A tailings pond quasi-three-dimensional tomographic estimation method, device and apparatus

Abstract

This invention relates to the field of tailings dam model calculation, and provides a quasi-three-dimensional tomographic estimation method for tailings ponds, comprising the following steps: processing the digital elevation model of the tailings pond to construct a surface dynamic tomographic model of the tailings pond; reconstructing the base topographic model of the tailings pond; constructing a solid-surface hybrid model of the tailings pond based on the surface dynamic tomographic model and the base topographic model of the tailings pond; confirming the resource calculation range of the tailings pond based on the solid-surface hybrid model; dividing the tailings pond within the resource calculation range into multiple voxelized sections with equal elevation intervals; accumulating the ore resource quantity and valuable metal quantity in each voxelized section, and using the accumulated result as the resource quantity of the tailings pond, which can more rationally plan the discharge and storage of tailings, avoid over-discharge or under-storage of tailings due to inaccurate estimation, and thus reduce resource waste.

Description

Technical Field

[0001] This invention relates to the field of tailings dam model calculation, and in particular to a quasi-three-dimensional tomographic estimation method, apparatus and equipment for tailings dams. Background Technology

[0002] Tailings dams are critical facilities for storing and managing tailings generated during mining operations. Their capacity calculations play a vital role in the safe management, rational planning, and environmental impact assessment of tailings dams. Accurate capacity data provides a scientific basis for the daily operation of tailings dams, ensuring their safe operation and facilitating the rational planning of tailings discharge and storage to avoid resource waste and environmental pollution. However, using 3D calculation methods to determine tailings dam capacity presents numerous complex and challenging problems. These problems not only significantly increase the difficulty of the calculations but can also have a major impact on the accuracy and reliability of the results. For example, insufficient precision in data acquisition, the dynamic nature of terrain changes, and technical challenges in the 3D modeling process can all lead to deviations between the calculated results and the actual situation. Summary of the Invention

[0003] The purpose of this invention is to provide a quasi-three-dimensional tomographic estimation method, apparatus and equipment for tailings ponds, which enables accurate calculation of the mineral quantity in tailings ponds.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a quasi-three-dimensional tomographic estimation method for tailings ponds, comprising the following steps: processing the digital elevation model of the tailings pond to construct a surface dynamic tomographic model of the tailings pond; reconstructing the base topographic model of the tailings pond; constructing a solid-surface hybrid model of the tailings pond based on the surface dynamic tomographic model and the base topographic model of the tailings pond; confirming the resource calculation range of the tailings pond based on the solid-surface hybrid model; dividing the tailings pond within the resource calculation range into multiple voxelized sections with equal elevation intervals; accumulating the ore resource quantity and valuable metal quantity within each voxelized section, and using the accumulated result as the resource quantity of the tailings pond.

[0005] Furthermore, the processing of the digital elevation model of the tailings dam includes the following steps: obtaining a digital elevation model of the tailings dam with a first degree of accuracy through actual measurement using measuring equipment; laying out orthogonal profile lines along the accumulation axis of the digital elevation model at a first distance interval to construct a differential elevation grid of the digital elevation model; calculating the saturated water storage volume and effective porosity of each layer of the differential elevation grid layer by layer; and correlating the saturated water storage volume and effective porosity of each layer of the differential elevation grid with historical time.

[0006] Furthermore, the reconstruction of the base topographic model of the tailings dam includes the following steps: obtaining the original topographic map of the tailings dam or the exploration results of the tailings dam; reconstructing the original bedrock interface of the tailings dam based on the original topographic map of the tailings dam or the exploration results of the tailings dam to generate a continuous contour line model with a contour interval no greater than the second distance, and using the continuous contour line model as the base topographic model of the tailings dam.

[0007] Furthermore, the process of determining the resource calculation range of the tailings dam based on the entity-surface hybrid model includes: taking the lowest point of the bottom layer in the entity-surface hybrid model as the resource calculation starting point; taking the lowest point of the top layer in the entity-surface hybrid model as the resource calculation ending point; and taking the area between the vertical height of the tailings dam and the resource calculation starting point and the resource calculation ending point as the resource calculation range.

