A dynamic meshing method based on earthwork distribution

Abstract

The present invention discloses a dynamic grid division method based on earthwork distribution. The method includes determining the stratigraphic attribute information and stratigraphic sequence information of the target land area based on the land description data of the target land area; constructing a three-dimensional geological model of the target land area based on the stratigraphic attribute information and stratigraphic sequence information; determining the soil complexity for the designated spatial area of ​​the three-dimensional geological model, and adjusting the initial grid division parameters of the designated spatial area based on the soil complexity to obtain adjusted grid division parameters; and gridding the three-dimensional geological model corresponding to the designated spatial area based on the adjusted grid division parameters. The technical solution of the present invention improves the adaptability of the grid division method in large-scale complex earthwork projects, thereby improving the accuracy of project planning and resource management.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a dynamic grid division method based on earthwork distribution. Background Art

[0002] In large-scale and complex earthwork projects, such as canal construction, the management of earthwork resources is often difficult. Traditional management methods use rough grid division methods, and the grid division method remains unchanged for different geological conditions. This leads to large errors in the estimation and management of large-scale and complex earthwork resources during construction. Summary of the Invention

[0003] The present invention provides a dynamic grid division method based on earthwork distribution to improve the adaptability of the grid division method in large-scale complex earthwork projects, thereby improving the accuracy of project planning and resource management.

[0004] According to one aspect of the present invention, a dynamic grid division method based on earthwork distribution is provided, comprising:

[0005] Determining stratigraphic attribute information and stratigraphic sequence information of the target land area based on land description data of the target land area;

[0006] constructing a three-dimensional geological model of the target land area based on the stratigraphic attribute information and the stratigraphic sequence information;

[0007] Determining soil complexity for a designated spatial region of the three-dimensional geological model, and adjusting initial meshing parameters of the designated spatial region according to the soil complexity to obtain adjusted meshing parameters;

[0008] The three-dimensional geological model corresponding to the designated spatial area is grid-divided according to the adjusted grid-division parameters.

[0009] According to another aspect of the present invention, a dynamic grid division device based on earthwork distribution is provided, comprising:

[0010] a stratigraphic information determination module, configured to determine stratigraphic attribute information and stratigraphic sequence information of a target land area based on land description data of the target land area;

[0011] a three-dimensional geological model construction module, configured to construct a three-dimensional geological model of the target land area based on the stratum attribute information and the stratum sequence information;

[0012] a parameter adjustment module, configured to determine soil complexity for a designated spatial region of the three-dimensional geological model, and adjust initial meshing parameters of the designated spatial region according to the soil complexity to obtain adjusted meshing parameters;

[0013] A grid division module is used to perform grid division on the three-dimensional geological model corresponding to the designated spatial area according to the adjusted grid division parameters.

[0014] According to another aspect of the present invention, an electronic device is provided, comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the dynamic grid division method based on earthwork distribution described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the dynamic grid division method based on earthwork distribution described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention determines the stratigraphic attribute information and stratigraphic sequence information of the target land area based on the land description data of the target land area; constructs a three-dimensional geological model of the target land area based on the stratigraphic attribute information and stratigraphic sequence information; determines the soil complexity for the specified spatial area of ​​the three-dimensional geological model, and adjusts the initial grid division parameters of the specified spatial area according to the soil complexity to obtain the adjusted grid division parameters; grids the three-dimensional geological model corresponding to the specified spatial area according to the adjusted grid division parameters, and adopts a technical means of establishing a three-dimensional geological model based on the stratigraphic description information of the land area, thereby adaptively adjusting the grid division parameters of the three-dimensional geological model according to the soil complexity. This solves the problem that the grid division method for large-scale complex earthwork resources in the existing technology is rough, and the grid division method for different geology is unchanged, resulting in large errors in the estimation and management of large-scale complex earthwork resources during the construction process, improves the adaptability of the grid division method in large-scale complex earthwork projects, and thus improves the accuracy of project planning and resource management.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flow chart of a dynamic grid division method based on earthwork distribution provided in the first embodiment of the present invention;

