CN116152461B

CN116152461B - Geological modeling method, device, computer equipment and computer readable storage medium

Info

Publication number: CN116152461B
Application number: CN202310432405.1A
Authority: CN
Inventors: 李健; 李建兵; 余优生; 吴�琳; 李靖; 温立文; 袁金国; 杨河鑫; 赵福斌; 高一凡; 星玉花; 王文军
Original assignee: Beijing Xingtiandi Information Technology Co Ltd
Current assignee: Beijing Xingtiandi Information Technology Co Ltd
Priority date: 2023-04-21
Filing date: 2023-04-21
Publication date: 2023-07-18
Anticipated expiration: 2043-04-21
Also published as: CN116152461A

Abstract

The application discloses a geological modeling method, a geological modeling device, computer equipment and a computer readable storage medium, relates to the technical field of three-dimensional geological modeling, and aims to improve model accuracy, ensure high coincidence between a geological model and a roadway model and between the geological model and a coal seam model, reduce human intervention in a modeling process, simplify a construction flow and reduce labor burden. The method comprises the following steps: responding to a data scanning instruction, acquiring a plurality of target point cloud data output by a scanner, and constructing a roadway model by using the plurality of target point cloud data; processing kilometer drilling data by using a Kriging interpolation algorithm to obtain a coal bed model, establishing a plurality of virtual drilling holes by using a roadway model, and establishing a layer model by using the plurality of virtual drilling holes and coal bed related data in the coal bed model; constructing a fault model by using fault data, and generating stratum frame grids by using the fault model; and importing the layer model into a stratum frame grid to obtain a stratum model, and adjusting the stratum model by using the breaking distance information to obtain the target geological model.

Description

Geological modeling method, device, computer equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of three-dimensional geologic modeling technologies, and in particular, to a geologic modeling method, apparatus, computer device, and computer readable storage medium.

Background

Along with the rapid development of the three-dimensional geological modeling technology, the method is widely applied to the fields of urban construction, mining, geotechnical engineering and the like. The three-dimensional geologic modeling technology fuses geologic theory knowledge and computer three-dimensional visualization together, so that the purpose of modeling an address space is achieved through the information technology under the three-dimensional condition, and various geologic spaces and structures are explained.

In the related art, three-dimensional geologic modeling methods can be classified into modeling methods based on drilling, geologic profile, multi-source data and the like according to the types of data sources. The automatic modeling based on drilling is suitable for layered geological modeling, the semi-automatic interactive modeling based on the section is suitable for the construction of complex geological structures, and the modeling method based on multi-source data such as geophysical prospecting, drilling, geology and the like has high model precision and can truly reflect three-dimensional space characteristics. However, the applicant realizes that the space spreading condition of complicated structures such as underground wrinkles and fractures cannot be well reflected based on borehole modeling, and the modeling process of adopting a geological profile is complex, so that a great amount of manpower and material resources are required to be consumed, the efficiency is low, the fusion difficulty of the modeling method based on multi-source data is high, the accuracy of the model is low, the modeling process of the profile data is complex, and the manual intervention is required, so that the subsequent updating of the model is difficult.

Disclosure of Invention

In view of this, the present application provides a geological modeling method, device, computer equipment and computer readable storage medium, and mainly aims to solve the problems that the space distribution situation of complex structures such as underground folds and breaks cannot be well reflected based on borehole modeling, and the modeling process of adopting geological profile is complex, needs to consume a great deal of manpower and material resources and has low efficiency, while the modeling method based on multi-source data has large fusion difficulty, low model accuracy, complex modeling process of profile data, needs manual intervention, and causes difficulty in subsequent updating of the model.

According to a first aspect of the present application, there is provided a method of geologic modeling, the method comprising:

responding to a data scanning instruction, running a scanner, acquiring a plurality of target point cloud data output by the scanner, and constructing a roadway model by adopting the plurality of target point cloud data;

processing kilometer drilling data by using a Kriging interpolation algorithm to obtain a coal bed model, establishing a plurality of virtual drilling holes by using the roadway model, and constructing a layer model by using the plurality of virtual drilling holes and coal bed related data in the coal bed model;

obtaining a fault chart, constructing a fault model by adopting fault data in the fault chart, and generating a stratum frame grid by utilizing the fault model;

And importing the layer model into the stratum frame grid to obtain a stratum model, and adjusting the stratum model by using the break distance information in the fault map to obtain a target geological model.

According to a second aspect of the present application there is provided a geological modeling apparatus comprising:

the acquisition module is used for responding to a data scanning instruction, running the scanner, acquiring a plurality of target point cloud data output by the scanner and constructing a roadway model by adopting the plurality of target point cloud data;

the construction module is used for processing kilometer drilling data by utilizing a Kriging interpolation algorithm to obtain a coal bed model, establishing a plurality of virtual drilling holes by utilizing the roadway model, and constructing a layer model by utilizing the plurality of virtual drilling holes and coal bed related data in the coal bed model;

the generation module is used for acquiring a fault graph, carrying out model construction by adopting fault data in the fault graph to obtain a fault model, and generating stratum frame grids by utilizing the fault model;

and the adjusting module is used for guiding the layer model into the stratum frame grid to obtain a stratum model, and adjusting the stratum model by using the break distance information in the fault map to obtain a target geological model.

According to a third aspect of the present application there is provided a computer device comprising a memory storing a computer program and a processor implementing the steps of the method of any of the first aspects described above when the computer program is executed by the processor.

According to a fourth aspect of the present application there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of any of the first aspects described above.

By means of the technical scheme, the geological modeling method, the geological modeling device, the computer equipment and the computer readable storage medium are used for responding to a data scanning instruction, running the scanner and acquiring a plurality of target point cloud data output by the scanner, constructing a roadway model by adopting the plurality of target point cloud data, processing kilometer drilling data by using a Kriging interpolation algorithm to obtain a coal seam model, constructing a plurality of virtual wells by using the roadway model, constructing a layer model by using coal seam related data in the plurality of virtual wells and the coal seam model, acquiring a fault map, constructing a fault model by using fault data in the fault map, generating a stratum frame grid by using the fault model, guiding the layer model into the stratum frame grid to obtain the stratum model, adjusting the stratum model by using fault distance information in the fault map to obtain a target geological model, introducing a large number of high-precision roadway layer sites, top and bottom plate data as the high-precision roadway model for restraining the stratum model, fully fusing data of drilling, fully fusing drilling, realizing the construction of the high-precision three-dimensional geological model by using the data, improving the geological model, simultaneously guaranteeing the geological model to be consistent with the high-precision model, reducing the human-induced geological process, and reducing the human-induced load of the geological model.

The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:

FIG. 1 is a schematic flow diagram of a method for geologic modeling according to an embodiment of the present application;

FIG. 2A is a schematic flow diagram of a method for geologic modeling according to an embodiment of the present application;

FIG. 2B shows a flow chart for constructing a three-dimensional model according to an embodiment of the present application;

FIG. 2C illustrates a schematic diagram of a downhole kilometer borehole profile trajectory provided by an embodiment of the present application;

FIG. 2D illustrates a schematic diagram of virtual drilling data provided by an embodiment of the present application;

FIG. 2E illustrates a ZL028 synthetic histogram provided by embodiments of the present application;

FIG. 2F illustrates a mining area large fault map provided by an embodiment of the present application;

FIG. 2G illustrates a schematic diagram of a fault top and bottom line provided by an embodiment of the present application;

FIG. 2H illustrates a planar tomographic image provided by an embodiment of the present application;

FIG. 2I is a schematic diagram of a planar fault digitizing result provided by an embodiment of the present application;

FIG. 2J illustrates an architectural diagram of a fault three-dimensional model provided by an embodiment of the present application;

FIG. 2K illustrates a schematic architecture of a stratigraphic framework grid provided in an embodiment of the present application;

FIG. 2L illustrates a schematic architecture of a geomesh model provided in an embodiment of the present application;

FIG. 2M illustrates a method flow diagram for geologic modeling provided by embodiments of the present application;

FIG. 3 shows a schematic structural diagram of a geologic modeling provided by an embodiment of the present application;

fig. 4 shows a schematic device structure of a computer device according to an embodiment of the present application.

Detailed Description

Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

The embodiment of the application provides a geological modeling method, as shown in fig. 1, which comprises the following steps:

101. and responding to the data scanning instruction, running the scanner, acquiring a plurality of target point cloud data output by the scanner, and constructing a roadway model by adopting the plurality of target point cloud data.

The current three-dimensional geologic model research and development process can be summarized into three stages: the first stage is mainly a three-dimensional geologic modeling study based on borehole data. The second stage is mainly a three-dimensional visualization study based on geophysical survey data. The third stage is comprehensive geological modeling research based on multi-source data, and the third stage mainly carries out construction and dynamic updating of a high-precision and transparent mining working face, so that geological condition requirements of intelligent and accurate coal mining are met. The three stages are independent and complement each other, and all stages are mutually inserted without limitation, so that the three stages are advanced to a high-precision transparent target together, but the whole transparent geological condition construction process is still required to be further advanced towards intellectualization.