[0008] Furthermore, the method for calculating the ore resource quantity and valuable metal quantity within each voxel section is as follows: obtaining the volume of each voxelized section and the ore weight of each voxelized section; calculating the ore resource quantity of each voxelized section based on the volume of each voxelized section and the ore weight of each voxelized section; obtaining the metal grade of each voxelized section; and calculating the valuable metal quantity of each voxelized section based on the volume of each voxelized section and the metal grade of each voxelized section.

[0009] Furthermore, the volume of each voxelized section is the product of the area of ​​each voxelized section and the height of each voxelized section.

[0010] Furthermore, the height of each voxelized section is 0.5m-1.0m.

[0011] Furthermore, the exploration results include geological exploration borehole data, lithological boundary identification results of the tailings dam, and measurement results of the outer control points of the tailings dam.

[0012] On the other hand, a quasi-three-dimensional tomographic estimation device for tailings dams is provided, comprising: a surface model building mechanism for processing the digital elevation model of the tailings dam to construct a surface dynamic tomographic model of the tailings dam; a bottom model building mechanism for reconstructing the base topographic model of the tailings dam; a model fusion mechanism for constructing a solid-surface hybrid model of the tailings dam based on the surface dynamic tomographic model and the base topographic model of the tailings dam; a resource interval calculation mechanism for determining the resource calculation interval of the tailings dam based on the solid-surface hybrid model; a division mechanism for dividing the tailings dam within the resource calculation interval into multiple voxelized sections with equal elevation intervals; and a resource quantity calculation mechanism for accumulating the ore resource quantity and valuable metal quantity in each voxelized section, and using the accumulated result as the resource quantity of the tailings dam.

[0013] On the other hand, an electronic device is provided, comprising: a processor and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described estimation method.

[0014] Analysis shows that the present invention discloses a quasi-three-dimensional tomographic estimation method, apparatus and equipment for tailings ponds. By improving the accuracy of pond capacity calculation and resource estimation, it can more rationally plan the discharge and storage of tailings, avoid excessive discharge or insufficient storage of tailings due to inaccurate estimation, and thus reduce resource waste. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. Wherein: Figure 1 A flowchart of an embodiment of the present invention.

[0016] Figure 2 A schematic diagram of a tailings dam estimation model according to an embodiment of the present invention.

[0017] Figure 3 A simulation diagram of the original topography at the bottom of a tailings dam according to an embodiment of the present invention.

[0018] Figure 4 A three-dimensional simulation of the original topography at the bottom of a tailings dam according to an embodiment of the present invention.

[0019] Figure 5 A schematic diagram of contour lines interpolated within the slope of a tailings dam according to an embodiment of the present invention.

[0020] Figure 6 A schematic diagram of the 1022m-1048m section division of a tailings dam according to an embodiment of the present invention. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. Indeed, those skilled in the art will recognize that modifications and variations can be made to the invention without departing from its scope or spirit. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. Therefore, it is desirable that the invention encompass such modifications and variations falling within the scope of the appended claims and their equivalents.

[0022] In the description of this invention, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," and "bottom," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and do not require the invention to be constructed and operated in a specific orientation; therefore, they should not be construed as limitations on the invention. The terms "connected," "linked," and "set up" used in this invention should be interpreted broadly. For example, they can refer to a fixed connection or a detachable connection; a direct connection or an indirect connection through intermediate components; a wired connection, a radio connection, or a wireless communication signal connection. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0023] The accompanying drawings illustrate one or more examples of the invention. The detailed description uses numerals and letters to refer to features in the drawings. Similar or analogous reference numerals in the drawings and description have been used to refer to similar or analogous parts of the invention. As used herein, the terms “first,” “second,” “third,” and “fourth,” etc., are used interchangeably to distinguish one component from another and are not intended to indicate the location or importance of individual components.

[0024] like Figure 1 As shown in the embodiment of the present invention, a quasi-three-dimensional tomographic estimation method for tailings dams is provided, comprising the following steps: Step S1: Process the digital elevation model of the tailings dam to construct a surface dynamic tomographic model of the tailings dam; Step S2: Reconstruct the base topographic model of the tailings dam; Step S3: Construct a solid-surface hybrid model of the tailings dam based on the surface dynamic tomographic model and the base topographic model of the tailings dam; Step S4: Confirm the resource calculation range of the tailings dam based on the solid-surface hybrid model; Step S5: Divide the tailings dam within the resource calculation range into multiple voxelized sections with equal elevation intervals; Step S6: Accumulate the ore resource quantity and valuable metal quantity in each voxelized section, and use the accumulated result as the resource quantity of the tailings dam.

