Three-dimensional geological modeling method and device for hydropower station grouting engineering, medium and terminal

Abstract

The application discloses a three-dimensional geological modeling method and device for a hydropower station grouting project, a medium and a terminal, relates to the geological survey and digital technology field, and mainly aims to improve the problem that the grouting design lacks reliable basis due to the fact that accurate and high-precision three-dimensional geological modeling cannot be realized in the prior art, and further lead to the problem that it is difficult to ensure the long-term safe operation of the project. It comprises the following steps: determining a plurality of drilling point positions based on a gravity field map, collecting rock layers and positioning the positions, and obtaining drilling point data of each drilling point position; based on each drilling point data and the number of first-round clustering clusters, performing iterative clustering processing and layered interpolation processing to generate a drilling point data distribution map; for each sub-region, taking the minimum rock layer thickness as the division unit, performing layered three-dimensional modeling and integration processing on the sub-region to obtain a sub-region three-dimensional geological model, and integrating all the sub-region three-dimensional geological models to obtain a three-dimensional geological model of a target region.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geological exploration and digital technology, in particular to a three-dimensional geological modeling method and device for hydropower station grouting engineering, medium and terminal. BACKGROUND

[0002] In hydropower station engineering, a high-precision three-dimensional geological model is the core basis for site selection, design, construction and operation evaluation.

[0003] At present, the existing three-dimensional geological modeling method mainly first arranges drill holes in the engineering area according to certain rules, obtains drill hole data, and then performs global geological attribute interpolation to generate a continuous three-dimensional geological model of the region.

[0004] However, in the global geological attribute interpolation processing, in order to pursue the smooth transition of the overall trend, the key local mutation geological features such as karst cavity and interlayer lens are easily smoothed and weakened, resulting in that the generated three-dimensional geological model cannot accurately depict the key geological structures controlling the seepage path and engineering stability, causing the deviation of the model from the actual situation, and at the same time, due to the inability to accurately represent the spatial position of the high gradient zone of permeability and the key leakage channel, the grouting design based on the three-dimensional geological model lacks reliable basis, thereby making it difficult to ensure the long-term safe operation of the project. SUMMARY

[0005] Therefore, the present application provides a three-dimensional geological modeling method and device for hydropower station grouting engineering, medium and terminal, which mainly aims to improve the problem that the grouting design lacks reliable basis due to the inability to achieve accurate and high-precision three-dimensional geological modeling in the prior art, thereby making it difficult to ensure the long-term safe operation of the project.

[0006] According to one aspect of the present application, a three-dimensional geological modeling method for hydropower station grouting engineering is provided, comprising:

[0007] Obtaining a gravity field map of a target area, determining a plurality of drill hole points in the target area based on the gravity field map, and collecting and positioning rock layers at each drill hole point to obtain drill hole point data of each drill hole point;

[0008] Performing iterative clustering and layered interpolation processing on the plurality of drill hole points based on the drill hole point data and the first round cluster number to generate a drill hole point data distribution map of the target area, wherein the drill hole point data distribution map includes a sub-region of the first round cluster number;

[0009] For each sub-region, find the minimum rock thickness from the drilling point data distribution map, and take the minimum rock thickness as the division unit, perform hierarchical three-dimensional modeling and integration processing on the sub-region to obtain a sub-region three-dimensional geological model of the sub-region, and integrate all the sub-region three-dimensional geological models to obtain a three-dimensional geological model of the target region, and generate a grouting scheme based on the three-dimensional geological model of the target region.

[0010] Preferably, the first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0011] The first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0012] The first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0013] The first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0014] Preferably, the drilling point data includes drilling point position information and gravity information, and the first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0015] The first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0016] The first round clustering cluster quantity is obtained by performing first round clustering processing on the plurality of drilling point positions based on each of the drilling point data and the first round clustering cluster quantity, and the hierarchical interpolation processing is performed on each of the first round sub-regions to obtain a first round interpolation result, wherein the first round interpolation result contains drilling point data of the plurality of drilling point positions and a plurality of first round interpolation point positions.

[0017] For each borehole location, the normalized borehole point data of the borehole location is calculated, and the Euclidean distance between the normalized borehole point data of each initial cluster center is calculated. The borehole location is then assigned to the cluster of the initial cluster center corresponding to the smallest Euclidean distance, resulting in multiple initial clusters.

[0018] For each initial cluster, the current cluster center is recalculated based on the normalized borehole point data of each borehole point contained in the initial cluster.

[0019] The clustering process iteratively divides the clusters and updates the cluster centers until the minimum objective function described below converges, obtaining the final clusters and corresponding final cluster centers of the first-round cluster count, thus completing the first round of clustering and obtaining the first-round sub-regions of the first-round cluster count.

[0020] ,

[0021] Where K represents the number of clusters, This represents the k-th cluster. Indicates the first Drilling point data for each drilling point With cluster center The Euclidean distance.

[0022] Preferably, the step of performing interpolation processing in each of the first-round sub-regions to obtain the first-round interpolation result includes:

[0023] For each final cluster, obtain the location information of the points to be interpolated;

[0024] Calculate the Euclidean distance between the location information of the point to be interpolated and the location information of each borehole point in the final cluster;

[0025] Based on the Euclidean distances and the borehole data for each borehole location, the borehole data for the point to be interpolated is calculated using the inverse distance interpolation formula, wherein the inverse distance interpolation formula is expressed as follows:

[0026] ,

[0027] Indicates the point to be interpolated Drilling point data, This represents the Euclidean distance between the location information of the point to be interpolated and the location information of the borehole points in the final cluster. Indicates the th in the final cluster Drilling point data for each drilling point location. This indicates the number of borehole locations in the final cluster.

[0028] Preferably, the method comprises the following steps:

[0029] For each sub-region, the minimum rock thickness in the sub-region is searched from the drilling point data distribution map, and the minimum rock thickness is taken as a division unit;

[0030] Based on the division unit, the sub-region is vertically stratified to obtain a plurality of layers;

[0031] Based on the Kriging interpolation method, each layer is three-dimensionally modeled to obtain a plurality of layer three-dimensional geological models, so as to complete the three-dimensional modeling of the layers of the sub-region;

[0032] All the layer three-dimensional geological models are integrated to obtain a sub-region three-dimensional geological model of the sub-region, so as to complete the integration processing.

[0033] Preferably, before the step of generating the drilling point data distribution map of the target region by iteratively clustering and stratified interpolation of the plurality of drilling point positions based on each drilling point data and the first round cluster quantity, the method further comprises the following steps:

[0034] It is determined whether there is a gravity mutation region in the gravity field map;

[0035] If there is no gravity mutation region, the first round cluster quantity of the target region is calculated based on a linear cluster decay function;

[0036] If there is a gravity mutation region, and the mutation characteristics of the gravity mutation region meet the isolated mutation characteristics, the first round cluster quantity of the target region is calculated based on a fast nonlinear cluster decay function;

[0037] If there is a gravity mutation region, and the mutation characteristics of the gravity mutation region meet the continuous mutation characteristics, the first round cluster quantity of the target region is calculated based on a robust nonlinear cluster decay function.

