Storage capacity calculation method and device, electronic equipment and storage medium

Abstract

The invention discloses a reservoir capacity calculation method and device, electronic equipment and a storage medium, and the method comprises the steps: collecting multi-source data which comprises a multi-beam point cloud of the underwater terrain of a reservoir area, a laser point cloud of the land terrain of the reservoir area, and a bay line of the reservoir area; processing the multi-source data to obtain an underwater elevation point cloud, an onshore elevation point cloud and a bay line with elevation information; performing fusion modeling on the underwater elevation point cloud, the land elevation point cloud and the bay line with the elevation information to obtain a triangulated irregular network model of the reservoir area earth surface; based on the boundary constraint and the triangulated irregular network model, obtaining a reservoir area triangulated irregular network after the boundary constraint; and calculating the storage capacity based on the triangulated irregular network of the storage area after boundary constraint. According to the embodiment of the invention, the technical problem of low storage capacity calculation precision in related technologies is solved.

Description

Technical Field

[0001] The present application relates to a storage capacity calculation method, device, electronic equipment and storage medium, and belongs to the field of river channel storage and reservoir capacity calculation. Background Art

[0002] The basic data used in traditional reservoir capacity calculations are underwater single-beam measurement elevation points and onshore GNSS or total station measurement elevation points. Since both underwater and onshore measurements are sampled at a certain distance, the number of elevation points in the reservoir area is limited, and some areas with terrain distortion cannot be measured. In addition, the boundary between land and water is difficult to reach due to steep terrain or mudflats, resulting in elevation data gaps (such as Figure 1 The calculation accuracy of the reservoir capacity is reduced as shown in the white solid rectangle box in the figure.

[0003] Traditional methods for calculating reservoir capacity include contour method or cross-section method, which are difficult to provide high-precision reservoir capacity calculation results. Taking the contour method as an example, the reservoir capacity calculation formula is formula ①, where: h i , S i is the elevation and enclosed area of ​​the ith contour line, and n is the number of contour lines in the topographic map:

[0004]

[0005] It is not difficult to see that when the contour method is used, the accuracy of reservoir capacity calculation depends to a large extent on the contour interval of the topographic map and the closure integrity of the contour lines. However, the contour interval of the topographic map is often 1m, 2m or even 5m, and the contour lines in the topographic map are disconnected due to ground objects (such as Figure 1 The white dotted rectangle in the middle makes it difficult to completely close the contour lines, and the calculation of reservoir capacity requires manual redrawing and closure. All these make it difficult to provide high-precision reservoir capacity results when using the contour line method. Summary of the invention

[0006] In view of this, the present application provides a storage capacity calculation method, device, electronic device and storage medium. The embodiments of the present application at least solve the technical problem of low storage capacity calculation accuracy in the related art.

[0007] The first aspect of an embodiment of the present application discloses a reservoir capacity calculation method, the method comprising: collecting multi-source data, the multi-source data comprising a multi-beam point cloud of the underwater terrain of the reservoir area, a laser point cloud of the land terrain of the reservoir area and the waterline of the reservoir area; processing the multi-source data to obtain an underwater elevation point cloud, an onshore elevation point cloud and a waterline with elevation information; fusing and modeling the underwater elevation point cloud, the onshore elevation point cloud and the waterline with elevation information to obtain an irregular triangulated network model of the reservoir surface; based on boundary constraints and the irregular triangulated network model, obtaining an irregular triangulated network of the reservoir area after boundary constraints; and calculating the reservoir capacity based on the irregular triangulated network of the reservoir area after boundary constraints.

[0008] In some embodiments, the multi-source data collection includes: collecting the underwater topography of the reservoir area based on a multi-beam bathymetry method; collecting the land topography of the reservoir area based on an airborne lidar measurement method; collecting digital orthophotos of the reservoir area based on aerial photogrammetry technology and extracting the waterline of the reservoir area through a land-water separation algorithm or a manual drawing method.

[0009] In some embodiments, the processing of the multi-source data includes: filtering abnormal points of the multi-beam point cloud based on an automatic filtering algorithm and / or manual interaction to obtain an underwater elevation point cloud; using the water edge line as a boundary range, eliminating the laser point cloud within the water edge line range to obtain an onshore elevation point cloud; assigning an elevation to the water edge line based on the elevation information of the laser point cloud on the water edge line to obtain a water edge line with elevation information.