[0023] Figure 2 A flow chart of another dynamic grid division method based on earthwork distribution provided in the second embodiment of the present invention;

[0024] Figure 3 A schematic structural diagram of a dynamic grid division device based on earthwork distribution provided in the third embodiment of the present invention;

[0025] Figure 4 The present invention is a schematic structural diagram of an electronic device for implementing a dynamic grid division method based on earthwork distribution according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Example 1

[0029] Figure 1This is a flow chart of a dynamic grid division method based on earthwork distribution provided in the first embodiment of the present invention. This embodiment is applicable to the management of earthwork resources. The method can be executed by a dynamic grid division device based on earthwork distribution. The dynamic grid division device based on earthwork distribution can be implemented in the form of hardware and / or software. The dynamic grid division device based on earthwork distribution can be configured in a server. Figure 1 As shown, the method includes:

[0030] S110 , determining stratigraphic attribute information and stratigraphic sequence information of the target land area based on the land description data of the target land area.

[0031] The target land area may refer to a portion of a large-scale earthwork project, or may be an area to be modeled. Land description data may refer to data describing the land conditions within the target land area, and may include stratigraphic profile data and borehole data. Strata attribute information may refer to information about the types of strata within the target land area, such as clay, sand, or rock. Strata sequence information may refer to information about the order of various strata within the target land area.

[0032] In this embodiment, land description data such as stratigraphic trend data and drilling data of the target land area may be collected, and stratigraphic attribute information and stratigraphic sequence information of the target land area may be determined based on the land description data.

[0033] Optionally, the stratum profile data may include stratum dip data; and the drilling data may include stratum top and bottom interface coordinates, stratum depth data, and stratum attribute data.

[0034] Accordingly, determining the stratigraphic attribute information and stratigraphic sequence information of the target land area based on the land description data of the target land area may include: regularly dividing the target land area in three-dimensional space according to preset segmentation parameters to obtain multiple grid segmentation units; interpolating each grid segmentation unit according to the stratigraphic inclination data and the stratigraphic depth data to obtain the interpolation result of each grid segmentation unit, and determining the stratigraphic attribute information of the target land area according to the interpolation result of each grid segmentation unit; the interpolation result represents the stratigraphic attribute type; determining the occurrence frequency of each stratum in the vertical position according to the coordinates of the top and bottom interfaces of the stratum, the stratigraphic depth data and the stratigraphic attribute data; and statistically sorting the strata of the target land area according to the occurrence frequency to determine the stratigraphic sequence information of the target land area.

[0035] The preset subdivision parameters may be parameters for regularly subdividing the target land area in three-dimensional space, and the preset subdivision parameters may be set based on human experience. The grid subdivision unit may refer to a unit space after the target land area is subdivided according to the preset subdivision parameters.

[0036] In this embodiment, stratigraphic profile data and drilling data can be collected and preprocessed, and the data can be converted into a data format that meets the requirements of geological modeling. By analyzing the stratigraphic profile data, characteristic information such as stratigraphic dip angle can be obtained, and the coordinates, depth and attribute information of the top and bottom interfaces of the stratigraphic formation can be extracted from the drilling data. The data can also be preprocessed, including data cleaning, removal of outliers and normalization, to improve data quality.

[0037] The land area for which a 3D geological model is to be generated can be spatially segmented, generating regular grid cells in 3D space. Furthermore, a co-kriging interpolation model can be used to interpolate each grid cell based on stratigraphic dip data and borehole data. The stratigraphic attribute information of the target land area can then be determined based on the interpolation results for each grid cell.

[0038] The occurrence frequency of various strata in the target land area can be determined based on geological theory and drilling data, thereby determining the stratigraphic sequence information of the target land area.