[0038] Preferably, the method for obtaining the gravity field map of the target region comprises the following steps:

[0039] Obtaining geological data and topographic data of the target region;

[0040] Based on the geological data and the topographic data, a plurality of gravity measurement points are determined in the target region;

[0041] The gravity measurement instrument is used to measure the gravity and locate the position at each gravity measurement point, and the gravity data and the gravity measurement point position information at each gravity measurement point are obtained.

[0042] The gravity data exceeding the preset gravity fluctuation range is selected from the plurality of gravity data as abnormal gravity data.

[0043] For each abnormal gravity data, a new gravity measurement point is arranged around the gravity measurement point corresponding to the abnormal gravity data, and the gravity measurement and position location are performed at each new gravity measurement point to obtain the gravity data and the gravity measurement point position information at each new gravity measurement point as new gravity data and new gravity measurement point position information.

[0044] Based on each gravity data and corresponding gravity measurement point position information, each new gravity data and corresponding new gravity measurement point position information, a gravity field map of the target area is generated.

[0045] According to another aspect of the present application, a three-dimensional geological modeling device for a hydropower station grouting project is provided, comprising:

[0046] A drill hole point data acquisition module is configured to acquire a gravity field map of a target area, determine a plurality of drill hole points in the target area based on the gravity field map, and collect rock strata and locate positions at each drill hole point to obtain drill hole point data of each drill hole point.

[0047] A drill hole point data distribution map generation module is configured to perform iterative clustering processing and layered interpolation processing on the plurality of drill hole points based on each drill hole point data and a first round cluster quantity to generate a drill hole point data distribution map of the target area, wherein the drill hole point data distribution map includes a sub-region of the first round cluster quantity.

[0048] A three-dimensional modeling module is configured to, for each sub-region, find a minimum rock stratum thickness from the drill hole point data distribution map, use the minimum rock stratum thickness as a division unit, perform layered three-dimensional modeling and integration processing on the sub-region to obtain a sub-region three-dimensional geological model of the sub-region, and integrate all the sub-region three-dimensional geological models to obtain a three-dimensional geological model of the target area, so as to generate a grouting scheme based on the three-dimensional geological model of the target area.

[0049] Preferably, the drill hole point data distribution map generation module comprises:

[0050] A clustering unit is configured to perform first round clustering processing on the plurality of drill hole points based on each drill hole point data and a first round cluster quantity to obtain a first round sub-region of the first round cluster quantity.

[0051] An interpolation unit is used to perform interpolation processing in each of the first-round sub-regions to obtain the first-round interpolation result, wherein the first-round interpolation result includes multiple drilling points and drilling point data of multiple first-round interpolation points;

[0052] An iterative unit is used to subtract 1 from the number of clusters in the first round to obtain the number of clusters in the second round. Based on the interpolation result of the first round and the number of clusters in the second round, the unit performs second-round clustering processing on the multiple borehole locations and the multiple first-round interpolation locations to obtain the second-round sub-regions of the number of clusters in the second round. Interpolation processing is performed in each of the second-round sub-regions to obtain the second-round interpolation result. Iterative clustering processing and hierarchical interpolation processing are performed until the number of clusters is reduced to 1. Global interpolation processing is then performed to obtain the global interpolation result. The second-round interpolation result includes borehole point data of multiple borehole locations, multiple first-round interpolation locations, and multiple second-round interpolation locations.

[0053] The borehole point data distribution map generation unit is used to perform clustering processing on the global interpolation result based on the number of clusters in the first round, to obtain a sub-region with the number of clusters in the first round, so as to generate a borehole point data distribution map of the target region.

[0054] Preferably, the borehole point data includes borehole point location information and gravity information, and the clustering unit is used for:

[0055] The location information of each borehole point and the gravity information are normalized respectively to obtain normalized borehole point data for each borehole point.

[0056] From the multiple borehole locations, the number of borehole locations selected in the first round of clustering is randomly chosen as the initial cluster centers;

[0057] For each borehole location, the normalized borehole point data of the borehole location is calculated, and the Euclidean distance between the normalized borehole point data of each initial cluster center is calculated. The borehole location is then assigned to the cluster of the initial cluster center corresponding to the smallest Euclidean distance, resulting in multiple initial clusters.

[0058] For each initial cluster, the current cluster center is recalculated based on the normalized borehole point data of each borehole point contained in the initial cluster.

[0059] The clustering process iteratively divides the clusters and updates the cluster centers until the minimum objective function described below converges, obtaining the final clusters and corresponding final cluster centers of the first-round cluster count, thus completing the first round of clustering and obtaining the first-round sub-regions of the first-round cluster count.

[0060] ,

[0061] Where K represents the number of clusters, This represents the k-th cluster. Indicates the first Drilling point data for each drilling point With cluster center The Euclidean distance.

[0062] Preferably, the interpolation unit is used for:

[0063] For each final cluster, obtain the location information of the points to be interpolated;

[0064] Calculate the Euclidean distance between the location information of the point to be interpolated and the location information of each borehole point in the final cluster;

[0065] Based on the Euclidean distances and the borehole data for each borehole location, the borehole data for the point to be interpolated is calculated using the inverse distance interpolation formula, wherein the inverse distance interpolation formula is expressed as follows:

[0066] ,

[0067] Indicates the point to be interpolated Drilling point data, This represents the Euclidean distance between the location information of the point to be interpolated and the location information of the borehole points in the final cluster. Indicates the th in the final cluster Drilling point data for each drilling point location. This indicates the number of borehole locations in the final cluster.

[0068] Preferably, the 3D modeling module is used for:

[0069] For each sub-region, the minimum rock layer thickness within the sub-region is found from the borehole point data distribution map, and the minimum rock layer thickness is used as the dividing unit;

[0070] Based on the division unit, the sub-region is vertically divided into multiple layers.

[0071] Based on the Kriging interpolation method, three-dimensional modeling is performed on each of the aforementioned layers to obtain multiple layered three-dimensional geological models, thereby completing the layered three-dimensional modeling of the sub-region.

[0072] By integrating all the aforementioned layered three-dimensional geological models, a sub-regional three-dimensional geological model of the sub-region is obtained to complete the integration process.

[0073] Preferably, before the borehole point data distribution map generation module, the device further includes a first-round cluster quantity calculation module, used for:

[0074] Check if there are any regions of sudden gravity changes in the gravity field map;

[0075] If there is no region of sudden gravity change, the number of clusters in the first round of the target region is calculated based on the linear cluster decay function;

[0076] If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the isolated mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the fast nonlinear cluster decay function.

[0077] If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the contiguous mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the robust nonlinear cluster decay function.

