Internal space relation speculation method and system based on rock mass structural plane surface

Abstract

The invention discloses an internal space relation speculation method and system based on a rock mass structural surface. The method comprises the steps that based on rock mass structural plane recognition results of a ground plane, a joint plane and a fault plane, correlation of rock mass structural plane surface features and internal space relations of the rock mass structural plane surface features is constructed, and surface constraint conditions of the ground plane, the joint plane and the fault plane are determined; based on key control point setting, thickness constraint and geometric calculation of the triangulated irregular network, realizing thickness-invariant extension of the rock mass structural surface; based on thickness constraint, triangularization curved surface mesh deformation is achieved, and then thickness change extension between different depth layers is achieved; and the triangular irregular net is cut based on the intersecting lines of the intersecting rock mass structural surfaces, and stratum pinching is achieved. According to the method, occurrence information such as the inclination angle of the rock mass internal structure and the internal space relation of the rock mass structural plane are obtained by extending the surface of the structural plane, and then a rock mass internal space relation speculation result serves as an internal constraint to provide data support for subsequent three-dimensional modeling.

Description

Technical Field

[0001] The invention belongs to the field of geology, and in particular relates to a method and system for estimating the internal spatial relationship of sedimentary rocks. Background Art

[0002] The inference of the internal spatial relationship of rock mass structural surfaces is an important research field that provides basic data for geological engineering, civil engineering, mining engineering, etc., and ensures the feasibility and safety of engineering construction. Rock mass structural surfaces such as faults and large joints are crucial to rock mass stability, and therefore become key factors in engineering design and construction. The inference of the internal spatial relationship of rock mass structural surfaces is mainly carried out through the following two methods: one is to use spatial interpolation algorithms to interpolate between known data points; the other is to allow expert geological knowledge to establish connections between data points. The spatial interpolation algorithm derives the spatial attribute values ​​of unknown points by interpolating between known data points, and presents spatial characteristics with continuous data surfaces. The theoretical assumption of its implementation is that the closer the spatial position, the more similar the characteristic values ​​are, and vice versa. However, domestic and foreign research mainly relies on drilling data to infer the internal spatial relationship of rock mass structural surfaces. The sparsity of drilling data leads to insufficient accuracy and completeness of the constructed relationship, which is difficult to apply to the inference of the internal spatial relationship of complex geological bodies. The method combining expert geological knowledge is highly subjective and has poor reproducibility, which limits its application scenarios.

[0003] In general, many geostatistical and database techniques can be used to interpolate between geological measurements, especially at regional scales. However, these methods are often not suitable for unevenly distributed data and may not appropriately deal with qualitative and interpretative factors of geology. Summary of the invention

[0004] Purpose of the invention: In view of the shortcomings of the prior art, the present invention proposes a method and system for inferring the internal spatial relationship based on the surface of the rock mass structural surface, which obtains the inclination and dip angle and other attitude information of the internal structure of the rock mass and the internal spatial relationship of the rock mass structural surface by extending the surface of the structural surface, and then uses the inference results of the internal spatial relationship of the rock mass as internal constraints to provide data support for subsequent three-dimensional modeling.

[0005] Technical solution: According to the first aspect of the present invention, a method for inferring the internal spatial relationship based on the surface of a rock mass structural surface comprises the following steps:

[0006] S1: Extract the rock mass structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock mass structure, construct the association between the surface characteristics of the rock mass structure plane and its internal spatial relationship, determine the surface constraints of the stratigraphic plane, joint plane, and fault plane, and update the results to the fact base;

[0007] S2: Under the constraints determined in step S1, based on the key control point setting, thickness constraint and geometric calculation of the irregular triangulated network, the thickness of the rock structure surface is extended unchanged, specifically including: starting from the known control points, based on the occurrence and interpolation algorithm of the rock structure surface, the control point position of the unknown area is determined; according to the determined control point position, the boundary constraint of the rock structure surface is determined based on the Graham-Scan convex hull algorithm, and under the boundary constraint, each stratum is extended upward or downward from the reference plane, keeping the vertical distance from the reference plane unchanged;

[0008] S3: Obtain the thickness data between layers at different depths of the rock mass structure, obtain the layer thickness of each triangle of the irregular triangulated network at different depths through interpolation processing, realize the deformation of the triangulated surface mesh under the specified thickness constraint, and then realize the thickness change extension between layers at different depths;

[0009] S4: Obtain the surface data of the rock mass structural surface, calculate the intersection line of the intersecting rock mass structural surfaces, and cut the irregular triangulated network based on the intersection line to achieve stratum pinch-out.

