil layer property measured by the real drilling hole of each stratum is different from the soil layer property measured by the virtual drilling hole, the contrast is pi0; when the soil layer property measured by the real drilling hole of each layer of stratum is the same as the soil layer property measured by the virtual drilling hole, the contrast is
Wherein, alpha, beta, eta are weighted values, and are all less than 1, DimaxMaximum layer thickness of the formation, D, measured for the actual boreholeiminThe minimum layer thickness of the formation measured for a real borehole,
average layer thickness of formation measured for real borehole, dimaxMaximum layer thickness of the formation, d, measured for a virtual boreholeiminThe minimum layer thickness of the formation measured for the virtual borehole,
the average layer thickness of the stratum measured by the virtual drilling is shown, i is the layer number of the stratum;
s62, calculating the contrast of the real drilling data and the simulated drilling data in the model
If P is greater than the set value, the three-dimensional geological analysis prediction model generated in step S5 is the final model, otherwise, step S1 is adjusted.
And the accuracy of the generated three-dimensional geological analysis prediction model is checked, so that the accuracy of the model is further ensured.
The invention has the beneficial effects that:
1) based on the drilling data of the three-dimensional geological model construction area as a modeling basis, triangulating and grouping the drilling data, and associating discrete points in the drilling data, so that the reutilization rate of the drilling data is improved, and the cost of geological survey is reduced;
2) by adopting pinch-out processing and interpolation encryption processing, the constructed three-dimensional geological body model can be fitted with a space entity to the maximum extent, the precision of the model is greatly improved, the design precision of subsequent electric power, municipal works and other projects is improved on the basis, the whole project cost of the electric power, the municipal works and other projects is optimized, and the construction efficiency of the projects is also improved;
3) all the discrete points are sequenced according to X coordinates and then inserted in sequence, if the circumscribed circle of the triangle is positioned on the left side of the insertion point, namely the X coordinate of the center of the circumscribed circle plus the X coordinate of which the radius is still smaller than that of the insertion point, the circumscribed circle of the triangle does not contain the subsequent insertion point and can be directly placed into a result triangulation network, and the number of testing times can be reduced when the insertion test is carried out later, so that the number of testing whether the discrete points are positioned in the circumscribed circle of the triangle is greatly reduced, and the modeling efficiency is improved;
4) different encryption levels are determined for each triangle in the triangular net according to the area size and the shape whether to be close to a regular triangle, so that the problem of model data redundancy or excessively harsh distortion of the model is avoided;
5) and the accuracy of the generated three-dimensional geological analysis prediction model is checked, so that the accuracy of the model is further ensured.
Drawings
FIG. 1 is a flow chart of a method of the present invention.
Fig. 2 is a diagram of a triangle encryption process.
FIG. 3 is a schematic diagram of the structure of adjacent sides of adjacent triangles with "cracks" created.
FIG. 4 is a diagram of a "crack" stitching process.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b): the method for constructing the three-dimensional geological analysis prediction model in the embodiment, as shown in fig. 1, includes the following steps:
s1, obtaining drilling data of a three-dimensional geological model construction area, wherein the drilling data comprises engineering space position data such as opening coordinates, azimuth and inclination angle of a drill hole, lithology and attitude of a rock stratum revealed by the drill hole, sample analysis data and various graphs;
s2, triangulating and grouping the drilling data to form an initial triangulation network;
s3, carrying out pinch-out processing on the initial triangulation network according to the pinch-out processing rule to generate a pinch-out processing triangulation network;
s4, carrying out interpolation encryption processing on the pinch-out processing triangular net to generate a self-adaptive interpolation encryption processing triangular net;
s5, carrying out staggered lamination on the adaptive interpolation encryption processing triangulation network to form a stratum, obtaining a stratum set, and generating a three-dimensional geological analysis prediction model;
and S6, performing precision verification on the three-dimensional geological analysis prediction model, and if the precision is not qualified, jumping to the step S1, otherwise, determining the three-dimensional geological analysis prediction model generated in the step S5 as the final model.
