Peeling determination method and device for geological density information, electronic equipment and medium

Abstract

The invention relates to the technical field of geology, in particular to a geological density information stripping determination method and device, electronic equipment and a medium, and the method comprises the steps: obtaining surface observation data of a target area; the earth surface observation data are input into the stripping model, the stripping model outputs density distribution of a plurality of material layers of a target area, a lower interface of an earth surface shallow layer model of the stripping model target area starts to extend downwards, a new interface in each extension and a lower interface of a previous material layer form a new material layer, and for each material layer, the density distribution of a plurality of material layers in the stripping model target area is determined; performing density filling on the material layer according to the global crustal structure model, optimizing the density distribution of the material layer until the geoid of the material layer is matched with the benchmark of the earth surface observation data, and continuing to extend downwards until the downward extending distance reaches the target distance; and generating geological density information of the target area according to the density distribution of the plurality of material layers. Therefore, the problem that geological density information measured by related technologies is not accurate enough is solved.

Description

Technical Field

[0001] This application relates to the field of geological technology, and in particular to a method, apparatus, electronic device, and medium for determining the stripping of geological density information. Background Technology

[0002] Since the PREM (Preliminary Reference Earth Model) model, numerous crustal models have been published internationally, including global and local models. While these models differ in structure, they generally encompass two important properties of the Earth's crust: geometric and physical properties. Geometric properties refer to the spatial configuration of the crust, such as surface shape, Moho (Mohorovičić discontinuity) depth, and the thickness of each layer. Physical properties refer to attributes such as the density of different crustal layers and seismic wave velocity. For determining the geoid, accurately measuring the "density problem" has always been one of the unresolved challenges. Summary of the Invention

[0003] This application provides a method, apparatus, electronic device, and medium for determining the stripping of geological density information, in order to solve the problem that the determination of geological density information by related technologies is not accurate enough.

[0004] The first aspect of this application provides a method for determining geological density information by stripping, comprising the following steps: acquiring surface observation data of a target area; inputting the surface observation data into a stripping model, the stripping model outputting the density distribution of multiple material layers in the target area, wherein the lower interface of the shallow surface model of the target area in the stripping model begins to extend downward, and the new interface at each extension and the lower interface of the previous material layer constitute a new material layer; for each material layer, the density of the material layer is filled according to a global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer matches the level point of the surface observation data, and the downward extension continues until the downward extension distance reaches the target distance; and generating geological density information of the target area based on the density distribution of multiple material layers.

[0005] Optionally, geological density information includes crustal density distribution information and mantle density distribution information.

[0006] Optionally, the first material layer is located between the upper and lower interfaces of the shallow surface model.

[0007] Optionally, the upper interface of the shallow surface layer is constructed based on digital terrain data and hydrodynamic terrain data; the extension surface of the reference ellipsoid is used as the lower interface of the shallow surface layer; the crustal density model and the surface ice layer model are obtained from the database; the ice layer information of the crustal density model is replaced by the surface ice layer model, and a refined crustal density model is constructed using the crustal density model after the ice layer information is replaced; the density of the shallow surface layer model is filled based on the refined crustal density model.

[0008] Optionally, the stripping model is also used to calculate underground gravitational potential, including: discretizing the shallow surface layer and calculating the gravitational potential generated by the shallow surface layer based on the discretization result; calculating the gravitational potential generated by the mass of the internal sphere in the target area according to the gravity field model; calculating the gravitational potential of the internal material outside the Γ-plane of the target area based on the gravitational potential generated by the mass of the internal sphere and the gravitational potential generated by the shallow surface layer; obtaining gravity potential information based on the gravitational potential generated by the shallow surface layer and the gravitational potential of the internal material inside the Γ-plane of the target area; and determining the geoid position based on the definition of the geoid by using an iterative search method.

[0009] Optionally, the shallow surface layer is discretized, and the gravitational potential generated by the shallow surface layer is calculated based on the discretization result, including: identifying the actual distance between the discretized region and the target point; if the actual distance is less than or equal to a distance threshold, the gravitational potential is calculated using a cylindrical model; if the actual distance is greater than the distance threshold, the gravitational potential is calculated using a wedge model.