[0010] According to certain implementations of the first aspect, in step S1, the constraint conditions include point constraint conditions, line constraint conditions, and surface constraint conditions, and the determination method is as follows:

[0011] Based on the Graham-Scan convex hull algorithm and the Douglas-Peuker point cloud feature thinning algorithm, the boundary point set of the rock mass structural surface is extracted. According to the boundary point set and under the specified key point extraction rules, the spatial information of all key points is obtained as the point constraint condition for internal relationship inference.

[0012] Extract rock mass structure traces based on digital image technology, and obtain all constraint line spatial information according to the rock mass structure traces under the specified constraint line extraction rules as the line constraint conditions for internal relationship inference;

[0013] Based on the regional growing method, the inclination and dip information of the rock mass structural surface is preliminarily extracted, and then the fact database is updated to store the inclination, dip and adjacent structural surface information of the rock mass structural surface as the surface constraint conditions for internal relationship inference.

[0014] According to certain embodiments of the first aspect, in step S2, starting from the known control points, based on the occurrence of the rock mass structure surface and the interpolation algorithm, the control point positions of the unknown area are determined, including:

[0015] Determine the stratigraphic interfaces that need to be extended, and identify key control points on each interface based on the key point spatial information obtained;

[0016] Determine the neighboring sampling points of the point to be interpolated, and calculate the elevation value of the interpolation point using the inverse distance weighted IDW algorithm based on the coordinate values ​​and elevation values ​​of these neighboring sampling points.

[0017] According to certain implementations of the first aspect, the IDW algorithm calculates the elevation value of the interpolation point, including:

[0018] For the interpolation point P (x, y, z) and its adjacent set of data points (X, Y, Z), i = 1, 2, 3 ... n, the elevation value of the interpolation point is calculated by the formula:

[0019]

[0020] w i (x) = 1 / d(x,x i ) m

[0021]

[0022] Among them, x i is the adjacent horizontal coordinate point, z i is the nearby elevation value, N is the number of sample points used for interpolation, m is a positive integer power, and w i It is the reciprocal of the sum of squared Euclidean distances between the interpolated point and its known neighboring points.

[0023] According to certain embodiments of the first aspect, in step S2, the boundary constraints of the surface of the rock mass structural plane are determined based on the Graham-Scan convex hull algorithm, and under the boundary constraints, each stratum is extended upward or downward from the reference plane to keep the vertical distance from the reference plane unchanged, including:

[0024] The boundary constraints of the rock mass structural surface are determined based on the Graham-Scan convex hull algorithm, and the internal boundaries of the rock mass structural surface are deduced under the constructed surface constraints.

[0025] Connect the upper and lower boundaries to construct the overall boundary constraint, and delete the interpolation points outside the boundary based on the boundary constraint;

[0026] Starting from the datum, extend each stratum upward or downward, maintaining a constant vertical distance from the datum.

[0027] According to certain embodiments of the first aspect, in step S3, the layer thickness of each triangle of the irregular triangulated network at different depths is obtained by interpolation processing, and the triangulated surface mesh deformation is realized under the specified thickness constraint, including:

[0028] For each triangle, interpolation processing is performed based on the depth information of its vertices and the corresponding inter-layer thickness data to calculate the layer thickness of each triangle at different depths;

[0029] According to the interpolated layer thickness data, new vertex coordinates are generated to represent the stratigraphic layers at different depths;

[0030] Taking into account the position restrictions of the surface mesh vertices, a new irregular triangulated network is constructed according to the obtained new vertex coordinates, and the new positions of the surface mesh vertices are calculated.