[0010] In some embodiments, the irregular triangulated network model includes a reservoir boundary range, a reservoir area and a non-reservoir area.

[0011] In some embodiments, obtaining the irregular triangulated network of the reservoir area after boundary constraints based on the boundary constraints and the irregular triangulated network model includes: using the boundary range of the reservoir area to clip and remove the triangular meshes outside the reservoir area to obtain the irregular triangulated network of the reservoir area after boundary constraints.

[0012] In some embodiments, the calculation of reservoir capacity based on the irregular triangulated network of the reservoir area after the boundary constraint includes: for the triangular mesh of the triangular mesh, calculating the water storage space volume of the triangular mesh based on the water depth values ​​at the vertices of the triangular mesh and the area of ​​the triangular mesh, and then calculating the reservoir capacity, wherein the vertices correspond to reservoir elevation points or water edge nodes.

[0013] In some embodiments, the method further includes: in response to calculation personnel A using software A to perform storage capacity calculation, obtaining a storage capacity main calculation result; in response to calculation personnel B using software B to perform storage capacity calculation, obtaining a storage capacity accounting result; based on the comparison of the storage capacity main calculation result and the storage capacity accounting result, obtaining the absolute value of the difference between the two; when the absolute value of the difference between the two divided by the storage capacity main calculation result is less than or equal to a threshold value, using the storage capacity main calculation result as the storage capacity calculation result; when the absolute value of the difference between the two divided by the storage capacity main calculation result is greater than a threshold value, instructing the calculation personnel to recalculate.

[0014] The second aspect of an embodiment of the present application discloses a reservoir capacity calculation device, which includes: an acquisition module for acquiring multi-source data, the multi-source data including a multi-beam point cloud of an underwater topography of a reservoir area, a laser point cloud of an onshore topography of a reservoir area, and a waterline of the reservoir area; a processing module for processing the multi-source data to obtain an underwater elevation point cloud, an onshore elevation point cloud, and a waterline with elevation information; a modeling module for fusion modeling of the underwater elevation point cloud, the onshore elevation point cloud, and the waterline with elevation information to obtain an irregular triangulated network model of the reservoir area surface; a constraint module for obtaining an irregular triangulated network of the reservoir area after boundary constraints based on boundary constraints and the irregular triangulated network model; and a calculation module for calculating the reservoir capacity based on the irregular triangulated network of the reservoir area after boundary constraints.

[0015] A third aspect of an embodiment of the present application discloses a computer-readable storage medium, which includes a stored program, wherein when the program is run, the storage capacity calculation method of the above embodiment is executed in a processor of a device where the program is located.

[0016] The fourth aspect of an embodiment of the present application discloses an electronic device, wherein the server includes: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors execute the storage capacity calculation method of the above embodiment.

[0017] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0018] (1) The present invention uses multi-source data such as underwater and onshore elevation point clouds and waterline with elevation information as basic data for constructing a fine three-dimensional surface model of the reservoir area, which can achieve a full coverage description of the reservoir area terrain and greatly improve the accuracy of reservoir capacity calculation.

[0019] (2) The fusion of multi-source data to construct a reservoir area triangulated irregular network (TIN) model can fully and accurately realize the three-dimensional terrain digital twin of the reservoir area. The refinement of the model is far superior to previous technical means, such as Figure 6 As shown, various terrain features in the reservoir area are clearly visible, such as embankments, ridges, roadbeds, small ditches, etc.

[0020] (3) The water edge line with elevation information can ensure a smooth transition at the water-land junction of the reservoir model in the process of constructing the reservoir area irregular triangulated network (TIN) model, which conforms to the actual terrain of the reservoir area, such as Figure 7 As shown, the blue line is the water edge, and the junction of water and land in the reservoir model is natural in shape.

[0021] (4) Boundary constraints can ensure that the irregular triangulated networks of the reservoir area involved in the calculation of reservoir capacity are all valid areas of the reservoir area, thus improving the accuracy of reservoir capacity calculation. Figure 8As shown, the white line is the boundary of the reservoir area, and the redundant triangulated networks outside the reservoir area have been clipped and eliminated.