[0039] Optionally, interpolation processing is performed on each grid subdivision unit based on the formation inclination data and the formation depth data to obtain the interpolation result of each grid subdivision unit, which may include: determining the current grid subdivision unit; searching for the first type of drilling data with known formation depth data and the second type of drilling data with known formation inclination data within the influence radius of the current grid subdivision unit; weighted summing the formation depth data of the first type of drilling data to obtain a first value, and weighted summing the formation inclination data of the second type of drilling data to obtain a second value; and obtaining the interpolation result of the current grid subdivision unit based on the sum of the first value and the second value.

[0040] In this embodiment, known borehole data points can be searched within the influence radius of the current grid subdivision unit, with the formation depth as the main variable and the formation dip as the auxiliary variable. Calculate the interpolation results of the current grid unit, including the formation depth value, interpolation standard error and formation attribute type, and use cross-validation method for quality control to ensure the accuracy and geological rationality of the interpolation results. represents the interpolation result of the current mesh subdivision unit, Indicates the main variable At known data points The weight coefficient at Represents auxiliary variables At known data points The weight coefficient at , n represents the number of known data points of the main variable, and m represents the number of known data points of the auxiliary variable. Equivalent to the stratigraphic depth of the first type of borehole data, Equivalent to the stratigraphic inclination of the second type of borehole data. Equivalent to the first value, Equivalent to the second value.

[0041] In this embodiment, the weight coefficient and This can be determined by:

[0042] The semivariogram model is established by analyzing the spatial correlation between multiple variables, where the autovariogram It represents half of the expected value of the square of the difference between two points at a distance h of the same variable, and is used to describe the spatial continuity of the variable itself, the cross-variogram function It represents half of the expected value of the product of the difference values ​​of two different variables at a distance h, and is used to quantify the spatial correlation between different variables.

[0043] The variogram can determine , the cross-variogram function can determine The variance function value is expressed through the covariance relationship Convert it into covariance value, then construct the co-kriging linear equation system, and solve the optimal weight coefficient by the least squares method. Represents the total variance of the variable, represented by the nugget value (random variation at the microscopic scale) and the sill value (macro-scale spatial structure), i.e. When the spatial distance The covariance reaches its maximum value when ; With the distance Increase, variogram Increase, covariance It decreases accordingly, reflecting the attenuation process of spatial correlation.

[0044] For the main variable stratum depth, the variogram Construct an n×n dimensional covariance matrix ,in Indicates location and The covariance value of the depth of the formation. The diagonal elements of the matrix is the total variance of the formation depth, and the non-diagonal elements are based on the spatial distance The results calculated from the variogram model show that the closer the distance, the larger the covariance value, reflecting a stronger spatial correlation.

[0045] Cross-variogram function Constructing the cross-covariance matrix ,in Indicates that the main variable is at position with auxiliary variables in position The covariance value of . is the initial value of the covariance of the two variables (obtained through sample data statistics), and the cross-covariance matrix is ​​of n×m dimensions, reflecting the coordinated change relationship between the main variable stratum depth and the auxiliary variables topographic trend and stratum dip in different spatial positions.

[0046] The final covariance matrix combination is: ,in is the covariance matrix of the main variables, is the covariance matrix of the auxiliary variables, and is the cross-covariance matrix. This comprehensive covariance matrix fully describes the correlation structure distribution of multiple variables in three-dimensional space, providing a complete mathematical basis for the optimal solution of weight coefficients in cokriging interpolation, ensuring that the interpolation process can fully utilize the spatial information of the main and auxiliary variables for collaborative estimation.

[0047] Cokriging solves the weight coefficients by formulating the following system of linear equations: ;in: represents the unit column vector used for unbiased constraints; Indicates valuation point and the covariance vector between each known main variable sample point, Indicates valuation point The covariance vector between α and each known auxiliary variable sample point; α and μ represent the weight coefficient vectors that need to be solved; θ represents the Lagrange multiplier.