[0031] According to certain embodiments of the first aspect, in step S4, data of the rock formation structural surface is obtained, including the spatial position and geometric shape of the stratigraphic surface, and the intersection line of the intersecting rock formation structural surfaces is calculated based on the spatial position and geometric shape of the stratigraphic surface;

[0032] The irregular triangulated network is trimmed based on the intersection line to achieve stratum pinch-out, including: inserting the stratum pinch-out line into the irregular triangulated network as a constraint condition, and performing a trimming operation on the irregular triangulated network model according to the constraint line, thereby achieving the stratum pinch-out effect.

[0033] According to a second aspect of the present invention, a system for inferring internal spatial relations based on the surface of a rock mass structural surface comprises:

[0034] The constraint condition determination module is used to extract the rock structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock structure, to build the association between the surface characteristics of the rock structure plane and its internal spatial relationship, to determine the surface constraint conditions of the stratigraphic plane, joint plane, and fault plane, and to update the results to the fact base;

[0035] The thickness-invariant extension module is used to achieve thickness-invariant extension of the rock mass structure surface based on key control point setting, thickness constraints and geometric calculations of irregular triangulated networks under certain constraints. Specifically, it includes: a control point setting unit, which is used to determine the control point positions of unknown areas based on the occurrence and interpolation algorithms of the rock mass structure surface from known control points; a vertical extension unit, which is used to determine the boundary constraints of the rock mass structure surface based on the Graham-Scan convex hull algorithm according to the determined control point positions, and to extend each stratum upward or downward from the reference plane under the boundary constraints, keeping the vertical distance from the reference plane unchanged;

[0036] Thickness variation extension module is used to obtain thickness data between layers at different depths of rock mass structure, obtain the thickness of each triangle of irregular triangulated network at different depths through interpolation processing, realize triangulated surface mesh deformation under specified thickness constraints, and then realize thickness variation extension between layers at different depths;

[0037] The formation pinch-out processing module is used to obtain the surface data of the rock structure surface, calculate the intersection line of the intersecting rock structure surfaces, and cut the irregular triangulated network based on the intersection line to achieve formation pinch-out.

[0038] According to a third aspect of the present invention, there is provided a computer device comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the method for inferring internal spatial relationships based on the surface of a rock structure surface as described in the first aspect of the present invention are implemented.

[0039] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for inferring the internal spatial relationship based on the surface of a rock structure surface as described in the first aspect of the present invention.

[0040] Beneficial effects: The present invention designs an internal spatial relationship inference method based on the surface of the rock mass structural surface based on the high-precision point cloud data in the field, extracts the characteristic information of the surface point cloud data and the image data as the constraint condition, and on this basis constructs the association between the surface characteristics of the rock mass structural surface and its internal spatial relationship, and designs a rock mass structural surface extension algorithm under three scenarios of constant thickness, thickness change and formation pinch-out between rock mass structural surfaces based on the key control point setting, thickness constraint and geometric calculation of the irregular triangulated network. The present invention realizes the acquisition of the dip angle and other occurrence information of the internal structure of the rock mass and the internal spatial relationship of the rock mass structural surface by extending the structural surface, and then uses the inference result of the internal spatial relationship of the rock mass as the internal constraint to provide data support for subsequent three-dimensional modeling. Compared with the rock mass internal spatial relationship inference technology based on drilling data in the prior art, the method of the present invention is more convenient, has lower cost, and avoids the problem of inaccurate and incomplete inference relationship caused by sparse drilling, and can be applied to the inference of the internal spatial relationship of complex geological bodies, and has strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 3D model data (left) and triangulated network data (right) corresponding to the study area in the embodiment of the present invention;

[0042] Figure 2 It is a flow chart of the method for estimating the internal spatial relationship based on the surface of the rock mass structural surface of the present invention;

[0043] Figure 3 It is a schematic diagram of the level corresponding to the present invention;

[0044] Figure 4 It is a schematic diagram of the joint surface corresponding to the present invention;