[0022] (5) During the storage capacity calculation process, different personnel use different software to independently perform the main calculation and accounting of the storage capacity. Only when the difference between the two is within 3%, the main calculation result is used as the final storage capacity result, ensuring the reliability of the calculation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0024] Figure 1 A schematic diagram of a traditional method for calculating reservoir capacity terrain provided in an embodiment of the present application.

[0025] Figure 2 A schematic diagram of a storage capacity calculation method provided in an embodiment of the present application.

[0026] Figure 3 A schematic diagram of a storage capacity calculation method provided in an embodiment of the present application.

[0027] Figure 4a A schematic diagram of an irregular triangulated network provided in an embodiment of the present application.

[0028] Figure 4b A schematic diagram of an irregular triangulated network provided in an embodiment of the present application.

[0029] Figure 5 A schematic diagram of a triangulated network method for calculating reservoir capacity provided in an embodiment of the present application.

[0030] Figure 6 A rendering of a refined three-dimensional surface model of a reservoir area provided in an embodiment of the present application.

[0031] Figure 7 A smooth transition effect diagram of the water-land boundary of a reservoir area provided in an embodiment of the present application.

[0032] Figure 8 An irregular triangulated network rendering of a reservoir area after boundary constraints provided in an embodiment of the present application.

[0033] Fig. 9 A schematic diagram of a storage capacity calculation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] Embodiment 1:

[0037] Figure 2 and Figure 3 A flow chart of a storage capacity calculation method provided in an embodiment of the present application is shown in FIG. Figure 2 and Figure 3 As shown, the method may include the following steps:

[0038] 201 collects multi-source data, wherein the multi-source data includes a multi-beam point cloud of the underwater topography of the reservoir area, a laser point cloud of the land topography of the reservoir area, and a waterline of the reservoir area.

[0039] In some embodiments, the multi-source data collection includes: collecting the underwater topography of the reservoir area based on a multi-beam bathymetry method; collecting the land topography of the reservoir area based on an airborne lidar measurement method; collecting the digital orthophoto (DOM) of the reservoir area based on aerial photogrammetry technology and extracting the waterline of the reservoir area through a land-water separation algorithm or a manual drawing method.

[0040] It is understandable that the traditional single-beam bathymetry is from point to line, while the multi-beam bathymetry is from line to surface. This embodiment uses the multi-beam bathymetry method to obtain the underwater topography of the reservoir area, and uses the multi-beam point cloud to fully describe the underwater topography. Traditional GNSS or total station measurement is a limited point measurement at a certain interval, while airborne laser radar measurement is a full coverage measurement of the land topography. This embodiment uses the airborne laser radar measurement method to obtain the land topography of the reservoir area, and uses the laser point cloud to fully describe the land topography.

[0041] It is worth noting that by using aerial photogrammetry technology to collect digital orthophotos of the reservoir area, the water edge can be accurately and quickly extracted through water-land separation algorithms or manual drawing methods.

[0042] Among them, the water edge line refers to the edge line where rivers, lakes, reservoirs and other water bodies meet the land, that is, the boundary line of the water body.

[0043] Among them, the multi-beam bathymetric method calculates the water depth by simultaneously emitting multiple sound beams and recording the echo time and intensity after the sound waves pass through the water body.

[0044] Among them, the airborne laser radar measurement method is a technology that uses laser radar equipment to scan the ground from the air to obtain high-precision three-dimensional spatial data. It determines the distance and position of the target by emitting laser pulses and receiving the reflected light, calculating the round-trip time of the laser pulses.

[0045] Among them, aerial photogrammetry technology is a technology that uses aerial photogrammetry equipment to take aerial photos in the air through aircraft, combining photogrammetry principles and related measurement methods to measure, map and analyze ground objects.

[0046] The land-water separation algorithm is a technology used in remote sensing image processing, which aims to separate water bodies from land in order to perform more accurate water extraction and analysis. Common land-water separation algorithms include the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI). This embodiment does not limit the land-water separation algorithm.

[0047] 202 processes the multi-source data to obtain underwater elevation point cloud, land elevation point cloud and waterline with elevation information.