[0048] S120: Construct a three-dimensional geological model of the target land area based on the stratum attribute information and the stratum sequence information.

[0049] In an optional embodiment, constructing a three-dimensional geological model of the target land area based on stratigraphic attribute information and stratigraphic sequence information may include: dividing each grid subdivision unit recording the interpolation results into discrete geological blocks based on the stratigraphic sequence information; determining the boundary range and discrete geological block range of the stratigraphic layers corresponding to different stratigraphic attributes based on the stratigraphic attribute information and stratigraphic sequence information; and constructing a three-dimensional geological model of the target land area based on the boundary range and discrete geological block range of each stratigraphic layer.

[0050] In this embodiment, based on the stratigraphic sequence information of the target land area, each grid cell containing the interpolation results can be further divided into discrete geological blocks. Each discrete geological block corresponds to a specific stratigraphic layer or geological unit. Based on the stratigraphic attribute information and stratigraphic sequence information, the boundary range of each stratigraphic layer and the range of the discrete geological blocks are determined, thereby constructing an accurate 3D geological model that reflects the spatial distribution and interrelationships of different stratigraphic layers.

[0051] S130 , determining soil complexity for a designated spatial region of the three-dimensional geological model, and adjusting initial meshing parameters of the designated spatial region according to the soil complexity to obtain adjusted meshing parameters.

[0052] In this embodiment, initial grid division parameters can be set for the three-dimensional geological model corresponding to the target land area. During actual operation, the initial grid division parameters are adaptively adjusted according to the soil complexity of the specified spatial area to obtain adjusted grid division parameters that match the specified spatial area.

[0053] S140 , gridding the three-dimensional geological model corresponding to the designated spatial area according to the adjusted gridding parameters.

[0054] In this embodiment, the specified spatial area of ​​the three-dimensional geological model is divided according to the adjusted grid division parameters. The grid division method set in this way can adapt to the geological characteristics of different areas, so that the degree of grid division is dynamically adjusted with the complexity of the spatial soil type, achieving the effect of finer division as the soil type becomes more complex.

[0055] The technical solution of this embodiment adopts a technical means of establishing a three-dimensional geological model based on the stratigraphic description information of the land area, and adaptively adjusting the grid division parameters of the three-dimensional geological model according to the complexity of the soil. This solves the problem that the grid division method of the existing technology for large-scale complex earth and stone resources is rough and the grid division method for different geological conditions is unchanged, which leads to large errors in the estimation and management of large-scale complex earth and stone resources during the construction process. It improves the adaptability of the grid division method in large-scale complex earth and stone projects, thereby improving the accuracy of project planning and resource management.

[0056] Example 2

[0057] Figure 2 This is a flow chart of another dynamic grid division method based on earthwork distribution provided in the second embodiment of the present invention. Based on the above embodiments, this embodiment refines the operation of determining the soil complexity for the specified spatial area of ​​the three-dimensional geological model. Figure 2 As shown, the method includes:

[0058] S210 , determining stratigraphic attribute information and stratigraphic sequence information of the target land area based on the land description data of the target land area; dividing the target land area into a plurality of grid subdivision units in three-dimensional space.

[0059] S220: Construct a three-dimensional geological model of the target land area based on the stratum attribute information and the stratum sequence information.

[0060] S230: Determine the number of soil types within a designated spatial area of ​​the three-dimensional geological model.

[0061] The designated spatial region can refer to a local space within a 3D geological model. The soil properties of the target land area can be complex and diverse. Through stratigraphic property analysis, the 3D geological model can be regionalized. The number of soil types can refer to the total number of soil types within the designated spatial region. Soil types can include, for example, clay, sand, and rock.

[0062] S240: Numerically encode the soil properties in each grid unit in the designated spatial region, and determine the spatial soil variation coefficient in the designated spatial region based on the numerical codes.

[0063] Among them, the spatial soil variation coefficient can be an indicator in the process of soil complexity assessment, and the spatial soil variation coefficient can be used to quantify the uniformity of soil distribution.