The drilling data are triangulated and grouped, discrete points in the drilling data are associated, the effective utilization rate of the drilling data is improved, pinch-out processing and interpolation encryption processing are adopted, a constructed three-dimensional geological body model can be fitted with a space entity to the maximum extent, the precision of the model is greatly improved, the design precision of subsequent electric power, municipal engineering and other engineering is improved on the basis, the whole engineering cost of the electric power, the municipal engineering and other engineering is optimized, and the construction efficiency of the engineering is also improved.
Step S2 specifically includes:
s21, arranging the discrete points in the drilling data in an ascending order according to X coordinates, and if the X coordinates are equal, arranging the discrete points in the drilling data in an ascending order according to Y coordinates to form a point set;
s22, creating an auxiliary triangle and adding the auxiliary triangle into the working triangulation network, wherein the auxiliary triangle comprises all discrete points;
s23, taking the first point in the point set as an insertion point and deleting the first point from the point set;
s24, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is smaller than the X coordinate of the insertion point, judging that the circumscribed circle of the triangle is positioned on the left side of the insertion point, screening triangles positioned on the left side of the insertion point in the circumscribed circle, screening out triangles without auxiliary triangle vertexes, and moving the screened triangles out of the working triangulation network and then into the result triangulation network;
s25, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is more than or equal to the X coordinate of the insertion point, judging that the circumscribed circle of the triangle comprises the insertion point, putting the side of the triangle of which the circumscribed circle comprises the insertion point into a side set, deleting the side which repeatedly appears in the side set, connecting the insertion point with each side in the side set, forming the triangle and moving the triangle into the working triangulation network;
s26, judging whether the point set is an empty set, if not, jumping to the step S23, otherwise, jumping to the step S27;
and S27, moving the triangles which do not contain the auxiliary triangle vertex in the working triangulation network into the result triangulation network, namely forming the initial base network.
All the discrete points are sequenced according to X coordinates and then inserted in sequence, if the circumscribed circle of the triangle is positioned on the left side of the insertion point, namely the sum of the X coordinate of the center of the circumscribed circle and the X coordinate of the radius is still smaller than that of the insertion point, the circumscribed circle of the triangle does not contain the subsequent insertion point and can be directly placed into a result triangulation network, the test times can be reduced when the insertion test is carried out later, the times for testing whether the discrete points are positioned in the circumscribed circle of the triangle or not are greatly reduced, and the modeling efficiency is improved.
Step S3 specifically includes:
and traversing all the triangular edges in the initial triangular network, and constructing a stratum pinch-out treatment virtual borehole at a pinch-out point according to a pinch-out treatment rule.
Step S4 specifically includes:
s41, calculating an encryption level:
the encryption factor of each triangle of the pinch-out processing triangular net is
Wherein l is the side length of the longest side of the triangle, h is the height on the longest side, s is the area of the triangle,
the similarity between the shape of the triangle and the regular triangle is defined, alpha is an adjustable weight, the smaller alpha is the more easily the encryption factor is influenced by the area size of the triangle, the larger alpha is the more easily the encryption factor is influenced by the similarity between the shape of the triangle and the regular triangle, and the higher the encryption factor is, the higher the encryption level is;
can be utilized in the above calculation process
Changing encryption factor to
Because alpha is an adjustable weight without absolute significance, the encryption factor can be directly written into
The height h of the triangle is avoided, so that the calculation efficiency is greatly improved;
s42, the pinch-out processing triangular network is encrypted to form an encrypted triangular network, the encryption processing comprises splitting from inside and splitting from edge, as shown in figure 2, wherein (a) splitting from inside refers to connecting one point inside the original triangle with three vertexes of the triangle, dividing the original triangle into three sub-triangles, and the sub-triangles can be decomposed recursively according to needs, wherein (b) splitting from edge,selecting splitting points on the edge from the edge splitting finger, equally dividing three edges n of the triangle into equal parts, and correspondingly connecting the equal dividing points to obtain n2A sub-triangle;
s43, calculating the elevation coordinates of each encrypted point by adopting an interpolation algorithm, wherein the interpolation algorithm comprises a linear interpolation method, a distance weight method and a spline surface method, the spline surface method is low in times of spline functions and has certain smoothness, the interpolation algorithm is suitable for the condition that drilling data are uniform and not sparse in the interpolation of a three-dimensional geological model, the distance weight method is generally used for small and medium-scale scattered point simulation in three-dimensional geological modeling, and the linear interpolation method is suitable for occasions with huge data volume and low requirements on three-dimensional fidelity, and the spline surface method is preferred in the embodiment;
and S44, generating the adaptive interpolation encryption processing triangular network.