[0025] This application achieves multi-level, high-precision estimation of tailings dam resources through a quasi-three-dimensional tomographic model; the dynamic tomographic model adapts to the spatiotemporal changes of the tailings dam surface; the solid-surface hybrid model integrates the upper and lower boundaries, avoiding the simplification assumptions of traditional methods; and the voxelized cross-section division makes the calculation more detailed and the results more reliable.

[0026] In one embodiment of this application, step S1, processing the digital elevation model of the tailings dam includes the following steps: obtaining a digital elevation model of the tailings dam with a first precision through actual measurement using a measuring device; laying out orthogonal profile lines along the accumulation axis of the digital elevation model at a first distance interval to construct a differential elevation grid of the digital elevation model; calculating the saturated water storage volume and effective porosity of each layer of the differential elevation grid layer by layer; and correlating the saturated water storage volume and effective porosity of each layer of the differential elevation grid with historical time.

[0027] Specifically, a 0.1m high-precision elevation model is obtained based on aerial photogrammetry or total station measurements. The specific scale can be determined according to the actual size of the tailings dam, generally 1:1000. Orthogonal profile lines are laid out on the digital elevation model at 1-meter intervals along the tailings dam accumulation axis to construct a differential elevation grid. An irregular triangular mesh and voxelization fusion modeling method is adopted to calculate the saturated water storage volume and effective porosity of each layer unit layer by layer. Specifically, based on the differential elevation grid, the irregular triangular mesh (TIN) algorithm is first used to construct continuous triangular mesh models for the top and bottom surfaces of each layer unit to accurately characterize its undulating boundaries. Then, within the three-dimensional space defined by the upper and lower triangular mesh surfaces, voxelization is performed at a preset resolution (such as 0.5m×0.5m×0.1m) to generate a series of regularly arranged voxel sets, each voxel representing a minimum attribute calculation unit. This method preserves the geometric accuracy of the surface morphology while transforming continuous entities into discrete voxel sets with assignable attribute values ​​(such as saturated water storage volume, effective porosity, and metal grade), providing a structured data foundation for subsequent layer-by-layer calculations. The layered unit is the basic spatial unit for constructing the surface dynamic tomography model. It is a three-dimensional layered grid unit created by dividing a two-dimensional planar grid along the depositional axis using orthogonal profile lines, and then further dividing the grid vertically with a certain thickness (connecting with the height concept of subsequent voxelized sections, such as 0.5m-1.0m). It can be understood that the entire tailings dam surface is first cut into vertical "pillars," each of which is the initial layered unit used to calculate hydrological parameters. The introduction of a time dimension enables dynamic accumulation of reservoir capacity and correction for settlement deformation, significantly improving the accuracy of depicting the surface tailings distribution morphology and hydrological parameters. Specifically, the "introduction of the time dimension" is the key to achieving "dynamic" tomography in this invention. It encompasses two levels of meaning: first, data association, which involves associating the calculated saturated water storage volume, effective porosity, and other parameters of each stratified unit with their corresponding data acquisition timestamps or historical tailings discharge stages; second, model evolution, which involves integrating multiple Digital Elevation Models (DEMs) obtained at different time points to analyze the spatial evolution of surface morphology (such as subsidence and slope changes) and reservoir capacity, thereby dynamically correcting and predicting the resource estimation model.

[0028] Understandably, aerial photogrammetry or total stations can acquire high-precision elevation data of the tailings dam surface, forming a digital elevation model. The deposition axis is the main direction of tailings deposition in the tailings dam, usually determined based on historical deposition processes or topographic features. Orthogonal profile lines are a series of mutually perpendicular lines laid along the deposition axis, used to sample elevation data. The first distance is the interval between profile lines, which determines the grid density and thus affects the model's detail; the first distance is typically set to 1 meter. The differential elevation grid is a grid structure generated by interpolating and differentially calculating elevation data. It represents the rate of change of elevation, thus reflecting the surface undulations and local gradients. This grid provides a spatial framework for subsequent parameter calculations. Saturated water storage volume refers to the volume of water that a layered unit can hold in a fully saturated state; it is related to the unit's geometry, depth, and pore structure. Effective porosity refers to the proportion of pores in a unit that can be filled with water; it depends on the tailings particle size, gradation, compaction degree, and mineral composition. Layer-by-layer settlement means calculating these parameters of each unit sequentially from the top layer to the bottom layer of the layered unit, thereby constructing a layered parameter model.

