A three-dimensional geological model construction method and system

Abstract

The present invention is applicable to the field of geological exploration technology and provides a method and system for constructing a three-dimensional geological model, comprising the following steps: collecting remote sensing images and DEM data, dividing the spatial area corresponding to the remote sensing images and DEM data into a number of blocks using an initial grid; extracting remote sensing feature information from the remote sensing images, determining a landform type map, and determining landform type information for each block; determining terrain factor information for each block based on the DEM data; calculating a geological complexity index for each block based on the landform type information and the terrain factor information, and determining candidate drilling sites based on the initial grid and the geological complexity index; adjusting the positions of the candidate drilling sites based on landform edge lines, and obtaining drilling data based on the drilling sites; and establishing a three-dimensional geological model based on the remote sensing images, DEM data, and drilling data. The present invention can accurately assess geological complexity, make the distribution of drilling sites more reasonable, and provide more reliable data support.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to a three-dimensional geological model construction method and system. Background Art

[0002] In many fields such as geological exploration, resource development, and engineering construction, an accurate understanding of underground geological structures is crucial for project planning, design, and implementation. As an effective tool for intuitively and comprehensively displaying underground geological conditions, three-dimensional geological models can provide an important basis for relevant decision-making. Traditional geological model construction methods mainly rely on limited geological borehole data, which are usually obtained through field drilling. However, field drilling is expensive and time-consuming, and the distribution of drilling points is often restricted by various factors such as terrain and environment, making it difficult to fully cover the study area. As a result, the accuracy of the constructed geological model is limited and it cannot accurately reflect the complex changes in underground geology.

[0003] With the development of remote sensing technology and geographic information systems (GIS), remote sensing images and digital elevation model (DEM) data have provided new data sources for geological model construction. Remote sensing images can obtain surface information over a large area, while DEM data contains surface elevation information. The combination of the two can provide rich surface features and terrain information. However, how to effectively integrate these data and comprehensively consider geological and geomorphological characteristics to construct high-precision three-dimensional geological models remains an urgent problem. In addition, existing methods often fail to comprehensively consider multiple factors such as landform type and topographic factors when determining drilling sites, resulting in irrational drilling site distribution, ineffective acquisition of key geological information, and affected model accuracy. Therefore, it is necessary to provide a three-dimensional geological model construction method and system to address the above problems. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention aims to provide a three-dimensional geological model construction method and system to solve the problems existing in the above-mentioned background technology.

[0005] The present invention is achieved by providing a method for constructing a three-dimensional geological model, the method comprising the following steps:

[0006] Collect remote sensing images and DEM data, and divide the spatial area corresponding to the remote sensing images and DEM data into several blocks through the initial grid;

[0007] Perform atmospheric correction on remote sensing images, extract remote sensing feature information from remote sensing images, input remote sensing feature information into the classifier, obtain landform type map, and determine the landform type information of each block;

[0008] Determine the terrain factor information of each block based on DEM data. The terrain factors include surface slope and surface curvature.

[0009] Calculate the geological complexity index of each block based on the landform type information and terrain factor information, and determine the candidate drilling sites based on the initial grid and the geological complexity index;

[0010] Perform edge detection on the landform type map to obtain landform edge lines, and adjust the positions of candidate drilling sites based on the landform edge lines so that workers can obtain drilling data based on the candidate drilling sites;

[0011] A three-dimensional geological model is established based on remote sensing images, DEM data and drill hole data.

[0012] As a further solution of the present invention, the steps of extracting remote sensing feature information from a remote sensing image, inputting the remote sensing feature information into a classifier, and obtaining a landform type map specifically include:

[0013] Extract the spectral features, texture features and morphological features of remote sensing images to obtain remote sensing feature information;

[0014] The remote sensing feature information is input into the trained random forest classifier to obtain a landform type map.

[0015] As a further solution of the present invention: the step of determining the terrain factor information of each block based on the DEM data specifically includes:

[0016] Unify the DEM data resolution and divide the corresponding spatial area into fine grids according to the resolution;

[0017] Taking each fine grid point as the center, the elevation values ​​of 9 pixels in the 3×3 neighborhood around it are analyzed. The surface slope is obtained by calculating the elevation difference between the center point and the adjacent pixels and combining the horizontal and vertical distances.