[0010] A second aspect of this application provides a device for determining the stripping of geological density information, comprising: an acquisition module for acquiring surface observation data of a target area; an input module for inputting the surface observation data into a stripping model, the stripping model outputting the density distribution of multiple material layers in the target area, wherein the lower interface of the shallow surface model of the target area in the stripping model begins to extend downward, and each extension of the new interface with the lower interface of the previous material layer constitutes a new material layer; for each material layer, the density of the material layer is filled according to a global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer coincides with the level point of the surface observation data, and the downward extension continues until the downward extension distance reaches the target distance; and a generation module for generating geological density information of the target area based on the density distribution of multiple material layers.

[0011] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the method for determining the stripping of geological density information as described in the above embodiments.

[0012] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the method for determining the stripping of geological density information as described in the above embodiments.

[0013] A fifth aspect of this application provides a computer program that, when executed, is used to implement the method for determining the stripping of geological density information as described in the above embodiments.

[0014] Therefore, this application has the following beneficial effects: This application's embodiments acquire surface observation data of the target area, input the surface observation data into a stripping model, and the stripping model outputs the density distribution of multiple material layers in the target area. Specifically, the lower interface of the shallow surface model of the target area in the stripping model begins to extend downwards. Each time the model extends, the new interface at each extension and the lower interface of the previous material layer constitute a new material layer. For each material layer, the density distribution of the material layer is optimized by filling it with density according to a global crustal structure model until the geoid of the material layer matches the level point of the surface observation data. The extension continues downwards until the downward extension reaches the target distance. Finally, the geological density information of the target area is generated based on the density distribution of multiple material layers, thus obtaining accurate geological density information. This solves the problem of insufficient accuracy in determining geological density information in related technologies.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a method for determining the stripping of geological density information according to an embodiment of this application; Figure 2 This is a block diagram illustrating a stripping and determining device for geological density information according to an embodiment of this application. Figure 3 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0017] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0018] In related technologies, taking CRUST2.0 (a global crustal structure model) as an example, although CRUST2.0 provides 360 crustal types, its rough resolution of 2° results in inaccurate assignment of crustal density values ​​for many regions. For instance, in regions with numerous lakes and icebergs, CRUST2.0 shows zero thickness for both ice and water layers across all crustal types in that region; that is, neither the first layer (ice layer) nor the second layer (water layer) exists. This is clearly inconsistent with reality, and the reason lies in CRUST2.0's resolution limitations. Although the water and snow-covered areas in these regions are numerous and large, none exceed 2° × 2° (approximately 200 km × 200 km), and therefore cannot be represented in the CRUST2.0 model. The upgraded version of CRUST2.0, CRUST1.0, may still not be able to resolve the issues of water and ice layers at a resolution of 1°×1° (approximately 100 km×100 km). Since CRUST2.0 gives zero thickness for the first and second layers for all crustal types in the region, the crustal density structure begins from the third layer (soft sedimentary layer). For the third and fourth layers (hard sedimentary layers), the thickness varies in different locations, but the density is constant for each layer; the density of the third layer is 2100 kg / m³, and the density of the fourth layer is 2400 kg / m³. From the fifth to the seventh layer, the thickness varies for each layer, and the lateral density also changes, no longer being constant. Therefore, accurately determining the "density problem" remains challenging.

[0019] Therefore, embodiments of this application provide a method, apparatus, electronic device, and medium for determining the stripping of geological density information, which will be described in detail below.

[0020] The following description, with reference to the accompanying drawings, outlines a method, apparatus, electronic device, and medium for determining geological density information through stripping according to embodiments of this application. Addressing the issue of insufficient accuracy in determining geological density information in related technologies mentioned in the background section, this application provides a method for determining geological density information through stripping. In this method, surface observation data of a target area is acquired and input into a stripping model. The stripping model outputs the density distribution of multiple material layers in the target area. Specifically, the lower interface of the shallow surface model of the target area in the stripping model begins to extend downwards. Each extension creates a new material layer by combining the new interface with the lower interface of the previous material layer. For each material layer, density is filled according to a global crustal structure model to optimize the density distribution until the geoid of the material layer matches the level point of the surface observation data. The downward extension continues until the downward distance reaches the target distance. Finally, the geological density information of the target area is generated based on the density distribution of multiple material layers, resulting in accurate geological density information. This solves the problem of insufficient accuracy in determining geological density information in related technologies.

