Modeling method and device for geological model

Abstract

The application provides a modeling method and device of a geological model, which can be applied to the fields of geological engineering and automatic modeling technology. The method comprises the following steps: initializing a target region based on basic geological data of the target region to obtain basic geological attribute data of the target region; remapping a plurality of initial geological units to obtain a plurality of corrected geological units; dividing the plurality of corrected geological units into a plurality of block partitions according to boundary position information in the basic geological attribute data; fitting physical property parameters of the plurality of block partitions based on the physical property parameters corresponding to the boundary position information of the plurality of block partitions to obtain simulation parameters of the plurality of block partitions; and performing visual processing on the plurality of block partitions and the simulation parameters to obtain a visual result of a geological model of the target region.

Description

Technical Field

[0001] This application relates to the fields of geological engineering and automated modeling technology, and specifically to a modeling method and apparatus for geological models. Background Technology

[0002] With advancements in geophysical and other multi-source observation technologies and analytical methods, massive amounts of observational data on regional lithosphere structure and surface deformation have been gradually accumulated. Using this vast amount of observational data as constraints, high-resolution geological models can be constructed to simulate and reproduce the dynamic evolution of multi-physics fields in the deep Earth, revealing the processes and mechanisms of volcanic eruptions, earthquakes, and deep mineralization.

[0003] However, current 3D geological modeling usually relies on manual interaction and is completed through a graphical interface. When modeling complex geological structures based on multi-source observation data such as topographic relief and geophysics, it is difficult to process massive amounts of data quickly. Furthermore, when segmenting the geometric model of complex structures, problems such as data omission and computer interface lag are prone to occur, resulting in reduced modeling accuracy and efficiency. Summary of the Invention

[0004] In view of the above problems, this application provides a modeling method and apparatus for geological models.

[0005] According to the first aspect of this application, a method for modeling a geological model is provided, comprising: initializing the target area based on basic geological data of the target area to obtain basic geological attribute data of the target area, the basic geological attribute data including geological attribute data of multiple sampling points in the target area; remapping multiple initial geological units based on depth data in the basic geological attribute data used to represent topographic elevation and crustal stratification to obtain multiple modified geological units, the initial geological units being obtained by dividing the regional range of the target area based on a preset division granularity, the regional range being determined according to the longitude and latitude in the basic geological attribute data; dividing the multiple modified geological units into multiple block partitions based on the boundary location information in the basic geological attribute data used to represent the block range; fitting the physical property parameters of each of the multiple block partitions based on the physical property parameters corresponding to the boundary location information of each of the multiple block partitions to obtain simulation parameters of each of the multiple block partitions; and visualizing the multiple block partitions and the simulation parameters of each of the multiple block partitions to obtain a geological model of the target area.

[0006] According to an embodiment of this application, based on the boundary location information used to represent the extent of a land parcel in the basic geological attribute data, multiple modified geological units are divided into multiple land parcel partitions, including: determining the land parcel edges of the multiple land parcel partitions and the respective extents of the multiple land parcel partitions based on the boundary location information; for a first modified geological unit that differs from the boundary location information, dividing the first modified geological unit into a land parcel partition corresponding to the extent to which the modified geological unit belongs; for a second modified geological unit that has the same boundary location information, determining the land parcel partition to which the modified geological unit belongs based on the positional relationship between the second modified geological unit and the edges of the multiple land parcels.

[0007] According to an embodiment of this application, the basic geological attribute data includes the seismic wave velocity of each of multiple sampling points in a three-dimensional mesh model of the target area; the geological attribute data also includes the category of each of the multiple sampling points, which includes regular sampling points and low-velocity sampling points; the category of the sampling points is determined by the following method: based on a preset seismic wave velocity threshold and the seismic wave velocity of each of the multiple sampling points, the multiple sampling points are divided into low-velocity sampling points and regular sampling points, wherein the seismic wave velocity of the low-velocity sampling points is less than the seismic wave velocity threshold, and the seismic wave velocity of the regular sampling points is greater than or equal to the velocity threshold.

