Geological model construction method, system, storage medium and electronic device

Abstract

The present invention discloses a geological model construction method, system, storage medium and electronic device, which relate to the field of geological exploration technology. The method uses a laser scanner to obtain a laser point cloud model of a geological area to be modeled, and performs aerial triangulation on image data of different shooting angles to obtain a dense point cloud model of the geological area to be modeled, and fuses the laser point cloud model and the dense point cloud model to obtain a more accurate point cloud fusion model, and then reconstructs a three-dimensional geological model. The beneficial effects of the present invention are: not only can the construction of a three-dimensional digital model of the geological area to be modeled be realized, but also the advantages of three-dimensional laser modeling technology and oblique photography technology can be combined to obtain the surface coordinates of the measured object in all directions, thereby obtaining a more refined three-dimensional geological model.

Description

Technical Field

[0001] The present invention belongs to the field of geological exploration technology, and in particular relates to a geological model construction method, system, storage medium and electronic equipment. Background Art

[0002] Geological outcrops are an important source of information for geological prospectors to understand the underground geological conditions. With the in-depth development of geological research, the description of the target geological area is becoming more and more refined and complex, and the scale of geological body representation is getting smaller. Therefore, the technical methods for geological unit characterization are in urgent need of improvement. In particular, the study of underground cave systems is more complicated and requires more refined geological characterization technology. As the difficulty of depicting geological phenomena in outcrops gradually increases, traditional geological survey methods such as rulers, compasses, and camera photography to obtain geological parameters can no longer meet the current needs of exploration and development. Moreover, traditional geological measurement methods, such as using benchmarks and geological hammers as scales, taking camera photos, and measuring the size of typical geological phenomena are prone to errors and the measurement process is cumbersome. Summary of the invention

[0003] The present invention is based on the technical problems that traditional geological survey methods, such as using benchmarks and geological hammers as scales and taking photos with cameras to measure the dimensions of typical geological phenomena are prone to errors and the measurement process is cumbersome. A geological model construction method, system, storage medium and electronic device are proposed to provide a method that can realize the construction of a three-dimensional digital model of the geological area to be modeled.

[0004] In a first aspect, an embodiment of the present invention provides a method for constructing a geological model, comprising:

[0005] Scan the geological area to be modeled using a laser scanner to obtain a laser point cloud model of the geological area to be modeled;

[0006] Acquire image data of the geological area to be modeled at different shooting angles;

[0007] Performing aerial triangulation on the image data to obtain a dense point cloud model of the geological area to be modeled;

[0008] Performing point cloud data fusion on the laser point cloud model and the dense point cloud model to obtain a point cloud fusion model;

[0009] Based on the point cloud fusion model, a three-dimensional geological model is constructed, so as to analyze the geological area to be modeled using the three-dimensional geological model.

[0010] Optionally, constructing a three-dimensional geological model based on the point cloud fusion model includes:

[0011] Connecting the point cloud data in the point cloud fusion model to generate an irregular triangulated network;

[0012] Assigning a triangular facet to each triangular face in the irregular triangulated network to obtain a white body model;

[0013] Texture is extracted from the original image data, and the texture is attached to the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0014] Optionally, after assigning a triangular facet to each triangular face in the irregular triangulated network to obtain a white body model, the method further includes:

[0015] Determining whether there is a hole area on the white body model;

[0016] When the hole area exists, determining the diameter of the hole area;

[0017] When the diameter of the hole area is not greater than a preset size, the hole area is filled with straight lines;

[0018] When the diameter of the hole area is greater than a preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

[0019] Optionally, performing aerial triangulation on the image data to obtain a dense point cloud model of the geological area to be modeled includes:

[0020] A first connection point is determined from the image data, and aerial triangulation is performed on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled.

[0021] Optionally, after determining the first connection point from the image data and performing aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled, the method further includes:

[0022] Determining whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation;

[0023] When the unmatched image exists, determining whether the unmatched image is in a point cloud density uniform area in the dense point cloud model;

[0024] When the unmatched image is in a point cloud density uniform area in the dense point cloud model, deleting the unmatched image;

[0025] When the unmatched image is in an area with uneven point cloud density in the dense point cloud model, a second connection point is added in an overlapping area between the unmatched image and an image adjacent to the unmatched image, and aerial triangulation is re-performed on the unmatched image based on the second connection point to obtain a new dense point cloud model.

[0026] Optionally, the second connection points are arranged at four corners and a center point in the overlapping area.

[0027] Optionally, the method further comprises:

[0028] Pre-setting a plurality of scale identification points on the geological area to be modeled, and measuring the distances between the scale identification points;

[0029] The scale identification points are used as scale constraint points on the three-dimensional geological model, and the distances between the scale identification points are used as the distances between the scale constraint points, so as to obtain a three-dimensional geological model with size information.

[0030] In a second aspect, an embodiment of the present invention further provides a geological model construction system, including:

[0031] A laser point cloud model acquisition module is configured to use a laser scanner to scan the geological area to be modeled to acquire a laser point cloud model of the geological area to be modeled;

[0032] An image acquisition module is configured to acquire image data of different shooting angles of the geological area to be modeled;

[0033] A dense point cloud model building module is configured to perform aerial triangulation on the image data to obtain a dense point cloud model of the geological area to be modeled;

[0034] A fusion module is configured to fuse the laser point cloud model with the dense point cloud model to obtain a point cloud fusion model;

[0035] The geological model building module is configured to build a three-dimensional geological model based on the point cloud fusion model, so as to use the three-dimensional geological model to analyze the geological area to be modeled.

[0036] Optionally, the geological model building module includes:

[0037] An irregular triangulated network construction unit is configured to connect the point cloud data in the point cloud fusion model to generate an irregular triangulated network;

[0038] A white-body model building unit, configured to assign a triangular facet to each triangular face in the irregular triangulated network to obtain a white-body model;

[0039] The texture pasting unit is configured to extract texture from the original image data and paste the texture on the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0040] Optionally, the system further comprises:

[0041] A hole detection module, configured to determine whether there is a hole area on the white body model;

[0042] A hole size determination module, configured to determine the diameter of the hole area;

[0043] The hole filling module is configured to fill the hole area with straight lines when the diameter of the hole area is not greater than a preset size; when the diameter of the hole area is greater than the preset size, construct similar curvature lines according to the curvature of the boundary lines of the hole area to fill the hole area.