[0078] Preferably, the borehole point data acquisition module is used for:

[0079] Acquire geological and topographic data for the target area;

[0080] Based on the geological data and the topographic data, multiple gravity measurement points are determined within the target area;

[0081] Using a gravity measuring instrument, gravity measurements and location positioning are performed at each gravity measurement point to obtain gravity data and gravity measurement point location information at each gravity measurement point.

[0082] Gravity data that exceeds the preset gravity fluctuation range is selected from multiple gravity data and designated as abnormal gravity data.

[0083] For each abnormal gravity data point, new gravity measurement points are arranged around the gravity measurement point corresponding to the abnormal gravity data point, and gravity measurements and location are performed at each of the new gravity measurement points to obtain the gravity data and gravity measurement point location information at each new gravity measurement point, which are used as the new gravity data and new gravity measurement point location information.

[0084] Based on the gravity data and the corresponding gravity measurement point location information, as well as the newly added gravity data and the corresponding newly added gravity measurement point location information, a gravity field map of the target area is generated.

[0085] According to another aspect of this application, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the three-dimensional geological modeling method for the grouting project of the hydropower station described above.

[0086] According to another aspect of this application, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0087] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the three-dimensional geological modeling method for the above-mentioned hydropower station grouting project.

[0088] By employing the above technical solutions, the technical solutions provided in the embodiments of this application have at least the following advantages:

[0089] This application provides a three-dimensional geological modeling method, device, medium, and terminal for grouting engineering in hydropower stations. First, a gravity field map of the target area is acquired. Based on the gravity field map, multiple borehole locations are determined within the target area, and rock strata are collected and their locations are determined at each borehole location to obtain borehole data. Based on the borehole data and the number of initial clusters, iterative clustering and hierarchical interpolation are performed on the multiple borehole locations to generate a borehole data distribution map of the target area. This distribution map includes sub-regions containing the number of initial clusters. For each sub-region, the minimum rock stratum thickness is found from the borehole data distribution map, and this minimum thickness is used as a dividing unit. Hierarchical three-dimensional modeling and integration are performed on the sub-region to obtain a sub-region three-dimensional geological model. Finally, all sub-region three-dimensional geological models are integrated to obtain a three-dimensional geological model of the target area. A grouting scheme is then generated based on this target area's three-dimensional geological model. Compared with existing technologies, the embodiments of this application first use gravity maps as guidance for drilling and collecting borehole point data. Since the gravity map comprehensively displays the underground density distribution and anomalous areas of the target area, the data collection process can be targeted, improving the comprehensiveness and efficiency of data collection. Furthermore, based on the decreasing number of clusters, iterative clustering is performed according to the location of the borehole points, gravity and other multi-source data. After each round of clustering, interpolation is performed within the sub-region to complete the hierarchical interpolation. By merging sub-regions step by step, the local high-precision model is gradually integrated, ensuring a smooth transition while reducing the risk of weakening local abrupt features. Finally, within each sub-region after completing the hierarchical interpolation, the minimum rock layer thickness is used as the dividing unit for hierarchical 3D modeling and layer-by-layer integration. This makes the final 3D geological model closer to the actual geological conditions, achieving accurate characterization of the geological structure and accurate representation of the spatial location of high permeability gradient zones and key leakage channels. This provides a reliable basis for grouting design and ensures the long-term safe operation of the project.

[0090] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0091] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0092] Figure 1 This paper presents a flowchart of a three-dimensional geological modeling method for a hydropower station grouting project according to an embodiment of this application.

[0093] Figure 2 This paper presents a flowchart of another three-dimensional geological modeling method for grouting engineering in hydropower stations, as provided in an embodiment of this application.

[0094] Figure 3 This illustration shows a schematic diagram of vertical stratigraphic division provided in an embodiment of this application;

[0095] Figure 4 This paper shows a block diagram of a three-dimensional geological modeling device for a hydropower station grouting project, as provided in an embodiment of this application.

[0096] Figure 5 A schematic diagram of the structure of a terminal provided in an embodiment of this application is shown. Detailed Implementation

[0097] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0098] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0099] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0100] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0101] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0102] The embodiments of this application can be applied to computer systems / servers that can operate with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations suitable for use with computer systems / servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems, etc.

[0103] Computer systems / servers can be described in the general context of computer system executable instructions (such as program modules) executed by the computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are performed by remote processing devices linked through a communication network. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0104] This application provides a three-dimensional geological modeling method for grouting engineering in hydropower stations, such as... Figure 1 As shown, the method includes:

[0105] 101. Obtain the gravity field map of the target area. Based on the gravity field map, determine multiple drilling points in the target area, and collect rock strata and locate the location at each drilling point to obtain the drilling point data of each drilling point.

[0106] The gravity field map is used to display the underground density distribution and anomalous areas of the target area, and can serve as a basis for selecting borehole locations. The borehole data includes at least borehole location information, gravity information, and rock strata information. In this embodiment, the current execution terminal can be the grouting scheme generation module for a hydropower station.

[0107] It should be noted that when determining the drilling locations, at least two boreholes must be arranged in the gravity anomaly area to ensure construction feasibility and safety.

[0108] 102. Based on the data of each borehole point and the number of clusters in the first round, iterative clustering and hierarchical interpolation are performed on multiple borehole points to generate a distribution map of borehole point data in the target area.

[0109] The borehole point data distribution map includes a sub-region containing the number of clusters in the first round. The number of clusters in the first round can be calculated based on the gravity mutation situation of the target region. The number of clusters used in each round of iterative clustering is obtained by subtracting 1 from the number of clusters in the first round in each round. This is to achieve the step-by-step fusion of the high-precision model of the sub-region. After each round of clustering is completed, interpolation is performed within the sub-region. Through hierarchical interpolation, a smooth transition is ensured while reducing the risk of weakening local mutation features.

[0110] 103. For each sub-region, find the minimum rock layer thickness from the borehole point data distribution map, and use the minimum rock layer thickness as the dividing unit to perform layered 3D modeling and integration processing on the sub-region to obtain the sub-region 3D geological model, and integrate all the sub-region 3D geological models to obtain the target region 3D geological model, and generate a grouting scheme based on the target region 3D geological model.

[0111] Among them, layered 3D modeling means dividing the rock strata into multiple layers using the minimum rock stratum thickness as the dividing unit, and performing 3D modeling on each layer; integration processing means integrating the 3D models of each layer to obtain the 3D geological model of the sub-region.