[0045] Figure 5 is a schematic diagram of the fault geometric elements corresponding to the present invention;

[0046] Figure 6 is a flowchart of the region growing method corresponding to the present invention;

[0047] Figure 7 is a schematic diagram of constrained data point interpolation corresponding to the present invention;

[0048] Figure 8 is a schematic diagram of boundary constraints corresponding to the present invention;

[0049] Fig. 9 Analysis diagram of an example of an algorithm for inferring the internal spatial relationship based on the surface of the rock mass structural plane;

[0050] Fig.10 The initial surface mesh corresponding to the present invention (left) and the deformation algorithm application effect diagram (right);

[0051] Fig.11 It is a schematic diagram of the clipping algorithm of the irregular triangulated network corresponding to the present invention;

[0052] Fig.12 It is the inference result of the internal space relationship corresponding to the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0054] In the embodiment of the present invention, the small-scale rock mass structural characteristics of Nanjing Tangshan Mine Park are taken as the research object, and the surface data of the rock mass structural surface in the research area is obtained to infer the internal spatial relationship. The multi-rotor drone DJI M300 RTK is used as the flight platform and the DJI Zenmuse P1 is used as the payload to collect data in the research area, and the three-dimensional surface model is constructed using the oblique three-dimensional reconstruction technology to perform internal data processing, so as to obtain the scene point cloud and its three-dimensional surface model data of the research area, such as Figure 1 As shown, (a) is the three-dimensional model data corresponding to the study area, and (b) is the triangulated network data, which serve as the input of the method of the present invention.

[0055] Reference Figure 2 The method for estimating the internal spatial relationship based on the surface of the rock mass structural surface proposed by the present invention comprises the following steps:

[0056] Step (1) is to extract the rock structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock structure based on the regional growing method and the "rock structure feature identification method considering spatial relationships in complex scenes" (patent number: ZL202310739126.X) (see Figure 3-Figure 5 ), build the association between the surface characteristics of the rock mass structure surface and its internal spatial relationship, determine the surface constraints of the layer, joint surface and fault surface, and update the results to the fact base, including:

[0057] (1-1) Determine the point constraints when the structural surface is extended internally based on the geometric elements of the rock mass structure: Extract the boundary point set of the rock mass structural surface based on the Graham-Scan convex hull algorithm and the Douglas-Peuker point cloud feature thinning algorithm, and then set the extraction rules of key points in combination with the spatial relationship between the rock mass structural surfaces extracted by the patent, that is, define the rules in combination with the geographic knowledge base and fact base constructed by the patent (the intersection points of rock layers with topological or contact relationships in the fact base, the starting points of the sequence, etc. are defined as key points), and the rule engine of the patent is used to implement rule matching, agenda triggering, and Drools execution to obtain the spatial information of all key points as the point constraints for subsequent internal relationship inference;

[0058] (1-2) Determine the line constraints when the structural surface is extended internally based on the geometric elements of the rock mass structure: Extract the rock mass structure trace based on digital image technology (image segmentation-denoising-expansion corrosion-filtering-thinning and burr removal), and then set the extraction rules of key segments in combination with the spatial relationship between the rock mass structural surfaces extracted by the patent, that is, define the rules in combination with the geographic knowledge base and fact base constructed by the patent (the boundaries of rock layers with topological relationships or contact relationships in the fact base, the contact lines between sequences, etc. are defined as constraint lines), and the rule engine of the patent is used to implement rule matching, agenda triggering, and Drools execution to obtain the spatial information of all constraint lines as the line constraint conditions for subsequent internal relationship inference;

[0059] (1-3) Determine the surface constraints for the internal extension of the structural surface based on the regional growing method and the geometric elements of the rock structure: Preliminarily extract the inclination and dip information of the rock structure surface based on the regional growing method, and then update the fact database to store the inclination, dip, and adjacent structural surface information of the rock structure surface as the surface constraints for subsequent internal relationship inference.