[0018] For each fine grid point, the local quadratic surface equation is fitted, the equation coefficients are solved by the least squares method, and the surface curvature is determined based on the equation coefficients;

[0019] The fine grid points in each block are determined, and the surface slope and surface curvature corresponding to the fine grid points are summarized to obtain the terrain factor information.

[0020] As a further solution of the present invention: the step of determining candidate drilling sites based on the initial grid and the geological complexity index specifically includes:

[0021] Determining whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determining the center point of the block as a candidate drilling site;

[0022] Based on the quadtree subdivision algorithm, the blocks above the complexity threshold are sub-grid-divided, the geological complexity index of each sub-block is calculated, and it is determined whether the geological complexity index is lower than or equal to the complexity threshold. If so, the center point of the sub-block is determined as the candidate drilling site; otherwise, the sub-grid division is continued until the complexity threshold is met or the sub-grid size is lower than the size threshold.

[0023] As a further solution of the present invention: the step of adjusting the position of the candidate drilling site based on the landform edge line specifically includes:

[0024] Determine the nearest edge line to each candidate drilling site and the corresponding shortest Euclidean distance;

[0025] Determine whether the shortest Euclidean distance is less than or equal to the search radius, where the search radius is a fixed value;

[0026] If yes, the candidate drilling site is adjusted to the nearest edge line; otherwise, the candidate drilling site is moved toward the nearest edge line, and the moving distance is the search radius.

[0027] As a further solution of the present invention: the step of establishing a three-dimensional geological model based on remote sensing images, DEM data and borehole data specifically includes:

[0028] Convert remote sensing images, DEM data and borehole data into the same projection system and resample the remote sensing images to make their resolution consistent with that of the DEM.

[0029] Generate digital terrain surface based on DEM data as the terrain base of 3D model, and combine it with remote sensing image to perform surface coverage;

[0030] The stratigraphic interfaces are extracted based on the borehole data, continuous stratigraphic interfaces are generated using Kriging interpolation, and the geological structure is expressed using a volume model.

[0031] According to the lithologic logs of the boreholes, indicator kriging was used to generate a 3D lithologic distribution model, which was then visualized and rendered using 3D GIS to obtain a 3D geological model.

[0032] Another object of the present invention is to provide a three-dimensional geological model construction system, the system comprising:

[0033] The initial grid division module is used to collect remote sensing images and DEM data, and divide the spatial area corresponding to the remote sensing images and DEM data into several blocks through the initial grid;

[0034] The landform type determination module is used to perform atmospheric correction on remote sensing images, extract remote sensing feature information from remote sensing images, input the remote sensing feature information into the classifier, obtain a landform type map, and determine the landform type information of each block;

[0035] The terrain factor determination module is used to determine the terrain factor information of each block based on the DEM data. The terrain factors include surface slope and surface curvature;

[0036] The candidate drilling site module is used to calculate the geological complexity index of each block based on the landform type information and terrain factor information, and determine the candidate drilling sites based on the initial grid and the geological complexity index;

[0037] The drilling site adjustment module is used to perform edge detection on the landform type map to obtain landform edge lines, and adjust the positions of candidate drilling sites based on the landform edge lines so that the staff can obtain drilling data according to the candidate drilling sites;

[0038] The geological model construction module is used to build a three-dimensional geological model based on remote sensing images, DEM data and drilling data.

[0039] As a further solution of the present invention: the terrain factor determination module includes:

[0040] Fine grid division unit is used to unify the resolution of DEM data and divide the corresponding spatial area into fine grids according to the resolution;

[0041] The surface slope determination unit is used to analyze the elevation values ​​of 9 pixels in a 3×3 neighborhood around each fine grid point. The surface slope is obtained by calculating the elevation difference between the center point and the adjacent pixels and combining the horizontal and vertical distances.

[0042] The surface curvature determination unit is used to fit the local quadratic surface equation to each fine grid point, solve the equation coefficients by the least squares method, and determine the surface curvature based on the equation coefficients;

[0043] The terrain factor information unit is used to determine the fine grid points in each block and summarize the surface slope and surface curvature corresponding to the fine grid points to obtain the terrain factor information.