[0112] Compared with existing technologies, the embodiments of this application first use gravity maps as guidance for drilling and collecting borehole point data. Since the gravity map comprehensively displays the underground density distribution and anomalous areas of the target area, the data collection process can be targeted, improving the comprehensiveness and efficiency of data collection. Furthermore, based on the decreasing number of clusters, iterative clustering is performed according to the location of the borehole points, gravity and other multi-source data. After each round of clustering, interpolation is performed within the sub-region to complete the hierarchical interpolation. By merging sub-regions step by step, the local high-precision model is gradually integrated, ensuring a smooth transition while reducing the risk of weakening local abrupt features. Finally, within each sub-region after completing the hierarchical interpolation, the minimum rock layer thickness is used as the dividing unit for hierarchical 3D modeling and layer-by-layer integration. This makes the final 3D geological model closer to the actual geological conditions, achieving accurate characterization of the geological structure and accurate representation of the spatial location of high permeability gradient zones and key leakage channels. This provides a reliable basis for grouting design and ensures the long-term safe operation of the project.

[0113] This application provides another method for three-dimensional geological modeling of hydropower station grouting projects, such as... Figure 2 As shown, the method includes:

[0114] 201. Obtain the gravity field map of the target area.

[0115] Accordingly, step 201 of the embodiment specifically includes: acquiring geological data and topographic data of the target area; determining multiple gravity measurement points within the target area based on the geological data and topographic data; using a gravity measuring instrument to perform gravity measurements and location positioning at each gravity measurement point to obtain gravity data and gravity measurement point location information at each gravity measurement point; filtering out gravity data that exceeds a preset gravity fluctuation range from multiple gravity data as abnormal gravity data; for each abnormal gravity data, arranging new gravity measurement points around the gravity measurement point corresponding to the abnormal gravity data, and performing gravity measurements and location positioning at each new gravity measurement point to obtain gravity data and gravity measurement point location information at each new gravity measurement point, which are used as new gravity data and new gravity measurement point location information; generating a gravity field map of the target area based on each gravity data and corresponding gravity measurement point location information, and each new gravity data and corresponding new gravity measurement point location information.

[0116] In this embodiment, firstly, existing geological and topographic data of the target area are acquired. Further, based on the existing data, gravity measurement points are deployed in areas with flat, stable terrain and far from human interference. For areas with complex geology or requiring focused analysis, a spacing of 20 to 50 meters is used; for areas with relatively uniform geology or large-scale exploration areas, a spacing of 50 to 100 meters is used. Further, using a gravity measuring instrument, gravity measurements and location information are performed at each gravity measurement point to obtain gravity data and location information at each point. During the measurement process, if gravity data exceeding the preset gravity fluctuation range is identified, it is considered abnormal gravity data. New gravity measurement points are then set up around the gravity measurement points corresponding to the abnormal gravity data. Gravity measurements and location are performed at each new gravity measurement point to obtain the gravity data and gravity measurement point location information at each new gravity measurement point. Finally, based on the gravity data of all points (including the initially determined and new points) and the corresponding gravity measurement point location information, a gravity field map of the target area is generated.

[0117] 202. Based on the gravity field map, multiple borehole locations are determined within the target area, and rock strata are collected and their locations are determined at each borehole location to obtain borehole data for each location.

[0118] Step 202 of the embodiment can be referred to in the detailed description of step 101 of the aforementioned embodiment, and will not be repeated here.

[0119] 203. Calculate the number of clusters in the first round of clustering in the target region.

[0120] Accordingly, step 203 of the embodiment specifically includes: checking whether there is a gravity abrupt change region in the gravity site map; if there is no gravity abrupt change region, calculating the number of clusters in the first round of the target region based on the linear cluster decay function; if there is a gravity abrupt change region, and the abrupt change characteristics of the gravity abrupt change region conform to the isolated abrupt change characteristics, calculating the number of clusters in the first round of the target region based on the fast nonlinear cluster decay function; if there is a gravity abrupt change region, and the abrupt change characteristics of the gravity abrupt change region conform to the contiguous abrupt change characteristics, calculating the number of clusters in the first round of the target region based on the robust nonlinear cluster decay function.

[0121] Formula 1:

[0122] ,

[0123] in, Let x represent the number of clusters in the x-th cluster, and n represent the total number of boreholes. The strength parameter of the cluster decay function at the xth iteration ( ), This represents the total number of iterations for clustering;

[0124] Formula 2:

[0125] ,

[0126] Indicates the current clustering round;

[0127] Formula 3:

[0128] ,

[0129] Formula 4:

[0130] .

[0131] In this embodiment, the linear cluster decay function is composed of Formula 1 and Formula 2 above; the fast nonlinear cluster decay function is composed of Formula 1 and Formula 3 above; and the robust nonlinear cluster decay function is composed of Formula 1 and Formula 4 above.

[0132] It should be noted that gravity abrupt change regions are used to characterize drastic changes in the gravity field value within a region, which can manifest as abnormally dense contour lines on the gravity field map, a significant increase in gradient values, or the appearance of isolated anomalous extreme points; isolated abrupt change features are used to characterize the presence of small, dense, and isolated peaks or troughs; and contiguous abrupt change features are used to characterize large-scale, contiguous anomalous regions.

[0133] 204. Based on the data of each borehole point and the number of clusters in the first round, perform the first round of clustering on multiple borehole points to obtain the first round of sub-regions with the number of clusters in the first round.

[0134] The borehole data includes borehole location information and gravity information.

[0135] Accordingly, step 204 of the embodiment specifically includes: normalizing the location information of each borehole point and the gravity information to obtain normalized borehole point data for each borehole point; randomly selecting borehole points from multiple borehole points as initial cluster centers; calculating the Euclidean distance between the normalized borehole point data of each borehole point and the normalized borehole point data of each initial cluster center, and assigning the borehole points to the clusters to which the initial cluster centers corresponding to the smallest Euclidean distance belong, thus obtaining multiple initial clusters; recalculating the current cluster center for each initial cluster based on the normalized borehole point data of each borehole point included in the initial cluster; iteratively performing cluster division and cluster center update until the minimum objective function converges, obtaining the final clusters and corresponding final cluster centers of the first round of clustering, thus completing the first round of clustering processing and obtaining the first round of sub-regions of the first round of clustering.

[0136] ,

[0137] Where K represents the number of clusters, This represents the k-th cluster. Indicates the first Drilling point data for each drilling point With cluster center The Euclidean distance.

[0138] In this embodiment, the borehole location information and gravity information are first normalized to reduce the risk of errors caused by different magnitudes. Further, from multiple borehole locations, the number of borehole locations selected for the first round of clustering is randomly chosen as the initial cluster centers. Further, for each borehole location, the Euclidean distance between the normalized borehole data of that location and the normalized borehole data of each initial cluster center is calculated according to the following formula.

[0139] ,

[0140] in, Indicates the initial cluster centers ( (K represents the number of clusters in the first round). This represents the borehole data for the j-th borehole location;

[0141] The borehole locations are then assigned to the clusters corresponding to the initial cluster centers with the minimum Euclidean distance, resulting in multiple initial clusters. Further, based on the normalized borehole point data of each borehole location included in the initial clusters, the current cluster centers are recalculated using the following formula.

