CN117541741A - Construction method of three-dimensional model of geologic body and electronic equipment - Google Patents
Construction method of three-dimensional model of geologic body and electronic equipment Download PDFInfo
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Abstract
The invention discloses a method for constructing a three-dimensional model of a geologic body and electronic equipment, and relates to the field of three-dimensional model construction. According to the invention, the three-dimensional geologic body model is constructed in the ArcGIS platform, and model construction automation can be realized based on various secondary development modes supported by the ArcGIS platform. The invention directly carries out interpolation operation aiming at the elevation information with spatial autocorrelation in theory, thereby avoiding the defect of thickness interpolation in the simplified processing method. Determining the elevation of the bottom surface of each virtual stratum layer by means of a space searching mode from the ground surface to top, dividing the geologic body type of the plane area in the virtual stratum according to the classification condition reflected by drilling holes or sections, further constructing a preliminary three-dimensional geologic body model, supplementing modeling data or directly modifying the model according to the space spreading state of the geologic body in the preliminary three-dimensional geologic body model, and further greatly improving the modeling efficiency.
Description
Technical Field
The invention relates to the field of three-dimensional model construction, in particular to a construction method of a geological body three-dimensional model and electronic equipment.
Background
In the field of geological exploration, the spatial distribution characteristics of the geologic body are presumed by using drilling and profile information, so that the method has important practical significance, and the establishment of an interactable three-dimensional model of the geologic body is an effective means for realizing the above-mentioned objects. For a long time, a spatial interpolation algorithm is commonly used in the industry to convert point-like elevation data into planar elevation data, but since planar data obtained by the interpolation algorithm only reflects the spatial distribution condition of the top surface or the bottom surface of a single geologic body, spatial position conflicts among different planar data obtained by interpolation of different top surfaces or bottom surfaces are difficult to avoid, so that a technical difficulty exists in constructing a three-dimensional model based on the planar data. One common simplified processing method is: the geological body of the research area is generalized into a fixed sequence in the vertical space distribution condition, the elevation information of the top surface and the bottom surface in the original drilling hole is subjected to difference layer by layer according to the established sequence, namely, the elevation information is converted into thickness information, interpolation operation is carried out on the thickness information, and then all three-dimensional thickness models are combined to obtain an integral three-dimensional model. The processing mode has the defect that the spatial distribution sequence of the geologic body obtained by artificial generalization is indirectly introduced in the process of converting the elevation value into the thickness, so that the spatial autocorrelation of the thickness value which participates in interpolation operation is influenced, and the spatial autocorrelation is the theoretical basis of the interpolation operation, so that the simplified processing mode is only suitable for a simple stratum model. One common non-simplified treatment is: the method is limited by complex spatial relationships of a plurality of planar data, can not be quickly converted into a three-dimensional model, analyzes the geologic body relationship based on the planar data, presumes other factors influencing the spatial distribution of the geologic body such as geologic structures, returns elevation information after interpolation modification, completes three-dimensional modeling after multiple adjustment, and has the advantages of needing manual whole-course participation and low modeling efficiency.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a construction method of a three-dimensional model of a geologic body and electronic equipment.