Because the cost of engineering drilling is high, only a limited number of drilling data can be obtained in a specific research area, the distribution is extremely uneven, the original sampling point data is directly utilized without any processing, and the aim of constructing an accurate and complete entity model cannot be realized. Different encryption levels are determined for each triangle in the triangular net according to the area size and the shape whether to be close to a regular triangle, so that the problem of model data redundancy or excessively harsh distortion of the model is avoided.
In the encryption process of the pinch-out processing triangulation network, except for the original triangle coordinate, the drilling data is obtained, and other vertex data are obtained by interpolation, so when the encryption levels of adjacent triangles are not equal, a 'crack' may occur on adjacent edges, as shown in fig. 3, the encryption level of an upper triangle is 4, the encryption level of a lower triangle is 2, and L is the 'crack', in order to better suture the 'crack', the encryption level of the triangle is generally limited to be only the power of 2 (such as 2, 4, 8 … …), and when the encryption levels of the adjacent triangles are not equal, only the triangle with the higher encryption level needs to be processed.
For the stitching of the 'cracks', each triangle in the pinch-out processing triangulation network is processed in turn, and the triangle to be processed is called a target triangle. Considering the encryption level of the target triangle and the encryption levels of three adjacent triangles on three sides thereof, there are 7 cases: the encryption level of a target triangle is 0; the encryption level of the target triangle is 2, and the encryption levels of three adjacent triangles are all more than or equal to 2; the encryption level of the target triangle is 2, and the encryption level of at least one adjacent triangle is less than 2; fourthly, the encryption level of the target triangle is more than 2, and the encryption levels of the three adjacent triangles are all more than or equal to the target triangle; the encryption level of the target triangle is more than 2, and the encryption level of only one adjacent triangle is less than that of the target triangle; sixthly, the encryption level of the target triangle is more than 2, and the encryption levels of two adjacent triangles are less than that of the target triangle; the encryption level of the target triangle is greater than 2, and the encryption levels of three adjacent triangles are all smaller than the target triangle.
The specific sewing process of the 'crack' is shown in figure 4, and for the situation (i), (ii), the target triangle is subdivided according to the encryption level; for the case III, the encryption level of the target triangle is changed into 0; seventhly, reconstructing the subdivided triangles close to the common edge in the target triangle, taking the case sixthly as an example, and describing the following steps: the encryption level of a target triangle A is recorded as m, subdivided triangles adjacent to L1 and L2 in the target triangle are reconstructed for common edges L1 and L2 of two adjacent triangles with the encryption level smaller than that of the target triangle, the bisection points of the common edges of the adjacent triangles are bisection points in A because the encryption levels of the triangles are all powers of 2, the bisection points of the common edges of the adjacent triangles are also bisection points in A, a minimum trapezoid taking each bisection line segment of the adjacent triangles on the common edges as a base is taken in A, the subdivided triangles in the trapezoid are deleted, one top point on the lower base of the trapezoid is connected with each subdividing point on the upper base, the trapezoid is decomposed into a plurality of triangles again, and if the trapezoid contains the top point of the original large triangle, the top point is selected to be connected with the subdividing points on the upper base.