[0064] In an optional embodiment, determining the spatial soil variation coefficient within a specified spatial area based on numerical codes may include: determining the number of grid subdivision units within the specified spatial area; calculating the average value and standard deviation of the numerical codes of the soil properties in each grid subdivision unit in the specified spatial area based on the number of grid subdivision units; and determining the spatial soil variation coefficient within the specified spatial area based on the ratio of the standard deviation to the average value.

[0065] For example, the numerical code of the soil property may be clay=1, sand=2, rock=3, etc. Thus, the spatial soil variation coefficient of a specified spatial region may be calculated based on the numerical code of the soil property.

[0066] S250. Determine the soil complexity of a specified spatial area based on the number of soil types and the spatial soil variation coefficient.

[0067] Optionally, determining the soil complexity of a specified spatial area based on the number of soil types and the spatial soil variation coefficient may include: when the number of soil types is greater than a first quantity limit value and the spatial soil variation coefficient is greater than the first variation coefficient limit value, determining the soil complexity of the specified spatial area to be the first level; when the number of soil types is greater than a second quantity limit value and less than the first quantity limit value, and the spatial soil variation coefficient is greater than the second variation coefficient limit value and less than the first variation coefficient limit value, determining the soil complexity of the specified spatial area to be the second level; when the number of soil types is less than the second quantity limit value and the spatial soil variation coefficient is less than the second variation coefficient limit value, determining the soil complexity of the specified spatial area to be the third level.

[0068] For example, when the number of soil types N>5 (equivalent to the first quantitative limit value) and the spatial soil variation coefficient CV>0.8 (equivalent to the first coefficient of variation limit value), it is defined as a complex area (equivalent to the first level); when 2 (equivalent to the second quantitative limit value)≤N≤5 or 0.3 (equivalent to the second coefficient of variation limit value)≤CV≤0.8, it is defined as a moderately complex area (equivalent to the second level); when N<2 and CV<0.3, it is defined as a simple area (equivalent to the third level).

[0069] S260. Adjust initial mesh parameters of the designated spatial region according to the soil complexity to obtain adjusted mesh parameters.

[0070] In this embodiment, a spatial analysis of the three-dimensional geological model of the target soil area can be performed to identify the boundaries, characteristics, and variations of different geological regions, thereby establishing quantitative standards to determine the initial grid parameters. The initial grid parameters may include the minimum grid size, the maximum grid size, and the number of grid levels. For example, a minimum grid size of 5 meters is suitable for complex areas with ≥5 soil types, while a maximum grid size of 50 meters is suitable for simple areas with a single soil type. A three-level grid hierarchy is established, including a primary grid (30-50 meters), a secondary grid (15-25 meters), and a tertiary grid (5-10 meters). If the soil complexity is the first level, a third-level grid can be used for division, with the minimum and maximum grid sizes adaptively adjusted within the three-level grid range. If the soil complexity is the second level, a second-level grid can be used for division, with the minimum and maximum grid sizes adaptively adjusted within the second-level grid range. If the soil complexity is the third level, a primary grid can be used for division, with the minimum and maximum grid sizes adaptively adjusted within the primary grid range.

[0071] In this embodiment, the adaptive adjustment of the grid division can support the user to define the grid size and the number of levels, and can also support the user to manually adjust the grid.

[0072] S270 , gridding the three-dimensional geological model corresponding to the designated spatial area according to the adjusted gridding parameters.

[0073] In practical applications, the gridded results can be seamlessly integrated with BIM (Building Information Modeling) or GIS (Geographic Information System) platforms to achieve refined and grid-based management of large-scale earthwork resources, providing a scientific basis for project planning and resource management. Based on the gridding results, the earthwork volume can be accurately calculated for the actual project area, obtaining the volume, type, and distribution of earthwork within each grid cell. Based on this grid cell earthwork information, an earthwork resource allocation plan can be developed, taking into account factors such as transportation distance and cost, construction schedule requirements, and geological stability.