[0021] Specifically, Figure 1 This is a flowchart illustrating a method for determining the stripping of geological density information provided in an embodiment of this application.

[0022] like Figure 1 As shown, the method for determining the stripping of geological density information includes the following steps: In step S101, surface observation data of the target area are acquired.

[0023] Among them, surface observation data typically includes geodetic elevation information obtained through technologies such as GPS (Global Positioning System) leveling, as well as other forms of surface feature data, including GPS leveling data, topographic data, and gravity field data, which provide the real ground information needed to adjust and verify the density distribution of the upper crust.

[0024] In step S102, surface observation data is input into the stripping model, and the stripping model outputs the density distribution of multiple material layers in the target area. The lower interface of the shallow surface model of the target area of ​​the stripping model begins to extend downward. Each extension of the new interface and the lower interface of the previous material layer constitute a new material layer. For each material layer, the density of the material layer is filled according to the global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer matches the level point of the surface observation data. The extension continues downward until the downward extension distance reaches the target distance.

[0025] The stripping model is a theoretical method that uses known shallow surface models to determine a high-precision geoid by iteratively adjusting the density distribution of material layers. The shallow surface model refers to a geological structure model based on the Earth's surface to a certain depth, including information such as topography and crustal density distribution. The specific construction method will be described in detail below and will not be repeated here. Material layers are the hierarchical structure of the Earth's interior composed of materials of different densities, such as the different layers of the crust. Global crustal structure models, such as CRUST1.0 (a global crustal model that provides detailed information on the crustal structure between the Earth's surface and the Moho (the boundary between the crust and mantle),) provide preliminary estimates of the thickness and density of each crustal layer. The target distance is set according to actual needs and is not specifically limited here.

[0026] Understandably, in this embodiment, surface observation data is first input into the stripping model. The model starts from the lower interface of the shallow surface model of the target area and extends downwards layer by layer to construct new material layers. Each time it extends, the new interface and the lower interface of the previous material layer constitute a new material layer. The material layer is initially filled with density according to the global crustal structure model. Then, by comparing the calculated geoid with the leveling points in the actual surface observation data, the density distribution of the material layer is iteratively optimized until the two match. This process is repeated to gradually extend the material layer downwards until the predetermined target distance is reached. This achieves high-resolution refinement of the density distribution of each material layer, thereby providing a more accurate understanding of the underground geological structure.

[0027] In this embodiment of the application, the first material layer is located between the upper and lower interfaces of the shallow surface model.

[0028] It is understood that the upper interface of the shallow surface model in this application embodiment is the actual surface of the Earth, while the lower interface is a closed surface selected according to the research requirements. This closed surface is located below the geoid and maintains a certain distance to meet the modeling requirements. The first material layer is defined between these two interfaces, namely the crustal portion from the surface to the selected closed surface, which constitutes the first analysis unit in the stripping method for further crustal density refinement.

[0029] In this embodiment of the application, before inputting surface observation data into the stripping model, the method further includes: constructing an upper interface of the shallow surface layer based on digital terrain data and marine dynamic terrain data; using the extension surface of the reference ellipsoid as the lower interface of the shallow surface layer; obtaining a crustal density model and a surface ice layer model from a database; replacing the ice layer information of the crustal density model with the surface ice layer model, and constructing a refined crustal density model using the crustal density model after replacing the ice layer information; and performing density filling on the shallow surface layer model based on the refined crustal density model.

[0030] It is understood that, before inputting surface observation data into the stripping model, this embodiment first needs to construct the upper interface of the shallow surface layer based on digital topographic data and hydrodynamic topographic data, and determine the upper interface of the shallow surface layer. The upper interface includes the topographic height of the land area and the seabed topography of the ocean area. Then, the extension surface of the reference ellipsoid is used as the lower interface of the shallow surface layer, and the crustal density model and the surface ice layer model are obtained from the database. The ice layer information of the crustal density model is replaced by the surface ice layer model, and the refined crustal density model is constructed using the crustal density model after the ice layer information replacement. In this way, a three-dimensional shallow surface model is constructed from the surface containing land and seabed topography to the extension surface of the reference ellipsoid, which also includes surface ice layer information. This lays the foundation for the subsequent use of the stripping method to refine the crustal density distribution, ensuring that the shallow surface model used contains detailed topographic information, thereby improving the accuracy of crustal density refinement.