Step S5 specifically includes:
s51, constructing a generalized triangular prism set mapped by the triangles in the initial triangular network;
s52, constructing a mapping relation between an edge and a triangle and between an edge and a triangular prism, and setting the initial states of all the generalized triangular prisms in the generalized triangular prism set as successful;
s53, randomly extracting triangles from the initial triangular net, screening out triangular prisms which are in successful and unprocessed states in the generalized triangular prism set mapped by the triangles, obtaining the topmost triangular prism in the successful and unprocessed triangular prisms, performing seed method search on the lower surfaces of the topmost triangular prisms, searching all the lower surfaces of the unprocessed triangular prisms which are in successful states, and obtaining the triangular net belonging to the same geological property;
s54, obtaining the upper surfaces of the generalized triangular prisms where the triangles in the triangular network belong to the same geological attribute by using the topological mapping inertia of the generalized triangular prisms;
s55, sewing and connecting the boundaries of the upper surface and the lower surface to form a stratum;
and S56, repeating the steps S51-S55 to obtain a stratum set, splicing and combining the stratums in the stratum set from top to bottom in sequence according to the formation age from new to old to generate the three-dimensional geological analysis prediction model.
Step S6 specifically includes:
s61, calculating the contrast of the real drilling data and the simulated drilling data corresponding to each stratum in the model: when the soil layer property measured by the real drilling hole of each stratum is different from the soil layer property measured by the virtual drilling hole, the contrast is pi0; when the soil layer property measured by the real drilling hole of each layer of stratum is the same as the soil layer property measured by the virtual drilling hole, the contrast is
Wherein, alpha, beta, eta are weighted values, and are all less than 1, DimaxMaximum layer thickness of the formation, D, measured for the actual boreholeiminThe minimum layer thickness of the formation measured for a real borehole,
average layer thickness of formation measured for real borehole, dimaxMaximum layer thickness of the formation, d, measured for a virtual boreholeiminThe minimum layer thickness of the formation measured for the virtual borehole,
the average layer thickness of the stratum measured by the virtual drilling is shown, i is the layer number of the stratum;
s62, calculating the contrast of the real drilling data and the simulated drilling data in the model
If P is greater than the set value, the three-dimensional geological analysis prediction model generated in step S5 is the final model, otherwise, step S1 is adjusted.
And the accuracy of the generated three-dimensional geological analysis prediction model is checked, so that the accuracy of the model is further ensured.
Claims (9)
1. A three-dimensional geological analysis prediction model construction method is characterized by comprising the following steps:
s1, obtaining drilling data of the three-dimensional geological model construction area;
s2, triangulating and grouping the drilling data to form an initial triangulation network;
s3, carrying out pinch-out processing on the initial triangulation network according to the pinch-out processing rule to generate a pinch-out processing triangulation network;
s4, carrying out interpolation encryption processing on the pinch-out processing triangular net to generate a self-adaptive interpolation encryption processing triangular net;
s5, carrying out staggered lamination on the adaptive interpolation encryption processing triangulation network to form a stratum, obtaining a stratum set, and generating a three-dimensional geological analysis prediction model;
and S6, performing precision verification on the three-dimensional geological analysis prediction model, and if the precision is not qualified, jumping to the step S1, otherwise, determining the three-dimensional geological analysis prediction model generated in the step S5 as the final model.