[0044] As a further embodiment of the present invention, the candidate drilling site module includes:

[0045] a drilling site direct determination unit, configured to determine whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determine the center point of the block as a candidate drilling site;

[0046] The drilling site cyclic determination unit is used to sub-grid the blocks above the complexity threshold based on the quadtree subdivision algorithm, calculate the geological complexity index of each sub-block, and determine whether the geological complexity index is lower than or equal to the complexity threshold. If so, the center point of the sub-block is determined as the candidate drilling site; otherwise, the sub-grid division is continued until the complexity threshold is met or the sub-grid size is lower than the size threshold.

[0047] As a further solution of the present invention: the drilling point adjustment module includes:

[0048] The nearest edge line unit is used to determine the nearest edge line to each candidate drilling site and the corresponding shortest Euclidean distance;

[0049] The Euclidean distance determination unit is used to determine whether the shortest Euclidean distance is less than or equal to the search radius, where the search radius is a fixed value;

[0050] The drilling site adjustment unit is used to adjust the candidate drilling site to the nearest edge line when the answer is yes; otherwise, move the candidate drilling site toward the nearest edge line, and the moving distance is the search radius.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] By collecting remote sensing images and DEM data and combining them with geological borehole data, this method fully utilizes the advantages of multiple data sources, providing more comprehensive and rich information, and helping to improve the accuracy and reliability of the model. By comprehensively considering landform type information and terrain factor information to calculate the geological complexity index and determine candidate drilling sites based on this index, it can more accurately assess the degree of geological complexity, make the distribution of drilling sites more reasonable, help obtain key geological information, and improve the accuracy of the model. The position of candidate drilling sites is adjusted based on the landform edge line to ensure that the drilling sites are more accurately located in key geological locations, improving the quality of the acquired drilling data and providing more reliable data support. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A flowchart of a method for constructing a three-dimensional geological model.

[0054] Figure 2 A flowchart for obtaining a landform type map in a three-dimensional geological model construction method.

[0055] Figure 3 A flowchart for determining terrain factor information for each block in a three-dimensional geological model construction method.

[0056] Figure 4 A flowchart for determining candidate drilling sites in a three-dimensional geological model construction method.

[0057] Figure 5 A flowchart for adjusting the positions of candidate drill sites in a three-dimensional geological model construction method.

[0058] Figure 6 The present invention is a flowchart for establishing a three-dimensional geological model in a three-dimensional geological model construction method.

[0059] Figure 7 A schematic diagram of the structure of a three-dimensional geological model construction system. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0061] The specific implementation of the present invention is described in detail below with reference to specific embodiments.

[0062] like Figure 1 As shown, an embodiment of the present invention provides a method for constructing a three-dimensional geological model, the method comprising the following steps:

[0063] S100, collecting remote sensing images and DEM data, and dividing the spatial area corresponding to the remote sensing images and DEM data into a plurality of blocks using an initial grid;

[0064] S200, performing atmospheric correction on the remote sensing image, extracting remote sensing feature information of the remote sensing image, inputting the remote sensing feature information into a classifier, obtaining a landform type map, and determining landform type information of each block;

[0065] S300, determining terrain factor information of each block based on DEM data, where the terrain factors include surface slope and surface curvature;

[0066] S400, calculating the geological complexity index of each block according to the landform type information and the terrain factor information, and determining the candidate drilling sites based on the initial grid and the geological complexity index;

[0067] S500: edge detection is performed on the landform type map to obtain landform edge lines, and positions of candidate drilling sites are adjusted based on the landform edge lines so that workers can obtain drilling data based on the candidate drilling sites.

[0068] S600, builds a 3D geological model based on remote sensing images, DEM data and drilling data.

[0069] It should be noted that traditional methods mainly rely on geological drilling data, and the utilization of remote sensing images and DEM data is not deep and comprehensive enough. They fail to fully explore the geological and geomorphological information contained in these data, resulting in a lack of sufficient data support for model construction and limited accuracy. In addition, when determining the drilling site, existing methods often do not comprehensively consider multiple factors such as landform type and topographic factors, and are unable to accurately assess geological complexity, resulting in an unreasonable distribution of drilling sites and an inability to effectively obtain key geological information. In addition, the candidate drilling sites determined based on the initial grid may not fully consider special geological features such as landform edges, causing the drilling site to deviate from the actual required position, thereby reducing the quality of the acquired drilling data. The embodiments of the present invention are intended to solve the above problems.