[0044] Optionally, the dense point cloud model building module is specifically configured to determine a first connection point from the image data, and perform aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled.

[0045] Optionally, the system further comprises:

[0046] A first detection module is configured to determine whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation;

[0047] a second detection module, configured to determine whether the unmatched image is in a point cloud density uniform area in the dense point cloud model when the first detection module detects the unmatched image;

[0048] The image processing module is configured to delete the unmatched image when the unmatched image is in a point cloud density uniform area in the dense point cloud model; add a second connection point in the overlapping area of ​​the unmatched image and an image adjacent to the unmatched image when the unmatched image is in a point cloud density non-uniform area in the dense point cloud model, and send the unmatched image with the second connection point added to the dense point cloud model construction module to re-perform aerial triangulation to obtain a new dense point cloud model.

[0049] Optionally, the second connection points are arranged at four corners and a center point in the overlapping area.

[0050] Optionally, the system further comprises:

[0051] A scale identification point setting module is configured to pre-set a plurality of scale identification points on the geological area to be modeled and measure the distances between the scale identification points;

[0052] The three-dimensional geological model scale calculation module is configured to use the scale identification points as scale constraint points on the three-dimensional geological model and use the distance between the scale identification points as the distance between the scale constraint points to obtain a three-dimensional geological model with size information.

[0053] In a third aspect, an embodiment of the present invention further provides a storage medium having program code stored thereon, and when the program code is executed by a processor, a geological model construction method as described in any one of the above embodiments is implemented.

[0054] In a fourth aspect, an embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a program code that can be executed on the processor, and when the program code is executed by the processor, a geological model construction method as described in any one of the above embodiments is implemented.

[0055] In a geological model construction method provided in an embodiment of the present invention, a laser point cloud model of a geological area to be modeled is obtained by using a laser scanner, and a dense point cloud model of the geological area to be modeled is obtained by performing aerial triangulation on image data of different shooting angles, and the laser point cloud model and the dense point cloud model are fused to obtain a more accurate point cloud fusion model, and then a three-dimensional geological model is reconstructed. It can be seen that the geological model construction method provided in an embodiment of the present invention can not only realize the construction of a three-dimensional digital model of the geological area to be modeled through point cloud data fusion, but also can combine the advantages of three-dimensional laser modeling technology and oblique photography technology, and can obtain the surface coordinates of the measured object in all directions, thereby obtaining a more refined three-dimensional geological model. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The scope of the present invention can be better understood by reading the detailed description of the exemplary embodiments below in conjunction with the accompanying drawings. The accompanying drawings included are:

[0057] Figure 1 A schematic diagram of a process of constructing a geological model proposed in the first embodiment of the present invention is shown;

[0058] Figure 2 A schematic diagram showing a flow chart of a geological model construction method proposed in the second embodiment of the present invention;

[0059] Figure 3 A schematic diagram of the structure of a geological model building system proposed in the third embodiment of the present invention is shown;

[0060] Figure 4 A schematic diagram of the structure of an electronic device proposed in Embodiment 5 of the present invention is shown. DETAILED DESCRIPTION

[0061] In order to make the objectives, technical solutions and advantages of the present invention clearer, the implementation method of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0062] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0063] Embodiment 1

[0064] According to an embodiment of the present invention, a method for constructing a geological model is provided. Figure 1 A schematic diagram of a process of constructing a geological model proposed in the first embodiment of the present invention is shown. Figure 1 As shown, the geological model construction method may include: steps 110 to 150.

[0065] In step 110, a laser scanner is used to scan the geological area to be modeled to obtain a laser point cloud model of the geological area to be modeled.

[0066] Here, 3D laser scanning technology uses the principle of laser ranging. By recording the 3D coordinates, reflectivity, texture and other information of a large number of dense points on the surface of the measured object, it can quickly reconstruct the 3D geological model of the measured target and various map data such as lines, surfaces and volumes. Since the 3D laser scanning system can densely acquire a large number of data points of the target object, it can provide an accurate basis for subsequent internal processing, data analysis and other work.

[0067] Therefore, by using a laser scanner to scan the geological area to be modeled, a laser point cloud model of the geological area to be modeled can be obtained, thereby performing three-dimensional reconstruction of the geological area to be modeled.

[0068] In step 120, image data of the geological area to be modeled at different shooting angles are obtained.

[0069] Here, by acquiring image data from different shooting angles, the ground feature information can be acquired in all directions. Among them, an unmanned aerial vehicle or a single-lens reflex camera can be used to acquire image data from different shooting angles of the geological area to be modeled.

[0070] Taking drones as an example, drones use fixed-focus cameras throughout the entire process of collecting images of the geological area to be modeled. When shooting, the distance between the fixed-focus camera and the geological area to be modeled is kept as consistent as possible, and the shooting angles of the drone and the ground are 30°, 90°, and 150°, respectively. That is, the drone shoots the geological area to be surveyed and mapped at shooting angles of 30°, 90°, and 150°, respectively, to obtain image data at different angles. It is worth noting that the image data collected at shooting angles of 30°, 90°, and 150° can better obtain surface information and reduce hole areas.

[0071] In addition, when the drone is shooting, it collects image data of the geological area to be modeled according to a specific order. Moreover, the overlap rate between each adjacent image taken by it is kept greater than 75%. For example, the drone flies in a preset heading band and collects images. After shooting the current shooting point, the drone flies to the next preset shooting point to continue shooting the geological area to be modeled under the shooting point, so that the image overlap of the images collected by the camera in this heading is kept within a preset range.