[0060] The implementation process of the region growing method is as follows Figure 6 As shown, refer to Figure 6 , steps (1-3) specifically include:

[0061] (1-3-1) According to the basic situation of the study area, set the seed triangle Pi;

[0062] (1-3-2) According to the topological relationship of the triangulated network, the growth rules are set, and the candidate point set of the current plane is expanded by adding adjacent similar triangulated networks Qj based on the outward growth of the seed triangle;

[0063] (1-3-3) Calculate the angle between the normal vectors of adjacent triangles (Pi, Qj) as α, calculate the angle between Qj and the average normal vector of the plane Ai where Pi is located as θ, and perform α and θ threshold judgments. When there are no edge points to be queried or the remaining points can no longer meet the candidate points of the target rule, the growth is completed and the plane set An is generated.

[0064] (1-3-4) Update the dip, inclination and other information of each plane in the fact base, and the subsequent rock structure surface will extend inward based on this information.

[0065] Step (2) is to achieve the extension of the rock mass structural surface with constant thickness based on the key control point setting, thickness constraint and geometric calculation of the irregular triangulated network (TIN), which specifically includes:

[0066] (2-1) Starting from the known control points, based on the occurrence of the rock mass surface and the interpolation algorithm, determine the control point positions in the unknown area;

[0067] (2-2) Based on the Graham-Scan convex hull algorithm, the boundary constraints of the rock mass structural surface are determined. Starting from the reference plane, each stratum is extended upward or downward, keeping the vertical distance from the reference plane (i.e., stratum thickness) unchanged.

[0068] Further, step (2-1) includes:

[0069] (2-1-1) determining the stratigraphic interface to be extended, and marking key control points on each interface based on the key point spatial information obtained in step (1-1);

[0070] (2-1-2) Determine the neighboring sampling points of the interpolation point, and use the inverse distance weighted IDW algorithm to calculate the elevation of the interpolation point based on the coordinate values ​​and elevation values ​​of these neighboring points. Specifically, for the interpolation point P (x, y, z) and its neighboring data points (X, Y, Z), i = 1, 2, 3 ... n, the elevation of the interpolation point is calculated by the formula:

[0071]

[0072] w i (x) = 1 / d(x,x i ) m

[0073]

[0074] Among them, x i is the adjacent horizontal coordinate point, z i is the nearby elevation value, N is the number of sample points used for interpolation, m is a positive integer power (usually 0.5 to 3 can obtain the most reasonable results), w i is the reciprocal of the sum of squares of the Euclidean distances between the interpolation point and the known neighboring points, i.e., the weight. Figure 7As shown, (a) is a schematic diagram of the original structural surface before interpolation, and (b) is a schematic diagram after interpolation, wherein the red points are control points established according to the concept of the present invention, i.e., constraint data points, and the blue points are interpolation data points.

[0075] Further, step (2-2) includes:

[0076] (2-2-1) Determine the boundary constraints of the rock mass structural surface based on the Graham-Scan convex hull algorithm, and infer the internal boundary of the rock mass structural surface under the surface constraint conditions constructed in step (1);

[0077] (2-2-2) Connect the upper and lower boundaries to construct the overall boundary constraint. Delete the interpolation points outside the boundary based on the boundary constraint. The boundary constraint diagram is as follows: Figure 8 As shown, (a) is a schematic diagram of the original structural surface, and (b) is a schematic diagram of the constructed boundary constraints;

[0078] (2-2-3) Starting from the base plane, extend each stratum upward or downward, keeping the vertical distance from the base plane (i.e., stratum thickness) unchanged. The result of the algorithm applied in the example is shown in the figure below: Fig. 9 As shown in (a), the three layers of blue, purple and green are extended downward from the base plane respectively, while keeping the vertical distance between the layers (i.e., the thickness of the formation) unchanged.