[0142] ,

[0143] ,

[0144] in, This represents the borehole point data of the i-th borehole point contained in the initial cluster. This represents the theoretical value of the current cluster center. This represents the actual value of the current cluster center. This indicates the number of borehole locations within a cluster;

[0145] The clustering process iteratively divides the clusters and updates the cluster centers until the minimum objective function described below converges. This yields the final clusters and their corresponding final cluster centers for the first round of clustering, completing the first round of clustering and obtaining the first round of sub-regions.

[0146] .

[0147] 205. Perform interpolation processing in each first-round sub-region to obtain the first-round interpolation result.

[0148] The first round of interpolation results includes data on multiple borehole locations and multiple borehole points from the first round of interpolation.

[0149] Accordingly, step 205 of the embodiment specifically includes: for each final cluster, obtaining the location information of the point to be interpolated; calculating the Euclidean distance between the location information of the point to be interpolated and the location information of each borehole point in the final cluster; and calculating the borehole point data of the point to be interpolated based on the Euclidean distance and the borehole point data of each borehole point, using the inverse distance interpolation formula, wherein the inverse distance interpolation formula is expressed as follows:

[0150] ,

[0151] Indicates the point to be interpolated Drilling point data, This represents the Euclidean distance between the location information of the point to be interpolated and the location information of the borehole points in the final cluster. Indicates the th in the final cluster Drilling point data for each drilling point location. This indicates the number of borehole locations in a cluster.

[0152] In this embodiment of the application, for each final cluster, the location information of the points to be interpolated is first determined; further, the Euclidean distance between the location information of the points to be interpolated and the location information of each borehole point in the final cluster is calculated respectively.

[0153] ,

[0154] in, This represents the borehole point data indicating the location to be interpolated.

[0155] Furthermore, based on the Euclidean distances and borehole data for each borehole location, the borehole data for the point to be interpolated is calculated using the inverse distance interpolation formula, which is expressed as follows:

[0156] .

[0157] 206. Subtract 1 from the number of clusters in the first round to obtain the number of clusters in the second round. Based on the interpolation results of the first round and the number of clusters in the second round, perform second-round clustering on multiple borehole locations and multiple first-round interpolation locations to obtain the second-round sub-regions of the second-round clusters. Perform interpolation on each second-round sub-region to obtain the second-round interpolation results. Perform iterative clustering and hierarchical interpolation until the number of clusters is reduced to 1. Perform global interpolation to obtain the global interpolation results.

[0158] The second-round interpolation results include borehole point data from multiple borehole locations, multiple first-round interpolation locations, and multiple second-round interpolation locations.

[0159] In this embodiment, the number of clusters in the first round is reduced by 1 to obtain the number of clusters in the second round. Based on the interpolation results of the first round and the number of clusters in the second round, a second round of clustering is performed on multiple borehole locations and multiple first-round interpolation locations to obtain the second-round sub-regions of the second-round clusters. Interpolation is then performed in each of the second-round sub-regions to obtain the second-round interpolation results. The number of clusters in the second round is reduced by 1 to obtain the number of clusters in the third round. Based on the interpolation results of the second round and the number of clusters in the third round, a second round of clustering is performed on multiple borehole locations, multiple first-round interpolation locations, and multiple second-round interpolation locations to obtain the third-round sub-regions of the third-round sub-regions. Interpolation is then performed in each of the third-round sub-regions to obtain the third-round interpolation results. This process is repeated iteratively, performing iterative clustering and hierarchical interpolation until the number of clusters is reduced to 1. Finally, global interpolation is performed to obtain the global interpolation results.

[0160] 207. Based on the number of clusters in the first round, perform clustering processing on the global interpolation results to obtain sub-regions with the number of clusters in the first round, so as to generate a distribution map of borehole point data in the target area.

[0161] The borehole point data distribution map includes multiple sub-regions generated after multiple rounds of iterative clustering and hierarchical interpolation. Each sub-region contains multiple borehole point data (including borehole locations and interpolation locations). The borehole point data includes borehole location information, gravity information, and rock strata information.

[0162] 208. For each sub-region, find the minimum rock layer thickness from the borehole point data distribution map, and use the minimum rock layer thickness as the dividing unit to perform layered 3D modeling and integration processing on the sub-region to obtain the sub-region 3D geological model.

[0163] Accordingly, step 208 of the embodiment specifically includes: for each sub-region, finding the minimum rock layer thickness in the sub-region from the borehole point data distribution map, and using the minimum rock layer thickness as the dividing unit; based on the dividing unit, dividing the sub-region into vertical strata to obtain multiple layers; based on the Kriging interpolation method, performing three-dimensional modeling on each layer to obtain multiple layered three-dimensional geological models to complete the layered three-dimensional modeling for the sub-region; and integrating all layered three-dimensional geological models to obtain the sub-region three-dimensional geological model of the sub-region to complete the integration process.

[0164] In this embodiment of the application, for each sub-region, the minimum rock layer thickness within the sub-region is first found from the borehole point data distribution map, and this thickness is used as a dividing unit to vertically divide the sub-region into multiple layers, such as... Figure 3 As shown; further, based on the Kriging interpolation method, three-dimensional modeling is performed on each layer to obtain multiple layered three-dimensional geological models; finally, all layered three-dimensional geological models are integrated to obtain a sub-regional three-dimensional geological model.

[0165] 209. Integrate all sub-region three-dimensional geological models to obtain the target region's three-dimensional geological model, and generate a grouting scheme based on the target region's three-dimensional geological model.

[0166] In this embodiment of the application, the three-dimensional geological models of all sub-regions are stitched together to obtain the three-dimensional geological model of the target region.

[0167] This application provides a three-dimensional geological modeling method for grouting engineering in hydropower stations. First, a gravity field map of the target area is obtained. Based on the gravity field map, multiple borehole locations are determined within the target area, and rock strata are collected and their locations are determined at each borehole location to obtain borehole data. Based on the borehole data and the number of initial clusters, iterative clustering and hierarchical interpolation are performed on the multiple borehole locations to generate a borehole data distribution map of the target area. This distribution map includes sub-regions containing the number of initial clusters. For each sub-region, the minimum rock stratum thickness is found from the borehole data distribution map, and this minimum thickness is used as a dividing unit. Hierarchical three-dimensional modeling and integration are performed on the sub-region to obtain a sub-region three-dimensional geological model. Finally, all sub-region three-dimensional geological models are integrated to obtain a three-dimensional geological model of the target area. A grouting scheme is then generated based on this three-dimensional geological model of the target area. Compared with existing technologies, the embodiments of this application first use gravity maps as guidance for drilling and collecting borehole point data. Since the gravity map comprehensively displays the underground density distribution and anomalous areas of the target area, the data collection process can be targeted, improving the comprehensiveness and efficiency of data collection. Furthermore, based on the decreasing number of clusters, iterative clustering is performed according to the location of the borehole points, gravity and other multi-source data. After each round of clustering, interpolation is performed within the sub-region to complete the hierarchical interpolation. By merging sub-regions step by step, the local high-precision model is gradually integrated, ensuring a smooth transition while reducing the risk of weakening local abrupt features. Finally, within each sub-region after completing the hierarchical interpolation, the minimum rock layer thickness is used as the dividing unit for hierarchical 3D modeling and layer-by-layer integration. This makes the final 3D geological model closer to the actual geological conditions, achieving accurate characterization of the geological structure and accurate representation of the spatial location of high permeability gradient zones and key leakage channels. This provides a reliable basis for grouting design and ensures the long-term safe operation of the project.