[0048] In some embodiments, the processing of the multi-source data includes: filtering abnormal points of the multi-beam point cloud based on an automatic filtering algorithm and / or manual interaction to obtain an underwater elevation point cloud; using the water edge line as a boundary range, eliminating the laser point cloud within the water edge line range to obtain an onshore elevation point cloud; assigning an elevation to the water edge line based on the elevation information of the laser point cloud on the water edge line to obtain a water edge line with elevation information.

[0049] It is understandable that the point cloud collected by the multi-beam bathymetry method inevitably has abnormal points. This embodiment uses an automatic filtering algorithm and manual interaction to filter out abnormal points to obtain an underwater elevation point cloud that accurately expresses the underwater terrain. The same is true for noise points. The point cloud collected by the airborne lidar measurement method will have some laser point clouds in the water area due to turbid water and surface reflection. This embodiment uses the water edge as the boundary range, removes the laser point cloud within the water edge range, and obtains an onshore elevation point cloud that accurately expresses the onshore terrain.

[0050] It is worth noting that the water edge extracted from the digital orthophoto does not contain elevation information. In order to ensure a smooth transition at the water-land junction of the subsequent fusion modeling results, the water edge needs to be assigned an elevation value according to the actual elevation. This embodiment uses laser point cloud superposition to fuse the water edge for processing. Specifically, the elevation of the water edge is assigned to the water edge using the laser point cloud elevation on the water edge to obtain a water edge with actual elevation information.

[0051] For example, in geographic information system (GIS) software, elevation values ​​can be assigned to water edge line elements in batches by adding elevation values ​​to line features or using an automatic value assignment function.

[0052] 203 The underwater elevation point cloud, the land elevation point cloud and the waterline with elevation information are fused and modeled to obtain an irregular triangulated network model of the reservoir area surface.

[0053] 204 Based on the boundary constraint and the irregular triangulated network model, an irregular triangulated network of the reservoir area after boundary constraint is obtained.

[0054] In some embodiments, the irregular triangulated network model includes a reservoir boundary range, a reservoir area and a non-reservoir area.

[0055] In some embodiments, obtaining the irregular triangulated network of the reservoir area after boundary constraints based on the boundary constraints and the irregular triangulated network model includes: using the boundary range of the reservoir area to clip and remove the triangular meshes outside the reservoir area to obtain the irregular triangulated network of the reservoir area after boundary constraints.

[0056] It should be noted that the underwater elevation point cloud, the land elevation point cloud and the water edge line with elevation information are integrated and modeled to preliminarily construct an irregular triangulated network (TIN) model of the entire reservoir surface. However, due to the irregular triangulated network construction rules, the outermost boundary of the irregular triangulated network after the preliminary construction is a convex polygon. Although this feature can play a role in optimizing edges in fields such as three-dimensional graphics modeling, in the field of reservoir capacity calculation, the convex polygon boundary will include the original non-reservoir area into the triangulated network, thereby increasing the error of reservoir capacity calculation.

[0057] For example, Figure 4a and Figure 4b As shown in Figure 4a This is the preliminary construction of the irregular triangulated network of the reservoir area, which includes the triangulated network of the non-reservoir area; Figure 4b As shown, the blue line is the boundary of the reservoir area, the green triangular mesh is the reservoir area, and the red triangular mesh is the non-reservoir area.

[0058] Therefore, in order to reduce the impact of non-reservoir area triangular meshes on reservoir capacity calculation, this embodiment uses the closed boundary range of the reservoir area to clip and remove the triangular meshes outside the reservoir area, thereby obtaining a triangular mesh that can be used to accurately calculate the reservoir capacity, that is, the reservoir area irregular triangular mesh after boundary constraints. This embodiment can quickly and accurately remove the triangular meshes of non-reservoir areas, thereby improving the accuracy of reservoir capacity calculation.

[0059] 205 Calculate the reservoir capacity based on the irregular triangulated network of the reservoir area after the boundary constraints.

[0060] In some embodiments, the calculation of reservoir capacity based on the irregular triangulated network of the reservoir area after the boundary constraint includes: for the triangular mesh of the triangular mesh, calculating the water storage space volume of the triangular mesh based on the water depth values ​​at the vertices of the triangular mesh and the area of ​​the triangular mesh, and then calculating the reservoir capacity, wherein the vertices correspond to reservoir elevation points or water edge nodes.