[0070] In this embodiment of the present invention, high-resolution remote sensing images are acquired and digital elevation model (DEM) data is generated using LiDAR. The spatial area corresponding to the remote sensing images and DEM data is divided into several blocks using an initial grid (e.g., 1000m x 1000m). By combining remote sensing images, DEM data, and subsequent geological drill hole data, the advantages of multiple data sources are fully utilized, providing more comprehensive and rich information for the construction of a three-dimensional geological model, thereby improving the model's accuracy and reliability. The remote sensing images are then atmospherically corrected. The DN values ​​of the remote sensing images are converted to surface reflectance, and a linear regression model is established using the measured ground reflectance and the image DN values ​​for correction. Remote sensing feature information is then extracted from the remote sensing images. A landform type map is generated using this remote sensing feature information to determine the landform type information for each block. This effectively eliminates the influence of atmospheric interference, improves the accuracy of landform type identification, and enables the constructed model to better reflect the actual geological and geomorphological conditions. Next, the terrain factor information for each block needs to be determined based on the DEM data, and the geological complexity index for each block is calculated based on the landform type and terrain factor information. This requires constructing a formula that involves the geological complexity index, landform type, surface slope, and surface curvature. Next, candidate drill sites are determined based on the initial grid and the geological complexity index. This allows for a more reasonable distribution of drill sites, helps obtain key geological information, and improves the accuracy of the model. Additionally, edge detection is performed on the landform type map to obtain landform edge lines. The Canny edge detection method can be used here. The previously determined candidate drill sites are then repositioned based on the landform edge lines to ensure that the drill sites are more accurately located in key geological locations, reducing unnecessary drilling, improving the quality of the acquired borehole data, and providing more reliable data support for the construction of the 3D geological model. Finally, a 3D geological model can be constructed based on the remote sensing imagery, DEM data, and borehole data. The constructed 3D geological model is more accurate and reliable, providing stronger support for decision-making in fields such as geological exploration, resource development, and engineering construction.

[0071] like Figure 2 As shown, as a preferred embodiment of the present invention, the steps of extracting remote sensing feature information of a remote sensing image, inputting the remote sensing feature information into a classifier, and obtaining a landform type map specifically include:

[0072] S201, extracting spectral features, texture features, and morphological features of the remote sensing image to obtain remote sensing feature information;

[0073] S202: Input the remote sensing feature information into the trained random forest classifier to obtain a landform type map.

[0074] In an embodiment of the present invention, when extracting spectral features, the reflectance of the multispectral / hyperspectral band (such as the B1-B7 bands of Landsat) is first extracted, and then the vegetation index, water index, and bare soil index are calculated. When extracting texture features, the gray-level co-occurrence matrix (GLCM) is used to extract contrast, correlation, and entropy information texture parameters, and a Gabor filter or wavelet transform is applied to capture local texture patterns. When extracting morphological features, landform morphology (such as ridges and valleys) is extracted through opening and closing operations. In an embodiment of the present invention, a random forest classifier is selected, and the RF classifier is pre-trained using historical annotated data. In this way, by inputting remote sensing feature information into the random forest classifier, a landform type map will be obtained.

[0075] like Figure 3 As shown in FIG. 1 , as a preferred embodiment of the present invention, the step of determining the terrain factor information of each block based on the DEM data specifically includes:

[0076] S301, unify the DEM data resolution and divide the corresponding spatial area into fine grids according to the resolution;

[0077] S302: Analyze the elevation values ​​of 9 pixels in a 3×3 neighborhood around each fine grid point. Calculate the elevation difference between the center point and adjacent pixels, and combine the horizontal and vertical distances to obtain the surface slope.

[0078] S303, fitting a local quadratic surface equation for each fine grid point, solving the equation coefficients using the least squares method, and determining the surface curvature based on the equation coefficients;

[0079] S304: Determine the fine grid points in each block, and summarize the surface slope and surface curvature corresponding to the fine grid points to obtain terrain factor information.