[0072] In addition, the route of the drone can be a plurality of parallel straight lines in the same plane, and the lateral overlap of the images captured under the plurality of routes is also maintained within a preset range. The preset shooting points are points on the route, and the distances between adjacent preset shooting points and the distances between adjacent routes can be set according to actual conditions, so that the overlap of the images collected by the drone in the heading direction is within a preset range, and the overlap of the images in the lateral direction is within a preset range, thereby ensuring that the drone captures the entire image of the monitored area without omission.

[0073] Taking a SLR camera as an example, when a laser scanner collects point cloud data of the geological area to be modeled, the high-precision camera built into the laser scanner can be used to obtain image data from different shooting angles.

[0074] In step 130, aerial triangulation is performed on the image data to obtain a dense point cloud model of the geological area to be modeled.

[0075] Here, aerial triangulation is based on the coordinates of the image points measured on the film, using a rigorous mathematical model, according to the principle of least squares, using a small number of ground control points as adjustment conditions, and solving the ground coordinates of the control points required for mapping on an electronic computer. Among them, the image data is input into the corresponding software platform for aerial triangulation, which can automatically match the same-name points of all image data, and extract more feature points from the image data, thereby obtaining a dense point cloud model of the geological area to be modeled.

[0076] In step 140, point cloud data fusion is performed on the laser point cloud model and the dense point cloud model to obtain a point cloud fusion model.

[0077] Here, since the laser point cloud model of the geological area to be modeled obtained by using a laser scanner and the dense point cloud model of the geological area to be modeled obtained by aerial triangulation both contain a large amount of point cloud data, the point cloud data in the laser point cloud model can be fused with the point cloud data in the dense point cloud model to obtain a point cloud fusion model.

[0078] The fusion of the laser point cloud model and the dense point cloud model is to register the point cloud data in the two point cloud models. The iterative nearest neighbor registration method can be used to register the laser point cloud model with the point cloud data in the dense point cloud model to obtain a point cloud fusion model.

[0079] In step 150, a three-dimensional geological model is constructed based on the point cloud fusion model, so as to analyze the geological area to be modeled using the three-dimensional geological model.

[0080] Here, after obtaining the point cloud fusion model after the point cloud data is fused, the three-dimensional geological model of the geological area to be modeled can be obtained according to the point cloud fusion model, thereby obtaining a three-dimensional geological model reflecting the real scene of the geological area to be modeled.

[0081] In this embodiment, a laser point cloud model of the geological area to be modeled is obtained by using a laser scanner, and an aerial triangulation is performed on the image data of different shooting angles to obtain a dense point cloud model of the geological area to be modeled, and the laser point cloud model and the dense point cloud model are fused to obtain a more accurate point cloud fusion model, and then a three-dimensional geological model is reconstructed. Therefore, through the fusion of point cloud data, not only can the construction of a three-dimensional digital model of the geological area to be modeled be realized, but also the advantages of three-dimensional laser modeling technology and oblique photography technology can be combined to obtain the surface coordinates of the measured object in all directions, thereby obtaining a more refined three-dimensional geological model.

[0082] In an optional implementation, in step 150 , constructing a three-dimensional geological model based on the point cloud fusion model may include steps 151 to 153 .

[0083] In step 151, the point cloud data in the point cloud fusion model are connected to generate an irregular triangulated network.

[0084] Here, the point cloud data in the point cloud fusion model are connected to generate an irregular triangulated network, which is to construct triangulated network (TIN) models at different levels of detail based on the point cloud.

[0085] In step 152, a triangular patch is assigned to each triangular face in the irregular triangulated network to obtain a white body model.

[0086] Here, a triangular facet is assigned to each triangular face in the irregular triangulated network, so as to obtain the white body model, wherein the color of the triangular facet is preferably white.

[0087] In step 153, texture is extracted from the original image data, and the texture is attached to the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0088] Here, texture fitting is to extract texture from the original image data and attach the texture to the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0089] Among them, the texture used for fitting is preferably selected from the original image data, which has no obstruction from debris, uniform posture and no misalignment.

[0090] It is worth mentioning that the tile technology can be used to fit the texture. By dividing the white body model into several sub-areas (tiles) of a certain size, each tile is packaged and established as a task based on the parallel processing mechanism of the cluster processing system, which is automatically assigned to each computing node for model and texture image alignment and texture attachment. At the same time, a multi-detail, multi-level LOD is established for the textured model to facilitate the optimization of the corresponding file organization structure and improve the efficiency of hierarchical browsing of the model, thereby generating the final three-dimensional geological model.

[0091] Therefore, a three-dimensional geological model with real texture can be obtained by constructing an irregular triangulated network, assigning a triangular facet to each triangular face in the irregular triangulated network, and performing model texture fitting.

[0092] In an optional implementation, after step 152, the following steps may also be included:

[0093] Determining whether there is a hole area on the white body model;

[0094] When the hole area exists, determining the diameter of the hole area;

[0095] When the diameter of the hole area is not greater than a preset size, the hole area is filled with straight lines;

[0096] When the diameter of the hole area is greater than a preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

[0097] When a hole area appears on the 3D geological model, it means that there is no image in the hole area or the corresponding image was not collected in the image collection stage. In order to obtain a complete 3D geological model, the hole area on the 3D geological model needs to be filled.

[0098] In this embodiment, different filling methods are used for hole areas of different sizes. When the diameter of the hole area is not greater than the preset size, the hole area is filled with straight lines. When the diameter of the hole area is greater than the preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

[0099] It is worth noting that when the diameter of the hole area is larger than the preset size, using straight lines to fill it will make the model too stiff. By constructing similar curvature lines to fill the hole area, a perfect transition of the hole area can be achieved.

[0100] The preset size is preferably 0.2 meters. That is, when the diameter of the hole area is less than 0.2 meters, it is directly filled with straight lines; when the diameter of the hole area is greater than 0.2 meters, similar curvature lines can be constructed according to the curvature of the boundary lines of the hole area to fill the white body model and obtain the filled white body model.