In order to achieve the above object, the present invention provides the following solutions:
the construction method of the three-dimensional model of the geologic body is realized based on an ArcGIS platform; the construction method comprises the following steps:
extracting elevation information of the surface contour line, and converting the elevation information of the surface contour line into surface elevation point element types;
extracting the elevation information of the geologic body classification place, and converting the elevation information of the geologic body classification place into an elevation point element class of the geologic body classification place;
converting the surface elevation point element class into a corresponding surface two-dimensional grid object;
converting the elevation point element class of the geologic body classification position into a corresponding two-dimensional grid object group;
acquiring pixels with elevation values exceeding the elevation values of the same projection positions in the two-dimensional grid objects on the ground surface in the two-dimensional grid object group, setting the acquired elevation values of all the pixels to be the elevation values of the pixels at the same projection positions in the two-dimensional grid objects on the ground surface by using a grid function Con, and recording the minimum elevation values in all the grid objects;
marking the surface two-dimensional grid object as a top grid, and converting the top grid into top triangle network data;
acquiring the maximum elevation value sources of all plane space positions in the two-dimensional grid object group by adopting a grid function HighestPosition, and recording the maximum elevation value sources of all plane space positions in the two-dimensional grid object group as a position grid in an integer grid data form; the pixel value of the position grid is used for expressing the serial number value of the grid object to which the maximum elevation value belongs in the two-dimensional grid object group;
converting the position grid into vector surface data, updating the vector surface data to obtain updated vector surface data, and obtaining a geologic body type in the process of updating the vector surface data;
updating the position grid by using the updated vector surface data as parameters and using a grid function Nibble to obtain an updated position grid;
selecting grid pixels at corresponding positions from a two-dimensional grid object group by using a grid function Pick on the basis of a position grid to obtain virtual stratum grid data consisting of single or multiple geological bottom elevation grids, and converting the virtual stratum grid data into bottom triangle network data;
based on each geologic body type, generating polyhedral data corresponding to the geologic body in virtual stratum raster data based on top triangle network data and bottom triangle network data and on the condition that the distribution range of the geologic body corresponding to the geologic body type in updated vector surface data;
setting pixel values of a portion of grid objects selected by Pick in a two-dimensional grid object group to be (Min_ Elv-1) by using a grid function Con on the basis of the updated position grid, and returning to execute the steps of acquiring maximum elevation value sources of all plane space positions in the two-dimensional grid object group by using a grid function HighestPosition and recording the maximum elevation value sources of all plane space positions in the two-dimensional grid object group as position grids in an integer grid data form by using a geologic body classification n contained in the two-dimensional grid object group as circulation times so as to generate a plurality of polyhedral data; where min_ Elv represents the minimum elevation value;
summarizing a plurality of polyhedral data to obtain a preliminary three-dimensional geologic body model, and based on the preliminary three-dimensional geologic body model, obtaining an ideal three-dimensional geologic body model through interactive browsing and editing.
Optionally, extracting elevation information of the surface contour line, and converting the elevation information of the surface contour line into a surface elevation point element class, which specifically includes:
extracting elevation information of the surface contour line from the digital line drawing of the research area, and converting the extracted elevation information of the surface contour line into a first point element class by utilizing an element inflection point turning tool;
extracting orifice elevation information from the drilling data, and converting the extracted orifice elevation information into a second point element class by using an XY event layer creating tool and an element class-to-element class tool;
and merging the first point element class and the second point element class by using a merging tool to obtain the surface elevation point element class.
Optionally, extracting elevation information of the geologic body classification place, and converting the elevation information of the geologic body classification place into an elevation point element class of the geologic body classification place, specifically including:
extracting elevation information of the geologic body classification place from the drilling data or the profile data, and arranging the extracted elevation information of the geologic body classification place into a spreadsheet;
and converting the electronic table into the elevation point element class of the geologic body classification by using an XY event layer creating tool and an element class-to-element class tool.
Optionally, each row in the spreadsheet represents a point; the electronic form comprises at least 4 columns; the electronic form includes an X coordinate, a Y coordinate, an elevation value, and a geologic volume classification.
Optionally, converting the surface elevation point element class into a surface two-dimensional grid object using a terrain rotation grid tool;
and performing type-by-type conversion on the elevation point element class at the classification position of the geologic body by using a spatial interpolation algorithm based on the data density to obtain a two-dimensional grid object group.
Optionally, during the conversion of the surface two-dimensional grid object and the two-dimensional grid object set, a clipping grid tool is used to remove the excess area according to the investigation region scope.
Optionally, the position grid is converted into vector surface data, the vector surface data is updated to obtain updated vector surface data, and in the process of updating the vector surface data, a geologic body type is obtained, which specifically includes:
converting the position grid into vector surface data by using a grid surface turning tool;
selecting and filtering out surface elements with areas smaller than a threshold value in the vector surface data by using a selection analysis tool to obtain updated vector surface data;
and in the process of selecting and filtering out the surface elements with areas smaller than the threshold value in the vector surface data by using a selection analysis tool, recording the sequence number value indicated by the undeleted part in the vector surface data to obtain the geologic body type.