[0061] In some embodiments, the method further includes: in response to calculation personnel A using software A to perform storage capacity calculation, obtaining a storage capacity main calculation result; in response to calculation personnel B using software B to perform storage capacity calculation, obtaining a storage capacity accounting result; based on the comparison of the storage capacity main calculation result and the storage capacity accounting result, obtaining the absolute value of the difference between the two; when the absolute value of the difference between the two divided by the storage capacity main calculation result is less than or equal to a threshold value, using the storage capacity main calculation result as the storage capacity calculation result; when the absolute value of the difference between the two divided by the storage capacity main calculation result is greater than a threshold value, instructing the calculation personnel to recalculate.

[0062] This embodiment uses the triangulated network method to calculate the reservoir capacity. Figure 5 As shown on the right, the dots on the coordinate plane represent the elevation points of the reservoir area or the nodes on the waterline. The dots are connected according to the preset rules to construct an irregular triangulated network with the dots as vertices and no overlap. The water storage space of the reservoir area is divided into multiple triangular prisms with the triangular grid as the base and the water depth at the triangle vertex as the edge length. Figure 5 The blue triangular mesh ΔABC on the right side corresponds to the water storage space as shown in the figure below: Figure 5 As shown on the left, A, B, and C are the corresponding reservoir elevation points or water edge line nodes (the two are collectively referred to as reservoir points), A', B', and C' are water surface points, and the length of the line between the water surface point and the corresponding reservoir point is the water depth value. Therefore, the water storage space volume corresponding to the grid ΔABC can be calculated using formula ②:

[0063]

[0064] In the formula, h x is the water depth at point x; S ΔABC represents the area of ​​ΔABC.

[0065] Assume that there are N triangular meshes in the reservoir plane, and the volume of the triangular prism corresponding to the i-th triangular mesh is v i , then the storage capacity calculation value V of the reservoir area is calculated according to formula ③:

[0066]

[0067] In the calculation process, different people usually use different software to calculate the storage capacity and verify each other. Calculator A uses software A to calculate, and the result is used as the main calculation result of storage capacity, while calculator B uses software B to calculate the storage capacity, and the result is used as the storage capacity accounting result.

[0068] According to the requirements of the specification, the main calculation result is compared with the accounting result. When the absolute value of the difference between the two divided by the main calculation result is less than or equal to 3%, the main calculation result is used as the final storage capacity calculation result; if the difference is greater than 3%, check whether the calculation data and calculation method are wrong, and recalculate until the difference is less than or equal to 3%. It should be noted that different comparison thresholds can be set according to different specifications.

[0069] Furthermore, the main calculation results include the reservoir capacity and water surface area at different water levels. The water level, reservoir capacity and water surface area are compiled into the final reservoir capacity curve of the reservoir area.

[0070] Embodiment 2:

[0071] Fig. 9 A schematic diagram of a storage capacity calculation device provided in an embodiment of the present application is shown in FIG. Fig. 9 As shown, the device may include the following modules:

[0072] The acquisition module 901 is used to acquire multi-source data, wherein the multi-source data includes a multi-beam point cloud of the underwater topography of the reservoir area, a laser point cloud of the land topography of the reservoir area, and the waterline of the reservoir area.

[0073] The processing module 902 is used to process the multi-source data to obtain underwater elevation point clouds, land elevation point clouds and waterline with elevation information.

[0074] The modeling module 903 is used to integrate the underwater elevation point cloud, the land elevation point cloud and the waterline with elevation information to obtain an irregular triangulated network model of the reservoir surface.

[0075] The constraint module 904 is used to obtain the irregular triangulated network of the reservoir area after boundary constraints based on the boundary constraints and the irregular triangulated network model.

[0076] The calculation module 905 is used to calculate the storage capacity based on the irregular triangulated network of the storage area after the boundary constraints.

[0077] In some embodiments, the multi-source data collection includes: collecting the underwater topography of the reservoir area based on a multi-beam bathymetry method; collecting the land topography of the reservoir area based on an airborne lidar measurement method; collecting digital orthophotos of the reservoir area based on aerial photogrammetry technology and extracting the waterline of the reservoir area through a land-water separation algorithm or a manual drawing method.