[0080] In the embodiment of the present invention, in order to determine the terrain factor information, it is first necessary to unify the DEM data resolution, divide the corresponding spatial area into fine grids (such as 1 meter × 1 meter grids) according to the resolution, and then analyze the 9 pixel elevation values ​​of the 3 × 3 neighborhood around each fine grid point as the center. By calculating the elevation difference between the center point and the adjacent pixels, combined with the horizontal (east-west) and vertical (north-south) distances, the surface slope is obtained. For example, the pixel elevation to the east of the center point is 2 meters higher than the pixel elevation to the west, and the horizontal distance is 1 meter. Then, the east-west slope is arctan (2 / 1). When calculating the surface curvature, it is necessary to fit the local quadratic surface equation to each fine grid point: z = ax 2 +by 2 +cxy+dx+ey+f, solve the equation coefficients using the least squares method, and determine the surface curvature = 2(a+b) based on the equation coefficients. Finally, determine the fine grid points in each block, and summarize the surface slope and surface curvature corresponding to the fine grid points to obtain the terrain factor information of the block.

[0081] In the local quadratic surface equation, z represents the elevation of the ground at that fine grid point. x and y represent the horizontal coordinate and vertical coordinate of that fine grid point on the horizontal plane, respectively. a, b, c, d, e, and f are the coefficients of the quadratic surface equation, which need to be solved by the least squares method. a and b are respectively related to x 2 and y 2 The terms a and b are related and reflect the degree of curvature of the surface in the x and y directions. Specifically, the values ​​of a and b determine the degree of curvature of the quadratic surface in the corresponding directions, with larger absolute values ​​indicating stronger curvature. 2(a+b) reflects the overall curvature of the surface at that fine grid point. A larger value of 2(a+b) indicates a more pronounced curvature at that point; conversely, a smaller value indicates a flatter surface.

[0082] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of determining candidate drilling sites based on the initial grid and the geological complexity index specifically includes:

[0083] S401, determining whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determining the center point of the block as a candidate drilling site;

[0084] S402, based on the quadtree subdivision algorithm, sub-grid the blocks that are higher than the complexity threshold, calculate the geological complexity index of each sub-block, and determine whether the geological complexity index is lower than or equal to the complexity threshold. If so, determine the center point of the sub-block as the candidate drilling site; otherwise, continue sub-gridding until the complexity threshold is met or the sub-grid size is lower than the size threshold.

[0085] In the embodiment of the present invention, before determining the candidate drilling sites, it is necessary to calculate the geological complexity index of each block. , E represents the complexity value corresponding to the landform type where the fine grid point is located. Each landform type has a predetermined complexity value. T represents the surface slope of the fine grid point. Represents the absolute value of the surface curvature of the fine grid point, K1, K2 and K3 are constant coefficients, and there are n fine grid points in the block. Then determine whether the geological complexity index of each block in the initial grid is lower than or equal to the complexity threshold. The complexity threshold is a fixed value set in advance. If it is, the center point of the block is determined to be a candidate drilling site. Otherwise, the blocks above the complexity threshold are sub-grid-divided according to the quadtree subdivision algorithm. A block is divided into four sub-blocks, and the geological complexity index of each sub-block is calculated. It is again determined whether the geological complexity index is lower than or equal to the complexity threshold. If it is, the center point of the sub-block is determined to be a candidate drilling site; otherwise, continue to sub-grid until the complexity threshold is met, or the sub-grid size is lower than the size threshold, and the sub-grid division will also be terminated. For example, the size threshold is 50 meters × 50 meters.

[0086] like Figure 5 As shown, as a preferred embodiment of the present invention, the step of adjusting the position of the candidate drilling site based on the landform edge line specifically includes:

[0087] S501, determining the nearest edge line to each candidate drilling site and the corresponding shortest Euclidean distance;

[0088] S502, determining whether the shortest Euclidean distance is less than or equal to a search radius, where the search radius is a fixed value;

[0089] S503, if yes, adjust the candidate drilling site to the nearest edge line; otherwise, move the candidate drilling site toward the nearest edge line, with the moving distance being the search radius.