[0079] Step (3) is to achieve triangulated surface mesh deformation based on thickness constraints, thereby achieving thickness variation extension between different depth levels, specifically including:

[0080] (3-1) Obtain thickness data between layers at different depths of rock mass structure through profile data, virtual data or other data;

[0081] (3-2) Perform linear interpolation processing. For each triangle in the TIN, use the IDW algorithm to perform interpolation processing based on the depth information of its vertices and the corresponding inter-layer thickness data to calculate the layer thickness of each triangle at different depths;

[0082] (3-3) Generate new vertex coordinates based on the interpolated layer thickness data to represent the stratigraphic layers at different depths;

[0083] (3-4) Deformation of triangulated surface mesh is realized based on thickness constraint, that is, taking into account the position restrictions of some vertices of the surface mesh, a new irregular triangulated network is constructed according to the obtained new vertex coordinates to calculate the new position of the surface mesh vertices. The application effect of the deformation algorithm is as follows: Fig.10 As shown, the region of interest is characterized by green vertices (unconstrained vertices) and red vertices (control vertices). Fig.10(a) is the initial surface mesh, and (b) is the effect of the deformation algorithm. After the triangulated surface mesh is deformed, the thickness variation extension is achieved.

[0084] The results of applying the algorithm in the example are shown in the figure Fig. 9 As shown in (b), it is known that the purple, red and green layers are parallel layers, and the red layer and the green layer intersect. The thickness change extension algorithm changes its original thickness (0.56m) and sets its final thickness to half (1.17m) of the thickness between the purple and green layers (2.34m) to achieve thickness change extension between layers.

[0085] Step (4), based on the intersection lines of the intersecting rock mass structural surfaces, the irregular triangulated network is cut to achieve stratum pinch-out, specifically including:

[0086] (4-1) Obtaining data on rock stratum structural surfaces, including the spatial position and geometric shape of the stratum surface, and calculating the intersection lines of intersecting rock stratum structural surfaces as constraint conditions;

[0087] (4-2) Insert the stratum pinch-out line as a constraint condition into the irregular triangulated network, and perform the TIN model clipping operation according to the constraint line, that is, remove the part between the stratum pinch-out points and retain the effective stratum structure; the clipping algorithm flow chart is shown in Fig.11 As shown, the effect of formation pinch-out is achieved.

[0088] The results of applying the algorithm in the example are shown in the figure Fig. 9 As shown in (c) of the figure, the blue layer pinches out during the extension process due to the known or set pinch-out condition. When the distance between two layers meets the pinch-out condition, the intersection of the two layers is defined as the pinch-out line (e.g. Fig. 9 (shown by the black line in (c)), the newer layer is formed after the pinch-out line is removed according to the superposition principle.

[0089] Step (5), sequentially execute steps (2), (3), and (4) to obtain the final internal space relationship inference result (such as Fig.12 As shown in the figure, it can be seen that the example has 12 joint planes and 31 levels. Based on the inference result of the internal spatial relationship, the internal spatial distribution of the rock mass structural plane in the example can be clearly seen.

[0090] Based on the same technical concept as the method embodiment, the present invention also provides an internal spatial relationship inference system based on the surface of a rock mass structural surface, comprising:

[0091] The constraint condition determination module is used to extract the rock structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock structure, to build the association between the surface characteristics of the rock structure plane and its internal spatial relationship, to determine the surface constraint conditions of the stratigraphic plane, joint plane, and fault plane, and to update the results to the fact base;

[0092] The thickness-invariant extension module is used to achieve thickness-invariant extension of the rock mass structure surface based on key control point setting, thickness constraints and geometric calculations of irregular triangulated networks under certain constraints. Specifically, it includes: a control point setting unit, which is used to determine the control point positions of unknown areas based on the occurrence and interpolation algorithms of the rock mass structure surface from known control points; a vertical extension unit, which is used to determine the boundary constraints of the rock mass structure surface based on the Graham-Scan convex hull algorithm according to the determined control point positions, and to extend each stratum upward or downward from the reference plane under the boundary constraints, keeping the vertical distance from the reference plane unchanged;

[0093] Thickness variation extension module is used to obtain thickness data between layers at different depths of rock mass structure, obtain the thickness of each triangle of irregular triangulated network at different depths through interpolation processing, realize triangulated surface mesh deformation under specified thickness constraints, and then realize thickness variation extension between layers at different depths;

[0094] The formation pinch-out processing module is used to obtain the surface data of the rock structure surface, calculate the intersection line of the intersecting rock structure surfaces, and cut the irregular triangulated network based on the intersection line to achieve formation pinch-out.