[0078] In some embodiments, the processing of the multi-source data includes: filtering abnormal points of the multi-beam point cloud based on an automatic filtering algorithm and / or manual interaction to obtain an underwater elevation point cloud; using the water edge line as a boundary range, eliminating the laser point cloud within the water edge line range to obtain an onshore elevation point cloud; assigning an elevation to the water edge line based on the elevation information of the laser point cloud on the water edge line to obtain a water edge line with elevation information.

[0079] In some embodiments, the irregular triangulated network model includes a reservoir boundary range, a reservoir area and a non-reservoir area.

[0080] In some embodiments, obtaining the irregular triangulated network of the reservoir area after boundary constraints based on the boundary constraints and the irregular triangulated network model includes: using the boundary range of the reservoir area to clip and remove the triangular meshes outside the reservoir area to obtain the irregular triangulated network of the reservoir area after boundary constraints.

[0081] In some embodiments, the calculation of reservoir capacity based on the irregular triangulated network of the reservoir area after the boundary constraint includes: for the triangular mesh of the triangular mesh, calculating the water storage space volume of the triangular mesh based on the water depth values ​​at the vertices of the triangular mesh and the area of ​​the triangular mesh, and then calculating the reservoir capacity, wherein the vertices correspond to reservoir elevation points or water edge nodes.

[0082] In some embodiments, the method further includes: in response to calculation personnel A using software A to perform storage capacity calculation, obtaining a storage capacity main calculation result; in response to calculation personnel B using software B to perform storage capacity calculation, obtaining a storage capacity accounting result; based on the comparison of the storage capacity main calculation result and the storage capacity accounting result, obtaining the absolute value of the difference between the two; when the absolute value of the difference between the two divided by the storage capacity main calculation result is less than or equal to a threshold value, using the storage capacity main calculation result as the storage capacity calculation result; when the absolute value of the difference between the two divided by the storage capacity main calculation result is greater than a threshold value, instructing the calculation personnel to recalculate.

[0083] Embodiment 3:

[0084] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0085] The above-mentioned memory may refer to a device inside a computer for storing data and programs, and may include memory, hard disk, etc., wherein the memory may be used to temporarily store running programs and data, the hard disk may be used to store programs and data for a long time, and the memory may be used to enable the computer to read and write data, and execute programs; the above-mentioned processor may be responsible for executing instructions in computer programs and performing data processing, and may be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0086] Embodiment 4:

[0087] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0088] The above-mentioned computer storage medium may refer to a medium in a computer memory used to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc.; the stored program included in the computer-readable storage medium may be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0089] Embodiment 5:

[0090] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0091] The above-mentioned computer program product may refer to a software program that has been written, tested and released and can be run on a computer or other device. The computer program product may include an application, an operating system, tool software, etc., which is used to implement specific functions or solve specific problems.

[0092] Embodiment 6:

[0093] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0094] The above-mentioned non-volatile computer-readable storage medium may refer to a medium for storing data. The non-volatile computer-readable storage medium can keep the data from being lost when the power is off, and can be used to store long-term data, such as operating systems, applications, and user files. The non-volatile storage medium may include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0095] Embodiment 7:

[0096] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0097] The above-mentioned computer program may refer to a collection of instructions used to tell a computer to perform a specific task or operation. A computer program may be written by a programmer using a specific programming language and may include algorithms, data structures, logic, and control flows. A computer program may be used for a variety of purposes, including application software, operating systems, and the like.

[0098] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0100] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0101] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0102] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0103] In summary, the embodiments of the present invention utilize underwater multi-beam point cloud and onshore laser point cloud as basic data, which can achieve full coverage of the reservoir terrain and greatly improve the accuracy of reservoir capacity calculation; the waterline with elevation information can make the water-land junction of the constructed irregular triangulated network of the reservoir smooth and conform to the natural form; for the redundant triangulated meshes generated when constructing the irregular triangulated network in the reservoir area, the boundary constraints can effectively eliminate the impact of this on the accuracy of reservoir capacity calculation.