Thus, three-dimensional geologic modeling methods can be categorized into borehole-based, geologic profile-based, multi-source data-based, etc. modeling methods, depending on the type of data source. The automatic modeling speed is high based on drilling, and the method is suitable for lamellar geological modeling, but the modeling accuracy has a direct relation with the drilling distribution quantity, and the spatial distribution condition of complex structures such as underground folds, fractures and the like can not be well reflected. The semi-automatic interactive modeling based on the profile is suitable for the construction of complex geological structures, and although the modeling result accords with geological knowledge of professionals, the modeling process is complex, a large amount of manpower and material resources and time investment are required, and the modeling efficiency is low. The modeling method based on multi-source data such as geophysical prospecting, drilling, geology and the like has high model precision, can truly reflect three-dimensional space characteristics, but has high fusion difficulty.

In order to solve the problem, the application provides a geological modeling method, a large number of high-precision virtual drilling holes are introduced into a high-precision laser roadway three-dimensional model to serve as stratum constraint, and then data such as drilling holes, faults and stratum exposure information are fused to realize the construction of the high-precision three-dimensional geological model, so that the accuracy of the whole geological model can be improved, and meanwhile, the geological model can be guaranteed to be highly consistent with the roadway model and the coal seam model. The execution subject of the application can be a geological modeling system, the geological modeling system provides a front-end application for a user, namely a client, the user (such as staff) can perform geological modeling based on a front-end application request, so that the geological modeling system can provide modeling services for the user by means of the computing capability of a server, the server can be an independent server, and can also provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (Content Delivery Network, CDNs), and servers for basic cloud computing such as big data and artificial intelligent platforms, so that the artificial intervention of the modeling process is reduced, the construction flow of a geological model is simplified, and the labor burden is lightened.

The traditional coal mine underground roadway data are two-dimensional plane CAD (Computer Aided Design ) drawings, and roadway model reconstruction generally adopts a method of plane drawing and section drawing. However, the roadway model obtained by the method has low precision and insufficient detail abundance, so that the three-dimensional modeling of the entity target can be realized by directly acquiring and rapidly copying the three-dimensional information of the coal mine roadway through the GeoSLAM horizontal hand-held mobile three-dimensional laser scanner. In the embodiment of the application, the geological modeling system responds to the data scanning instruction and operates the scanner according to the data scanning instruction, wherein the scanner can be a GeoSLAM horizontal handheld mobile three-dimensional laser scanner, and can acquire underground laser point cloud data through the scanner to provide high-precision data for the geological modeling system. The data scanning instruction can be issued by a staff through a front-end application provided by the geological modeling system, and the staff can bind the scanner or access the scanner into the geological modeling system through the front-end application in advance, so that when the staff issues the data scanning instruction, the geological modeling system can operate the scanner to acquire point cloud data obtained by scanning of the scanner in response to the data scanning instruction. And then, the geological modeling system acquires a plurality of target point cloud data output by the scanner, and adopts the plurality of target point cloud data to construct a roadway model, wherein the plurality of target point cloud data are laser point cloud data obtained by scanning a target roadway by the handheld mobile three-dimensional laser scanner. In this way, the geological modeling system can construct a high-precision roadway three-dimensional model through high-precision laser point cloud data, so that the precision of the bottom layer model is improved.

102. And processing kilometer drilling data by using a Kriging interpolation algorithm to obtain a coal bed model, establishing a plurality of virtual drilling holes by using a roadway model, and constructing a layer model by using the plurality of virtual drilling holes and coal bed related data in the coal bed model.

In order to better improve the precision of the whole geological model, the high-precision roadway model and the high-precision coal seam model are constructed by introducing a large number of high-precision roadway layer sites and coal seam top and bottom plate data points serving as virtual drilling through a high-precision roadway three-dimensional model based on laser point cloud data and a coal seam layer model based on kilometer drilling data so as to restrain the stratum model. In the embodiment of the application, the geological modeling system processes kilometer drilling data by utilizing a kriging interpolation algorithm to obtain a coal seam model, wherein the geological modeling system can extract coordinates of top and bottom points of a coal seam from the kilometer drilling data, so that a high-precision coal seam layer model is constructed. And then, the geological modeling system utilizes the roadway model to establish a plurality of virtual drilling wells, and utilizes the data related to the coal seam in the plurality of virtual drilling wells and the coal seam model to establish a layer model, wherein the virtual drilling wells are drilling wells with single geological properties like the real drilling wells, so that the geological model and the geological body can be more attached. Therefore, the geological modeling system can generate virtual drilling by utilizing high-precision roadway layer sites and coal seam roof and floor data points, so that the stratum is restrained, and the influence caused by drilling data quality and distribution is reduced.

103. Obtaining a fault map, constructing a fault model by using fault data in the fault map, and generating a stratum frame grid by using the fault model.

In order to fuse drilling, fault and other data more accurately, a geological modeling system digitizes a geological map to obtain fault data, builds a fault model according to the fault data, and then builds a corner grid model according to a given grid size to form a three-dimensional stratum frame. In the embodiment of the application, a geological modeling system acquires a fault map, and fault data in the fault map is adopted to construct a fault model. By processing the fault map, fault data information such as a fault top line, a fault bottom line, a coal seam top line, a coal seam bottom line and the like can be obtained from the fault map, and a fault model is constructed by using the fault data information, so that the follow-up geological modeling system can integrate high-precision fault data into a geological model. Then, the geological modeling system generates stratum frame grids by using the fault model, so that the geological modeling system can construct the fault model by using fault data, further construct a corner grid model to obtain three-dimensional stratum frame grids, reduce human intervention in a modeling process, simplify the construction flow of the geological model, and further improve the accuracy of the whole geological model.

104. And importing the layer model into a stratum frame grid to obtain a stratum model, and adjusting the stratum model by using the break distance information in the fault map to obtain a target geological model.

According to the method, the layer model is inserted into the three-dimensional stratum frame grid, the vertical grid is built according to the stratum thickness and the model precision, the preliminary construction of the three-dimensional stratum model is completed, then, the stratum model is adjusted to the stratum at two sides of the fault according to the breaking distance, the three-dimensional geological model with reasonable structure is adjusted, and the influence of manual operation on the construction of the geological model is reduced. In the embodiment of the application, the geological modeling system guides the layer model into the stratum framework grid to obtain the stratum model. And then, the geological modeling system adjusts the stratum model by using the fault distance information in the fault map to obtain a target geological model. According to the method, multi-source data such as high-precision laser point cloud data, ground drilling, underground drilling and geological fault data are fused, so that a target geological model has higher precision, high anastomosis among a kilometer drilling coal seam model, a roadway model and a geological layer model can be achieved, the model construction process is simplified, the geological model construction efficiency is improved, the resolution of stratum data is improved, and meanwhile the requirements of a coal mine on the geological model in the aspects of actual production, geological early warning, emergency rescue and the like can be met.

According to the method provided by the embodiment of the application, in response to a data scanning instruction, a scanner is operated, a plurality of target point cloud data output by the scanner are acquired, a roadway model is built by adopting the plurality of target point cloud data, a high-precision roadway model is built by adopting a kriging interpolation algorithm to process kilometer drilling data to obtain a coal seam model, a plurality of virtual drilling holes are built by utilizing the roadway model, a layer model is built by utilizing coal seam related data in the plurality of virtual drilling holes and the coal seam model, a fault map is acquired, the fault model is built by adopting fault data in the fault map, a stratum frame grid is generated by utilizing the fault model, the layer model is led into the stratum frame grid to obtain the stratum model, the fault distance information in the fault map is utilized to adjust the stratum model to obtain a target geological model, a large number of high-precision roadway layer sites and coal seam top and bottom plate data are used as virtual drilling holes to build the high-precision roadway model and the high-precision coal seam model to restrain the stratum model, the high-precision three-dimensional geological model is fully fused to build the high-precision three-dimensional geological model, the whole geological model is improved, meanwhile the artificial geological model and the human geological model is well is guaranteed, the geological model is reduced, the human geological model is simplified, and the construction process is simplified.

Further, as a refinement and extension of the foregoing embodiment, to fully describe the implementation of this embodiment, another geological modeling method is provided in this application, as shown in fig. 2A, where the method includes:

201. in response to the data scanning instruction, the scanner is operated and a plurality of target point cloud data output by the scanner are acquired.

In the prior art, conventional geological data such as drilling holes, sections and the like are utilized to constrain a geological model, and the quantity quality and distribution of the drilling data can directly influence the accuracy of a stratum three-dimensional model. However, in actual production, due to the complexity of geological conditions and the problem of cost, the quality and distribution of drilling data are difficult to reach an ideal state, the accuracy of a model is difficult to be consistent, the modeling process of profile data is complicated, manual intervention is too large, and the model is difficult to update subsequently. Therefore, the ground control points are introduced into the underground by adopting the control measurement method, and a large number of high-precision control points are distributed, so that the coordinate systems of the upper part and the lower part of the mine are unified, and the precision of the laser scanner in scanning construction of the roadway three-dimensional model is ensured.