[0101] Therefore, by selecting different filling methods according to the diameter of the hole area, the three-dimensional geological model can be filled quickly and more smoothly.

[0102] In an optional implementation, in step 130, performing aerial triangulation on the image data to obtain a dense point cloud model of the geological area to be modeled includes:

[0103] A first connection point is determined from the image data, and aerial triangulation is performed on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled.

[0104] Here, the first connection points set on each image data include 8, which are located at the corners and center of each image data, that is, one connection point is distributed at each of the four corners of the image data, and four connection points are distributed in a square at the center of the image data. Such a distribution of the first connection points is stable and representative. When the number of connection points is large, it will be unfavorable for operation and adjustment. Then, aerial triangulation is performed through the first connection point, and the position of each image is determined by reverse calculation, so as to obtain a dense point cloud model of the geological area to be modeled.

[0105] Therefore, through the first connection point, it is possible to obtain a fast and accurate aerial triangulation of the image data.

[0106] In an optional embodiment, after determining the first connection point from the image data and performing aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled, the method further includes:

[0107] Determining whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation;

[0108] When the unmatched image exists, determining whether the unmatched image is in a point cloud density uniform area in the dense point cloud model;

[0109] When the unmatched image is in a point cloud density uniform area in the dense point cloud model, deleting the unmatched image;

[0110] When the unmatched image is in an area with uneven point cloud density in the dense point cloud model, a second connection point is added in an overlapping area between the unmatched image and an image adjacent to the unmatched image, and aerial triangulation is re-performed on the unmatched image based on the second connection point to obtain a new dense point cloud model.

[0111] Here, after executing the aerial triangulation, according to the calculation result of the aerial triangulation, if an unmatched image appears, it means that the unmatched image cannot be aerially triangulated according to the first connection point, so the position of the unmatched image cannot be determined, resulting in the loss of the unmatched image.

[0112] By judging whether the unmatched image is in a uniform point cloud density region in the dense point cloud model, when the unmatched image is in a uniform point cloud density region in the dense point cloud model, it means that the region can be reconstructed in three dimensions based on the point cloud data of the region to reflect the real situation of the region. Therefore, the unmatched image can be directly eliminated.

[0113] When the unmatched image is in an area with uneven point cloud density in the dense point cloud model, it indicates that image loss has occurred in the area of ​​the unmatched image, and three-dimensional reconstruction of the area based only on the point cloud of the area may not reflect the actual situation of the area.

[0114] Therefore, a second connection point is added in the overlapping area between the unmatched image and the image adjacent to the unmatched image, wherein the second connection point is set at the four corners and the center point in the overlapping area, so as to re-perform aerial triangulation on the unmatched image based on the second connection point to obtain a new dense point cloud model.

[0115] In an optional implementation, before step 110, the method further includes:

[0116] Pre-setting a plurality of scale identification points on the geological area to be modeled, and measuring the distances between the scale identification points;

[0117] The scale identification points are used as scale constraint points on the three-dimensional geological model, and the distances between the scale identification points are used as the distances between the scale constraint points, so as to obtain a three-dimensional geological model with size information.

[0118] Here, by presetting a plurality of scale identification points on the geological area to be modeled and measuring the distances between the scale identification points, the scale identification points are used as scale constraint points on the three-dimensional geological model, and the distances between the scale identification points are used as the distances between the scale constraint points, so that a three-dimensional geological model with size information can be obtained.

[0119] Among them, 6 spherical target feature points can be placed in the geological area to be modeled as scale identification points, three target feature points are set in front of the laser scanner, and three target feature points are set behind the laser scanner. In addition, the setting of the target feature points is as equilateral triangle as possible. Experiments have shown that the arrangement of the scale identification points as an equilateral triangle is optimal, and the arrangement of the equilateral triangle is representative of the region. In addition, the size of the target feature point should be greater than the minimum resolution of the image acquisition device. That is, it can be distinguished at a glance on the image. During laser scanning, the distance between the laser scanner and the target feature point is maintained between 1.5 and 3m.

[0120] It is worth noting that the purpose of the scale mark point is to give scale information to the 3D geological model. The scale mark point is not only used for scale constraints of the laser point cloud model, but also can be used as a scale mark point for oblique photogrammetry.

[0121] Therefore, by presetting scale identification points and measuring the distances of the scale identification points, the scale identification points can be used to constrain the scale of the three-dimensional geological model during the three-dimensional reconstruction process, thereby obtaining a three-dimensional geological model with real size information.

[0122] Embodiment 2

[0123] On the basis of the above-mentioned embodiment, the second embodiment of the present invention can also provide a method for constructing a geological model. Figure 2 A schematic diagram of a process of constructing a geological model according to a second embodiment of the present invention is shown. Figure 2 As shown, the geological model construction method may include: steps 210 to 290.

[0124] In step 210, a scale marker point is set.

[0125] Here, by presetting a plurality of scale identification points on the geological area to be modeled and measuring the distances between the scale identification points, the scale identification points are used as scale constraint points on the three-dimensional geological model, and the distances between the scale identification points are used as the distances between the scale constraint points, so that a three-dimensional geological model with size information can be obtained.

[0126] Among them, six spherical target feature points can be placed in the geological area to be modeled as scale identification points, three target feature points are set in front of the laser scanner, and three target feature points are set behind the laser scanner. In addition, the setting of the target feature points is set as an equilateral triangle as much as possible. After experiments, it is found that the arrangement of the scale identification points is optimal when it is set as an equilateral triangle, and the arrangement of the equilateral triangle is representative of the region.

[0127] In addition, the size of the target feature point should be larger than the minimum resolution of the image acquisition device, that is, it can be distinguished at a glance on the image. During laser scanning, the distance between the laser scanner and the target feature point is maintained between 1.5 and 3 meters.

[0128] It is worth noting that the purpose of the scale mark point is to give scale information to the 3D geological model. The scale mark point is not only used for scale constraints of the laser point cloud model, but also can be used as a scale mark point for oblique photogrammetry.