[0104] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A storage capacity calculation method, characterized in that: include: Collecting multi-source data, the multi-source data including a multi-beam point cloud of the underwater topography of the reservoir area, a laser point cloud of the land topography of the reservoir area, and the waterline of the reservoir area; Processing the multi-source data to obtain underwater elevation point clouds, land elevation point clouds and waterline with elevation information; The underwater elevation point cloud, the land elevation point cloud and the water edge line with elevation information are fused and modeled to obtain an irregular triangulated network model of the reservoir area surface; Based on the boundary constraint and the irregular triangulated network model, an irregular triangulated network of the reservoir area after boundary constraint is obtained; The reservoir capacity is calculated based on the irregular triangulated network of the reservoir area after the boundary constraints.

2. The storage capacity calculation method according to claim 1, characterized in that: The collecting of multi-source data includes: Collect the underwater topography of the reservoir area based on the multi-beam bathymetry method; Collect the land topography of the reservoir area based on airborne LiDAR measurement method; Digital orthophotos of the reservoir area are collected based on aerial photogrammetry technology, and the water edge of the reservoir area is extracted through water-land separation algorithm or manual drawing method.

3. The storage capacity calculation method according to claim 1, characterized in that: The processing of the multi-source data comprises: Filtering abnormal points of the multi-beam point cloud based on an automatic filtering algorithm and / or a manual interaction method to obtain an underwater elevation point cloud; Taking the water edge line as the boundary range, removing the laser point cloud within the water edge line range to obtain the land elevation point cloud; The elevation of the waterline is assigned based on the laser point cloud elevation information on the waterline to obtain a waterline with elevation information.

4. The storage capacity calculation method according to claim 1, characterized in that: The irregular triangulated network model includes the reservoir boundary range, the reservoir area and the non-reservoir area.

5. The storage capacity calculation method according to claim 4, characterized in that ,Based on the boundary constraint and the irregular triangulated network model, the irregular triangulated network of the reservoir area after boundary constraint is obtained, including: The reservoir area boundary range is used to clip and remove the triangular mesh outside the reservoir area to obtain an irregular triangulated network of the reservoir area after boundary constraints.

6. The storage capacity calculation method according to claim 1, characterized in that: The calculation of the reservoir capacity based on the irregular triangulated network of the reservoir area after the boundary constraint includes: For the triangular mesh of the triangular network, the water storage space volume of the triangular mesh is calculated based on the water depth value at the vertex of the triangular mesh and the area of ​​the triangular mesh, and then the reservoir capacity is calculated, wherein the vertex corresponds to the reservoir elevation point or water edge line node.

7. The storage capacity calculation method according to claim 6, characterized in that: The method further comprises: Response calculation personnel A uses software A to calculate the storage capacity and obtains the main calculation result of the storage capacity; Response calculation personnel B uses software B to calculate the storage capacity and obtains the storage capacity calculation result; Based on the comparison between the storage capacity main calculation result and the storage capacity accounting result, the absolute value of the difference between the two is obtained; When the absolute value of the difference between the two divided by the storage capacity main calculation result is less than or equal to the threshold, the storage capacity main calculation result is used as the storage capacity calculation result; When the absolute value of the difference between the two divided by the main calculation result of the storage capacity is greater than the threshold, the calculator is instructed to recalculate.

8. A storage capacity calculation device, characterized in that: include: A collection module, used to collect multi-source data, wherein the multi-source data includes a multi-beam point cloud of the underwater topography of the reservoir area, a laser point cloud of the land topography of the reservoir area, and the waterline of the reservoir area; A processing module, used for processing the multi-source data to obtain underwater elevation point cloud, land elevation point cloud and waterline with elevation information; A modeling module is used to fuse the underwater elevation point cloud, the land elevation point cloud and the water edge line with elevation information to obtain an irregular triangulated network model of the reservoir area surface; A constraint module, used for obtaining a boundary-constrained irregular triangulated network of the reservoir area based on the boundary constraint and the irregular triangulated network model; The calculation module is used to calculate the storage capacity based on the irregular triangulated network of the storage area after the boundary constraints.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the storage capacity calculation method described in any one of claims 1 to 7 is executed in a processor of the device where the program is controlled.

10. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors execute the storage capacity calculation method described in any one of claims 1 to 7.

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