[0090] In an embodiment of the present invention, it is also necessary to fine-tune the determined candidate drilling sites. Specifically, the nearest edge line and the corresponding shortest Euclidean distance from each candidate drilling site will be determined, and a search radius, such as 30m, needs to be set in advance. Then it is determined whether the shortest Euclidean distance is less than or equal to the search radius. If it is, the candidate drilling site is adjusted to the nearest edge line. Here, the foot point of the perpendicular from the drilling site to the edge line can be calculated, and the position can be adjusted to the foot point of the perpendicular. If the shortest Euclidean distance is greater than the search radius, the candidate drilling site is moved in the direction of the nearest edge line. Here, it is necessary to determine the direction vector from the drilling site to the nearest point of its edge line, and move along this direction vector. In this way, the ability of the candidate drilling site to reveal changes in geological interfaces is significantly improved.

[0091] like Figure 6 As shown in FIG. 1 , as a preferred embodiment of the present invention, the step of establishing a three-dimensional geological model based on remote sensing images, DEM data, and borehole data specifically includes:

[0092] S601, converting the remote sensing image, DEM data and borehole data into the same projection system, and resampling the remote sensing image to make its resolution consistent with the DEM;

[0093] S602, generating a digital terrain surface based on the DEM data as the terrain base of the three-dimensional model, and combining it with remote sensing images for surface coverage;

[0094] S603, extracting the stratigraphic interfaces based on the borehole data, generating continuous stratigraphic interfaces using Kriging interpolation, and expressing the geological structure using a volume model;

[0095] S604: Based on the lithologic logs of the boreholes, a three-dimensional lithologic distribution model is generated using indicator kriging, and a three-dimensional GIS is used for visualization rendering to obtain a three-dimensional geological model.

[0096] In this embodiment of the present invention, remote sensing images (UTM projection), DEM data (WGS84 geographic coordinate system), and borehole data (local coordinate system) must be uniformly converted to the same projection system (e.g., UTM Zone 50N). The remote sensing images must also be resampled to a resolution consistent with the DEM (e.g., 1 meter x 1 meter). The DEM data is then used to generate a digital terrain surface (DTM), which serves as the topographic base for the 3D model. Combined with the remote sensing imagery, surface cover classification, such as vegetation, water bodies, and bare rock, is performed to enhance surface geological information. Next, the borehole data is used to extract stratigraphic interfaces (e.g., bedrock roof, aquifer boundaries, etc.), and kriging interpolation is used to generate continuous stratigraphic interfaces. Landform type maps and topographic factors can also be combined to optimize stratigraphic interfaces to ensure they conform to geological laws. A volume model (e.g., voxel or tetrahedral mesh) is then used to represent the geological structure. Finally, indicator kriging is used to generate a 3D lithologic distribution model based on the borehole lithologic logs. This model can be visualized and rendered using 3D GIS or specialized geological modeling software (e.g., GOCAD, Leapfrog, or Petrel).

[0097] like Figure 7 As shown, an embodiment of the present invention further provides a three-dimensional geological model construction system, the system comprising:

[0098] The initial grid division module 100 is used to collect remote sensing images and DEM data, and divide the spatial area corresponding to the remote sensing images and DEM data into a number of blocks through the initial grid;

[0099] The landform type determination module 200 is used to perform atmospheric correction on the remote sensing image, extract remote sensing feature information of the remote sensing image, input the remote sensing feature information into the classifier, obtain a landform type map, and determine the landform type information of each block;

[0100] A terrain factor determination module 300 is used to determine terrain factor information of each block based on DEM data, where the terrain factors include surface slope and surface curvature;

[0101] The candidate drilling site module 400 is used to calculate the geological complexity index of each block according to the landform type information and the terrain factor information, and determine the candidate drilling site based on the initial grid and the geological complexity index;

[0102] The drilling site adjustment module 500 is used to perform edge detection on the landform type map to obtain landform edge lines, and adjust the positions of candidate drilling sites based on the landform edge lines so that workers can obtain drilling data based on the candidate drilling sites;

[0103] The geological model building module 600 is used to build a three-dimensional geological model based on remote sensing images, DEM data and drilling data.

[0104] In the embodiment of the present invention, the terrain factor determination module 300 includes:

[0105] Fine grid division unit is used to unify the resolution of DEM data and divide the corresponding spatial area into fine grids according to the resolution;

[0106] The surface slope determination unit is used to analyze the elevation values ​​of 9 pixels in a 3×3 neighborhood around each fine grid point. The surface slope is obtained by calculating the elevation difference between the center point and the adjacent pixels and combining the horizontal and vertical distances.