[0008] According to an embodiment of this application, the land parcel zoning further includes anomaly zoning; the anomaly zoning is determined by: determining anomaly regions of seismic wave velocity from a three-dimensional mesh model based on the location of at least one low-velocity sampling point; determining anomalous geological units belonging to the anomaly regions of seismic wave velocity from multiple modified geological units based on the correspondence between the three-dimensional mesh model and multiple modified geological units, and determining the anomaly zoning based on at least one anomalous geological unit.

[0009] According to embodiments of this application, the simulation parameters of each of the multiple land parcel partitions include simulation parameters of a first modified geological unit and simulation parameters of a second modified geological unit within the land parcel partition. Based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, the physical property parameters of each of the multiple land parcel partitions are fitted to obtain the simulation parameters of each of the multiple land parcel partitions, including: for each second modified geological unit, determining the physical property parameters of the land parcel partition where the second modified geological unit is located; using the mean of the physical property parameters within the land parcel partition as the simulation parameters of the second modified geological unit; for each first modified geological unit, based on the boundary location information of the land parcel partition to which the first modified geological unit belongs, the simulation parameters of the second modified geological unit, and the location of the first modified geological unit, using an interpolation algorithm to determine the simulation parameters of the first modified geological unit.

[0010] According to an embodiment of this application, based on the depth data in the basic geological attribute data used to represent topographic elevation and crustal stratification, multiple initial geological units are remapped to obtain multiple modified geological units, including: determining the edge shape and internal structure of the target area based on topographic elevation and depth data, wherein the edge shape is determined according to the topographic elevation and the internal structure is determined according to the depth of the crustal stratification interface; and remapping the multiple initial geological units based on the edge shape and internal structure to obtain modified geological units corresponding to the multiple initial geological units respectively.

[0011] According to an embodiment of this application, multiple land parcel partitions and their respective simulation parameters are visualized to obtain a geological model of the target area. This includes: for each land parcel partition, rendering a geological sub-model corresponding to the land parcel partition based on its shape and simulation parameters, wherein the shape of the geological sub-model is determined according to the shape of the land parcel partition, and the color of the geological sub-model is determined according to the simulation parameters of the land parcel partition; and stitching together the multiple geological sub-models based on the positional relationship between the multiple land parcel partitions to obtain a geological model of the target area.

[0012] According to an embodiment of this application, the target area is initialized based on the basic geological data of the target area to obtain the basic geological attribute data of the target area, including: constructing a three-dimensional mesh model for the target area based on the regional range and modeling accuracy requirements of the target area, wherein the three-dimensional mesh model includes multiple sampling points and edges between the multiple sampling points; determining the edge geological attribute data of multiple edge sampling points located at the edges of the three-dimensional mesh model based on the basic geological data; determining the internal geological attribute data of each of the multiple internal sampling points using a spatial interpolation algorithm based on the edge geological attribute data, the positional relationship between the edge sampling points and multiple internal sampling points located inside the three-dimensional mesh model; and using the edge geological attribute data and the internal geological attribute data as the basic geological attribute data.

[0013] According to embodiments of this application, the basic geological data and basic geological attribute data include at least one of the following: latitude and longitude data, depth data; the method for constructing a geological model further includes: performing coordinate transformation based on latitude and longitude data and depth data to obtain data in the Cartesian coordinate system corresponding to the basic geological attribute data.

[0014] A second aspect of this application provides a geological modeling apparatus, comprising: an initialization module for initializing the target area based on basic geological data of the target area to obtain basic geological attribute data of the target area, the basic geological attribute data including geological attribute data of multiple sampling points in the target area; a remapping module for remapping multiple initial geological units based on depth data representing topographic elevation and crustal stratification in the basic geological attribute data to obtain multiple modified geological units, the initial geological units being obtained by dividing the area of ​​the target area based on a preset granularity, the area being determined according to longitude and latitude in the basic geological attribute data; a partitioning module for dividing the multiple modified geological units into multiple block partitions based on boundary location information representing block extent in the basic geological attribute data; a fitting module for fitting physical property parameters of the multiple block partitions based on physical property parameters corresponding to the boundary location information of each of the multiple block partitions to obtain simulation parameters of each of the multiple block partitions; and a processing module for visualizing the multiple block partitions and their respective simulation parameters to obtain a geological model of the target area.