In the tunneling process of the coal mine tunnel, the tunnel floor is always pushed along the coal seam floor, so that the tunnel floor is the coal seam floor and comprises the geological properties of the coal seam layer, and therefore, the subsequent geological modeling system can consider the characteristic points of the floor as virtual drilling with single geological properties, and the construction precision of a geological model can be greatly improved. Before the method, a geological modeling system needs to construct a high-precision roadway model, so that a virtual drilling well is built according to the characteristic points obtained by the high-precision roadway model. In the embodiment of the application, when a data scanning instruction is received, the geological modeling system determines a target roadway indicated by the data scanning instruction, and obtains a preset first interval, such as 100 meters. Then, the geological modeling system determines a plurality of control points according to a preset first interval based on the target roadway. Because the point cloud data generated by the GeoSLAM is a local coordinate, control points are required to be distributed in the underground roadway and used for converting the local coordinate into a unified national coordinate system. Subsequently, the geologic modeling system obtains the planar position of each control point based on the planar control measurement method and obtains the elevation of each control point based on the elevation control measurement method. And then, the geological modeling system determines the control point coordinates of each control point by using the plane position of each control point and the elevation of each control point to obtain a plurality of control point coordinates, so that the geological modeling system establishes a three-dimensional affine transformation model by using the plurality of control point coordinates and the local coordinates acquired by the scanner at the plurality of control point coordinates, and registered laser point cloud data is acquired. And finally, the geological modeling system operates the scanner to acquire a plurality of point cloud data output by the scanner at each control point coordinate, and a plurality of target point cloud data are obtained. It should be noted that, if the geological modeling system does not receive the multiple target point cloud data output by the bound scanner, the multiple target point cloud data obtained from the scanner may be input by the front end application of the staff, so that the geological modeling system may process the multiple target point cloud data rapidly and accurately. The acquisition of the cloud data of the target point can be performed by using a hand-held mobile three-dimensional laser scanner according to a planned scanning route from a certain control point to another control point or from one control point to form a closed loop by winding around the control point and returning to the starting point. And at least three and more control points are covered per scan in order to ensure scanning accuracy.

202. And constructing a roadway model by adopting a plurality of target point cloud data.

In the embodiment of the application, the geological modeling system utilizes a plurality of target point cloud data and a plurality of control point coordinates to construct a three-dimensional affine transformation model. And then, the geological modeling system acquires a plurality of pieces of alignment point cloud data from the three-dimensional affine transformation model, and carries out preprocessing operation on the plurality of pieces of alignment point cloud data, wherein the preprocessing operation comprises filtering and denoising, data reduction and data interpolation. Because the data acquired by laser scanning is often accompanied with miscellaneous points or noise, the subsequent data processing can be influenced, and therefore, in order to acquire a complete roadway model, certain preprocessing needs to be performed on point cloud data. And then, the geological modeling system acquires a multi-dimensional binary tree algorithm, the preprocessed plurality of alignment point cloud data are clustered into a plurality of target data by utilizing the multi-dimensional binary tree algorithm, namely, the segmentation operation is carried out, the whole point cloud, namely, the plurality of alignment point cloud data are clustered into a plurality of point clouds, and each point cloud, namely, the target data, corresponds to an independent object. Finally, in order to facilitate subsequent grid rendering, the point cloud needs to be triangulated in advance, so that a geological modeling system acquires a preset construction algorithm, and triangulated processing is carried out on a plurality of target data by adopting the preset construction algorithm to obtain a roadway model, wherein the preset construction algorithm is one of a convex hull algorithm and a concave hull algorithm. It should be noted that, the geological modeling system performs triangular meshing on a plurality of target data to obtain a space topological structure, then performs mesh rendering of texture mapping to obtain a roadway model, and improves the accuracy of the roadway model, so that the high-accuracy roadway model is used for restraining the stratum model later, and the flow of model construction is simplified.

For this reason, a three-dimensional model construction flow chart provided in the embodiment of the present application is as follows:

as shown in fig. 2B, the geological modeling system firstly obtains control points in the roadway through roadway control measurement, then performs roadway laser scanning to obtain point cloud data obtained by a scanner from the laser scanning of the control points, then performs laser point cloud registration to obtain registered point cloud data, and finally performs preprocessing, segmentation and triangular gridding operation on the registered point cloud data to realize point cloud modeling to obtain a three-dimensional roadway model.

203. And processing the kilometer drilling data by using a Kriging interpolation algorithm to obtain a coal bed model.

The underground kilometer directional drilling is mainly used for gas drainage of coal mines and is also used for boundary exploration of the coal mines, goaf water drainage and the like, so that a coal bed model is built through track coordinates of the underground kilometer directional drilling, and human intervention in a modeling process is reduced. In the embodiment of the application, a geological modeling system acquires drilling track coordinates, a plurality of branch holes are determined according to the drilling track coordinates, and a starting point coordinate value and an ending point coordinate value of each branch hole are extracted from the drilling track coordinates to obtain a plurality of starting point coordinate values and a plurality of ending point coordinate values. And then, the geological modeling system acquires a least square algorithm, a plurality of starting point coordinate values and end point coordinate values are subjected to fitting calculation by using the least square algorithm, a drilling track trend line is obtained, and the coordinates of the top and bottom points of the coal bed can be determined through the drilling track trend line, so that a high-precision coal bed model is constructed. And then, the geological modeling system calculates distances from the coordinate values of the plurality of starting points and the coordinate values of the plurality of ending points to the trendline of the drilling track respectively to obtain a plurality of distance values, and calculates an average value of the plurality of distance values to obtain an average distance value. Then, the geological modeling system obtains a preset distance threshold calculation rule, calculates the average distance value by using the preset distance threshold calculation rule, and obtains a target distance threshold, for example, the preset distance threshold calculation rule can be 0.3 multiplied by the average distance value.

Then, the geological modeling system acquires a plurality of first distance values which do not exceed the target distance threshold value in the plurality of distance values, and deletes the first distance values in the plurality of distance values to obtain a plurality of target distance values. Then, the geological modeling system determines a plurality of target starting point coordinate values and a plurality of target ending point coordinate values corresponding to the plurality of target distance values, and determines a plurality of coal seam vertex coordinates and a plurality of coal seam bottom point coordinates by using the plurality of target starting point coordinate values and the plurality of target ending point coordinate values. And the geological modeling system generates a coal seam section line by utilizing the plurality of coal seam vertex coordinates and the plurality of coal seam bottom point coordinates.

Therefore, a schematic diagram of a downhole kilometer drilling section track is provided in the embodiment of the present application as follows:

as shown in fig. 2C, the geologic modeling system obtains a borehole profile map of kilometers downhole, where the solid line is the borehole trajectory, the dash-dot line is the trend line, and the dashed line is the top-bottom plate. Specifically, the geological modeling system reads the coordinates of the drilling track in the profile track map, and extracts the coordinate values of the start and end points of the branch holes. The geologic modeling system then fits a polynomial least squares algorithm to the borehole trajectory trend line, i.e., the dash-dot line. Then, the geologic modeling system calculates the distances from the starting point and the ending point of each branch hole to the trend line, and calculates the average value of all the distances, for example, the average value can be D, and the starting point and the ending point of which the rejecting distance is smaller than a threshold value, for example, the threshold value can be 0.3 x D, so as to obtain the coordinates of the top point and the bottom point of the coal bed, namely the triangular mark. And finally, connecting the top and bottom points by the geological modeling system to obtain a coal seam section line, and combining the coordinates of the top and bottom points of the coal seam extracted from all drilling data to obtain the top and bottom plates of the coal seam, namely a dotted line.

And finally, the geological modeling system acquires a Kriging interpolation algorithm, and processes the plurality of coal seam vertex coordinates, the plurality of coal seam bottom point coordinates and the coal seam section line by utilizing the Kriging interpolation algorithm to obtain a coal seam model. Therefore, the geological modeling system can automatically extract the coordinates of the top and bottom plates of the coal seam and construct a high-precision coal seam model according to the coordinates of the kilometer drilling track by combining the profile track processing with the exploration information in the drilling process, so that the subsequently constructed geological model is highly matched with the coal seam model, and the model precision is improved.

204. And establishing a plurality of virtual wells by using the roadway model.

Because the influence of drilling data quality and distribution can be to the precision of geological model, this application replaces true drilling with virtual drilling, can reduce the quantity, quality and the deviation that the distribution caused to the model of true drilling data, and this application increases the data of virtual drilling simultaneously for stratum data resolution is high. Further, the virtual drilling is the same as the real drilling, and the drilling with single geological attribute after preprocessing and expert research and judgment by using the geological information disclosed in practice can restrict the stratum model, so that the geological model and the geologic body are more closely attached and vivid. In the embodiment of the application, the geological modeling system acquires a roadway model, acquires a preset second interval, such as 100 meters, and sets virtual drilling according to the preset second interval in the roadway model to obtain a plurality of virtual drilling. The preset second distance can be used for arranging uniformly distributed characteristic points on the roadway model bottom plate at certain intervals by the geological modeling system to serve as virtual drilling. In this way, the geological modeling system establishes a plurality of virtual wells through the high-precision roadway model so as to acquire more accurate well drilling data from the plurality of subsequent virtual wells.

205. Acquiring a plurality of drilling data corresponding to the virtual drilling in a roadway model, acquiring a plurality of preset projects, and sorting the drilling data according to the mapping relation between each item of the drilling data and the preset projects to obtain first well position data.