[0168] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this application provides a three-dimensional geological modeling device for grouting engineering in hydropower stations, such as... Figure 4 As shown, the device includes:

[0169] Drilling point data acquisition module 31, drilling point data distribution map generation module 32, 3D modeling module 33;

[0170] The borehole data acquisition module 31 is used to acquire a gravity field map of the target area, determine multiple borehole locations within the target area based on the gravity field map, and collect rock strata and locate the location at each of the borehole locations to obtain borehole data for each of the borehole locations.

[0171] The borehole point data distribution map generation module 32 is used to perform iterative clustering and hierarchical interpolation processing on the multiple borehole points based on the data of each borehole point and the number of clusters in the first round, to generate a borehole point data distribution map of the target area, wherein the borehole point data distribution map includes a sub-region of the number of clusters in the first round.

[0172] The 3D modeling module 33 is used to find the minimum rock layer thickness from the borehole point data distribution map for each sub-region, and use the minimum rock layer thickness as a dividing unit to perform layered 3D modeling and integration processing on the sub-region to obtain the sub-region 3D geological model, and to integrate all the sub-region 3D geological models to obtain the target region 3D geological model, so as to generate a grouting scheme based on the target region 3D geological model.

[0173] In specific application scenarios, the borehole point data distribution map generation module includes:

[0174] A clustering unit is used to perform a first-round clustering process on the multiple borehole locations based on the data of each borehole point and the number of first-round clusters, to obtain the first-round sub-regions with the number of first-round clusters.

[0175] An interpolation unit is used to perform interpolation processing in each of the first-round sub-regions to obtain the first-round interpolation result, wherein the first-round interpolation result includes multiple drilling points and drilling point data of multiple first-round interpolation points;

[0176] An iterative unit is used to subtract 1 from the number of clusters in the first round to obtain the number of clusters in the second round. Based on the interpolation result of the first round and the number of clusters in the second round, the unit performs second-round clustering processing on the multiple borehole locations and the multiple first-round interpolation locations to obtain the second-round sub-regions of the number of clusters in the second round. Interpolation processing is performed in each of the second-round sub-regions to obtain the second-round interpolation result. Iterative clustering processing and hierarchical interpolation processing are performed until the number of clusters is reduced to 1. Global interpolation processing is then performed to obtain the global interpolation result. The second-round interpolation result includes borehole point data of multiple borehole locations, multiple first-round interpolation locations, and multiple second-round interpolation locations.

[0177] The borehole point data distribution map generation unit is used to perform clustering processing on the global interpolation result based on the number of clusters in the first round, to obtain a sub-region with the number of clusters in the first round, so as to generate a borehole point data distribution map of the target region.

[0178] In specific application scenarios, the borehole point data includes borehole point location information and gravity information, and the clustering unit is used for:

[0179] The location information of each borehole point and the gravity information are normalized respectively to obtain normalized borehole point data for each borehole point.

[0180] From the multiple borehole locations, the number of borehole locations selected in the first round of clustering is randomly chosen as the initial cluster centers;

[0181] For each borehole location, the normalized borehole point data of the borehole location is calculated, and the Euclidean distance between the normalized borehole point data of each initial cluster center is calculated. The borehole location is then assigned to the cluster of the initial cluster center corresponding to the smallest Euclidean distance, resulting in multiple initial clusters.

[0182] For each initial cluster, the current cluster center is recalculated based on the normalized borehole point data of each borehole point contained in the initial cluster.

[0183] The clustering process iteratively divides the clusters and updates the cluster centers until the minimum objective function described below converges, obtaining the final clusters and corresponding final cluster centers of the first-round cluster count, thus completing the first round of clustering and obtaining the first-round sub-regions of the first-round cluster count.

[0184] ,

[0185] Where K represents the number of clusters, This represents the k-th cluster. Indicates the first Drilling point data for each drilling point With cluster center The Euclidean distance.

[0186] In specific application scenarios, the interpolation unit is used for:

[0187] For each final cluster, obtain the location information of the points to be interpolated;

[0188] Calculate the Euclidean distance between the location information of the point to be interpolated and the location information of each borehole point in the final cluster;

[0189] Based on the Euclidean distances and the borehole data for each borehole location, the borehole data for the point to be interpolated is calculated using the inverse distance interpolation formula, wherein the inverse distance interpolation formula is expressed as follows:

[0190] ,

[0191] Indicates the point to be interpolated Drilling point data, This represents the Euclidean distance between the location information of the point to be interpolated and the location information of the borehole points in the final cluster. Indicates the th in the final cluster Drilling point data for each drilling point location. This indicates the number of borehole locations in the final cluster.

[0192] In specific application scenarios, the 3D modeling module is used for:

[0193] For each sub-region, the minimum rock layer thickness within the sub-region is found from the borehole point data distribution map, and the minimum rock layer thickness is used as the dividing unit;

[0194] Based on the division unit, the sub-region is vertically divided into multiple layers.

[0195] Based on the Kriging interpolation method, three-dimensional modeling is performed on each of the aforementioned layers to obtain multiple layered three-dimensional geological models, thereby completing the layered three-dimensional modeling of the sub-region.

[0196] By integrating all the aforementioned layered three-dimensional geological models, a sub-regional three-dimensional geological model of the sub-region is obtained to complete the integration process.

[0197] In specific application scenarios, before the borehole point data distribution map generation module, the device further includes a first-round cluster count calculation module, used for:

[0198] Check if there are any regions of sudden gravity changes in the gravity field map;

[0199] If there is no region of sudden gravity change, the number of clusters in the first round of the target region is calculated based on the linear cluster decay function;

[0200] If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the isolated mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the fast nonlinear cluster decay function.

[0201] If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the contiguous mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the robust nonlinear cluster decay function.

[0202] In specific application scenarios, the borehole point data acquisition module is used for:

[0203] Acquire geological and topographic data for the target area;

[0204] Based on the geological data and the topographic data, multiple gravity measurement points are determined within the target area;

[0205] Using a gravity measuring instrument, gravity measurements and location positioning are performed at each gravity measurement point to obtain gravity data and gravity measurement point location information at each gravity measurement point.