[0015] According to embodiments of this application, the target area is divided into initial geological units based on a preset granularity. Then, based on depth data representing topographic elevation and crustal stratification from basic geological attribute data, the external shape and internal structure of the target area are determined. This allows for the remapping of multiple initial geological units to obtain multiple modified geological units, achieving fully automated modeling of the external shape of the geological model of the target area and improving modeling efficiency. Following the boundary location information representing the block extent, the remapped modified geological units are divided into multiple block partitions. Simulation parameters are determined for each block partition, enabling automated filling of the physical property parameters of the geological model, further improving modeling efficiency and ensuring modeling accuracy. Attached Figure Description

[0016] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments of this application with reference to the accompanying drawings.

[0017] Figure 1 The diagram illustrates an application scenario of the geological modeling method and apparatus according to embodiments of this application.

[0018] Figure 2 A flowchart of a modeling method for a geological model according to an embodiment of this application is shown.

[0019] Figure 3A schematic diagram illustrating the determination of simulation parameters according to an embodiment of this application is shown.

[0020] Figure 4 A structural block diagram of a modeling apparatus for a geological model according to an embodiment of this application is shown.

[0021] Figure 5 A block diagram of an electronic device suitable for implementing a modeling method for geological models according to an embodiment of this application is shown. Detailed Implementation

[0022] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0024] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0025] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0026] In the technical solution of this application, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0027] In scenarios involving automated decision-making using personal information, the methods, devices, and systems provided in this application all offer users corresponding entry points for choosing to agree to or reject the automated decision-making results; if the user chooses to reject, the process proceeds to the expert decision-making stage. Here, "automated decision-making" refers to activities that automatically analyze and make decisions through computer programs. Here, "expert decision-making" refers to activities where personnel specializing in a particular field, possessing specialized experience, knowledge, and skills, and reaching a certain level of professional expertise make decisions.

[0028] This application provides a geological modeling method, comprising: initializing the target area based on basic geological data of the target area to obtain basic geological attribute data of the target area, the basic geological attribute data including geological attribute data of multiple sampling points in the target area; remapping multiple initial geological units based on depth data in the basic geological attribute data used to represent topographic elevation and crustal stratification to obtain multiple modified geological units, the initial geological units being obtained by dividing the regional range of the target area based on a preset division granularity, the regional range being determined according to the longitude and latitude in the basic geological attribute data; dividing the multiple modified geological units into multiple block partitions according to the boundary location information in the basic geological attribute data used to represent the block range; fitting the physical property parameters of each of the multiple block partitions based on the physical property parameters corresponding to the boundary location information of each of the multiple block partitions to obtain simulation parameters of each of the multiple block partitions; and visualizing the multiple block partitions and their simulation parameters to obtain a geological model of the target area.

[0029] Figure 1 The diagram illustrates an application scenario of the geological modeling method and apparatus according to embodiments of this application.

[0030] like Figure 1As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0031] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as web browser applications, search applications, instant messaging tools, email clients, etc. (for example only).

[0032] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to portable computers, desktop computers, and high-performance supercomputers.

[0033] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0034] It should be noted that the geological modeling method provided in this application embodiment can generally be executed by server 105. Correspondingly, the geological modeling apparatus provided in this application embodiment can generally be located in server 105. The geological modeling method provided in this application embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the geological modeling apparatus provided in this application embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0035] It should be understood that Figure 1The number of first terminal devices, second terminal devices, third terminal devices, networks, and servers shown in the diagram is merely illustrative. Depending on implementation needs, any number of first terminal devices, second terminal devices, third terminal devices, networks, and servers can be included.

[0036] The following will be based on Figure 1 The described scene, through Figures 2-3 The modeling method for the geological model in the embodiments of this application will be described in detail.

[0037] Figure 2 A flowchart of a modeling method for a geological model according to an embodiment of this application is shown.

[0038] like Figure 2 As shown, the geological modeling method of this embodiment includes operations S210 to S250.