2. The method for constructing a three-dimensional geological analysis prediction model according to claim 1, wherein the step S2 specifically comprises:
s21, arranging the discrete points in the drilling data in an ascending order according to X coordinates, and if the X coordinates are equal, arranging the discrete points in the drilling data in an ascending order according to Y coordinates to form a point set;
s22, creating an auxiliary triangle and adding the auxiliary triangle into the working triangulation network, wherein the auxiliary triangle comprises all discrete points;
s23, taking the first point in the point set as an insertion point and deleting the first point from the point set;
s24, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is smaller than the X coordinate of the insertion point, judging that the circumscribed circle of the triangle is positioned on the left side of the insertion point, screening triangles positioned on the left side of the insertion point in the circumscribed circle, screening out triangles without auxiliary triangle vertexes, and moving the screened triangles out of the working triangulation network and then into the result triangulation network;
s25, calculating the radius of the circumscribed circle of each triangle in the working triangulation network and the X coordinate of the circle center, if the value obtained by adding the X coordinate of the circle center of the circumscribed circle of the triangle and the radius is more than or equal to the X coordinate of the insertion point, judging that the circumscribed circle of the triangle comprises the insertion point, putting the side of the triangle of which the circumscribed circle comprises the insertion point into a side set, deleting the side which repeatedly appears in the side set, connecting the insertion point with each side in the side set, forming the triangle and moving the triangle into the working triangulation network;
s26, judging whether the point set is an empty set, if not, jumping to the step S23, otherwise, jumping to the step S27;
and S27, moving the triangles which do not contain the auxiliary triangle vertex in the working triangulation network into the result triangulation network, namely forming the initial base network.
3. The method for constructing a three-dimensional geological analysis prediction model according to claim 1, wherein the step S3 specifically comprises:
and traversing all the triangular edges in the initial triangular network, and constructing a stratum pinch-out treatment virtual borehole at a pinch-out point according to a pinch-out treatment rule.
4. The method for constructing a three-dimensional geological analysis prediction model according to claim 1, wherein the step S4 specifically comprises:
s41, calculating an encryption level:
the encryption factor of each triangle of the pinch-out processing triangular net is
Wherein l is the side length of the longest side of the triangle, h is the height on the longest side, s is the area of the triangle,
the similarity between the shape of the triangle and the regular triangle is defined, alpha is an adjustable weight, the smaller alpha is the more easily the encryption factor is influenced by the area size of the triangle, the larger alpha is the more easily the encryption factor is influenced by the similarity between the shape of the triangle and the regular triangle, and the higher the encryption factor is, the higher the encryption level is;
s42, carrying out encryption processing on the pinch-out processing triangular net to form an encryption triangular net;
s43, calculating the elevation coordinates of each encrypted point by adopting an interpolation algorithm;
and S44, generating the adaptive interpolation encryption processing triangular network.
5. The method of claim 4, wherein the interpolation algorithm comprises a linear interpolation method, a distance weighted method and a spline surface method.
6. The method according to claim 4, wherein the encryption level of each triangle of the pinch-out triangulated mesh is raised to a power of 2.
7. The method for constructing a three-dimensional geological analysis prediction model according to claim 4, wherein in the step S42 of forming the encrypted triangulation network: when the encryption levels of the adjacent triangles are not equal, only the triangles with higher encryption levels need to be encrypted.
8. The method for constructing a three-dimensional geological analysis prediction model according to claim 1, wherein the step S5 specifically comprises:
s51, constructing a generalized triangular prism set mapped by the triangles in the initial triangular network;
s52, constructing a mapping relation between an edge and a triangle and between an edge and a triangular prism, and setting the initial states of all the generalized triangular prisms in the generalized triangular prism set as successful;
s53, randomly extracting triangles from the initial triangular net, screening out triangular prisms which are in successful and unprocessed states in the generalized triangular prism set mapped by the triangles, obtaining the topmost triangular prism in the successful and unprocessed triangular prisms, performing seed method search on the lower surfaces of the topmost triangular prisms, searching all the lower surfaces of the unprocessed triangular prisms which are in successful states, and obtaining the triangular net belonging to the same geological property;
s54, obtaining the upper surfaces of the generalized triangular prisms where the triangles in the triangular network belong to the same geological attribute by using the topological mapping inertia of the generalized triangular prisms;
s55, sewing and connecting the boundaries of the upper surface and the lower surface to form a stratum;
and S56, repeating the steps S51-S55 to obtain a stratum set, splicing and combining the stratums in the stratum set from top to bottom in sequence according to the formation age from new to old to generate the three-dimensional geological analysis prediction model.