[0129] Therefore, by presetting scale identification points and measuring the distances of the scale identification points, the scale identification points can be used to constrain the scale of the three-dimensional geological model during the three-dimensional reconstruction process, thereby obtaining a three-dimensional geological model with real size information.

[0130] In step 220, scanning is performed using a laser scanner.

[0131] Here, 3D laser scanning technology uses the principle of laser ranging. By recording the 3D coordinates, reflectivity, texture and other information of a large number of dense points on the surface of the measured object, it can quickly reconstruct the 3D geological model of the measured target and various map data such as lines, surfaces and volumes. Since the 3D laser scanning system can densely acquire a large number of data points of the target object, it can provide an accurate basis for subsequent internal processing, data analysis and other work.

[0132] Therefore, the laser scanner can be mounted on a tripod, and the tripod and the laser scanner can be placed on a stable and level ground. Then, by rotating the laser scanner or the tripod, the laser scanner can scan the geological area to be modeled, thereby obtaining a laser point cloud model of the geological area to be modeled.

[0133] In step 230, image data is collected.

[0134] Here, a drone or a SLR camera can be used to obtain image data of the geological area to be modeled at different shooting angles.

[0135] Taking drones as an example, drones use fixed-focus cameras throughout the entire process of collecting images of the geological area to be modeled. When shooting, the distance between the fixed-focus camera and the geological area to be modeled is kept as consistent as possible, and the shooting angles of the drone and the ground are 30°, 90°, and 150°, respectively. That is, the drone shoots the geological area to be mapped at shooting angles of 30°, 90°, and 150°, respectively, to obtain image data at different angles.

[0136] It is worth mentioning that the image data collected through shooting angles of 30°, 90°, and 150° can better obtain surface information and reduce hole areas.

[0137] In addition, when the drone is shooting, it collects image data of the geological area to be modeled according to a specific order. Moreover, the overlap rate between each adjacent image taken by it is kept greater than 75%. For example, the drone flies in a preset heading band and collects images. After shooting the current shooting point, the drone flies to the next preset shooting point to continue shooting the geological area to be modeled under the shooting point, so that the image overlap of the images collected by the camera in this heading is kept within a preset range.

[0138] In addition, the route of the drone can be a plurality of parallel straight lines in the same plane, and the lateral overlap of the images captured under the plurality of routes is also maintained within a preset range. The preset shooting points are points on the route, and the distances between adjacent preset shooting points and the distances between adjacent routes can be set according to actual conditions, so that the overlap of the images collected by the drone in the heading direction is within a preset range, and the overlap of the images in the lateral direction is within a preset range, thereby ensuring that the drone captures the entire image of the monitored area without omission.

[0139] Taking a SLR camera as an example, when a laser scanner collects point cloud data of the geological area to be modeled, the high-precision camera built into the laser scanner can be used to obtain image data from different shooting angles. Among them, the use of a SLR camera for image acquisition can be to use the high-precision camera built into the laser scanner, and collect image data by rotating 360°. Among them, within 10m indoors, the image quality of the image data is 4 times. Images collected with such parameters can better obtain information on the surface of the object being measured and reduce the appearance of hole areas. In addition, it is necessary to ensure that the overlap rate between each image remains greater than 90%.

[0140] It is worth noting that step 220 and step 230 can be performed simultaneously or separately. For example, step 220 is performed first to collect the laser point cloud model, and then the image data of different shooting angles are shot.

[0141] In step 240, aerial triangulation is performed.

[0142] Here, aerial triangulation is performed on the image data collected at different shooting angles to obtain a dense point cloud model of the geological area to be modeled.

[0143] Among them, aerial triangulation is based on the coordinates of the image points measured on the film, using a rigorous mathematical model, according to the principle of least squares, using a small number of ground control points as adjustment conditions, and solving the ground coordinates of the control points required for mapping on an electronic computer. Among them, the image data is input into the corresponding software platform for aerial triangulation, which can automatically match the same-name points of all image data, and extract more feature points from the image data, so as to obtain a dense point cloud model of the geological area to be modeled.

[0144] In addition, after executing the aerial triangulation, if an unmatched image appears according to the calculation result of the aerial triangulation, it means that the unmatched image cannot be aerially triangulated according to the first connection point, so the position of the unmatched image cannot be determined, resulting in the loss of the unmatched image.

[0145] By judging whether the unmatched image is in a uniform point cloud density region in the dense point cloud model, when the unmatched image is in a uniform point cloud density region in the dense point cloud model, it means that the region can be reconstructed in three dimensions based on the point cloud data of the region to reflect the real situation of the region. Therefore, the unmatched image can be directly eliminated.

[0146] When the unmatched image is in an area with uneven point cloud density in the dense point cloud model, it indicates that image loss has occurred in the area of ​​the unmatched image, and three-dimensional reconstruction of the area based only on the point cloud of the area may not reflect the actual situation of the area.

[0147] Therefore, a second connection point is added in the overlapping area between the unmatched image and the image adjacent to the unmatched image, wherein the second connection point is set at the four corners and the center point in the overlapping area, so as to re-perform aerial triangulation on the unmatched image based on the second connection point to obtain a new dense point cloud model.

[0148] In step 250 , the point clouds are fused.

[0149] Here, the laser point cloud model and the dense point cloud model are subjected to point cloud data fusion to obtain a point cloud fusion model.

[0150] Among them, since the laser point cloud model of the geological area to be modeled obtained by using a laser scanner and the dense point cloud model of the geological area to be modeled obtained by aerial triangulation both contain a large amount of point cloud data, the point cloud data in the laser point cloud model can be fused with the point cloud data in the dense point cloud model to obtain a point cloud fusion model.

[0151] It is worth noting that fusing the laser point cloud model with the dense point cloud model is to register the point cloud data in the two point cloud models. The iterative nearest neighbor registration method can be used to register the laser point cloud model with the point cloud data in the dense point cloud model to obtain a point cloud fusion model.

[0152] In step 260, an irregular triangulated network is constructed.