In order to construct a bedding model, it is necessary to construct with target horizon data comprising first well position data obtained with a plurality of virtual wells, a first data table obtained with a well pattern, second well position data obtained with a well pattern, and second well position data obtained with a coal seam model. For the first well position data, the virtual drilling established according to the high-precision roadway point data coordinates is directly written into the target horizon data according to the same format of the real drilling data. In the embodiment of the application, the geological modeling system acquires a plurality of preset items in the roadway model, wherein the plurality of preset items comprise drilling names, horizontal axis coordinates, vertical axis coordinates, bottom depth and kilobytes. Next, the geologic modeling system obtains a plurality of well data corresponding to the plurality of virtual wells, wherein the plurality of well data may be well coordinates, a Bottom Depth value, a KB value, and the like. And finally, the geological modeling system sorts the plurality of drilling data according to the mapping relation between each item of the plurality of drilling data and a plurality of preset items to obtain first well position data. For example, the geologic modeling system takes the abscissa of the well coordinate as the abscissa, the ordinate of the well coordinate as the ordinate, the Bottom Depth value as the Bottom Depth, the KB value as the kilobytes, and these data as the first well position data. A schematic representation of virtual drilling data is described below:

As shown in FIG. 2D, the real borehole data is limited, and more abundant data can be provided by constructing the virtual borehole data, so the application writes the virtual borehole data into the horizon data according to the format of the real borehole data. And for convenience in calculation, the geologic modeling system uniformly sets the format to a Bottom depth value and a KB value.

206. And reading the top depth information corresponding to each horizon in the drilling histogram to obtain a plurality of top depth information, and arranging the plurality of top depth information into a table to obtain a first data table.

Because horizon data are important parameters of three-dimensional geological modeling of a coal field, and accurate layering and layering digitization are important preconditions for good modeling display, the method and the device provide more comprehensive data support for model construction by reading top depth information in a drilling histogram. In an embodiment of the present application, a geologic modeling system obtains a drilling histogram, such as a ZL028 synthetic histogram. A ZL028 synthetic histogram is described as follows:

as shown in fig. 2E, the present application describes a drilling horizon digitizing process using actual geological data of a bamboo mountain coal mine as an example, and the mining area has 21 drilling comprehensive bar charts, and is divided into six horizons: the bottom of the No. 15 coal bed, namely the top of the upper stone coal system Taiyuan group, namely the top of the C3t, the top of the lower two stacks of Shanxi groups, namely the top of the P1s, the top of the lower two stacks of lower stone boxes, namely the top of the P1x, and the top of the upper two stacks of upper stone boxes, namely the top of the P2s. Thus, the geologic modeling system reads the top depths of groups of layers in each well from the well synthetic columns. Specifically, taking a ZL028 synthetic histogram in actual geological data of a bamboo forest mountain coal mine as an example, the geological modeling system determines that the top depth of the P1x layer is at a first line mark, namely 218.35m, and the top depth of the P1s layer is at a second line mark, namely 251.9m, and the top and bottom depths of the coal seam No. 3 and the coal seam No. 15 are respectively named as 3top, 3bottom, 15top and 15bottom. Thus, the coal seam is a black rectangular area, with a depth of 3top corresponding to 267.5m and a depth of 3bottom corresponding to 271.05m. Thus, the geologic modeling system sorts the top depths of the groups of layers in a tabular form, generating a horizon file, and the horizon file is in the format of b.txt (text format). It should be noted that the original ZL028 synthetic columnar image is too large and is not completely displayed.

With the above-described drilling histogram, the geologic modeling system determines a plurality of horizons in the drilling histogram. And then, the geological modeling system reads the top depth information corresponding to each horizon in the drilling histogram to obtain a plurality of top depth information. And finally, the geological modeling system collates the plurality of top depth information into a table to obtain a first data table.

207. And reading the drilling related information in the drilling histogram, and sorting the drilling related information according to the mapping relation between each item of data in the drilling related information and a plurality of preset items to obtain second well position data.

In the embodiment of the application, the geological modeling system reads drilling related information in the drilling histogram, and sorts the drilling related information according to the mapping relation between each item of data in the drilling related information and a plurality of preset items to obtain second well position data. For example, the name of the well, the plane coordinates of the well, the Bottom depth of the well, the heart rate of the well are obtained in a well histogram, and a well location file is created in a format of well name, X-chord, Y-chord, bottom depth, KB (kilobyte), and the well location file is in a format of a.txt (text format).

208. And acquiring the coal seam related data in the coal seam model, and arranging the coal seam related data into a table to obtain a second data table.

In the embodiment of the application, the geological modeling system acquires coal seam related data in a coal seam model, wherein the coal seam related data comprises a plurality of coal seam vertex coordinates, a plurality of coal seam bottom point coordinates and coal seam horizon information. And then, the geological modeling system sorts the data related to the coal seam into a table to obtain a second data table. In this way, the geological modeling system obtains the first well position data by utilizing a plurality of virtual wells, obtains the first data table by utilizing the well drilling histogram, obtains the second well position data by utilizing the well drilling histogram and obtains the second well position data by the coal bed model, so that the subsequent blending of the drilling holes, the horizon and the coal bed data into the layer model is facilitated, the manual intervention is reduced, and the model construction process is simplified.

209. Generating target horizon data using the first well location data, the first data table, the second data table, and the second well location data.

In order to improve model accuracy, the method and the system utilize digitally acquired well position and horizon data, introduce roadway three-dimensional model feature points and coal seam roof and floor data points as virtual drilling wells to construct a stratum layer model, and therefore in the embodiment of the application, a geological modeling system utilizes first well position data, a first data table, a second data table and second well position data to generate target horizon data. Thus, the geological modeling system can construct a layer model by utilizing the target horizon data, so that the data of drilling holes, horizons and the like can be fused accurately.

210. And (3) acquiring a Kriging interpolation algorithm, and calculating the target horizon data by using the Kriging interpolation algorithm to obtain a layer model.

The method adopts the Kriging interpolation method to process the target horizon data, thereby establishing a top surface model of each layer. The principle of the kriging interpolation method is that no bias and minimum variance condition exists in the probability statistics estimation theory, and the spatial correlation of the described object is considered in the interpolation process, so that the interpolation is more scientific and is closer to the actual situation. In the embodiment of the application, for each horizon, the geological modeling system extracts a plurality of horizon coordinates of the horizon and horizon coordinate values corresponding to each horizon coordinate from target horizon data, calculates horizon distance values and half variances of any two horizon coordinates in the plurality of horizon coordinates by using the plurality of horizon coordinate values, and obtains a plurality of horizon distance values and a plurality of half variances, namely, calculates distances and half variances for coordinate data of the same horizon in pairs. And then, the geological modeling system establishes a relation function by adopting a plurality of horizon distance values and a plurality of half variances, acquires an index model, and fits the relation function by utilizing the index model to obtain a fitting function, so that the corresponding half variances can be calculated according to any distance. Then, the geological modeling system calculates a plurality of horizon distance values by using a fitting function to obtain a plurality of first half variances, and calculates a half variance coefficient matrix by using the plurality of first half variances. Then, the geological modeling system obtains unknown horizon coordinates of the horizon, calculates half variances from the unknown horizon coordinates to the plurality of horizon coordinates, obtains a plurality of second half variances, and calculates a coefficient equation by using the plurality of second half variances. And then, the geological modeling system calculates a half variance coefficient matrix and a coefficient equation to obtain a weighting coefficient, acquires a plurality of attribute values corresponding to a plurality of horizon coordinates in the target horizon data, and performs weighted summation calculation on the attribute values by using the weighting coefficient to obtain an estimated value of the unknown horizon coordinates. And finally, respectively calculating a plurality of horizon coordinates of each horizon by using the geological modeling system to obtain a plurality of estimated values, and constructing a layer model by using the target horizon data and the estimated values. In this way, the geological modeling system utilizes the Kriging interpolation algorithm to calculate the statistical characteristics of the target horizon data, so that the construction of a layer model is realized, the high fusion of a kilometer drilling coal bed model and a roadway model can be realized, and the model precision is improved.

211. And acquiring a fault chart, and acquiring fault data of the fault chart by using a preset processing algorithm.

In order to effectively improve the accuracy of the overall geologic model, fault data and data such as drilling, horizons and the like are fused. Thus, in embodiments of the present application, a geologic modeling system obtains a fault map and coordinates-corrects the fault map. The tomographic map is corrected, that is, the positions in the tomographic map are calibrated to actual coordinates. A description of a large fault map of a mine is provided below:

as shown in fig. 2F, the mining area large fault map includes Bai Zhuang syncline, north slope ditch anticline and urban rear waist fault. The geological modeling system calibrates the positions of the white village syncline, the north slope ditch anticline and the urban and posturban waist fault to determine the actual coordinates.

Through the fault map, the geological modeling system reads the fault dip angle and the elevation range in the corrected fault map. And then, the geological modeling system calculates the projection positions of the coal seam roof line and the coal seam floor line in the fault chart by using the fault inclination angle and the elevation range, and determines parallel lines of the fault line at the projection positions of the fault chart, wherein the parallel lines comprise the fault roof line, the fault floor line, the coal seam roof line and the coal seam floor line. A schematic representation of a fault roof line is described below:

As shown in fig. 2G, the geological modeling system reads out the fault inclination angle and the elevation range according to the fault map, calculates the projection positions of the TOP and BOTTOM lines of the coal seam on the plane, and draws parallel lines of the fault lines at the corresponding positions, namely a fault TOP line F1304-TOP and a fault BOTTOM line F1304-BOTTOM.