Optionally, updating the position grid by using the updated vector surface data as a parameter and using a grid function Nibble to obtain an updated position grid, which specifically includes:
and integrating grid pixels corresponding to the surface elements with the area smaller than the threshold value in the position grid into adjacent pixels by using the updated vector surface data as parameters and using a grid function Nibble to obtain the updated position grid.
Further, the present invention also provides an electronic device, including:
a memory for storing a computer program;
and the processor is connected with the memory and is used for calling and executing the computer program so as to implement the method for constructing the three-dimensional model of the geologic body.
Optionally, the memory is a computer readable storage medium.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, the three-dimensional model of the geologic body is built in the ArcGIS platform, and the automation of model building can be realized based on various secondary development modes supported by the ArcGIS platform. In addition, the invention directly carries out interpolation operation aiming at the elevation information with spatial autocorrelation in theory, thereby avoiding the defect of thickness interpolation in the simplified processing method. The invention further relies on a space searching mode from the ground surface to the top, determines the elevation of the bottom surface of each virtual stratum layer by layer, divides the types of the geologic bodies in the plane area in the virtual stratum according to the classification condition reflected by drilling holes or sections, further constructs a preliminary three-dimensional geologic body model, supplements modeling data or directly modifies the model according to the space state of the geologic bodies in the preliminary three-dimensional geologic body model, and further greatly improves modeling efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for constructing a three-dimensional model of a geologic body according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method for constructing a three-dimensional model of a geologic body and electronic equipment, which can realize automation of model construction based on various secondary development modes supported by an ArcGIS platform, and can avoid defects aiming at thickness interpolation in a simplified processing method and greatly improve modeling efficiency.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
The construction method of the three-dimensional model of the geologic body is realized based on an ArcGIS platform, as shown in figure 1, and comprises the following realization processes:
step 1, extracting elevation information of the surface contour line, and converting the extracted elevation information of the surface contour line into surface elevation point element types.
In the practical application process, the elevation information of the surface contour line can be extracted from the digital line drawing of the research area, and the extracted elevation information of the surface contour line is converted into a first point element class by utilizing an element inflection point turning tool of the ArcGIS platform. Orifice elevation information is extracted from the borehole data, and the extracted orifice elevation information is converted to a second point element class using a create XY event map layer and element class-to-element class tool. And combining the first point element class and the second point element class into an earth Surface elevation point element class by using a combining tool, and marking the earth Surface elevation point element class as surface_ Elv _FC.
And 2, extracting elevation information of the geologic body classification position, and converting the extracted elevation information of the geologic body classification position into elevation point element types of the geologic body classification position.
In the practical application process, the elevation information of the geologic body classification position can be extracted from the drilling data or the profile data, and the extracted elevation information of the geologic body classification position is arranged into an electronic form. Each row in the sorted electronic form represents a point, which at least comprises 4 columns, an X coordinate, a Y coordinate, an elevation value and a geologic body classification. The electronic form is converted into the elevation point element Class of the geologic body classification by using an XY event layer and element Class-to-element Class tool, and the elevation point element Class of the geologic body classification is marked as class_ Elv _FC.
And step 3, converting the surface elevation point element class into a corresponding surface two-dimensional grid object, and converting the elevation point element class at the classification position of the geologic body into a corresponding two-dimensional grid object group. The surface elevation point element class is converted into a surface two-dimensional grid object, and a plurality of two-dimensional grid objects obtained by converting the elevation point element class at other classification positions form a two-dimensional grid object group. Whether it be a surface two-dimensional grid object or other two-dimensional grid objects in a two-dimensional grid object set, they are not essentially different, but are named separately because of the different primary and secondary positions throughout the process flow.
In the practical application process, a terrain rotation grid tool can be used for surface_elevation_fc (Surface Elevation point element class) to obtain a Surface two-dimensional grid object Elv _r0. For class_ Elv _fc (Class of elevation point elements at the geologic volume classification), then a suitable spatial interpolation algorithm is used (inverse distance weighted interpolation is used when the data density is low, kriging interpolation is used when the data density is high), and the data is converted into a two-dimensional grid object group type by type, which is denoted as Elv _rn. The value of n in Elv _Rn is an integer from 1, and is allocated to a fixed geologic body type.