[0153] Here, the point cloud data in the point cloud fusion model generated in step 250 are connected to generate an irregular triangulated network, and the purpose is to construct triangulated network (TIN) models at different levels of detail based on the point cloud.

[0154] Among them, the irregular triangulated network (TIN) uses a series of connected triangles to fit the ground surface or other irregular surfaces, and is often used to construct digital ground models, especially digital elevation models. The most commonly used generation method is the Delaunay subdivision method.

[0155] After point cloud fusion, a point cloud fusion model will be obtained. The point cloud fusion model includes a large amount of point cloud data. By connecting the point cloud data in the point cloud fusion model to generate an irregular triangulated network, three-dimensional visualization of the geological area to be modeled can be achieved.

[0156] Among them, the irregular triangulated network can also be optimized. The specific optimization process is to adjust the size of the internal triangle to a ratio that matches the resolution of the original image, and at the same time simplify the triangulated network in relatively flat areas to reduce data redundancy.

[0157] In step 270, a white body model is constructed.

[0158] Here, in the irregular triangulated network obtained in step 260, a triangular face is assigned to each triangular face in the irregular triangulated network, so as to obtain the white body model. The color of the triangular face is preferably white.

[0159] In step 280, the three-dimensional geological model is optimized.

[0160] Here, in the process of constructing the 3D geological model, incomplete image acquisition or lack of laser scanning may cause holes in the 3D geological model. Therefore, in order to obtain a more detailed and complete 3D geological model, it is necessary to optimize the white body model after obtaining it. The optimization of the 3D geological model specifically includes the following steps:

[0161] Determining whether there is a hole area on the white body model;

[0162] When the hole area exists, determining the diameter of the hole area;

[0163] When the diameter of the hole area is not greater than a preset size, the hole area is filled with straight lines;

[0164] When the diameter of the hole area is greater than a preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

[0165] Here, when a hole area appears on the three-dimensional geological model, it means that there is no image in the hole area or the corresponding image was not collected in the image collection stage. In order to obtain a complete three-dimensional geological model, the hole area on the three-dimensional geological model needs to be filled.

[0166] In this embodiment, different filling methods are used for hole areas of different sizes. When the diameter of the hole area is not greater than the preset size, the hole area is filled with straight lines. When the diameter of the hole area is greater than the preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

[0167] It is worth noting that when the diameter of the hole area is larger than the preset size, using straight lines to fill it will make the model too stiff. By constructing similar curvature lines to fill the hole area, a perfect transition of the hole area can be achieved.

[0168] The preset size is preferably 0.2 meters. That is, when the diameter of the hole area is less than 0.2 meters, it is directly filled with straight lines; when the diameter of the hole area is greater than 0.2 meters, similar curvature lines can be constructed according to the curvature of the boundary lines of the hole area to fill the white body model and obtain the filled white body model.

[0169] Therefore, by selecting different filling methods according to the diameter of the hole area, the three-dimensional geological model can be filled quickly and more smoothly.

[0170] In addition, the optimization of the 3D geological model can also include deleting areas of no interest, such as large areas of flat land or deserts that are not within the scope of the study, thereby simplifying the 3D geological model and making it more streamlined.

[0171] In step 290, the texture is fitted.

[0172] Here, texture fitting is to extract texture from the original image data and attach the texture to the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0173] Among them, the texture used for fitting is preferably selected from the original image data, which has no obstruction from debris, uniform posture and no misalignment.

[0174] Therefore, by attaching texture to the white body model, a three-dimensional geological model with real texture can be obtained.

[0175] It is worth mentioning that the tile technology can be used to fit the texture. By dividing the white body model into several sub-areas (tiles) of a certain size, each tile is packaged and established as a task based on the parallel processing mechanism of the cluster processing system, which is automatically assigned to each computing node for model and texture image alignment and texture attachment. At the same time, a multi-detail, multi-level LOD is established for the textured model to facilitate the optimization of the corresponding file organization structure and improve the efficiency of hierarchical browsing of the model, thereby generating the final three-dimensional geological model.

[0176] In this embodiment, a laser point cloud model of the geological area to be modeled is obtained by using a laser scanner, and an aerial triangulation is performed on the image data of different shooting angles to obtain a dense point cloud model of the geological area to be modeled, and the laser point cloud model and the dense point cloud model are fused to obtain a more accurate point cloud fusion model, and then a three-dimensional geological model is reconstructed. Therefore, through the fusion of point cloud data, not only can the construction of a three-dimensional digital model of the geological area to be modeled be realized, but also the advantages of three-dimensional laser modeling technology and oblique photography technology can be combined to obtain the surface coordinates of the measured object in all directions, thereby obtaining a more refined three-dimensional geological model.

[0177] The above embodiment is described below by an example:

[0178] When reconstructing the three-dimensional geological model of the cave, first place six spherical target feature points as scale identification points in the cave scanning area. The laser scanner is set in the middle of the area to be collected, three scale identification points are located in front of the laser scanner, and three scale identification points are located behind the laser scanner. Moreover, the distance between the scale identification points and the laser scanner is between 1.5-3m. Moreover, the scale identification points are arranged in an equilateral triangle as much as possible, which can be used for three matching feature points between two scanning stations. In addition, the size of the scale identification point must be larger than the minimum resolution of the image acquisition device, so that the scale identification point can be distinguished at a glance on the image.

[0179] Then, the laser scanner is mounted on a tripod, and the tripod and laser scanner are placed on a stable and level ground. During the scanning process, the tripod must not move. The laser scanner is rotated so that the laser scanner's built-in high-precision camera can be used to collect point cloud data and image data by 360° rotation. Among them, the scanning parameters of the 3D scanner are set to within 10m indoors, and the image quality is 4 times. The point cloud and images collected by these parameters can better obtain surface information, reduce the hole area, keep the overlap rate between each image greater than 90%, and collect image data of geological outcrops in a specific order.

[0180] Furthermore, the acquired laser point cloud model and the dense point cloud model obtained according to the data images taken at different shooting angles are subjected to point cloud data fusion to obtain a point cloud fusion model, and then the three-dimensional reconstruction of the cave is performed based on the point cloud fusion model.