[0107] The surface curvature determination unit is used to fit the local quadratic surface equation to each fine grid point, solve the equation coefficients by the least squares method, and determine the surface curvature based on the equation coefficients;

[0108] The terrain factor information unit is used to determine the fine grid points in each block and summarize the surface slope and surface curvature corresponding to the fine grid points to obtain the terrain factor information.

[0109] In an embodiment of the present invention, the candidate drilling site module 400 includes:

[0110] a drilling site direct determination unit, configured to determine whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determine the center point of the block as a candidate drilling site;

[0111] The drilling site cyclic determination unit is used to sub-grid the blocks above the complexity threshold based on the quadtree subdivision algorithm, calculate the geological complexity index of each sub-block, and determine whether the geological complexity index is lower than or equal to the complexity threshold. If so, the center point of the sub-block is determined as the candidate drilling site; otherwise, the sub-grid division is continued until the complexity threshold is met or the sub-grid size is lower than the size threshold.

[0112] In the embodiment of the present invention, the drilling point adjustment module 500 includes:

[0113] The nearest edge line unit is used to determine the nearest edge line to each candidate drilling site and the corresponding shortest Euclidean distance;

[0114] The Euclidean distance determination unit is used to determine whether the shortest Euclidean distance is less than or equal to the search radius, where the search radius is a fixed value;

[0115] The drilling site adjustment unit is used to adjust the candidate drilling site to the nearest edge line when the answer is yes; otherwise, move the candidate drilling site toward the nearest edge line, and the moving distance is the search radius.

[0116] The above is only a detailed description of the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0117] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered merely as exemplary, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A three-dimensional geological model construction method, characterized in that: The method comprises the following steps: Collect remote sensing images and DEM data, and divide the spatial area corresponding to the remote sensing images and DEM data into several blocks through the initial grid; Perform atmospheric correction on remote sensing images, extract remote sensing feature information from remote sensing images, input remote sensing feature information into the classifier, obtain landform type map, and determine the landform type information of each block; Determine the terrain factor information of each block based on DEM data. The terrain factors include surface slope and surface curvature. Calculate the geological complexity index of each block based on the landform type information and terrain factor information, and determine the candidate drilling sites based on the initial grid and the geological complexity index; Perform edge detection on the landform type map to obtain landform edge lines, and adjust the positions of candidate drilling sites based on the landform edge lines so that workers can obtain drilling data based on the candidate drilling sites; Establish a three-dimensional geological model based on remote sensing images, DEM data and drilling data; The step of determining the terrain factor information of each block based on the DEM data specifically includes: unifying the resolution of the DEM data and dividing the corresponding spatial area into fine grids according to the resolution; taking each fine grid point as the center, analyzing the elevation values ​​of 9 pixels in a 3×3 neighborhood around it, and obtaining the surface slope by calculating the elevation difference between the center point and the adjacent pixels and combining the horizontal and vertical distances; fitting the local quadratic surface equation for each fine grid point, solving the equation coefficient by the least squares method, and determining the surface curvature based on the equation coefficient; determining the fine grid points in each block, and summarizing the surface slope and surface curvature of the corresponding fine grid points to obtain the terrain factor information; Among them, the step of adjusting the position of the candidate drilling site based on the landform edge line specifically includes: determining the nearest edge line and the corresponding shortest Euclidean distance from each candidate drilling site; determining whether the shortest Euclidean distance is less than or equal to the search radius, and the search radius is a fixed value; if so, adjusting the candidate drilling site to the nearest edge line; otherwise, moving the candidate drilling site in the direction of the nearest edge line, and the moving distance is the search radius.

2. The three-dimensional geological model construction method according to claim 1, characterized in that: The steps of extracting remote sensing feature information from a remote sensing image, inputting the remote sensing feature information into a classifier, and obtaining a landform type map specifically include: Extract the spectral features, texture features and morphological features of remote sensing images to obtain remote sensing feature information; The remote sensing feature information is input into the trained random forest classifier to obtain a landform type map.