Further, depending on the area of investigation, a clipping grid tool is used to remove the excess area. This is typically done because the region of interest is typically an irregular polygon, and the interpolated raster data distribution is a circumscribed rectangle of the polygon of the region of interest, and therefore needs to be cropped.
Step 4, comparing the two-dimensional grid object Elv _r0 with the two-dimensional grid object group Elv _rn.
In the practical application process, with reference to the two-dimensional grid object Elv _r0, the pixel whose elevation value exceeds the elevation value in the two-dimensional grid object Elv _r0 at the same projection position in the two-dimensional grid object group Elv _rn is set to the same value by using the grid function Con (i.e., the condition function), and the minimum elevation value min_ Elv in all grid data is recorded.
Step 5, taking the two-dimensional grid object Elv _R0 as a top grid, marking the top grid as upper_Raster, and converting the top grid into an irregular triangular network (TIN) data set to serve as top triangular network data. The top triangle mesh data is denoted upper_tin.
And 6, acquiring the maximum elevation value sources of all plane space positions in the two-dimensional grid object group Elv _Rn.
In the practical application process, the grid function HighestPosition (i.e. the highest Position function is obtained) can be used to obtain the maximum elevation value source of all plane space positions in the two-dimensional grid object group Elv _rn, and the maximum elevation value source is recorded as position_ster (i.e. Position grid) in the form of integer grid data. The pixel value of the maximum elevation value source position_register expresses the sequence number value of the grid to which the maximum elevation value belongs in the two-dimensional grid object group.
And 7, converting the maximum elevation value source position_Raster into vector surface data by using a grid surface turning tool (RasterToPolygon), wherein the vector surface data is marked as position_FC. The vector data is presented in the form of element class, and the data carries area information.
And selecting and filtering out surface elements with areas smaller than a threshold value in the vector surface data position_FC by using a selection analysis tool to obtain updated vector surface data, and recording the updated vector surface data as filtered_position_FC. In this process, if a deleted part is not needed, the updated vector surface data filtered_position_fc is equal to the vector surface data position_fc, and at this time, a sequence number value indicated by the undeleted part in the vector surface data position_fc may be recorded, so that the geologic body type may be obtained. In this process, the surfaces smaller than the threshold are deleted to avoid the situation that two elevation grids with smaller heights Cheng Chazhi are abnormal corresponding to the three-dimensional model when the partial winding occurs.
And 8, taking the updated vector surface data filtered_position_FC as a parameter, using a grid function Nibble (i.e. a silkworm function) for the maximum elevation value source position_Raster, and merging grid pixels corresponding to the surface elements with the area smaller than the threshold value into adjacent pixels to obtain an updated Position grid, and marking the updated Position grid as the filtered_position_Raster.
And 9, selecting grid pixels at corresponding positions from the two-dimensional grid object group Elv _Rn by using a grid function Pick (namely a selection function) and taking a maximum elevation value source position_Raster as a basis to obtain virtual stratum grid data consisting of single or multiple geological bottom elevation grids, converting the virtual stratum grid data into bottom triangle network data, and recording the bottom triangle network data as vTIN. Wherein the virtual stratigraphic grid data is denoted as vRaster.
And 10, according to the types of the geologic body obtained in the step 6, generating all polyhedron data corresponding to the geologic body in the virtual stratum grid data vRaster by using an extradobetween tool stretched between two TINs on the condition that the distribution range of the geologic body in the updated vector surface data filtered_position_FC is based on the top triangle network data upper_TIN and the bottom triangle network data vTIN one by one, wherein the polyhedron data format is MultiPatch.