[0074] The technical solution of this embodiment combines stratum inclination and drilling data to perform sparse data interpolation, thereby improving the interpolation accuracy under sparse data conditions. It also adopts a dynamic grid division method, which can adjust the grid division in real time according to changes in actual geological conditions, making the grid more consistent with geological characteristics, improving the accuracy of earthwork volume calculation, and realizing refined and gridded management of earthwork resources. It provides a scientific basis for project planning, construction progress control, cost management and quality assurance, and helps to improve the overall efficiency and sustainability of the project.

[0075] Example 3

[0076] Figure 3 This is a schematic diagram of the structure of a dynamic grid division device based on earthwork distribution provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: a stratum information determination module 310, a three-dimensional geological model construction module 320, a parameter adjustment module 330 and a grid division module 340. Among them:

[0077] Stratum information determination module 310, for determining stratigraphic attribute information and stratigraphic sequence information of the target land area based on land description data of the target land area;

[0078] A three-dimensional geological model construction module 320 is used to construct a three-dimensional geological model of the target land area based on the stratigraphic attribute information and the stratigraphic sequence information;

[0079] a parameter adjustment module 330 for determining soil complexity for a designated spatial region of the three-dimensional geological model and adjusting initial meshing parameters of the designated spatial region according to the soil complexity to obtain adjusted meshing parameters;

[0080] The grid division module 340 is configured to perform grid division on the three-dimensional geological model corresponding to the designated spatial area according to the adjusted grid division parameters.

[0081] The technical solution of this embodiment adopts a technical means of establishing a three-dimensional geological model based on the stratigraphic description information of the land area, and adaptively adjusting the grid division parameters of the three-dimensional geological model according to the complexity of the soil. This solves the problem that the grid division method of the existing technology for large-scale complex earth and stone resources is rough and the grid division method for different geological conditions is unchanged, which leads to large errors in the estimation and management of large-scale complex earth and stone resources during the construction process. It improves the adaptability of the grid division method in large-scale complex earth and stone projects, thereby improving the accuracy of project planning and resource management.

[0082] Optionally, the land description data includes stratigraphic profile data and drilling data; the stratigraphic profile data includes stratigraphic dip data; the drilling data includes stratigraphic top and bottom interface coordinates, stratigraphic depth data, and stratigraphic attribute data;

[0083] Accordingly, the formation information determination module 310 includes:

[0084] A grid subdivision unit acquisition unit, configured to regularly subdivide the target land area in three-dimensional space according to preset subdivision parameters to obtain a plurality of grid subdivision units;

[0085] a stratum attribute information determining unit, configured to perform interpolation processing on each grid subdivision unit based on the stratum dip data and the stratum depth data to obtain an interpolation result for each grid subdivision unit, and determine the stratum attribute information of the target land area based on the interpolation result for each grid subdivision unit; the interpolation result indicates a stratum attribute type;

[0086] a stratum occurrence frequency determination unit, configured to determine the occurrence frequency of each stratum in a vertical position according to the coordinates of the top and bottom interfaces of the stratum, the stratum depth data, and the stratum attribute data;

[0087] The stratigraphic sequence information determining unit is configured to statistically sort the stratigraphic layers of the target land area according to the occurrence frequencies, and determine the stratigraphic sequence information of the target land area.

[0088] Optionally, the stratum attribute information determination unit may be used to:

[0089] Determine the current mesh subdivision unit;

[0090] Searching for first-category drilling data with known stratum depth data and second-category drilling data with known stratum dip data within the influence radius of the current grid subdivision unit;

[0091] A first value is obtained by weighted summing of the stratum depth data of the first type of drilling data, and a second value is obtained by weighted summing of the stratum inclination data of the second type of drilling data;

[0092] An interpolation result of the current grid subdivision unit is obtained according to the sum of the first value and the second value.