Then, the geological modeling system acquires a preset processing algorithm, the corrected fault diagram is subjected to vectorization processing, the background color and the target color of the corrected fault diagram are set, and pixel automatic tracking is performed on fault lines and parallel lines of the fault lines, so that dense pixel point coordinates are obtained. Finally, the geological modeling system acquires a preset pixel point filtering rule, performs thinning filtering on the dense pixel point coordinates by using the preset pixel point filtering rule, and generates fault data by using the sparse pixel point coordinates after thinning filtering. It should be noted that, the preset pixel point filtering rule may be a Douglas-Peucker (Douglas-Peucker) algorithm, specifically, when the coordinates of the dense pixels are subjected to thinning filtering, the Douglas-Peucker algorithm is adopted to make a line AB from two end points of the dense pixels, namely, the pixel point a and the pixel point B, and if the vertical distance from all the pixel points to the line AB is smaller than a threshold d, the line AB is used to replace the line AB, and the remaining pixel points except the pixel point a and the pixel point B are removed, where the threshold d is usually set to 2 pixels. And in the process of sequentially checking the vertical distance of the pixel points, if the vertical distance of one pixel point is larger than the threshold d, reserving the pixel point, taking the pixel point as a new endpoint, namely a pixel point C, and respectively connecting the pixel point A and the pixel point B to obtain a straight line AC and a straight line CB, and then continuously checking the vertical distance of the next pixel point. And repeating the above operation, traversing all the pixel points, and finishing the operation of reserving or extracting the middle pixel point. The density of the arc line pixel points can be properly reduced through the thinning and filtering of the dense pixel points, the number of the pixel point coordinates is reduced under the condition that the accuracy of straight lines or curves is ensured, the calculation process of subsequent fault data is simplified, and the calculation rate is improved. Thus, the geological modeling system can construct a fault model by using fault data, and the efficiency of model construction is improved.

212. And constructing a model by using the fault data to obtain a fault model.

The fault is the projection of the actual fault on a certain plane, so the fault normal vector is calculated according to the inclination angle and the tendency of the fault, thereby calculating the fault plane equation and the coordinates of points on the plane, and further constructing a fault model. A planar tomographic image is described below:

as shown in fig. 2H, the fault is a projection of an actual fault on a certain plane, and in the planar fault scan, the inclination angle and the inclination of the fault can be obtained, the inclination angle of the fault with the fault number F1 is 70 degrees, the fault drop H is 8m, the inclination angle of the fault with the fault number F1304 is 75 degrees, the fault drop H is 2.5m-6.0m, the inclination angle of the fault with the fault number F1408 is 70 degrees, the fault drop H is 5m-9m, the inclination angle of the urban lumbar fault is 75 degrees, and the fault drop H includes 260m, 269m, 318m, 328m and 364m.

In the embodiment of the application, the geological modeling system acquires a preset third interval, and performs digital processing on fault data according to the preset third interval to obtain a plurality of discrete line segments. A planar fault digitization result is described as follows:

as shown in fig. 2I, the geologic modeling system digitizes fault data into discrete strings of points, i.e., segments, at a given distance. Specifically, the fault numbers F1, F1304, F1408 and the city rear waist fault are digitalized according to preset intervals to obtain corresponding line segments.

Then, for each discrete line segment, the geological modeling system obtains the end point coordinates of the discrete line segment to obtain a first end point coordinate and a second end point coordinate, for example, the first end point coordinate isThe second end point coordinates are->. Subsequently, the geologic modeling system calculates a plane vector, a vertical vector, for example, the plane vector is +.>The vertical vector is +.>And determining the fault plane corresponding to the fault line. The geologic modeling system then calculates a target vector perpendicular to the discrete line segments and parallel to the fault plane using the planar vector, the perpendicular vector, e.g., the target vector +.>And calculating the plane vector and the target vector to obtain a fault plane normal vector +.>The calculation formula of the fault plane normal vector is shown in the following formula 1:

equation 1:

wherein, the liquid crystal display device comprises a liquid crystal display device,is a plane vector and the coordinates are +.>，/>Is a target vector and the coordinates are +.>。

Then, the geological modeling system acquires an initial plane equation, adds the normal vector of the fault plane and the first endpoint coordinate into the initial plane equation to obtain a fault plane equation, and the calculation formula of the fault plane equation is shown in the following formula 2:

equation 2:

where m is the abscissa of the fault plane normal vector, n is the ordinate of the fault plane normal vector, p is the height of the fault plane normal vector, x0 is the abscissa of the first endpoint coordinate, y0 is the ordinate of the first endpoint coordinate, and z0 is the height of the first endpoint coordinate.

And finally, constructing a fault model by using a fault plane equation and an elevation range by using the geological modeling system. Thus, the geological modeling system utilizes fault data to construct a fault model, and can better reflect the spatial distribution conditions of complex structures such as underground folds, fractures and the like. An architectural diagram of a fault three-dimensional model is described below:

as shown in fig. 2J, the geologic modeling system builds a fault three-dimensional model from the cross-sectional plane equations and elevation ranges. Where elevation refers to the distance of a point from the absolute base in the direction of the plumb line.

213. And generating a stratum framework grid by using the fault model.

The angular point grid model is a structured grid type widely applied at present, grid positions can be defined by i, j and k, the length and width of unit grids are variable, grid faces vertically connected with top and bottom grid points can be inclined, grids can be twisted, and fault lines, boundaries or tip-extinguishing lines can be conveniently simulated. Therefore, the method and the device determine the model boundary according to the drilling horizon information and the fault information, and generate the frame grid by using the corner grid model so as to better construct the geological model. In the embodiment of the application, the geological modeling system extracts intermediate shape points in the fault model, obtains the model boundary of the fault model, and obtains the preset coordinate direction and the preset grid number corresponding to the preset coordinate direction, wherein the intermediate shape points are the intersection points of three planes and a fault plane, which are divided into by the geological body corresponding to the fault model in the elevation direction. And then, the geological modeling system generates a plane quadrilateral grid by utilizing the intermediate shape points, the model boundaries, the preset coordinate directions and the preset grid numbers corresponding to the preset coordinate directions. Then, the geological modeling system acquires fault trend, fault top and fault bottom in the fault model, builds a planar quadrilateral grid to the fault top and the fault bottom according to the fault trend, obtains a columnar three-dimensional frame network for connecting the fault top, the fault middle and the fault bottom, and uses the columnar three-dimensional frame network as stratum frame grids, so that after the geological modeling system builds the fault model according to fault data, the geological modeling system builds a corner grid model according to given grid size to form a three-dimensional stratum frame, the modeling process is simplified, a great amount of investment of manpower, material resources and time is avoided, and the geological model building efficiency is improved.

Therefore, the architecture schematic diagram of the stratigraphic framework grid provided in the embodiment of the application is as follows:

as shown in fig. 2K, the geologic modeling system extracts intermediate shape points of the fault model, combines the model boundaries, and generates planar quadrilateral meshes according to a given number of meshes along the X, Y directions. Wherein, the geologic body of the region is divided into three surface and fault surface intersection points in the elevation direction as intermediate shape points. Then, the geological modeling system pushes the generated plane grid points to the top and bottom of the fault model along the fault trend, and a columnar three-dimensional framework grid connecting the top, the middle and the bottom is generated.

214. And importing the layer model into a stratum frame grid to obtain a stratum model.

According to the method, the generated bedding model is imported into the stratum framework grid model, the vertical grids are built according to stratum thickness and model accuracy, the preliminary construction of the three-dimensional stratum model is completed, the high fusion of the kilometer drilling coal bed model, the roadway model and the geological bedding model is achieved, and the model progress is improved. In the embodiment of the application, the geological modeling system guides the layer model into the stratum framework grid to obtain the three-dimensional grid. Wherein the intersections between all grids and the layers become one node of the three-dimensional grid, so that grid cells in the Z-axis direction are defined simultaneously, generating a rough three-dimensional grid. Then, the geologic modeling system obtains target horizon data, reads a plurality of formation thickness values in the target horizon data, and obtains a preset formation model accuracy. Subsequently, the geologic modeling system builds a plurality of vertical grids using the plurality of formation thickness values and the pre-set formation model accuracy. Finally, the geological modeling system adjusts the stratum frame grid imported into the stratum model by utilizing the plurality of vertical grids and the target horizon data to obtain the stratum model. It should be noted that, the geological modeling system constructs finer vertical grids according to the stratum thickness and the model precision, that is, the vertical grids are divided into a plurality of vertical grids between stratum layers of each layer, and the model is optimized and adjusted by using the drilling horizon points. Therefore, the geological modeling system fully fuses multi-source data such as high-precision laser point cloud data, ground drilling, underground drilling, geological fault data and the like, so that the model has higher precision.

215. And adjusting the stratum model by using the breaking distance information in the fault map to obtain the target geological model.