And 11, setting the pixel value of the part of the grid objects selected by Pick in the two-dimensional grid object group Elv-Rn to be (Min_ Elv-1) by using a grid function Con according to the updated Position grid filtered_position_Raster. The significance of this step is: the part of the pixels of the two-dimensional grid object set Elv _rn that has been selected is marked because when its pixel value is set to min_ Elv-1, it will not be possible to select these pixels again by the loop selection process of step 12, i.e. it will not be possible to select the source of the maximum elevation value in step 6.
And 12, taking the geologic body classification n contained in the two-dimensional grid object group Elv _Rn as a limiting condition of the cycle times, and repeating the steps 5-11 to select n virtual stratum grids so as to generate corresponding polyhedral data.
And step 13, summarizing all polyhedral data to obtain a preliminary three-dimensional geologic body model. Based on the preliminary three-dimensional geologic body model, the ideal three-dimensional geologic body model can be obtained through interactive browsing and editing.
In the practical application process, the obtained ideal three-dimensional geologic body model is divided into three parts: (1) the measured data (2) is based on an organic combination of the estimation of the measured data and the geological background conditions of the epitaxial (3) region. The first part of measured data is completely utilized in the modeling method, the presumption and the extension are realized by means of elevation interpolation, the geological background condition comes from other investigation and research data, modeling staff find contradiction or unreasonable places according to the comparison of the space three-dimensional characteristics of the preliminary model and the background condition, and the mode of supplementing the measured data or independently modifying the model is confirmed to optimize the preliminary model.
Based on the above description, the construction method provided by the invention has the following advantages relative to the prior art:
the advantages are as follows: the invention directly applies interpolation operation to the elevation value of the geologic body classification position reacted in the drilling or profile to obtain an elevation grid, and takes the elevation grid as the data base of the whole three-dimensional model, thereby maximally ensuring that the geologic body classification information reflected in each drilling or profile data matches the classification condition of the corresponding space position of the geologic body three-dimensional model, fully utilizing precious exploration data, and simultaneously reflecting the space autocorrelation of geologic body distribution in the three-dimensional model.
The advantages are as follows: the invention can realize the automation of model construction by means of various automation technologies of the ArcGIS platform, and greatly improves the efficiency of model tuning. The advantage comes from the mode that the whole technical method framework is realized based on the ArcGIS platform, and all the used tools and methods and flow control can adopt a model builder (ModelBuilder), an ArcPy site package or other secondary development means supported by the platform to realize scripting of the technical flow.
The method has the following advantages: the final result model of the invention adopts a universal data format, namely a polyhedron (MultiPatch). This advantage results from step 9, generating polyhedral data for each formation based on the TIN dataset. Multipatch is a data format for storing three-dimensional geometry, mainly used for building modeling, supporting rendering material and texture information, and also supporting attribute data, so that it is a data format that is convenient for spatial analysis and can realize complex visualization effects.
In summary, the invention collects the elevation information of the ground surface of the research area from the digital map and the drilling data, collects the elevation value information of the classification place of the geologic body from the drilling or the section, and selects a proper interpolation algorithm to generate corresponding raster data; searching from top to bottom in a vertical space and generating bottom raster data of a virtual stratum closest to the top, classifying real geobodies of the virtual stratum in a plane space, and constructing a polyhedral three-dimensional model of the geobodies in a single virtual stratum one by one; taking the total classification number of the geologic bodies in the research area as a circulation limiting condition, searching and constructing a virtual stratum and a corresponding three-dimensional geologic body model layer by layer, and summarizing to obtain a primary model; and obtaining the ideal three-dimensional geologic body model through interactive editing or iterative modeling of the preliminary model.
Further, the present invention provides an electronic apparatus including: memory and a processor.
And a memory for storing a computer program.
And the processor is connected with the memory and is used for calling and executing the computer program so as to implement the method for constructing the three-dimensional model of the geologic body.