[0093] Optionally, the 3D geological model building module 320 may be used to:

[0094] According to the stratigraphic sequence information, each grid unit recording the interpolation result is divided into discrete geological blocks;

[0095] Determining the boundary ranges of strata and the ranges of discrete geological blocks corresponding to different strata attributes based on the stratum attribute information and the stratum sequence information;

[0096] A three-dimensional geological model of the target land area is constructed based on the boundary range of each stratum and the range of discrete geological blocks.

[0097] Optionally, the parameter adjustment module 330 includes:

[0098] a soil type quantity determination unit, configured to determine the number of soil types within a specified spatial region of the three-dimensional geological model;

[0099] a spatial soil variation coefficient determination unit, configured to numerically encode the soil properties in each grid unit in the designated spatial region, and determine the spatial soil variation coefficient in the designated spatial region according to the numerical encoding;

[0100] The soil complexity determination unit is used to determine the soil complexity of the designated spatial area according to the number of soil types and the spatial soil variation coefficient.

[0101] Optional, spatial soil variation coefficient determination unit, specifically can be used for:

[0102] Determining the number of mesh subdivision units within the specified spatial region;

[0103] Calculating the average value and standard deviation of the numerical codes of the soil properties in each grid unit in the designated spatial area according to the number of grid units;

[0104] The spatial soil variation coefficient in the designated spatial area is determined based on the ratio of the standard deviation to the average value.

[0105] Optional soil complexity determination unit, specifically used for:

[0106] When the number of soil types is greater than a first quantity limit value and the spatial soil variation coefficient is greater than a first variation coefficient limit value, determining that the soil complexity of the designated spatial area is the first level;

[0107] When the number of soil types is greater than the second quantity limit value and less than the first quantity limit value, and the spatial soil variation coefficient is greater than the second variation coefficient limit value and less than the first variation coefficient limit value, the soil complexity of the designated spatial area is determined to be the second level;

[0108] When the number of soil types is less than the second quantity limit value and the spatial soil variation coefficient is less than the second variation coefficient limit value, the soil complexity of the designated spatial area is determined to be the third level.

[0109] The dynamic mesh division device based on earthwork distribution provided by the embodiment of the present invention can execute the dynamic mesh division method based on earthwork distribution provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0110] Example 4

[0111] Figure 4 A schematic diagram of an electronic device 400 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers or various forms of mobile devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0112] like Figure 4 As shown, electronic device 400 includes at least one processor 401 and memory, such as read-only memory (ROM) 402 and random access memory (RAM) 403, communicatively connected to at least one processor 401. The memory stores computer programs executable by the at least one processor. Processor 401 can perform various appropriate actions and processes based on the computer programs stored in ROM 402 or loaded from storage unit 408 into RAM 403. RAM 403 can also store various programs and data required for the operation of electronic device 400. Processor 401, ROM 402, and RAM 403 are interconnected via bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0113] Multiple components in the electronic device 400 are connected to the I / O interface 405, including an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0114] Processor 401 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 401 executes the various methods and processes described above, such as the dynamic meshing method based on earthwork distribution.

[0115] In some embodiments, the dynamic meshing method based on earthwork distribution can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by processor 401, one or more steps of the dynamic meshing method based on earthwork distribution described above can be performed. Alternatively, in other embodiments, processor 401 can be configured to execute the dynamic meshing method based on earthwork distribution via any other appropriate means (e.g., via firmware).