[0029] In one embodiment of this application, regarding step S2, reconstructing the base topographic model of the tailings dam includes the following steps: obtaining the original topographic map of the tailings dam or the exploration results of the tailings dam; based on the original topographic map of the tailings dam or the exploration results of the tailings dam, reconstructing the original bedrock interface of the tailings dam to generate a continuous contour line model with a contour interval no greater than a second distance, and using the continuous contour line model as the base topographic model of the tailings dam. The exploration results include geological exploration borehole data, lithological boundary identification results of the tailings dam, and measurement results of the outer control points of the tailings dam body, with the second distance typically no greater than 1m.

[0030] Specifically, when constructing a base topographic model based on exploration results, the geological exploration borehole data, lithological boundary identification results, and control point measurement results of the tailings dam body are first integrated. Based on the Kriging interpolation method and the constrained Delaunay triangulation algorithm, the original bedrock interface at the bottom of the reservoir is reconstructed with high fidelity. Typically, high fidelity requires a fitting error of < 0.3 meters to generate a continuous contour line model with a contour interval of no more than 1 meter, effectively overcoming the smoothing effect and accuracy loss of traditional linear interpolation under complex geological bottom conditions.

[0031] Understandably, the original topographic map is a topographic survey map taken before the construction of the tailings dam, usually produced by the surveying department in the early stages of mining development. It contains detailed elevation information and topographic features. The original topographic map can be used to directly construct a basement topographic model. Geological exploration borehole data, obtained through drilling, provides information on the tailings dam's basement and internal structure, including core samples, stratigraphic records, and depth information. This data provides direct subsurface information. Lithological boundary identification results refer to the boundaries of different lithologies or soil layers identified through geological surveys or geophysical methods, which helps to delineate the geological units of the basement. Measurement results of the outer control points of the dam body are data points obtained through precise measurements of the tailings dam body boundaries, ensuring the geometric accuracy of the dam area. These data collectively constitute the multi-source foundation for reconstructing the basement model.

[0032] Understandably, the original bedrock interface is the bedrock surface at the bottom of the tailings dam, and its morphology is complex, potentially including features such as valleys, hills, and faults. Surface reconstruction is the process of transforming discrete data points into a continuous surface using mathematical algorithms. A continuous contour line model is a series of closed curves, each curve representing a point at the same elevation. This model visually represents the undulations of the basement topography, facilitating visualization and analysis.

[0033] In one embodiment of this application, determining the resource calculation range of a tailings dam based on a solid-surface hybrid model includes: taking the lowest point of the bottom layer in the solid-surface hybrid model as the resource calculation starting point; taking the lowest point of the top layer in the solid-surface hybrid model as the resource calculation ending point; taking the area between the vertical height of the tailings dam and the resource calculation ending point as the resource calculation range, that is, taking the bottom surface (i.e., the base terrain model) in the solid-surface hybrid model as the bottom surface for resource volume calculation; taking the top surface (i.e., the surface dynamic tomography model) in the solid-surface hybrid model as the top surface for resource volume calculation; the resource calculation range is the three-dimensional spatial region enclosed by the bottom surface and the top surface.

[0034] Specifically, the lowest point is typically the deepest part of the tailings dam, such as a valley or depression. The resource calculation starting point indicates the height at which resource calculations begin; areas below this point may have no tailings or extremely low resource content and are therefore not included in the estimation. When determining the lowest point, the overall morphology of the base topography must be considered to ensure that the starting point covers all potential resource areas. This point is selected based on geometric analysis, usually through automatic identification using a digital model or manual verification. The top layer refers to the surface dynamic tomography model, and its lowest point may be a low-lying area on the tailings dam surface, such as a waterlogged area or a weakly deposited region. The resource calculation ending point indicates the height at which resource calculations end; areas above this point may simply be overburden or ineffective material, such as surface vegetation or recently deposited non-resource material. Vertical height refers to the vertical distance from the base to the surface. The resource calculation interval defines the spatial range within the tailings dam that actually contains resources; it is a three-dimensional region located between the starting and ending points. Within the calculation interval, the tailings dam is considered a continuous entity, and its resource distribution may vary with height and location.