[0181] After obtaining the three-dimensional geological model of the cave, three-dimensional geological parameters can be collected from the three-dimensional geological model. The actual measured distance of the scale mark point is compared with the measured distance of the scale mark point on the three-dimensional geological model. The actual measured value is considered to be the true distance, and the error of the model length is calculated. Each group of mark points represents an area. Later, the error correction is performed for the measured cave parameters and crack parameters. For the inside of the cave, the measurement tools are used to extract the filling material, cave morphological parameters, and crack parameters (density, length, and opening). For the cave measurement within 2m, the crack parameters are extracted. The extraction of geological parameters requires the selection of appropriate areas in advance to measure and extract different quantitative parameters of cracks and caves. In this way, the extracted parameters are analyzed, the cave development characteristics and crack development characteristics are clarified, and then the combination relationship of cracks and caves and the matching relationship between different parameters are summarized.

[0182] Embodiment 3

[0183] According to an embodiment of the present invention, a geological model construction system is also provided. Figure 3 FIG. 4 shows a schematic diagram of a geological model construction system proposed in Embodiment 3 of the present invention. Figure 3As shown, the system may include:

[0184] A laser point cloud model acquisition module is configured to use a laser scanner to scan the geological area to be modeled to acquire a laser point cloud model of the geological area to be modeled;

[0185] An image acquisition module is configured to acquire image data of different shooting angles of the geological area to be modeled;

[0186] A dense point cloud model building module is configured to perform aerial triangulation on the image data to obtain a dense point cloud model of the geological area to be modeled;

[0187] A fusion module is configured to fuse the laser point cloud model with the dense point cloud model to obtain a point cloud fusion model;

[0188] The geological model building module is configured to build a three-dimensional geological model based on the point cloud fusion model, so as to use the three-dimensional geological model to analyze the geological area to be modeled.

[0189] Optionally, the geological model building module includes:

[0190] An irregular triangulated network construction unit is configured to connect the point cloud data in the point cloud fusion model to generate an irregular triangulated network;

[0191] A white-body model building unit, configured to assign a triangular facet to each triangular face in the irregular triangulated network to obtain a white-body model;

[0192] The texture pasting unit is configured to extract texture from the original image data and paste the texture on the corresponding area of ​​the white body model to obtain the three-dimensional geological model.

[0193] Optionally, the system further comprises:

[0194] A hole detection module, configured to determine whether there is a hole area on the white body model;

[0195] A hole size determination module, configured to determine the diameter of the hole area;

[0196] The hole filling module is configured to fill the hole area with straight lines when the diameter of the hole area is not greater than a preset size; when the diameter of the hole area is greater than the preset size, construct similar curvature lines according to the curvature of the boundary lines of the hole area to fill the hole area.

[0197] Optionally, the dense point cloud model building module is specifically configured to determine a first connection point from the image data, and perform aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled.

[0198] Optionally, the system further comprises:

[0199] A first detection module is configured to determine whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation;

[0200] a second detection module, configured to determine whether the unmatched image is in a point cloud density uniform area in the dense point cloud model when the first detection module detects the unmatched image;

[0201] The image processing module is configured to delete the unmatched image when the unmatched image is in a point cloud density uniform area in the dense point cloud model; add a second connection point in the overlapping area of ​​the unmatched image and an image adjacent to the unmatched image when the unmatched image is in a point cloud density non-uniform area in the dense point cloud model, and send the unmatched image with the second connection point added to the dense point cloud model construction module to re-perform aerial triangulation to obtain a new dense point cloud model.

[0202] Optionally, the second connection points are arranged at four corners and a center point in the overlapping area.

[0203] Optionally, the system further comprises:

[0204] A scale identification point setting module is configured to pre-set a plurality of scale identification points on the geological area to be modeled and measure the distances between the scale identification points;

[0205] The three-dimensional geological model scale calculation module is configured to use the scale identification points as scale constraint points on the three-dimensional geological model and use the distance between the scale identification points as the distance between the scale constraint points to obtain a three-dimensional geological model with size information.

[0206] Embodiment 4

[0207] According to an embodiment of the present invention, a storage medium is further provided, on which a program code is stored. When the program code is executed by a processor, the geological model construction method as described in any one of the above embodiments is implemented.

[0208] Embodiment 5

[0209] According to an embodiment of the present invention, an electronic device is also provided, comprising a memory and a processor, wherein the memory stores a program code that can be run on the processor, and when the program code is executed by the processor, the geological model construction method as described in any one of the above embodiments is implemented.

[0210] Figure 4 FIG. 4 shows a schematic diagram of the structure of an electronic device proposed in Embodiment 5 of the present invention. Figure 4 As shown, the electronic device 400 may include: a processor 401 , a memory 402 , a multimedia component 403 , an input / output (I / O) interface 404 , a communication component 405 and an electronic device body 406 .

[0211] The processor 401 is used to control the overall operation of the electronic device 400 to complete all or part of the steps in the above method. The memory 402 is used to store various types of data to support the operation of the electronic device 400, which may include instructions for any application or method used to operate on the electronic device 400, as well as application-related data. The memory 402 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The electronic device body 406 includes all components used for electronic device detection, and the multimedia component 403 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 402 or sent through the communication component 405. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 404 provides an interface between the processor 401 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 405 is used for wired or wireless communication between the device 400 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 405 may include: Wi-Fi module, Bluetooth module, NFC module.

[0212] The technical solution of the present invention is described in detail above in conjunction with the accompanying drawings. Considering that in the related art, the method of measuring the size of typical geological phenomena based on traditional geological survey means, such as using a benchmark or geological hammer as a scale and taking photos with a camera, is prone to errors and the measurement process is cumbersome. The present invention provides a geological model construction method, system, storage medium and electronic device, which obtains a laser point cloud model of the geological area to be modeled by using a laser scanner, and obtains a dense point cloud model of the geological area to be modeled by performing aerial triangulation on image data from different shooting angles, and fuses the laser point cloud model and the dense point cloud model to obtain a more accurate point cloud fusion model, and then reconstructs a three-dimensional geological model. Not only can the construction of a three-dimensional digital model of the geological area to be modeled be realized, but also the advantages of three-dimensional laser modeling technology and oblique photography technology can be combined to obtain the surface coordinates of the measured object in all directions, thereby obtaining a more refined three-dimensional geological model.