[0031] In this embodiment, the stripping model is also used to calculate the underground gravitational potential; including: discretizing the shallow surface layer, calculating the gravitational potential generated by the shallow surface layer based on the discretization result; calculating the gravitational potential generated by the internal spherical mass of the target area according to the gravity field model, and calculating the target area based on the gravitational potential generated by the internal spherical mass and the gravitational potential generated by the shallow surface layer. The gravitational potential of internal matter outside the surface; based on the gravitational potential generated in the shallow surface layer and the target area. The gravitational potential information is obtained from the gravitational potential of the internal material of the surface. When determining the geoid based on the definition of the geoid, the position of the geoid is determined by an iterative search method.

[0032] Here, the Γ-plane is the lower surface of the shallow layer of the Earth's surface; the gravitational potential describes the energy per unit mass in a gravitational field and can be used to represent the gravitational effects caused by different material layers inside and on the Earth's surface; the iterative search method is a numerical calculation method that gradually approximates the exact solution of a problem by repeatedly executing a series of calculation steps. Each repetition is called an iteration. In each iteration, the algorithm uses the result obtained in the previous iteration as a new input or starting point to perform more accurate calculations or adjustments until the preset convergence conditions are met.

[0033] Understandably, the embodiments of this application first divide the shallow surface layer into discrete units and calculate the gravitational potential generated at each point in space. At the same time, the gravitational potential generated by the mass of the sphere deep inside the target area is obtained using a global gravity field model. The gravitational potential generated by the local internal material below the Γ plane is calculated. The gravitational potential of the shallow surface layer is superimposed with the gravitational potential of the local internal material to obtain more accurate total gravitational potential information of the target area. Based on this, according to the definition of the geoid as a gravity equipotential surface, the shape of the surface is continuously adjusted by an iterative search method until the calculated gravitational potential of each point on it tends to be consistent, thereby determining the spatial position of the geoid.

[0034] In this context, the grid profile of the material layer refers to dividing the study area into a series of regular grids, each grid representing an analysis unit. For each such unit, the gravitational influence of its internal material on the surrounding environment can be calculated. Spherical harmonic integrals are a mathematical processing method used to analyze and represent the physical field of spherical or near-spherical objects. By integrating the gravitational potential at various points within the material layer, the density distribution of the material layer is gradually optimized to match actual surface observation data.

[0035] It is understood that the stripping model in this application embodiment is not only used to adjust the density distribution of each layer of the crust to match the surface observation data, but also to calculate the gravitational potential of each material layer at each point on its grid profile. For each grid point in the selected area, the gravitational potential generated at that point due to the presence of the underlying material layer is calculated. Based on the gravitational potential information of these points, the spherical harmonic integral method is used for processing, thereby obtaining a more accurate density distribution of the entire material layer, improving the accuracy of understanding the underground geological structure, and making the determination of the geoid more accurate. This enables the effective use of surface observation data to refine the crustal density model and enhances the understanding of the Earth's internal structure.

[0036] In this embodiment of the application, the shallow surface layer is discretized, and the gravitational potential generated by the shallow surface layer is calculated based on the discretization result, including: identifying the actual distance between the discretized region and the target point; if the actual distance is less than or equal to a distance threshold, the gravitational potential is calculated using a cylindrical model; if the actual distance is greater than the distance threshold, the gravitational potential is calculated using a wedge model.

[0037] Among them, the distance threshold is a preset distance value, which can be set according to actual needs and is not specifically limited here; the cylinder model is a simplified model for calculating the contribution of nearby matter to the gravitational field. It assumes that the matter is distributed in a cylinder perpendicular to the ground and has a uniform density. It is suitable for accurately calculating the gravitational potential of the matter layer near the target point; the wedge model is a simplified model for calculating the contribution of distant matter to the gravitational field. This model takes into account the distribution of matter along a slope and can be used to quickly estimate the gravitational potential of the matter layer far from the target point.