[0035] In one embodiment of this application, regarding step S6, the method for calculating the ore resource quantity and valuable metal quantity in each voxel section is as follows: obtaining the volume of each voxel section and the ore weight of each voxel section; calculating the ore resource quantity of each voxel section based on the volume of each voxel section and the ore weight of each voxel section; obtaining the metal grade of each voxel section; and calculating the valuable metal quantity of each voxel section based on the volume of each voxel section and the metal grade of each voxel section.

[0036] Understandably, the method involves taking the volume and minimum weight of the ore at each voxelized section; calculating the ore resource quantity at each voxelized section based on its volume and minimum weight; obtaining the metal grade at each voxelized section; and calculating the valuable metal content at each voxelized section based on its volume and metal grade. This calculation method enables a layered and refined estimation of tailings dam resources, improving the accuracy of the results by integrating volume, density, and grade parameters. Metal grade refers to the content of valuable metals in the tailings. Grade data comes from exploration samples, production records, or historical monitoring data from the tailings dam. The valuable metal content is the product of the ore resource quantity and the grade, representing the mass of valuable metals within that section.

[0037] Therefore, stratified calculation improves the accuracy of resource estimation; it considers the spatial variation of tailings weight and grade; and through voxelized sections, it achieves a refined assessment of tailings dam resources. Furthermore, this method supports vertical distribution analysis of resources, which helps identify enrichment areas and optimize mining strategies.

[0038] In one embodiment of this application, the volume of each voxelized section is the product of the area of ​​each voxelized section and the height of each voxelized section. The height of each voxelized section is 0.5m-1.0m.

[0039] Understandably, a height range of 0.5 meters to 1.0 meters is considered a reasonable compromise, capturing subtle changes within the tailings dam without resulting in excessive data volume. Smaller voxel heights can more precisely reflect the vertical heterogeneity of resource distribution, such as abrupt changes in grade or density, but increase computation time and storage requirements. Larger voxel heights simplify the calculation process but may overlook local features, leading to estimation bias. Therefore, the choice of height range needs to be adjusted according to the specific characteristics of the tailings dam. For example, a larger voxel height may be used for tailings dams with uniform resource distribution, while a smaller voxel height is used for areas with drastic changes.

[0040] Taking a tailings dam as an example, the estimation method of this application is used for estimation, and the specific process is as follows: First, a schematic diagram of the overall model of the tailings dam is shown below. Figure 2 As shown, regarding the current topographic stratification of the tailings dam, based on the 1:1000 topographic survey, sections ranging from 1048m to 1055m were divided at 1m intervals. The tailings surface morphology is characterized by a lower elevation in the center and northeast corner, gradually increasing in elevation towards the edges. The water area is located in the center of the tailings dam. Through engineering surveys, the water storage capacity of each layer was calculated, with a cumulative calculated capacity of approximately 3,188,430 m³. 3 The specific calculation results are shown in Table 1. Table 1. Calculation of water storage capacity at different elevations in tailings dam storage areas. Secondly, in Figure 2 Regarding the analysis of the irregular original topography at the bottom of the tailings dam, the existing data only includes the elevation points around the outer perimeter of the tailings dam and the bottom control status of the drilled boreholes. Therefore, the project team first combined the final rock boundary elevation of the drilled boreholes to preliminarily determine the original elevation of different parts of the tailings dam bottom. Figure 2 The model simulates the original terrain of the tailings dam by using the red dots on the outer side of the dam body, and then, based on the elevation of the surrounding area, interpolating contour lines at 1m intervals. This results in the creation of an original terrain model of the tailings dam. Figure 3 As shown, the overall shape is high in the northeast and low in the southwest, with slopes on three sides, and the southern part is a relatively low-lying area.