After the formation model is generated, the fault distance of the generated geological model fault is possibly unreasonable due to the influence of the software algorithm and geological condition complexity, so that the fault distance of the model is required to be adjusted by using the model editing function of modeling software according to the fault distance and the fault influence range marked by the large fault diagram, and the position of the model is enabled to enable the geological model to be reasonable and coincide with the actual situation. In the embodiment of the application, a geological modeling system acquires a fault chart, and the fault distance information and the fault influence range are read in the fault chart. And then, the geological modeling system acquires first interval information and fault information of the stratum model, and adjusts the first interval information and fault information of the stratum model by utilizing the interval information and fault influence range to obtain the target geological model. In this way, the geological modeling system pushes the obtained target geological model to the staff through the front-end application, so that the staff can refer to and use the target geological model, and the requirements of the coal mine on the geological model in the aspects of actual production, geological early warning, emergency rescue and the like are met. The geological modeling system adjusts strata on two sides of a fault of the stratum model according to the size of the breaking distance, a three-dimensional geological model with reasonable structure can be constructed, functions of model visualization and sectioning, reserve calculation, mining planning design, mining progress display, rescue scheme and the like can be completed on the basis of the geological model, and the updating difficulty of a follow-up model can be reduced.

Therefore, the architecture schematic diagram of the geological grid model provided in the embodiment of the application is as follows:

after the formation model is generated, the breaking distance needs to be adjusted, and a geological model with reasonable breaking distance is constructed as shown in fig. 2L. Wherein the break distance is extracted from the planar tomographic map and refers to the relative distance between the corresponding formations of the staggered formation on the two discs.

In summary, a flow chart of a geological modeling method provided by the embodiment of the present application is as follows:

as shown in fig. 2M, the geological modeling system adopts a control measurement method to introduce ground control points into the pit and lays a large number of high-precision control points, so that the coordinate systems of the upper part and the lower part of the mine are unified, and the precision of the three-dimensional model of the roadway constructed by scanning by the laser scanner is ensured. And then, the geological modeling system filters underground kilometer drilling data to obtain data points of the top and bottom of the coal bed, and a coal bed layer model is constructed. And then, the geological modeling system utilizes the digitally acquired well position, horizon and fault data, introduces roadway three-dimensional model feature points and coal seam roof and floor data points as virtual drilling to construct a stratum layer model, and simultaneously constructs a fault model by using the fault data so as to construct a corner grid model to obtain a three-dimensional stratum frame. Then, the geological modeling system inserts the layer model into the three-dimensional stratum frame, and constructs a vertical grid according to the stratum thickness and the model precision, so as to complete the preliminary construction of the three-dimensional stratum model. Finally, the geological modeling system adjusts the stratum models at two sides of the fault according to the size of the breaking distance to form a three-dimensional geological model with reasonable structure.

Further, as a specific implementation of the method illustrated in fig. 1, an embodiment of the present application provides a geological modeling apparatus, as shown in fig. 3, where the apparatus includes: the device comprises an acquisition module 301, a construction module 302, a generation module 303 and an adjustment module 304.

An acquisition module 301, configured to respond to a data scanning instruction, run a scanner, acquire a plurality of target point cloud data output by the scanner, and construct a roadway model using the plurality of target point cloud data;

the construction module 302 is configured to process kilometer drilling data by using a kriging interpolation algorithm to obtain a coal seam model, establish a plurality of virtual drilling wells by using the roadway model, and construct a bedding model by using the plurality of virtual drilling wells and coal seam related data in the coal seam model;

the generating module 303 is configured to obtain a fault chart, perform model construction by using fault data in the fault chart, obtain a fault model, and generate a stratum frame grid by using the fault model;

and the adjustment module 304 is configured to import the layer model into the stratigraphic framework grid to obtain a stratigraphic model, and adjust the stratigraphic model by using the break distance information in the fault map to obtain a target geological model.

In a specific application scenario, the acquiring module 301 is configured to determine, when the data scanning instruction is received, a target lane indicated by the data scanning instruction, acquire a preset first interval, and determine, based on the target lane, a plurality of control points according to the preset first interval; acquiring the plane position of each control point obtained based on a plane control measurement method, acquiring the elevation of each control point obtained based on an elevation control measurement method, and obtaining a plurality of control point coordinates by utilizing the plane position of each control point and the control point coordinates of each control point corresponding to the elevation Cheng Queding of each control point; operating the scanner, acquiring a plurality of point cloud data output by the scanner at each control point coordinate, obtaining a plurality of target point cloud data, and constructing a three-dimensional affine transformation model by utilizing the plurality of target point cloud data and the plurality of control point coordinates; acquiring a plurality of alignment point cloud data from the three-dimensional affine transformation model, and preprocessing the plurality of alignment point cloud data, wherein the preprocessing comprises filtering and denoising, data compaction and data interpolation; acquiring a multi-dimensional binary tree algorithm, and clustering the preprocessed plurality of registration point cloud data into a plurality of target data by using the multi-dimensional binary tree algorithm; and acquiring a preset construction algorithm, and performing triangular gridding treatment on the plurality of target data by adopting the preset construction algorithm to obtain the roadway model, wherein the preset construction algorithm is one of a convex hull algorithm and a concave hull algorithm.

In a specific application scenario, the construction module 302 is configured to obtain a drilling track coordinate, determine a plurality of branch holes according to the drilling track coordinate, and extract a start point coordinate value and an end point coordinate value of each branch hole in the drilling track coordinate to obtain a plurality of start point coordinate values and a plurality of end point coordinate values; obtaining a least square algorithm, performing fitting calculation on the plurality of starting point coordinate values and the end point coordinate values by using the least square algorithm to obtain a drilling track trend line, and respectively calculating distances from the plurality of starting point coordinate values and the plurality of end point coordinate values to the drilling track trend line to obtain a plurality of distance values; calculating an average value of the plurality of distance values to obtain an average distance value, acquiring a preset distance threshold calculation rule, and calculating the average distance value by using the preset distance threshold calculation rule to obtain a target distance threshold; acquiring a plurality of first distance values which do not exceed the target distance threshold value from the plurality of distance values, and deleting the first distance values from the plurality of distance values to obtain a plurality of target distance values; determining a plurality of target starting point coordinate values and a plurality of target ending point coordinate values corresponding to the plurality of target distance values, and determining a plurality of coal seam vertex coordinates and a plurality of coal seam bottom point coordinates by utilizing the plurality of target starting point coordinate values and the plurality of target ending point coordinate values; generating a coal seam section line by using the plurality of coal seam vertex coordinates and the plurality of coal seam bottom point coordinates, acquiring the Kriging interpolation algorithm, and processing the plurality of coal seam vertex coordinates, the plurality of coal seam bottom point coordinates and the coal seam section line by using the Kriging interpolation algorithm to obtain the coal seam model; the method comprises the steps of obtaining a roadway model, obtaining a preset second interval, setting virtual drilling holes in the roadway model according to the preset second interval to obtain a plurality of virtual drilling holes, and constructing the layer model by utilizing the plurality of virtual drilling holes and coal seam related data obtained from the coal seam model.

In a specific application scenario, the construction module 302 is configured to obtain a plurality of drilling data corresponding to the plurality of virtual drilling in the roadway model, obtain a plurality of preset items, and sort the plurality of drilling data according to a mapping relationship between each item of the plurality of drilling data and the plurality of preset items to obtain first well position data, where the plurality of preset items include a drilling name, a horizontal axis coordinate, a vertical axis coordinate, a bottom depth, and kilobytes; acquiring a drilling histogram, determining a plurality of horizons in the drilling histogram, and reading top depth information corresponding to each horizon in the drilling histogram to obtain a plurality of top depth information; arranging the plurality of top-depth information into a table to obtain a first data table; reading drilling related information from the drilling histogram, and sorting the drilling related information according to the mapping relation between each item of data in the drilling related information and the preset items to obtain second well position data; acquiring coal seam related data in the coal seam model, and arranging the coal seam related data into a table to obtain a second data table, wherein the coal seam related data comprises a plurality of coal seam vertex coordinates, a plurality of coal seam bottom point coordinates and coal seam horizon information; generating target horizon data using the first well location data, the first data table, the second data table, and the second well location data; and acquiring a Kriging interpolation algorithm, and calculating the target horizon data by using the Kriging interpolation algorithm to obtain the layer model.

In a specific application scenario, the construction module 302 is further configured to extract, for each horizon, a plurality of horizon coordinates of the horizon and horizon coordinate values corresponding to each horizon coordinate in the target horizon data, and calculate, using the plurality of horizon coordinate values, a horizon distance value and a half variance of any two horizon coordinates in the plurality of horizon coordinates, so as to obtain a plurality of horizon distance values and a plurality of half variances; establishing a relation function by adopting the plurality of horizon distance values and the plurality of half variances, obtaining an index model, and fitting the relation function by utilizing the index model to obtain a fitting function; calculating the horizon distance values by using a fitting function to obtain a plurality of first half variances, and calculating a half variance coefficient matrix by using the first half variances; obtaining unknown horizon coordinates of the horizon, calculating half variances from the unknown horizon coordinates to the plurality of horizon coordinates to obtain a plurality of second half variances, and calculating a coefficient equation by using the plurality of second half variances; calculating the half variance coefficient matrix and the coefficient equation to obtain a weighting coefficient, acquiring a plurality of attribute values corresponding to the plurality of horizon coordinates from the target horizon data, and carrying out weighted summation calculation on the plurality of attribute values by using the weighting coefficient to obtain an estimated value of the unknown horizon coordinates; and respectively calculating a plurality of horizon coordinates of each horizon to obtain a plurality of estimated values, and constructing the layer model by utilizing the target horizon data and the estimated values.