[0095] It should be understood that the internal spatial relationship inference system based on the surface of the rock structure surface in the embodiment of the present invention can realize all the technical solutions in the above-mentioned method embodiment, and the functions of its various functional modules can be specifically implemented according to the methods in the above-mentioned method embodiments. The specific implementation process can refer to the relevant description in the above-mentioned embodiments, which will not be repeated here.

[0096] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the method for inferring the internal spatial relationship based on the surface of the rock structure surface as described above are implemented.

[0097] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for inferring the internal spatial relationship based on the surface of the rock mass structural surface as described above are implemented.

[0098] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices (systems), computer equipment or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0099] The present invention is described with reference to a flowchart of a method according to an embodiment of the present invention. It should be understood that each process in the flowchart and a combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A device that specifies functions in a process or multiple processes.

[0100] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 The steps of a specified function in a process or multiple processes.

Claims

1. A method for estimating internal spatial relations based on the surface of a rock mass structural surface, characterized in that: The steps include: S1: Extract the rock mass structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock mass structure, construct the association between the surface characteristics of the rock mass structure plane and its internal spatial relationship, determine the surface constraints of the stratigraphic plane, joint plane, and fault plane, and update the results to the fact base; S2: Under the constraints determined in step S1, based on the key control point setting, thickness constraint and geometric calculation of the irregular triangulated network, the thickness of the rock structure surface is extended unchanged, specifically including: starting from the known control points, based on the occurrence and interpolation algorithm of the rock structure surface, the control point position of the unknown area is determined; according to the determined control point position, the boundary constraint of the rock structure surface is determined based on the Graham-Scan convex hull algorithm, and under the boundary constraint, each stratum is extended upward or downward from the reference plane, keeping the vertical distance from the reference plane unchanged; S3: Obtain the thickness data between layers at different depths of the rock mass structure, obtain the layer thickness of each triangle of the irregular triangulated network at different depths through interpolation processing, realize the deformation of the triangulated surface mesh under the specified thickness constraint, and then realize the thickness change extension between layers at different depths; S4: Obtain the surface data of the rock mass structural surface, calculate the intersection line of the intersecting rock mass structural surfaces, and cut the irregular triangulated network based on the intersection line to achieve stratum pinch-out.

2. The method according to claim 1, characterized in that In step S1, the constraint conditions include point constraint conditions, line constraint conditions, and surface constraint conditions, and the determination method is as follows: Based on the Graham-Scan convex hull algorithm and the Douglas-Peuker point cloud feature thinning algorithm, the boundary point set of the rock mass structural surface is extracted. According to the boundary point set and under the specified key point extraction rules, the spatial information of all key points is obtained as the point constraint condition for internal relationship inference. Extract rock mass structure traces based on digital image technology, and obtain all constraint line spatial information according to the rock mass structure traces under the specified constraint line extraction rules as the line constraint conditions for internal relationship inference; Based on the regional growing method, the inclination and dip information of the rock mass structural surface is preliminarily extracted, and then the fact database is updated to store the inclination, dip and adjacent structural surface information of the rock mass structural surface as the surface constraint conditions for internal relationship inference.

3. The method according to claim 2, characterized in that In step S2, starting from the known control points, based on the occurrence of the rock mass structure surface and the interpolation algorithm, the control point positions of the unknown area are determined, including: Determine the stratigraphic interfaces that need to be extended, and identify key control points on each interface based on the key point spatial information obtained; Determine the neighboring sampling points of the point to be interpolated, and calculate the elevation value of the interpolation point using the inverse distance weighted IDW algorithm based on the coordinate values ​​and elevation values ​​of these neighboring sampling points.