[0038] It is understood that, in calculating the gravitational potential at each point on the grid profile of the material layer in this embodiment of the application, it is first necessary to determine the actual distance between each discrete region on the grid profile and the target point. If the actual distance is less than or equal to a set distance threshold, the cylindrical model is used for accurate gravitational potential calculation because the cylindrical model can provide higher calculation accuracy for regions close to the target point. Conversely, if the actual distance is greater than the set distance threshold, the wedge model is used to calculate the gravitational potential. In this case, the wedge model can more efficiently estimate the influence of distant matter on the gravitational field. Combining these two models can achieve high accuracy while ensuring computational efficiency.

[0039] In step S103, geological density information of the target area is generated based on the density distribution of multiple material layers.

[0040] The density distribution of multiple material layers refers to the density information of each layer obtained by stratifying the Earth's crust through the above steps and refining it layer by layer.

[0041] It is understood that the embodiments of this application can integrate the density distribution of multiple material layers to generate overall geological density information of the target area. Specifically, it summarizes the refined density data of each layer to form a dataset that comprehensively reflects the density characteristics of the geological structure of the area from the surface to the deep layers, thereby achieving an accurate depiction of the density distribution of different layers of the Earth's crust, such as sedimentary layers, upper crust, middle crust, and lower crust.

[0042] In this embodiment of the application, the geological density information includes crustal density distribution information and mantle density distribution information.

[0043] Among them, crustal density distribution information describes the density variations at different locations and depths within the crust, i.e., the outermost layer of the Earth; mantle density distribution information involves the density characteristics of the mantle region below the crust up to the core.

[0044] It is understood that the geological density information in the embodiments of this application includes at least one of crustal density distribution information or mantle density distribution information. Specifically, by analyzing the data obtained from the stripping model, details of the density distribution from the surface to the depths of the crust and even extending to the mantle within the target area can be obtained, covering an accurate description of the density characteristics of each layer of the crust. The comprehensive geological density information obtained not only helps to reveal the complexity of underground geological structures, but also provides basic data support for resource exploration, seismic activity research, and broader earth science research.

[0045] According to the method for determining geological density information by stripping proposed in the embodiments of this application, surface observation data of the target area is acquired and input into the stripping model. The stripping model outputs the density distribution of multiple material layers in the target area. Specifically, the lower interface of the shallow surface model of the target area in the stripping model begins to extend downward. Each extension of the new interface and the lower interface of the previous material layer constitute a new material layer. For each material layer, the density of the material layer is filled according to the global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer matches the level point of the surface observation data. The extension continues downward until the downward extension distance reaches the target distance. Finally, the geological density information of the target area is generated based on the density distribution of multiple material layers to obtain accurate geological density information.

[0046] The method for determining the stripping of geological density information will be further described below through a specific embodiment.

[0047] Based on relevant technologies, a high-precision geoid can be determined using a known and accurate shallow surface model, especially its density distribution. Conversely, if a geoid is determined based on a certain initial crustal density distribution, how to refine the crustal density model according to surface observation constraints, such as GPS leveling, is a problem that urgently needs to be solved. To address this, this embodiment proposes a theoretical method—the "stripping method"—as follows: (1) Select a reference ellipsoid extension surface S1, and denote the material layer between the Earth's surface and surface S1 as L1. Based on the density distribution of layer L1 provided by the crustal density model, a geoid can be determined through relevant techniques, denoted as G1. Compare the determined geoid with the GPS level point, and adjust the density distribution of layer L1 so that G1 matches the GPS level point best. In this way, the density distribution of layer L1 is refined, and the refined L1 is denoted as D1.

[0048] (2) Extend the closed surface S1 downward (for example, 1 km) to obtain a new interface S2. The material layer between surface S1 and surface S2 is denoted as L2. Based on the density distribution of layer D1 and the density distribution of layer L2 provided by the initial density model, a geoid can be determined using the new theoretical method, denoted as G2. The determined geoid is compared with the GPS level point. By adjusting the density distribution of layer L2, G2 is made to match the GPS level point best. In this way, the density distribution of layer L2 is refined. The refined L2 is denoted as D2. (3) The above process can be repeated until the density distribution of the entire crust is refined.

[0049] It is important to note that: S1 must be located below the geoid and at a certain distance to meet the requirements of the new theoretical method for the lower surface of the shallow surface model. Thus, the "first shallow surface layer" L1, which is the boundary between the surface and S1, may contain several layers of crustal density model in some areas.