Furthermore, the computer program in the above-described memory may be stored in a computer-readable storage medium when it is implemented in the form of a software functional unit and sold or used as a separate product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the electronic device disclosed in the embodiment, since the electronic device corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. The construction method of the three-dimensional model of the geologic body is characterized by being realized based on an ArcGIS platform; the construction method comprises the following steps:
extracting elevation information of the surface contour line, and converting the elevation information of the surface contour line into surface elevation point element types;
extracting the elevation information of the geologic body classification place, and converting the elevation information of the geologic body classification place into an elevation point element class of the geologic body classification place;
converting the surface elevation point element class into a corresponding surface two-dimensional grid object;
converting the elevation point element class of the geologic body classification position into a corresponding two-dimensional grid object group;
acquiring pixels with elevation values exceeding the elevation values of the same projection positions in the two-dimensional grid objects on the ground surface in the two-dimensional grid object group, setting the acquired elevation values of all the pixels to be the elevation values of the pixels at the same projection positions in the two-dimensional grid objects on the ground surface by using a grid function Con, and recording the minimum elevation values in all the grid objects;
marking the surface two-dimensional grid object as a top grid, and converting the top grid into top triangle network data;
acquiring the maximum elevation value sources of all plane space positions in the two-dimensional grid object group by adopting a grid function HighestPosition, and recording the maximum elevation value sources of all plane space positions in the two-dimensional grid object group as a position grid in an integer grid data form; the pixel value of the position grid is used for expressing the serial number value of the grid object to which the maximum elevation value belongs in the two-dimensional grid object group;
converting the position grid into vector surface data, updating the vector surface data to obtain updated vector surface data, and obtaining a geologic body type in the process of updating the vector surface data;
updating the position grid by using the updated vector surface data as parameters and using a grid function Nibble to obtain an updated position grid;
selecting grid pixels at corresponding positions from a two-dimensional grid object group by using a grid function Pick on the basis of a position grid to obtain virtual stratum grid data consisting of single or multiple geological bottom elevation grids, and converting the virtual stratum grid data into bottom triangle network data;
based on each geologic body type, generating polyhedral data corresponding to the geologic body in virtual stratum raster data based on top triangle network data and bottom triangle network data and on the condition that the distribution range of the geologic body corresponding to the geologic body type in updated vector surface data;
setting pixel values of a portion of grid objects selected by Pick in a two-dimensional grid object group to be (Min_ Elv-1) by using a grid function Con on the basis of the updated position grid, and returning to execute the steps of acquiring maximum elevation value sources of all plane space positions in the two-dimensional grid object group by using a grid function HighestPosition and recording the maximum elevation value sources of all plane space positions in the two-dimensional grid object group as position grids in an integer grid data form by using a geologic body classification n contained in the two-dimensional grid object group as circulation times so as to generate a plurality of polyhedral data; where min_ Elv represents the minimum elevation value;
summarizing a plurality of polyhedral data to obtain a preliminary three-dimensional geologic body model, and based on the preliminary three-dimensional geologic body model, obtaining an ideal three-dimensional geologic body model through interactive browsing and editing.
2. The method for constructing a three-dimensional model of a geologic body according to claim 1, wherein extracting elevation information of a surface contour line and converting the elevation information of the surface contour line into a surface elevation point element class specifically comprises:
extracting elevation information of the surface contour line from the digital line drawing of the research area, and converting the extracted elevation information of the surface contour line into a first point element class by utilizing an element inflection point turning tool;
extracting orifice elevation information from the drilling data, and converting the extracted orifice elevation information into a second point element class by using an XY event layer creating tool and an element class-to-element class tool;
and merging the first point element class and the second point element class by using a merging tool to obtain the surface elevation point element class.
3. The method for constructing a three-dimensional model of a geologic body according to claim 1, wherein extracting elevation information of a classification place of the geologic body and converting the elevation information of the classification place of the geologic body into an elevation point element class of the classification place of the geologic body, comprises:
extracting elevation information of the geologic body classification place from the drilling data or the profile data, and arranging the extracted elevation information of the geologic body classification place into a spreadsheet;
and converting the electronic table into the elevation point element class of the geologic body classification by using an XY event layer creating tool and an element class-to-element class tool.
4. A method of constructing a three-dimensional model of a geologic volume according to claim 3, wherein each row in the electronic form represents a point; the electronic form comprises at least 4 columns; the electronic form includes an X coordinate, a Y coordinate, an elevation value, and a geologic volume classification.