In a specific application scenario, the generating module 303 is configured to obtain the tomogram, perform coordinate correction on the tomogram, and read a tomogram inclination angle and an elevation range in the corrected tomogram; calculating projection positions of a coal seam roof line and a coal seam floor line in the fault chart by using the fault inclination angle and the elevation range, and determining parallel lines of the fault line at the projection positions of the fault chart, wherein the parallel lines comprise the fault roof line, the fault floor line, the coal seam roof line and the coal seam floor line; acquiring a preset processing algorithm, carrying out vectorization processing on the corrected fault graph by using the preset processing algorithm, setting the background color and the target color of the corrected fault graph, and carrying out pixel automatic tracking on the fault line and parallel lines of the fault line to obtain a plurality of pixel point coordinates; acquiring a preset pixel point filtering rule, filtering the pixel point coordinates by using the preset pixel point filtering rule, and generating fault data by using the filtered pixel point coordinates; acquiring a preset third interval, and performing digital processing on the fault data according to the preset third interval to obtain a plurality of discrete line segments; for each discrete line segment, acquiring an end point coordinate of the discrete line segment, obtaining a first end point coordinate and a second end point coordinate, calculating a plane vector and a vertical vector corresponding to the discrete line segment, and determining a fault plane corresponding to the fault line; calculating a target vector perpendicular to the discrete line segment and parallel to the fault plane by using the plane vector and the perpendicular vector; calculating the plane vector and the target vector to obtain a fault plane normal vector, acquiring an initial plane equation, and adding the fault plane normal vector and the first endpoint coordinate into the initial plane equation to obtain a fault plane equation; constructing the fault model by using the fault plane equation and the elevation range; extracting middle shape points from the fault model, acquiring a model boundary of the fault model, and acquiring a preset coordinate direction and a preset grid number corresponding to the preset coordinate direction, wherein the middle shape points are intersection points of three planes, which are divided into by a geologic body corresponding to the fault model in the elevation direction, and the fault plane; generating a plane quadrilateral grid by using the intermediate shape points, the model boundary, the preset coordinate direction and the preset grid number corresponding to the preset coordinate direction; and acquiring a fault trend, a fault top and a fault bottom in the fault model, constructing the plane quadrilateral grid to the fault top and the fault bottom according to the fault trend to obtain a columnar three-dimensional frame network connected with the fault top, the fault middle and the fault bottom, and taking the columnar three-dimensional frame network as the stratum frame grid.

In a specific application scenario, the adjustment module 304 is configured to import the layer model into the stratigraphic framework grid to obtain a three-dimensional grid, obtain target horizon data, read a plurality of stratigraphic thickness values from the target horizon data, and obtain a preset stratigraphic model accuracy; constructing a plurality of vertical grids by utilizing the plurality of stratum thickness values and the preset stratum model precision, and adjusting stratum frame grids imported into the stratum model by utilizing the plurality of vertical grids and the target horizon data to obtain the stratum model; and acquiring the fault map, reading the fault distance information and the fault influence range in the fault map, acquiring the first fault distance information and the fault information of the stratum model, and adjusting the first fault distance information and the fault information of the stratum model by utilizing the fault distance information and the fault influence range to obtain the target geological model.

The device provided by the embodiment of the application responds to a data scanning instruction, the scanner is operated, a plurality of target point cloud data output by the scanner are obtained, a roadway model is built by adopting the plurality of target point cloud data, kilometer drilling data are processed by utilizing a Kriging interpolation algorithm to obtain a coal seam model, a plurality of virtual drilling holes are built by utilizing the roadway model, a layer model is built by utilizing coal seam related data in the plurality of virtual drilling holes and the coal seam model, a fault map is obtained, the fault model is built by utilizing fault data in the fault map, a stratum frame grid is generated by utilizing the fault model, the layer model is led into the stratum frame grid to obtain the stratum model, the fault distance information in the fault map is utilized to adjust the stratum model to obtain a target geological model, a large number of high-precision roadway layer sites and coal seam top and bottom plate data are used as virtual drilling holes to build the high-precision roadway model and the high-precision coal seam model to restrain the stratum model, the construction of the high-precision three-dimensional geological model is fully fused, the high-precision geological model is built by improving the precision of the whole geological model, meanwhile, the artificial geological model and the artificial geological model of the roadway model and the coal seam model is also ensured to be high, the geological model is reduced, the human-based geological model is simplified, the construction process is simplified, and the manpower burden is reduced.

It should be noted that, for other corresponding descriptions of each functional unit related to the geological modeling apparatus provided in the embodiments of the present application, reference may be made to corresponding descriptions in fig. 1 and fig. 2A to fig. 2M, and detailed descriptions thereof are omitted herein.

In an exemplary embodiment, referring to fig. 4, there is also provided a computer device, which includes a bus, a processor, a memory, and a communication interface, and may further include an input-output interface and a display device, where each functional unit may perform communication with each other through the bus. The memory stores a computer program, and a processor is configured to execute the program stored in the memory to perform the geologic modeling method in the above embodiment.

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the geologic modeling method.

From the above description of the embodiments, it will be apparent to those skilled in the art that the present application may be implemented in hardware, or may be implemented by means of software plus necessary general hardware platforms. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to perform the methods described in various implementation scenarios of the present application.

Those skilled in the art will appreciate that the drawings are merely schematic illustrations of one preferred implementation scenario, and that the modules or flows in the drawings are not necessarily required to practice the present application.

Those skilled in the art will appreciate that modules in an apparatus in an implementation scenario may be distributed in an apparatus in an implementation scenario according to an implementation scenario description, or that corresponding changes may be located in one or more apparatuses different from the implementation scenario. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.

The foregoing application serial numbers are merely for description, and do not represent advantages or disadvantages of the implementation scenario.

The foregoing disclosure is merely a few specific implementations of the present application, but the present application is not limited thereto and any variations that can be considered by a person skilled in the art shall fall within the protection scope of the present application.

Claims

1. A method of geologic modeling, comprising:

Obtaining a fault chart, constructing a fault model by using fault data in the fault chart, generating a stratum frame grid by using the fault model, obtaining the fault chart, carrying out coordinate correction on the fault chart, reading a fault inclination angle and an elevation range in the corrected fault chart, calculating projection positions of a coal seam top line and a coal seam bottom line in the fault chart by using the fault inclination angle and the elevation range, determining parallel lines of the fault line at the projection positions of the fault chart, wherein the parallel lines comprise the fault top line, the fault bottom line, the coal seam top line and the coal seam bottom line, obtaining a preset processing algorithm, carrying out vectorization processing on the corrected fault chart by using the preset processing algorithm, setting background colors and target colors of the corrected fault chart, carrying out pixel automatic tracking on the parallel lines of the fault line and the fault line, obtaining a plurality of pixel coordinates, obtaining a preset pixel filtering rule, filtering the pixel coordinates by using the preset pixel filtering rule, generating fault data by using the filtered pixel coordinates, obtaining a preset third interval, digitizing the fault data according to the preset third interval to obtain a plurality of discrete line segments, obtaining the end point coordinates of the discrete line segments for each discrete line segment, obtaining a first end point coordinate and a second end point coordinate, calculating a plane vector and a vertical vector corresponding to the discrete line segments, determining a fault plane corresponding to the fault line, calculating a target vector which is perpendicular to the discrete line segments and parallel to the fault plane by using the plane vector and the vertical vector, calculating the plane vector and the target vector, obtaining a fault plane normal vector, obtaining an initial plane equation, adding the fault plane normal vector and the first end point coordinate into the initial plane equation to obtain a fault plane equation, constructing a fault model by using the fault plane equation and the elevation range, extracting middle shape points in the fault model, obtaining a model boundary of the fault model, obtaining preset coordinate directions and preset grid numbers corresponding to the preset coordinate directions, wherein the middle shape points are intersection points of three planes which are divided into by a geological body corresponding to the fault model in the elevation directions and the fault plane, generating a plane quadrilateral grid by using the middle shape points, the model boundary, the preset coordinate directions and the preset grid numbers corresponding to the preset coordinate directions, obtaining a fault trend, a fault top and a fault bottom in the fault model, constructing the plane quadrilateral grid to the fault top and the fault bottom according to the fault trend, and obtaining a columnar framework network which is connected with the columnar top, the middle and the fault bottom, and taking the columnar framework network as the columnar framework;

2. The method of claim 1, wherein the running the scanner and the obtaining the plurality of target point cloud data output by the scanner in response to the data scanning instruction, and constructing the roadway model using the plurality of target point cloud data comprises:

when the data scanning instruction is received, determining a target roadway indicated by the data scanning instruction, acquiring a preset first interval, and determining a plurality of control points according to the preset first interval based on the target roadway;

acquiring the plane position of each control point obtained based on a plane control measurement method, acquiring the elevation of each control point obtained based on an elevation control measurement method, and obtaining a plurality of control point coordinates by utilizing the plane position of each control point and the control point coordinates of each control point corresponding to the elevation Cheng Queding of each control point;

operating the scanner, acquiring a plurality of point cloud data output by the scanner at each control point coordinate, obtaining a plurality of target point cloud data, and constructing a three-dimensional affine transformation model by utilizing the plurality of target point cloud data and the plurality of control point coordinates;

Acquiring a plurality of alignment point cloud data from the three-dimensional affine transformation model, and preprocessing the plurality of alignment point cloud data, wherein the preprocessing comprises filtering and denoising, data compaction and data interpolation;

acquiring a multi-dimensional binary tree algorithm, and clustering the preprocessed plurality of registration point cloud data into a plurality of target data by using the multi-dimensional binary tree algorithm;

and acquiring a preset construction algorithm, and performing triangular gridding treatment on the plurality of target data by adopting the preset construction algorithm to obtain the roadway model, wherein the preset construction algorithm is one of a convex hull algorithm and a concave hull algorithm.