[0050] In each 1◦ × 1◦ grid profile, there may be several unknown parameters (each grid in each layer has one undetermined parameter). Then, the unknown parameters for each grid layer are determined using the Monte Carlo heuristic (a method of numerical calculation through random sampling, used in crustal density distribution studies to simulate different density distributions by generating a large number of random parameter combinations, and then comparing the simulation results with actual surface observation data to optimize the model parameters) or the least squares method, thus determining D1. Next, when determining Di (i>1), the number of unknown parameters decreases, and each grid layer contains only a portion of a single layer of the crustal density model. This can be achieved by appropriately selecting Li (i>1).

[0051] The essence of the stripping method lies in refining the uppermost shallow surface layer, then allowing the underlying material layers to influence the geoid, thereby refining the second material layer, and so on, until all material layers are refined. Theoretically, the stripping method can be used not only to refine the density distribution of the Earth's crust but also to refine the density distribution of the upper mantle.

[0052] Next, the stripping and determination apparatus for geological density information according to the embodiments of this application is described with reference to the accompanying drawings.

[0053] Figure 2 This is a block diagram of a device for determining the stripping of geological density information according to an embodiment of this application.

[0054] like Figure 2 As shown, the stripping and determination device 10 for geological density information includes: an acquisition module 201, an input module 202, and a generation module 203.

[0055] The acquisition module 201 is used to acquire surface observation data of the target area; the input module 202 is used to input the surface observation data into the stripping model, and the stripping model outputs the density distribution of multiple material layers in the target area. The lower interface of the shallow surface model of the target area in the stripping model begins to extend downward. Each extension of the new interface and the lower interface of the previous material layer constitute a new material layer. For each material layer, the density of the material layer is filled according to the global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer matches the level point of the surface observation data. The extension continues downward until the downward extension distance reaches the target distance; the generation module 203 is used to generate geological density information of the target area based on the density distribution of multiple material layers.

[0056] In this embodiment of the application, the geological density information includes at least one of crustal density distribution information and mantle density distribution information.

[0057] In this embodiment of the application, the first material layer is located between the upper and lower interfaces of the shallow surface model.

[0058] In this embodiment of the application, a determination module is further included, wherein the determination module is further configured to: before inputting the surface observation data into the stripping model, further include: determining the upper interface of the target area based on the digital elevation model and the global ocean gravity field and seafloor topography model, determining the geoid of the target area based on the global geoid model; and constructing a shallow surface model using the geoid as the lower interface of the target area.

[0059] In this embodiment of the application, the stripping model is also used to: calculate the gravitational potential at each point on the grid profile of the material layer; and obtain the density distribution of the material layer by performing spherical harmonic integration based on the gravitational potential at each point.

[0060] In this embodiment of the application, calculating the gravitational potential of each point on the grid profile of the material layer includes: calculating the actual distance between each point on the grid profile and the target point; if the actual distance is less than or equal to a distance threshold, then calculating the gravitational potential using a cylindrical model; if the actual distance is greater than the distance threshold, then calculating the gravitational potential using a wedge model.

[0061] It should be noted that the explanation of the above-mentioned method for determining the stripping of geological density information also applies to the device for determining the stripping of geological density information in this embodiment, and will not be repeated here.

[0062] According to the geological density information stripping and determination device proposed in the embodiments of this application, surface observation data of the target area is acquired and input into the stripping model. The stripping model outputs the density distribution of multiple material layers in the target area. Specifically, the lower interface of the shallow surface model of the target area of ​​the stripping model begins to extend downward. Each extension of the new interface and the lower interface of the previous material layer constitute a new material layer. For each material layer, the density of the material layer is filled according to the global crustal structure model to optimize the density distribution of the material layer until the geoid of the material layer matches the level point of the surface observation data. The extension continues downward until the downward extension distance reaches the target distance. Finally, the geological density information of the target area is generated according to the density distribution of multiple material layers to obtain accurate geological density information.

[0063] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 301, the processor 302, and the computer program stored on the memory 301 and capable of running on the processor 302.

[0064] When the processor 302 executes the program, it implements the method for determining the stripping of geological density information provided in the above embodiments.

[0065] Furthermore, electronic devices also include: Communication interface 303 is used for communication between memory 301 and processor 302.

[0066] The memory 301 is used to store computer programs that can run on the processor 302.