4. The method according to claim 3, characterized in that The IDW algorithm calculates the elevation value of the interpolation point, including: For the interpolation point P (x, y, z) and its adjacent set of data points (X, Y, Z), i = 1, 2, 3 ... n, the elevation value of the interpolation point is calculated by the formula: w i (x)=1 / d(x,x i ) m Among them, x i is the adjacent horizontal coordinate point, z i is the nearby elevation value, N is the number of sample points used for interpolation, m is a positive integer power, and w i It is the reciprocal of the sum of squared Euclidean distances between the interpolated point and its known neighboring points.

5. The method according to claim 2, characterized in that: In step S2, the boundary constraints of the surface of the rock mass structural plane are determined based on the Graham-Scan convex hull algorithm, and under the boundary constraints, each stratum is extended upward or downward from the reference plane to keep the vertical distance from the reference plane unchanged, including: The boundary constraints of the rock mass structural surface are determined based on the Graham-Scan convex hull algorithm, and the internal boundaries of the rock mass structural surface are deduced under the constructed surface constraints. Connect the upper and lower boundaries to construct the overall boundary constraint, and delete the interpolation points outside the boundary based on the boundary constraint; Starting from the datum, extend each stratum upward or downward, maintaining a constant vertical distance from the datum.

6. The method according to claim 1, characterized in that In step S3, the layer thickness of each triangle of the irregular triangulated network at different depths is obtained by interpolation processing, and the triangulated surface mesh deformation is realized under the specified thickness constraint, including: For each triangle, interpolation processing is performed based on the depth information of its vertices and the corresponding inter-layer thickness data to calculate the layer thickness of each triangle at different depths; According to the interpolated layer thickness data, new vertex coordinates are generated to represent the stratigraphic layers at different depths; Taking into account the position restrictions of the surface mesh vertices, a new irregular triangulated network is constructed according to the obtained new vertex coordinates, and the new positions of the surface mesh vertices are calculated.

7. The method according to claim 1, characterized in that In the step S4, data of the rock formation structural surface is obtained, including the spatial position and geometric shape of the stratigraphic surface, and the intersection line of the intersecting rock formation structural surface is calculated based on the spatial position and geometric shape of the stratigraphic surface; The irregular triangulated network is trimmed based on the intersection line to achieve stratum pinch-out, including: inserting the stratum pinch-out line into the irregular triangulated network as a constraint condition, and performing a trimming operation on the irregular triangulated network model according to the constraint line, thereby achieving the stratum pinch-out effect.

8. A system for estimating internal spatial relations based on the surface of a rock mass structure, characterized in that: include: The constraint condition determination module is used to extract the rock structure characteristics and spatial relationships of the stratigraphic plane, joint plane, and fault plane from the three-dimensional surface model data of the rock structure, to build the association between the surface characteristics of the rock structure plane and its internal spatial relationship, to determine the surface constraint conditions of the stratigraphic plane, joint plane, and fault plane, and to update the results to the fact base; The thickness-invariant extension module is used to achieve thickness-invariant extension of the rock mass structure surface based on key control point setting, thickness constraints and geometric calculations of irregular triangulated networks under certain constraints. Specifically, it includes: a control point setting unit, which is used to determine the control point positions of unknown areas based on the occurrence and interpolation algorithms of the rock mass structure surface from known control points; a vertical extension unit, which is used to determine the boundary constraints of the rock mass structure surface based on the Graham-Scan convex hull algorithm according to the determined control point positions, and to extend each stratum upward or downward from the reference plane under the boundary constraints, keeping the vertical distance from the reference plane unchanged; Thickness variation extension module is used to obtain thickness data between layers at different depths of rock mass structure, obtain the thickness of each triangle of irregular triangulated network at different depths through interpolation processing, realize triangulated surface mesh deformation under specified thickness constraints, and then realize thickness variation extension between layers at different depths; The formation pinch-out processing module is used to obtain the surface data of the rock structure surface, calculate the intersection line of the intersecting rock structure surfaces, and cut the irregular triangulated network based on the intersection line to achieve formation pinch-out.

9. A computer device, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the method for inferring the internal spatial relationship based on the surface of the rock structure surface as described in any one of claims 1-7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for inferring the internal spatial relationship based on the surface of a rock mass structural surface as described in any one of claims 1 to 7 are implemented.

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