[0041] According to preliminary dam construction data, the initial tailings dam was 11.5 km long. Construction was carried out in stages. The initial dam sections on the west and south sides had a crest elevation of approximately 1033.0 m and a height of 4.0-8.0 m. The initial dam sections on the north and east sides had a crest elevation of approximately 1045.0-1055.0 m and a height of 5.0-12.0 m. Except for a 1950 m earthen dam section in the northeast corner used as a water-retaining section, the remaining dam sections were constructed of sandy loam.

[0042] Then, please see Figures 4-5 Regarding the constraints of tailings dams on each layer, the calculation range of tailings reserves is referenced, and the angle differences of tailings dams in different locations are considered. Contour lines are interpolated using the method of interpolating 1m contour intervals to divide the space into sections of 1022~1048m. Specifically, the dam body information is used to help determine the spatial range of the tailings dam, and then the overall three-dimensional voxel division based on contour lines is carried out within this range.

[0043] When constructing a three-dimensional solid model of a tailings dam, the measurement results of the outer control points of the tailings dam body and the design parameters of the dam slope are used as constraints to accurately construct the three-dimensional boundary surface of the tailings accumulation body.

[0044] Finally, the minimum ore weight of this tailings dam is estimated at 1.86 t / m³; the thickness of each layer is estimated at 1 m. Other estimation methods are as follows: Ore quantity: Q = ∑(S 各段块 *h*D 各段块体重 Metal content: P = ∑(S) 各段块 *h*D 各段块体重 *C 各段块加权平均 ), S 各段块 Let D be the area of ​​each voxelized section, h be the height of the voxelized section, and D be the area of ​​each voxelized section. 各段块体重 Weight of the voxelized section, C 各段块加权平均 The "representative metallic element grade value assigned to each voxelized section (i.e., 'segment')" is calculated by weighted averaging of all original grade data within its spatial influence range. Based on this estimation, the total tailings dam volume is estimated to be approximately 134.4 million m³. 3 The estimated tailings volume is approximately 250 million tons. Other resource estimates are shown in Table 2. Table 2. Results of Tailings Dam Resource Estimation This invention also discloses a quasi-three-dimensional tomographic estimation device for tailings dams, comprising: a surface model building mechanism for processing the digital elevation model of the tailings dam to construct a surface dynamic tomographic model of the tailings dam; a bottom model building mechanism for reconstructing the base topographic model of the tailings dam; a model fusion mechanism for constructing a solid-surface hybrid model of the tailings dam based on the surface dynamic tomographic model and the base topographic model of the tailings dam; a resource interval calculation mechanism for confirming the resource calculation interval of the tailings dam based on the solid-surface hybrid model; a division mechanism for dividing the tailings dam within the resource calculation interval into multiple voxelized sections with equal elevation intervals; and a resource quantity calculation mechanism for accumulating the ore resource quantity and valuable metal quantity in each voxelized section, and using the accumulated result as the resource quantity of the tailings dam.

[0045] The present invention also discloses an electronic device comprising: a processor and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described estimation method.

[0046] As can be seen from the above description, the embodiments of the present invention achieve the following technical effects: By improving the accuracy of tailings capacity calculation and resource estimation, the discharge and storage of tailings can be planned more rationally, avoiding excessive discharge or insufficient storage of tailings due to inaccurate estimation, thereby reducing resource waste. Simultaneously, accurate resource data also helps optimize tailings recycling schemes, improve the recovery rate of valuable elements in tailings, and achieve efficient resource utilization. Secondly, the present invention can adapt well to complex terrain conditions in tailings ponds. Whether it is the water area at the top of the tailings pond, the surface morphology of low center and high perimeter, or the irregular original terrain at the bottom of the tailings pond, accurate calculations can be performed through three-dimensional modeling and layered estimation methods. Even in the absence of original topographic maps, existing data and interpolation contour lines can be used to simulate the original terrain and establish a reliable terrain model, thereby ensuring the applicability and reliability of the estimation method. Finally, regardless of the size of the tailings dam, the dam structure, or the nature of the tailings, the quasi-three-dimensional tomographic estimation method of this invention can be adaptively adjusted by changing the layer thickness, model parameters, etc., making it applicable to tailings dams in various situations. This gives the invention broad applicability and provides effective technical support for the design and management of various tailings dams.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A quasi-three-dimensional tomographic estimation method for tailings dams, characterized in that, Includes the following steps: The digital elevation model of the tailings dam is processed to construct a dynamic tomographic model of the tailings dam's surface. Reconstruct the base topography model of the tailings dam; Based on the surface dynamic tomography model and the base topography model of the tailings dam, a solid-surface hybrid model of the tailings dam is constructed. Based on the aforementioned solid-surface hybrid model, the resource calculation range of the tailings dam was determined; The tailings pond within the resource calculation interval is divided into multiple voxel sections with equal elevation intervals. The amount of ore resources and valuable metals in each voxel section are summed up, and the sum is taken as the resource amount of the tailings dam.