[0206] Gravity data that exceeds the preset gravity fluctuation range is selected from multiple gravity data and designated as abnormal gravity data.

[0207] For each abnormal gravity data point, new gravity measurement points are arranged around the gravity measurement point corresponding to the abnormal gravity data point, and gravity measurements and location are performed at each of the new gravity measurement points to obtain the gravity data and gravity measurement point location information at each new gravity measurement point, which are used as the new gravity data and new gravity measurement point location information.

[0208] Based on the gravity data and the corresponding gravity measurement point location information, as well as the newly added gravity data and the corresponding newly added gravity measurement point location information, a gravity field map of the target area is generated.

[0209] This application provides a three-dimensional geological modeling device for grouting engineering in hydropower stations. First, a gravity field map of the target area is acquired. Based on the gravity field map, multiple borehole locations are determined within the target area, and rock strata are collected and their locations are determined at each borehole location to obtain borehole data. Based on the borehole data and the number of initial clusters, iterative clustering and hierarchical interpolation are performed on the multiple borehole locations to generate a borehole data distribution map of the target area. This distribution map includes sub-regions containing the number of initial clusters. For each sub-region, the minimum rock stratum thickness is found from the borehole data distribution map, and this minimum thickness is used as a dividing unit. Hierarchical three-dimensional modeling and integration are performed on the sub-region to obtain a sub-region three-dimensional geological model. Finally, all sub-region three-dimensional geological models are integrated to obtain a three-dimensional geological model of the target area. A grouting scheme is then generated based on this target area's three-dimensional geological model. Compared with existing technologies, the embodiments of this application first use gravity maps as guidance for drilling and collecting borehole point data. Since the gravity map comprehensively displays the underground density distribution and anomalous areas of the target area, the data collection process can be targeted, improving the comprehensiveness and efficiency of data collection. Furthermore, based on the decreasing number of clusters, iterative clustering is performed according to the location of the borehole points, gravity and other multi-source data. After each round of clustering, interpolation is performed within the sub-region to complete the hierarchical interpolation. By merging sub-regions step by step, the local high-precision model is gradually integrated, ensuring a smooth transition while reducing the risk of weakening local abrupt features. Finally, within each sub-region after completing the hierarchical interpolation, the minimum rock layer thickness is used as the dividing unit for hierarchical 3D modeling and layer-by-layer integration. This makes the final 3D geological model closer to the actual geological conditions, achieving accurate characterization of the geological structure and accurate representation of the spatial location of high permeability gradient zones and key leakage channels. This provides a reliable basis for grouting design and ensures the long-term safe operation of the project.

[0210] According to one embodiment of this application, a storage medium is provided, the storage medium storing at least one executable instruction, the computer-executable instruction being able to execute the three-dimensional geological modeling method for hydropower station grouting engineering in any of the above method embodiments.

[0211] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0212] Figure 5The diagram shows a structural schematic of a terminal according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the terminal.

[0213] like Figure 5 As shown, the terminal may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0214] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408.

[0215] Communication interface 404 is used to communicate with other network elements such as clients or other servers.

[0216] The processor 402 is used to execute program 410, specifically to execute the relevant steps in the above-mentioned embodiment of the three-dimensional geological modeling method for hydropower station grouting project.

[0217] Specifically, program 410 may include program code that includes computer operation instructions.

[0218] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0219] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0220] Specifically, program 410 can be used to cause processor 402 to perform the following operations:

[0221] Obtain a gravity field map of the target area. Based on the gravity field map, determine multiple borehole locations within the target area. Collect rock strata and locate the location at each of the borehole locations to obtain borehole data for each of the borehole locations.

[0222] Based on the data of each borehole point and the number of clusters in the first round, iterative clustering and hierarchical interpolation are performed on the multiple borehole points to generate a borehole point data distribution map of the target area, wherein the borehole point data distribution map includes a sub-region containing the number of clusters in the first round.

[0223] For each sub-region, the minimum rock layer thickness is found from the borehole point data distribution map, and the minimum rock layer thickness is used as the dividing unit. The sub-region is then subjected to layered three-dimensional modeling and integration processing to obtain the sub-region three-dimensional geological model. All the sub-region three-dimensional geological models are then integrated to obtain the three-dimensional geological model of the target region. A grouting scheme is then generated based on the three-dimensional geological model of the target region.

[0224] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the physical device for the aforementioned three-dimensional geological modeling method for hydropower station grouting projects, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0225] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0226] The methods and systems of this application may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this application are not limited to the order specifically described above, unless otherwise specifically stated. Furthermore, in some embodiments, this application may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this application. Thus, this application also covers recording media storing programs for performing the methods according to this application.

[0227] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0228] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A three-dimensional geological modeling method for grouting engineering in hydropower stations, characterized in that, include: Obtain a gravity field map of the target area. Based on the gravity field map, determine multiple borehole locations within the target area. Collect rock strata and locate the location at each of the borehole locations to obtain borehole data for each of the borehole locations. Based on the data of each borehole point and the number of clusters in the first round, iterative clustering and hierarchical interpolation are performed on the multiple borehole points to generate a borehole point data distribution map of the target area, wherein the borehole point data distribution map includes a sub-region containing the number of clusters in the first round. For each sub-region, the minimum rock layer thickness is found from the borehole point data distribution map, and the minimum rock layer thickness is used as the dividing unit. The sub-region is then subjected to layered three-dimensional modeling and integration processing to obtain the sub-region three-dimensional geological model. All the sub-region three-dimensional geological models are then integrated to obtain the three-dimensional geological model of the target region. A grouting scheme is then generated based on the three-dimensional geological model of the target region. Before generating the borehole point data distribution map of the target area by iteratively clustering and hierarchical interpolation of the multiple borehole points based on the data of each borehole point and the number of clusters in the first round, the method further includes: Check if there are any regions of sudden gravity changes in the gravity field map; If there is no region of sudden gravity change, the number of clusters in the first round of the target region is calculated based on the linear cluster decay function; If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the isolated mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the fast nonlinear cluster decay function. If a gravity mutation region exists, and the mutation characteristics of the gravity mutation region conform to the contiguous mutation characteristics, then the number of clusters in the first round of the target region is calculated based on the robust nonlinear cluster decay function.