[0116] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0118] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device that has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0121] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0122] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0123] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A dynamic grid division method based on earthwork distribution, characterized in that: include: determining stratigraphic attribute information and stratigraphic sequence information of the target land area based on land description data of the target land area; the land description data includes stratigraphic profile data and drilling data; the stratigraphic profile data includes stratigraphic dip data; the drilling data includes stratigraphic top and bottom interface coordinates, stratigraphic depth data, and stratigraphic attribute data; Determining stratigraphic attribute information and stratigraphic sequence information of a target land area based on land description data of the target land area, including: regularly dividing the target land area in three-dimensional space according to preset subdivision parameters to obtain a plurality of grid subdivision units; performing interpolation processing on each grid subdivision unit according to the stratigraphic dip data and the stratigraphic depth data to obtain an interpolation result of each grid subdivision unit, and determining the stratigraphic attribute information of the target land area based on the interpolation result of each grid subdivision unit; the interpolation result represents a stratigraphic attribute type; determining the occurrence frequency of each stratum in a vertical position according to the coordinates of the stratigraphic top and bottom interfaces, the stratigraphic depth data, and the stratigraphic attribute data; and statistically sorting the strata of the target land area based on the occurrence frequency to determine the stratigraphic sequence information of the target land area. constructing a three-dimensional geological model of the target land area based on the stratigraphic attribute information and the stratigraphic sequence information; Determining soil complexity for a designated spatial region of the three-dimensional geological model, and adjusting initial meshing parameters of the designated spatial region according to the soil complexity to obtain adjusted meshing parameters; The three-dimensional geological model corresponding to the designated spatial area is grid-divided according to the adjusted grid-division parameters.

2. The method according to claim 1, characterized in that Performing interpolation processing on each grid subdivision unit according to the formation dip data and the formation depth data to obtain an interpolation result of each grid subdivision unit, including: Determine the current mesh subdivision unit; Searching for first-category drilling data with known stratum depth data and second-category drilling data with known stratum dip data within the influence radius of the current grid subdivision unit; A first value is obtained by weighted summing of the stratum depth data of the first type of drilling data, and a second value is obtained by weighted summing of the stratum inclination data of the second type of drilling data; An interpolation result of the current grid subdivision unit is obtained according to the sum of the first value and the second value.

3. The method according to claim 1, characterized in that Constructing a three-dimensional geological model of the target land area based on the stratum attribute information and the stratum sequence information includes: According to the stratigraphic sequence information, each grid unit recording the interpolation result is divided into discrete geological blocks; Determining the boundary ranges of strata and the ranges of discrete geological blocks corresponding to different strata attributes based on the stratum attribute information and the stratum sequence information; A three-dimensional geological model of the target land area is constructed based on the boundary range of each stratum and the range of discrete geological blocks.

4. The method according to claim 1, wherein Determining soil complexity for a specified spatial region of the three-dimensional geological model, including: determining the number of soil types within a specified spatial region of the three-dimensional geological model; Numerical coding is performed on the soil properties in each grid unit in the designated spatial region, and spatial soil variation coefficient in the designated spatial region is determined according to the numerical coding; The soil complexity of the designated spatial area is determined according to the number of soil types and the spatial soil variation coefficient.

5. The method according to claim 4, characterized in that Determining the spatial soil variation coefficient within the specified spatial area according to the numerical code includes: Determining the number of mesh subdivision units within the specified spatial region; Calculating the average value and standard deviation of the numerical codes of the soil properties in each grid unit in the designated spatial area according to the number of grid units; The spatial soil variation coefficient in the designated spatial area is determined based on the ratio of the standard deviation to the average value.

6. The method according to claim 4, characterized in that Determining the soil complexity of the designated spatial area according to the number of soil types and the spatial soil variation coefficient includes: When the number of soil types is greater than a first quantity limit value and the spatial soil variation coefficient is greater than a first variation coefficient limit value, determining that the soil complexity of the designated spatial area is the first level; When the number of soil types is greater than the second quantity limit value and less than the first quantity limit value, and the spatial soil variation coefficient is greater than the second variation coefficient limit value and less than the first variation coefficient limit value, the soil complexity of the designated spatial area is determined to be the second level; When the number of soil types is less than the second quantity limit value and the spatial soil variation coefficient is less than the second variation coefficient limit value, the soil complexity of the designated spatial area is determined to be the third level.

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