3. The three-dimensional geological model construction method according to claim 1, characterized in that: The step of determining candidate drilling sites based on the initial grid and the geological complexity index specifically includes: Determining whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determining the center point of the block as a candidate drilling site; Based on the quadtree subdivision algorithm, the blocks above the complexity threshold are sub-grid-divided, the geological complexity index of each sub-block is calculated, and it is determined whether the geological complexity index is lower than or equal to the complexity threshold. If so, the center point of the sub-block is determined as the candidate drilling site; otherwise, the sub-grid division is continued until the complexity threshold is met or the sub-grid size is lower than the size threshold.

4. The three-dimensional geological model construction method according to claim 1, characterized in that: The step of establishing a three-dimensional geological model based on remote sensing images, DEM data and drilling data specifically includes: Convert remote sensing images, DEM data and borehole data into the same projection system and resample the remote sensing images to make their resolution consistent with that of the DEM; Generate digital terrain surface based on DEM data as the terrain base of 3D model, and combine it with remote sensing image to perform surface coverage; The stratigraphic interfaces are extracted based on the borehole data, continuous stratigraphic interfaces are generated using Kriging interpolation, and the geological structure is expressed using a volume model. According to the lithologic logs of the boreholes, indicator kriging was used to generate a 3D lithologic distribution model, which was then visualized and rendered using 3D GIS to obtain a 3D geological model.

5. A three-dimensional geological model construction system, characterized in that: The system comprises: The initial grid division module is used to collect remote sensing images and DEM data, and divide the spatial area corresponding to the remote sensing images and DEM data into several blocks through the initial grid; The landform type determination module is used to perform atmospheric correction on remote sensing images, extract remote sensing feature information from remote sensing images, input the remote sensing feature information into the classifier, obtain a landform type map, and determine the landform type information of each block; The terrain factor determination module is used to determine the terrain factor information of each block based on the DEM data. The terrain factors include surface slope and surface curvature; The candidate drilling site module is used to calculate the geological complexity index of each block based on the landform type information and terrain factor information, and determine the candidate drilling sites based on the initial grid and the geological complexity index; The drilling site adjustment module is used to perform edge detection on the landform type map to obtain landform edge lines, and adjust the positions of candidate drilling sites based on the landform edge lines so that the staff can obtain drilling data according to the candidate drilling sites; The geological model building module is used to build a three-dimensional geological model based on remote sensing images, DEM data and drilling data; The terrain factor determination module includes: a fine grid division unit for unifying the DEM data resolution and dividing the corresponding spatial area into fine grids according to the resolution; a surface slope determination unit for analyzing the elevation values ​​of 9 pixels in a 3×3 neighborhood around each fine grid point, calculating the elevation difference between the center point and the adjacent pixels, and combining the horizontal and vertical distances to obtain the surface slope; a surface curvature determination unit for fitting the local quadratic surface equation for each fine grid point, solving the equation coefficients by the least squares method, and determining the surface curvature based on the equation coefficients; a terrain factor information unit for determining the fine grid points in each block, and summarizing the surface slope and surface curvature of the corresponding fine grid points to obtain terrain factor information; Among them, the drilling site adjustment module includes: a nearest edge line unit, used to determine the nearest edge line from each candidate drilling site and the corresponding shortest Euclidean distance; a Euclidean distance judgment unit, used to determine whether the shortest Euclidean distance is less than or equal to the search radius, and the search radius is a fixed value; a drilling site adjustment unit, used to adjust the candidate drilling site to the nearest edge line when it is; otherwise, move the candidate drilling site in the direction of the nearest edge line, and the moving distance is the search radius.

6. The three-dimensional geological model construction system according to claim 5, characterized in that: The candidate drilling site module includes: a drilling site direct determination unit, configured to determine whether the geological complexity index of each block in the initial grid is lower than or equal to a complexity threshold, and if so, determine the center point of the block as a candidate drilling site; The drilling site cyclic determination unit is used to sub-grid the blocks above the complexity threshold based on the quadtree subdivision algorithm, calculate the geological complexity index of each sub-block, and determine whether the geological complexity index is lower than or equal to the complexity threshold. If so, the center point of the sub-block is determined as the candidate drilling site; otherwise, the sub-grid division is continued until the complexity threshold is met or the sub-grid size is lower than the size threshold.

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