9. The method for constructing a three-dimensional geological analysis prediction model according to claim 1, wherein the step S6 specifically comprises:
s61, calculating the contrast of the real drilling data and the simulated drilling data corresponding to each stratum in the model: when the soil layer properties measured by the real drilling holes of each stratum are different from the soil layer properties measured by the virtual drilling holes,contrast ratio of pi0; when the soil layer property measured by the real drilling hole of each layer of stratum is the same as the soil layer property measured by the virtual drilling hole, the contrast is
Wherein, alpha, beta, eta are weighted values, and are all less than 1, DimaxMaximum layer thickness of the formation, D, measured for the actual boreholeiminThe minimum layer thickness of the formation measured for a real borehole,
average layer thickness of formation measured for real borehole, dimaxMaximum layer thickness of the formation, d, measured for a virtual boreholeiminThe minimum layer thickness of the formation measured for the virtual borehole,
the average layer thickness of the stratum measured by the virtual drilling is shown, i is the layer number of the stratum;
s62, calculating the contrast of the real drilling data and the simulated drilling data in the model
If P is greater than the set value, the three-dimensional geological analysis prediction model generated in step S5 is the final model, otherwise, step S1 is adjusted.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114509556A (en) * | 2022-01-10 | 2022-05-17 | 北京科技大学 | Method for predicting concentration of heavy metal pollutants in site |
| CN116721224A (en) * | 2023-05-31 | 2023-09-08 | 北京龙软科技股份有限公司 | Geological attribute dynamic modeling method based on stratum triangle network model |
| WO2023249111A1 (en) * | 2022-06-24 | 2023-12-28 | 株式会社デンソー | Triangle generation device, triangle generation method, and triangle generation program |
| WO2023249113A1 (en) * | 2022-06-24 | 2023-12-28 | 株式会社デンソー | Triangle generation device, triangle generation method, and triangle generation program |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015039375A1 (en) * | 2013-09-17 | 2015-03-26 | 中国科学院深圳先进技术研究院 | Method and system for automatically optimizing quality of point cloud data |
| CN108986213A (en) * | 2018-07-02 | 2018-12-11 | 南京师范大学 | A kind of three dimensional contour line method based on stacking technology |
| CN109003330A (en) * | 2018-07-02 | 2018-12-14 | 南京师范大学 | A kind of three dimensional contour line method based on basement rock boundary constraint |
-
2020
- 2020-12-04 CN CN202011415803.5A patent/CN112562078A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015039375A1 (en) * | 2013-09-17 | 2015-03-26 | 中国科学院深圳先进技术研究院 | Method and system for automatically optimizing quality of point cloud data |
| CN108986213A (en) * | 2018-07-02 | 2018-12-11 | 南京师范大学 | A kind of three dimensional contour line method based on stacking technology |
| CN109003330A (en) * | 2018-07-02 | 2018-12-14 | 南京师范大学 | A kind of three dimensional contour line method based on basement rock boundary constraint |
Non-Patent Citations (2)
| Title |
|---|
| 唐勇: "基于广义三棱柱的三维地质体建模及可视化研究", 《安徽农业科学》 * |
| 邵华: "自适应的三维地质建模插值加密方案", 《计算机工程》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114509556A (en) * | 2022-01-10 | 2022-05-17 | 北京科技大学 | Method for predicting concentration of heavy metal pollutants in site |
| WO2023249111A1 (en) * | 2022-06-24 | 2023-12-28 | 株式会社デンソー | Triangle generation device, triangle generation method, and triangle generation program |
| WO2023249113A1 (en) * | 2022-06-24 | 2023-12-28 | 株式会社デンソー | Triangle generation device, triangle generation method, and triangle generation program |
| CN116721224A (en) * | 2023-05-31 | 2023-09-08 | 北京龙软科技股份有限公司 | Geological attribute dynamic modeling method based on stratum triangle network model |
| CN116721224B (en) * | 2023-05-31 | 2024-05-31 | 北京龙软科技股份有限公司 | Geological attribute dynamic modeling method based on stratum triangle network model |
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