3. The method of claim 1, wherein processing kilometer borehole data using a kriging interpolation algorithm to obtain a coal seam model, establishing a plurality of virtual wells using the roadway model, and establishing a bedding model using the plurality of virtual wells and coal seam related data in the coal seam model, comprises:

acquiring drilling track coordinates, determining a plurality of branch holes according to the drilling track coordinates, and extracting a starting point coordinate value and an ending point coordinate value of each branch hole from the drilling track coordinates to obtain a plurality of starting point coordinate values and a plurality of ending point coordinate values;

Obtaining a least square algorithm, performing fitting calculation on the plurality of starting point coordinate values and the end point coordinate values by using the least square algorithm to obtain a drilling track trend line, and respectively calculating distances from the plurality of starting point coordinate values and the plurality of end point coordinate values to the drilling track trend line to obtain a plurality of distance values;

calculating an average value of the plurality of distance values to obtain an average distance value, acquiring a preset distance threshold calculation rule, and calculating the average distance value by using the preset distance threshold calculation rule to obtain a target distance threshold;

acquiring a plurality of first distance values which do not exceed the target distance threshold value from the plurality of distance values, and deleting the first distance values from the plurality of distance values to obtain a plurality of target distance values;

determining a plurality of target starting point coordinate values and a plurality of target ending point coordinate values corresponding to the plurality of target distance values, and determining a plurality of coal seam vertex coordinates and a plurality of coal seam bottom point coordinates by utilizing the plurality of target starting point coordinate values and the plurality of target ending point coordinate values;

generating a coal seam section line by using the plurality of coal seam vertex coordinates and the plurality of coal seam bottom point coordinates, acquiring the Kriging interpolation algorithm, and processing the plurality of coal seam vertex coordinates, the plurality of coal seam bottom point coordinates and the coal seam section line by using the Kriging interpolation algorithm to obtain the coal seam model;

The method comprises the steps of obtaining a roadway model, obtaining a preset second interval, setting virtual drilling holes in the roadway model according to the preset second interval to obtain a plurality of virtual drilling holes, and constructing the layer model by utilizing the plurality of virtual drilling holes and coal seam related data obtained from the coal seam model.

4. A method according to claim 3, wherein said constructing said bedding model from coal seam related data acquired from said coal seam model using said plurality of virtual wells comprises:

acquiring a plurality of drilling data corresponding to the plurality of virtual drilling in the roadway model, acquiring a plurality of preset items, and sorting the plurality of drilling data according to the mapping relation between each item of the plurality of drilling data and the plurality of preset items to obtain first well position data, wherein the plurality of preset items comprise drilling names, horizontal axis coordinates, vertical axis coordinates, bottom depth and kilobytes;

acquiring a drilling histogram, determining a plurality of horizons in the drilling histogram, and reading top depth information corresponding to each horizon in the drilling histogram to obtain a plurality of top depth information;

arranging the plurality of top-depth information into a table to obtain a first data table;

Reading drilling related information from the drilling histogram, and sorting the drilling related information according to the mapping relation between each item of data in the drilling related information and the preset items to obtain second well position data;

acquiring coal seam related data in the coal seam model, and arranging the coal seam related data into a table to obtain a second data table, wherein the coal seam related data comprises a plurality of coal seam vertex coordinates, a plurality of coal seam bottom point coordinates and coal seam horizon information;

generating target horizon data using the first well location data, the first data table, the second data table, and the second well location data;

and acquiring a Kriging interpolation algorithm, and calculating the target horizon data by using the Kriging interpolation algorithm to obtain the layer model.

5. The method of claim 4, wherein the computing the target horizon data using the kriging interpolation algorithm to obtain the horizon model comprises:

for each horizon, extracting a plurality of horizon coordinates of the horizon and horizon coordinate values corresponding to each horizon coordinate from the target horizon data, and calculating horizon distance values and half variances of any two horizon coordinates in the plurality of horizon coordinates by using the plurality of horizon coordinate values to obtain a plurality of horizon distance values and a plurality of half variances;

Establishing a relation function by adopting the plurality of horizon distance values and the plurality of half variances, obtaining an index model, and fitting the relation function by utilizing the index model to obtain a fitting function;

calculating the horizon distance values by using a fitting function to obtain a plurality of first half variances, and calculating a half variance coefficient matrix by using the first half variances;

obtaining unknown horizon coordinates of the horizon, calculating half variances from the unknown horizon coordinates to the plurality of horizon coordinates to obtain a plurality of second half variances, and calculating a coefficient equation by using the plurality of second half variances;

calculating the half variance coefficient matrix and the coefficient equation to obtain a weighting coefficient, acquiring a plurality of attribute values corresponding to the plurality of horizon coordinates from the target horizon data, and carrying out weighted summation calculation on the plurality of attribute values by using the weighting coefficient to obtain an estimated value of the unknown horizon coordinates;

and respectively calculating a plurality of horizon coordinates of each horizon to obtain a plurality of estimated values, and constructing the layer model by utilizing the target horizon data and the estimated values.

6. The method of claim 1, wherein the importing the layer model into the stratigraphic framework grid to obtain a stratigraphic model, and adjusting the stratigraphic model using the fault distance information in the fault map to obtain a target geologic model, comprises:

importing the layer model into the stratum frame grid to obtain a three-dimensional grid, obtaining target horizon data, reading a plurality of stratum thickness values in the target horizon data, and obtaining the accuracy of a preset stratum model;

constructing a plurality of vertical grids by utilizing the plurality of stratum thickness values and the preset stratum model precision, and adjusting stratum frame grids imported into the stratum model by utilizing the plurality of vertical grids and the target horizon data to obtain the stratum model;

and acquiring the fault map, reading the fault distance information and the fault influence range in the fault map, acquiring the first fault distance information and the fault information of the stratum model, and adjusting the first fault distance information and the fault information of the stratum model by utilizing the fault distance information and the fault influence range to obtain the target geological model.

7. A geologic modeling apparatus, comprising:

a generation module, configured to acquire a tomogram, perform model construction by using tomogram data in the tomogram to obtain a tomogram, generate a stratum frame grid by using the tomogram, acquire the tomogram, perform coordinate correction on the tomogram, read a tomogram inclination angle and an elevation range in the corrected tomogram, calculate projection positions of a coal seam roof line and a coal seam bottom line in the tomogram by using the tomogram inclination angle and the elevation range, determine parallel lines of the tomogram at the projection positions of the tomogram, wherein the parallel lines comprise the tomogram roof line, the tomogram bottom line, the coal seam roof line and the coal seam bottom line, acquire a preset processing algorithm, perform vectorization processing on the corrected tomogram by using the preset processing algorithm, set background colors and target colors of the corrected tomogram, and performing pixel automatic tracking on the fault line and parallel lines of the fault line to obtain a plurality of pixel point coordinates, obtaining a preset pixel point filtering rule, filtering the plurality of pixel point coordinates by using the preset pixel point filtering rule, generating fault data by using the filtered plurality of pixel point coordinates, obtaining a preset third interval, performing digital processing on the fault data according to the preset third interval to obtain a plurality of discrete line segments, obtaining end point coordinates of the discrete line segments for each discrete line segment to obtain a first end point coordinate and a second end point coordinate, calculating a plane vector and a vertical vector corresponding to the discrete line segments, determining a fault plane corresponding to the fault line, calculating a target vector which is perpendicular to the discrete line segments and parallel to the fault plane by using the plane vector and the vertical vector, calculating the plane vector and the target vector to obtain a fault plane normal vector, obtaining an initial plane equation, adding the fault plane normal vector and the first end point coordinate into the initial plane equation to obtain a fault plane equation, constructing a fault model by using the fault plane equation and the elevation range, extracting middle shape points in the fault model, obtaining a model boundary of the fault model, obtaining preset grid numbers corresponding to preset coordinate directions, wherein the middle shape points are intersection points of three planes, which are divided into by a geological body corresponding to the fault model in the elevation direction, and the fault plane, generating planar quadrilateral grids by using the middle shape points, the model boundary, the preset coordinate directions and the preset grid numbers corresponding to the preset coordinate directions, obtaining fault trend, fault top and fault bottom in the fault model, constructing the planar quadrilateral to the top, the bottom according to the fault trend, and obtaining a three-dimensional fault grid connected with the top, the middle and the bottom, and using the three-dimensional fault grid as a fault layer network;

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 6.