2. A method of quasi-three-dimensional tomographic estimation of a tailings pond according to claim 1, characterized in that, The process of processing the digital elevation model of the tailings dam includes the following steps: A digital elevation model of the tailings dam with the highest accuracy was obtained through actual measurement using measuring equipment. Orthogonal profile lines are laid out along the stacking axis of the digital elevation model at intervals of a first distance to construct the differential elevation grid of the digital elevation model; The saturated water storage volume and effective porosity of each layer of the differential elevation grid are calculated layer by layer. The saturated water storage volume and effective porosity of each layer cell of the differential elevation grid are correlated with historical time.

3. A method for quasi-3D tomographic estimation of a tailings pond according to claim 1, characterized in that, The reconstruction of the base topography model of the tailings dam includes the following steps: Obtain the original topographic map of the tailings dam or the exploration results of the tailings dam; Based on the original topographic map of the tailings dam or the exploration results of the tailings dam, the original bedrock interface of the tailings dam is reconstructed to generate a continuous contour line model with a contour interval no greater than the second distance. The continuous contour line model is used as the base topographic model of the tailings dam.

4. The method of claim 1, wherein the method is a quasi-3D tomographic estimation method for a tailings pond. The resource calculation range for the tailings dam, confirmed based on the entity-surface hybrid model, includes: The lowest point of the bottom layer in the solid-surface hybrid model is taken as the starting point for resource calculation; The lowest point of the top layer in the solid-surface hybrid model is taken as the starting and ending point of resource calculation; The vertical height of the tailings dam is defined as the area between the resource calculation starting point and the resource calculation ending point as the resource calculation interval.

5. A method for quasi-3D tomographic estimation of a tailings pond according to claim 1, characterized in that, The method for calculating the amount of ore resources and valuable metals in each voxel section is as follows: Obtain the volume of each voxelized section and the ore weight of each voxelized section; The ore resource quantity of each voxelized section is calculated based on the volume of each voxelized section and the ore weight of each voxelized section. Obtain the metal element grade of each voxelized section; The amount of valuable metal in each voxelized section is calculated based on the volume of each voxelized section and the metal element grade of each voxelized section.

6. The quasi-three-dimensional tomographic estimation method for tailings dams according to claim 5, characterized in that, The volume of each voxelized section is the product of the area of ​​each voxelized section and the height of each voxelized section.

7. The quasi-three-dimensional tomographic estimation method for tailings dams according to claim 1, characterized in that, The height of each voxelized section is 0.5m-1.0m.

8. The quasi-three-dimensional tomographic estimation method for tailings dams according to claim 1, characterized in that, The exploration results include geological exploration borehole data, lithological boundary identification results of the tailings dam, and measurement results of the outer control points of the tailings dam.

9. A quasi-three-dimensional tomographic estimation device for tailings dams, characterized in that, include: The surface model building mechanism processes the digital elevation model of the tailings dam to construct a surface dynamic tomographic model of the tailings dam. The underlying model is established to reconstruct the base terrain model of the tailings dam; The model fusion mechanism constructs a solid-surface hybrid model of the tailings dam based on the surface dynamic tomography model and the base topography model of the tailings dam. The resource range calculation mechanism determines the resource calculation range of the tailings dam based on the entity-surface hybrid model. The division mechanism divides the tailings pond within the resource calculation interval into multi-layered voxel sections with equal elevation intervals. The resource calculation mechanism accumulates the ore resources and valuable metals in each voxelized section, and uses the accumulated result as the resource quantity of the tailings dam.

10. An electronic device, characterized in that, The electronic device includes: a processor and a memory for storing executable instructions of the processor; The processor is configured to perform the estimation method according to any one of claims 1-8.

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