[0067] The memory 301 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0068] If the memory 301, processor 302, and communication interface 303 are implemented independently, then the communication interface 303, memory 301, and processor 302 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0069] Optionally, in a specific implementation, if the memory 301, processor 302, and communication interface 303 are integrated on a single chip, then the memory 301, processor 302, and communication interface 303 can communicate with each other through an internal interface.

[0070] Processor 302 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of this application.

[0071] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for determining the stripping of geological density information.

[0072] This application also provides a computer program product, including a computer program or instructions, which, when executed, implement the above-described method for determining the stripping of geological density information.

[0073] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0074] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0075] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0076] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0077] Those skilled in the art will understand that all or part of the steps of the methods implementing the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0078] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method of stripping determination of geodetic density information, characterized in that, The method comprises the following steps: obtaining surface observation data of a target area; inputting the surface observation data into a stripping model, the stripping model outputting density distribution of multiple material layers of the target area, wherein the stripping model extends downward from the lower interface of a surface shallow layer model of the target area, the new interface at each extension and the lower interface of the previous material layer form a new material layer, for each material layer, the material layer is filled with density according to a global crust structure model, the density distribution of the material layer is optimized until the geoid of the material layer matches the leveling points of the surface observation data, and the extension continues until the distance of the downward extension reaches a target distance; generating geological density information of the target area according to the density distribution of the multiple material layers.

2. The method of stripping determination of geodetic density information according to claim 1, characterized in that, The geological density information comprises crust density distribution information and mantle density distribution information.

3. The method of stripping determination of geodetic density information according to claim 1, characterized in that, The first material layer is between the upper interface and the lower interface of the surface shallow layer model.

4. The method of stripping determination of geodetic density information according to claim 1, characterized in that, Before inputting the surface observation data into the stripping model, the method further comprises the following steps: constructing the upper interface of the surface shallow layer according to digital terrain data and seawater dynamic terrain data; taking the continuation surface of a reference ellipsoid as the lower interface of the surface shallow layer; obtaining a crust density model and a surface ice layer model from a database; replacing the ice layer information of the crust density model with the surface ice layer model, and constructing a refined crust density model using the crust density model with the ice layer information replaced; performing density filling on the surface shallow layer model based on the refined crust density model.

5. The method of stripping determination of geodetic density information according to claim 1, characterized in that, The stripping model is also used to calculate the underground gravity potential, comprising: discretizing the surface shallow layer, and calculating the gravity potential generated by the surface shallow layer based on the discretization result; calculating a gravitational potential generated by an internal spherical mass of the target region according to the gravity field model, and calculating the target region a gravitational potential of internal matter outside the surface According to the gravity potential generated by the near-surface and a target area The gravity potential of the internal matter of the surface is used to obtain gravity potential information, and an iterative search method is used to determine the position of the geoid based on the definition of the geoid.

6. The method of stripping determination of geodetic density information according to claim 5, characterized in that, the discretization of the surface shallow layer and the calculation of the gravity potential generated by the surface shallow layer based on the discretization result, comprising: identifying the actual distance between the discrete area and the target point; if the actual distance is less than or equal to a distance threshold, calculating the gravity potential by using a cylinder model; if the actual distance is greater than the distance threshold, calculating the gravity potential by using a wedge model.

7. An apparatus for stripping determination of geological density information, characterized by The method comprises: an acquisition module configured to acquire surface observation data of a target area; an input module configured to input the surface observation data into a stripping model, the stripping model outputting density distribution of multiple material layers of the target area, wherein the stripping model extends downward from the lower interface of a surface shallow layer model of the target area, the new interface at each extension and the lower interface of the previous material layer form a new material layer, for each material layer, the material layer is filled with density according to a global crust structure model, the density distribution of the material layer is optimized until the geoid of the material layer matches the leveling points of the surface observation data, and the extension continues until the distance of the downward extension reaches a target distance; a generation module configured to generate geological density information of the target area according to the density distribution of the multiple material layers.

8. An electronic device, comprising: The method comprises: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the stripping determination method of the geological density information according to any one of claims 1-6.

9. A computer readable storage medium having stored thereon a computer program or instructions, characterized in that, The computer program or instructions, when executed, implement the method of stripping determination of geological density information according to any one of claims 1-6.

10. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions, when executed, implement the method of stripping determination of geological density information according to any one of claims 1-6.

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