[0213] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0214] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0215] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0216] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0217] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for constructing a geological model, characterized in that: include: Scan the geological area to be modeled using a laser scanner to obtain a laser point cloud model of the geological area to be modeled; Acquire image data of the geological area to be modeled at different shooting angles; wherein the image data is collected at shooting angles of 30°, 90°, and 150°; Determine a first connection point from the image data, and perform aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled; determine whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation; when the unmatched image exists, determine whether the unmatched image is in a uniform point cloud density area in the dense point cloud model; when the unmatched image is in a uniform point cloud density area in the dense point cloud model, delete the unmatched image; when the unmatched image is in an uneven point cloud density area in the dense point cloud model, add a second connection point in the overlapping area of ​​the unmatched image and an image adjacent to the unmatched image, and re-perform aerial triangulation on the unmatched image based on the second connection point to obtain a new dense point cloud model; wherein the first connection points set on each image data include 8, which are respectively located at the corners and center of each image data; Performing point cloud data fusion on the laser point cloud model and the dense point cloud model to obtain a point cloud fusion model; Based on the point cloud fusion model, a three-dimensional geological model is constructed to analyze the geological area to be modeled using the three-dimensional geological model; wherein, the three-dimensional geological model is constructed based on the point cloud fusion model, including: connecting the point cloud data in the point cloud fusion model to generate an irregular triangulated network; assigning a triangular facet to each triangular face in the irregular triangulated network to obtain a white body model; extracting texture from the original image data, and attaching the texture to the corresponding area of ​​the white body model to obtain the three-dimensional geological model; The method further comprises: A plurality of scale identification points are set in advance on the geological area to be modeled, and the distances between the scale identification points are measured; wherein, three spherical target feature points are set in front of and behind the laser scanner as the scale identification points, and the three spherical target feature points located in front of the laser scanner and the three spherical target feature points located behind the laser scanner are all set in the form of an equilateral triangle; the scale identification points are used as scale constraint points on the three-dimensional geological model, and the distances between the scale identification points are used as the distances between the scale constraint points, so as to obtain a three-dimensional geological model with size information.

2. The method for constructing a geological model according to claim 1, characterized in that: After assigning a triangular face to each triangular face in the irregular triangulated network to obtain a white body model, the method further includes: Determining whether there is a hole area on the white body model; When the hole area exists, determining the diameter of the hole area; When the diameter of the hole area is not greater than a preset size, the hole area is filled with straight lines; When the diameter of the hole area is larger than a preset size, a similar curvature line is constructed according to the curvature of the boundary line of the hole area to fill the hole area.

3. The geological model construction method according to claim 1, characterized in that: The second connection points are arranged at four corners and a center point in the overlapping area.

4. A geological model construction system, characterized in that: include: A laser point cloud model acquisition module is configured to use a laser scanner to scan the geological area to be modeled to acquire a laser point cloud model of the geological area to be modeled; An image acquisition module is configured to acquire image data of the geological area to be modeled at different shooting angles; wherein the image data is collected at shooting angles of 30°, 90° and 150°; A dense point cloud model building module is configured to determine a first connection point from the image data, and perform aerial triangulation on the image data according to the first connection point to obtain a dense point cloud model of the geological area to be modeled; A first detection module is configured to determine whether there is an unmatched image, wherein the unmatched image is image data that cannot be used for aerial triangulation; A second detection module is configured to determine whether the unmatched image is in a point cloud density uniform area in the dense point cloud model when the unmatched image exists; The image processing module is configured to delete the unmatched image when the unmatched image is in a point cloud density uniform area in the dense point cloud model; add a second connection point in an overlapping area between the unmatched image and an image adjacent to the unmatched image when the unmatched image is in a point cloud density non-uniform area in the dense point cloud model, and re-perform aerial triangulation on the unmatched image based on the second connection point to obtain a new dense point cloud model; wherein the first connection points set on each image data include 8, which are respectively located at the corners and the center of each image data; A fusion module is configured to fuse the laser point cloud model with the dense point cloud model to obtain a point cloud fusion model; A geological model construction module is configured to construct a three-dimensional geological model based on the point cloud fusion model, so as to analyze the geological area to be modeled by using the three-dimensional geological model; wherein the geological model construction module includes: an irregular triangulated network construction unit, configured to connect the point cloud data in the point cloud fusion model to generate an irregular triangulated network; a white body model construction unit, configured to assign a triangular face to each triangular face in the irregular triangulated network to obtain a white body model; a texture pasting unit, configured to extract texture from the original image data, and paste the texture on the corresponding area of ​​the white body model to obtain the three-dimensional geological model; The scale mark point setting module is configured to set a plurality of scale mark points in advance on the geological area to be modeled, and measure the distances between the scale mark points; wherein three spherical target feature points are set in front of and behind the laser scanner as the scale mark points, and the three spherical target feature points in front of the laser scanner and the three spherical target feature points behind the laser scanner are all set in the form of an equilateral triangle; The three-dimensional geological model scale calculation module is configured to use the scale identification points as scale constraint points on the three-dimensional geological model and use the distance between the scale identification points as the distance between the scale constraint points to obtain a three-dimensional geological model with size information.

5. A storage medium having a program code stored thereon, characterized in that: When the program code is executed by a processor, the geological model construction method according to any one of claims 1 to 3 is implemented.

6. An electronic device, characterized in that: The electronic device includes a memory and a processor. The memory stores program codes that can be run on the processor. When the program codes are executed by the processor, the geological model construction method according to any one of claims 1 to 3 is implemented.

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