2. The three-dimensional geological modeling method for hydropower station grouting projects according to claim 1, characterized in that, The step involves iterative clustering and hierarchical interpolation of the multiple borehole locations based on the data of each borehole point and the number of clusters in the first round of clustering, to generate a borehole point data distribution map of the target area, including: Based on the data of each borehole point and the number of clusters in the first round, the multiple borehole points are subjected to the first round of clustering to obtain the first round sub-regions of the first round clusters. Interpolation is then performed in each of the first round sub-regions to obtain the first round interpolation result. The first round interpolation result includes the data of the multiple borehole points and the data of the multiple first round interpolation points. The number of clusters in the first round is reduced by 1 to obtain the number of clusters in the second round. Based on the interpolation result of the first round and the number of clusters in the second round, the multiple borehole locations and the multiple interpolation points in the first round are subjected to the second round clustering process to obtain the second round sub-regions of the number of clusters in the second round. Interpolation processing is performed in each of the second round sub-regions to obtain the second round interpolation result. Iterative clustering processing and hierarchical interpolation processing are performed until the number of clusters is reduced to 1. Global interpolation processing is then performed to obtain the global interpolation result. The second round interpolation result contains the borehole point data of multiple borehole locations, multiple interpolation points in the first round, and multiple interpolation points in the second round. Based on the number of clusters in the first round, the global interpolation results are clustered to obtain sub-regions containing the number of clusters in the first round, thereby generating a borehole point data distribution map of the target region.

3. The three-dimensional geological modeling method for hydropower station grouting projects according to claim 2, characterized in that, The borehole point data includes borehole point location information and gravity information. Based on the borehole point data and the number of initial clusters, the multiple borehole points are subjected to initial clustering processing to obtain the first-round sub-regions, including: The location information of each borehole point and the gravity information are normalized respectively to obtain normalized borehole point data for each borehole point. From the multiple borehole locations, the number of borehole locations selected in the first round of clustering is randomly chosen as the initial cluster centers; For each borehole location, the normalized borehole point data of the borehole location is calculated, and the Euclidean distance between the normalized borehole point data of each initial cluster center is calculated. The borehole location is then assigned to the cluster of the initial cluster center corresponding to the smallest Euclidean distance, resulting in multiple initial clusters. For each initial cluster, the current cluster center is recalculated based on the normalized borehole point data of each borehole point contained in the initial cluster. The clustering process iteratively divides the clusters and updates the cluster centers until the minimum objective function described below converges, obtaining the final clusters and corresponding final cluster centers of the first-round cluster count, thus completing the first round of clustering and obtaining the first-round sub-regions of the first-round cluster count. ， Where K represents the number of clusters, This represents the k-th cluster. Indicates the first Drilling point data for each drilling point With cluster center The Euclidean distance.

4. The three-dimensional geological modeling method for hydropower station grouting projects according to claim 3, characterized in that, The interpolation process performed in each of the first-round sub-regions to obtain the first-round interpolation result includes: For each final cluster, obtain the location information of the points to be interpolated; Calculate the Euclidean distance between the location information of the point to be interpolated and the location information of each borehole point in the final cluster; Based on the Euclidean distances and the borehole data for each borehole location, the borehole data for the point to be interpolated is calculated using the inverse distance interpolation formula, wherein the inverse distance interpolation formula is expressed as follows: ， Indicates the point to be interpolated Drilling point data, This represents the Euclidean distance between the location information of the point to be interpolated and the location information of the borehole points in the final cluster. Indicates the th in the final cluster Drilling point data for each drilling location. This indicates the number of borehole locations in the final cluster.

5. The three-dimensional geological modeling method for hydropower station grouting projects according to claim 1, characterized in that, For each sub-region, the minimum rock layer thickness is found from the borehole point data distribution map, and this minimum rock layer thickness is used as a dividing unit to perform layered 3D modeling and integration processing on the sub-region, resulting in a sub-region 3D geological model, including: For each sub-region, the minimum rock layer thickness within the sub-region is found from the borehole point data distribution map, and the minimum rock layer thickness is used as the dividing unit; Based on the division unit, the sub-region is vertically divided into multiple layers. Based on the Kriging interpolation method, three-dimensional modeling is performed on each of the aforementioned layers to obtain multiple layered three-dimensional geological models, thereby completing the layered three-dimensional modeling of the sub-region. By integrating all the aforementioned layered three-dimensional geological models, a sub-regional three-dimensional geological model of the sub-region is obtained to complete the integration process.

6. The three-dimensional geological modeling method for hydropower station grouting projects according to claim 1, characterized in that, The acquisition of the gravity field map of the target area includes: Acquire geological and topographic data for the target area; Based on the geological data and the topographic data, multiple gravity measurement points are determined within the target area; Using a gravity measuring instrument, gravity measurements and location positioning are performed at each gravity measurement point to obtain gravity data and gravity measurement point location information at each gravity measurement point. Gravity data that exceeds the preset gravity fluctuation range is selected from multiple gravity data and designated as abnormal gravity data. For each abnormal gravity data point, new gravity measurement points are arranged around the gravity measurement point corresponding to the abnormal gravity data point, and gravity measurements and location are performed at each of the new gravity measurement points to obtain the gravity data and gravity measurement point location information at each new gravity measurement point, which are used as the new gravity data and new gravity measurement point location information. Based on the gravity data and the corresponding gravity measurement point location information, as well as the newly added gravity data and the corresponding newly added gravity measurement point location information, a gravity field map of the target area is generated.

7. A three-dimensional geological modeling device for grouting engineering in hydropower stations, characterized in that, include: The borehole point data acquisition module is used to acquire a gravity field map of the target area, determine multiple borehole points in the target area based on the gravity field map, and collect rock strata and locate the position at each of the borehole points to obtain borehole point data for each of the borehole points. The borehole point data distribution map generation module is used to perform iterative clustering and hierarchical interpolation processing on the multiple borehole points based on the data of each borehole point and the number of clusters in the first round, to generate a borehole point data distribution map of the target area, wherein the borehole point data distribution map includes a sub-region of the number of clusters in the first round. The 3D modeling module is used to find the minimum rock layer thickness from the borehole point data distribution map for each sub-region, and use the minimum rock layer thickness as the dividing unit to perform layered 3D modeling and integration processing on the sub-region to obtain the sub-region 3D geological model, and to integrate all the sub-region 3D geological models to obtain the target region 3D geological model, so as to generate a grouting scheme based on the target region 3D geological model; Before the borehole point data distribution map generation module, the device further includes a first-round cluster number calculation module, used to find whether there is a gravity abrupt change region in the gravity site map; if there is no gravity abrupt change region, the first-round cluster number of the target region is calculated based on the linear cluster decay function; if there is a gravity abrupt change region, and the abrupt change characteristics of the gravity abrupt change region conform to the isolated abrupt change characteristics, the first-round cluster number of the target region is calculated based on the fast nonlinear cluster decay function; if there is a gravity abrupt change region, and the abrupt change characteristics of the gravity abrupt change region conform to the contiguous abrupt change characteristics, the first-round cluster number of the target region is calculated based on the robust nonlinear cluster decay function.

8. A storage medium storing at least one executable instruction, characterized in that, The executable instructions cause the processor to perform the operations corresponding to the three-dimensional geological modeling method for hydropower station grouting projects as described in any one of claims 1-6.

9. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, characterized in that the executable instruction causes the processor to perform the operation corresponding to the three-dimensional geological modeling method for hydropower station grouting project as described in any one of claims 1-6.

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