5. The method for constructing a three-dimensional model of a geologic body according to claim 1, wherein the surface elevation point element class is converted into a surface two-dimensional grid object by using a terrain rotation grid tool;
and performing type-by-type conversion on the elevation point element class at the classification position of the geologic body by using a spatial interpolation algorithm based on the data density to obtain a two-dimensional grid object group.
6. The method for constructing a three-dimensional model of a geologic volume according to claim 5, wherein in the process of converting the two-dimensional grid object and the two-dimensional grid object group on the earth surface, a cutting grid tool is used to remove the redundant area according to the range of the investigation region.
7. The method for constructing a three-dimensional model of a geologic body according to claim 1, wherein the converting the position grid into vector surface data, updating the vector surface data to obtain updated vector surface data, and obtaining a geologic body type during updating the vector surface data, comprises:
converting the position grid into vector surface data by using a grid surface turning tool;
selecting and filtering out surface elements with areas smaller than a threshold value in the vector surface data by using a selection analysis tool to obtain updated vector surface data;
and in the process of selecting and filtering out the surface elements with the area smaller than the threshold value in the vector surface data by using a selection analysis tool, recording the sequence number value indicated by the undeleted part in the vector surface data, and obtaining the geologic body type.
8. The method for constructing a three-dimensional model of a geologic body according to claim 1, wherein the updating of the position grid by using the grid function Nibble with the updated vector surface data as a parameter, to obtain the updated position grid, comprises:
and integrating grid pixels corresponding to the surface elements with the area smaller than the threshold value in the position grid into adjacent pixels by using the updated vector surface data as parameters and using a grid function Nibble to obtain the updated position grid.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor, connected to the memory, for retrieving and executing the computer program to implement the method for constructing a three-dimensional model of a geological body according to any one of claims 1-8.
10. The electronic device of claim 9, wherein the memory is a computer-readable storage medium.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105321204A (en) * | 2014-12-18 | 2016-02-10 | 马鞍山城智信息技术有限公司 | Three-dimensional geological raster body model construction method |
| CN111968231A (en) * | 2020-08-14 | 2020-11-20 | 成都理工大学 | Three-dimensional stratum modeling method based on geological map section |
| CN113902861A (en) * | 2021-10-11 | 2022-01-07 | 安徽理工大学 | Three-dimensional geological modeling method based on machine learning |
| CN116933607A (en) * | 2023-09-15 | 2023-10-24 | 中国电建集团昆明勘测设计研究院有限公司 | Mine resource model creation method, device, equipment and storage medium |
| CN117351165A (en) * | 2023-11-16 | 2024-01-05 | 四川省天晟源环保股份有限公司 | Construction and calculation method of three-dimensional stratum model based on ArcGIS |
-
2024
- 2024-01-10 CN CN202410032353.3A patent/CN117541741B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105321204A (en) * | 2014-12-18 | 2016-02-10 | 马鞍山城智信息技术有限公司 | Three-dimensional geological raster body model construction method |
| CN111968231A (en) * | 2020-08-14 | 2020-11-20 | 成都理工大学 | Three-dimensional stratum modeling method based on geological map section |
| CN113902861A (en) * | 2021-10-11 | 2022-01-07 | 安徽理工大学 | Three-dimensional geological modeling method based on machine learning |
| CN116933607A (en) * | 2023-09-15 | 2023-10-24 | 中国电建集团昆明勘测设计研究院有限公司 | Mine resource model creation method, device, equipment and storage medium |
| CN117351165A (en) * | 2023-11-16 | 2024-01-05 | 四川省天晟源环保股份有限公司 | Construction and calculation method of three-dimensional stratum model based on ArcGIS |
Non-Patent Citations (2)
| Title |
|---|
| 殷梓峰: "泰州里下河区域三维地质建模方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, no. 2, 15 February 2023 (2023-02-15), pages 037 - 125 * |
| 马朝阳 等: "新型三维地质建模方法及其在成都-昌都区域建模的应用", 《西北地质》, vol. 55, no. 2, 23 May 2022 (2022-05-23), pages 82 - 92 * |
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