[0039] In operation S210, the target area is initialized based on the basic geological data of the target area to obtain the basic geological attribute data of the target area. The basic geological attribute data includes the geological attribute data of multiple sampling points in the target area.

[0040] In this embodiment, basic geological data of the target area can be observed and obtained through disciplines such as geology, geophysics, and geodesy.

[0041] The basic geological attribute data can include longitude, latitude, topographic elevation, Moho discontinuity, upper-middle-lower crustal interface undulation, seismic wave velocity structure, surface heat flow, rock composition, and lithospheric rheological parameters for the target area. Specifically, topographic elevation data can utilize EarthTopography (ETOPO) data. Moho discontinuity and upper-middle-lower crustal interface undulation can be obtained by referencing a digital model of the global crustal structure to determine the crustal layering. Seismic wave velocity structure data can refer to the velocity distribution provided by the digital model of the global crustal structure, further combined with the velocity structure provided by a three-dimensional high-resolution seismic wave velocity reference model and the latest local densified data results for the corresponding target area as constraints. Surface heat flow data uses the actual heat flow observed locally on the surface as the boundary input constraint for the temperature field of the geological model; the surface heat flow data can directly reference the latest regional geothermal heat flow dataset. Lithospheric rheological parameters can be set by referring to various rheological parameters obtained from experiments on different rock compositions.

[0042] Using nodes of a pre-built 3D mesh model as sampling points for a geological model, the geological attribute data of multiple sampling points in the target area are obtained using spatially discrete basic geological attribute data.

[0043] In operation S220, based on the depth data used to represent topographic elevation and crustal stratification in the basic geological attribute data, multiple initial geological units are remapped to obtain multiple corrected geological units. The initial geological units are obtained by dividing the target area based on a preset division granularity. The area range is determined according to the longitude and latitude in the basic geological attribute data.

[0044] In this embodiment, depth data such as the Moho discontinuity and the upper-middle-lower crustal interface undulation in the basic geological attribute data are used to represent crustal stratification. Based on a preset granularity, the regional scope of the target area is divided to obtain initial geological units. The preset granularity can be determined based on the actual computational needs of the target area.

[0045] Based on the topographic elevation data, Moho undulation, and depth data such as the upper-middle-lower crustal interface undulation in the basic geological attribute data, the external shape and internal structure of the target area are determined, and multiple initial geological units are remapped to obtain multiple corrected geological units.

[0046] In operation S230, based on the boundary location information used to represent the extent of the land parcel in the basic geological attribute data, multiple modified geological units are divided into multiple land parcel partitions.

[0047] In this embodiment, the basic geological attribute data may include boundary location information representing the extent of a land parcel. Based on the boundary location information and the location information such as the coordinates of each modified geological unit, multiple modified geological units can be divided into multiple land parcel partitions. For example, if the boundary location information of one or more modified geological units has the same physical properties, they can be divided into the same land parcel partition.

[0048] In operation S240, based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, the physical property parameters of each of the multiple land parcel partitions are fitted to obtain the simulation parameters of each of the multiple land parcel partitions.

[0049] In this embodiment, the boundary location information of each of the multiple land parcel partitions can be used as the basic constraint unit. Based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, the nearest neighbor search and local interpolation algorithms are used for fitting to obtain the simulated parameters of each of the multiple land parcel partitions. The physical property parameters may include parameters such as elastic modulus, viscosity, and density.

[0050] In the S250 operation, multiple plot partitions and their respective simulation parameters are visualized to obtain a geological model of the target area.

[0051] In this embodiment, multiple land parcel partitions and their respective physical property parameters are visualized. Specifically, visualization software can be used to display the multiple land parcel partitions and their respective physical property parameters in three dimensions, thereby obtaining a geological model of the target area.

[0052] According to embodiments of this application, the target area is divided into initial geological units based on a preset granularity. Then, based on depth data representing topographic elevation and crustal stratification from basic geological attribute data, the external shape and internal structure of the target area are determined. This allows for the remapping of multiple initial geological units to obtain multiple modified geological units, achieving fully automated modeling of the external shape of the geological model of the target area and improving modeling efficiency. Following the boundary location information representing the block extent, the remapped modified geological units are divided into multiple block partitions. Simulation parameters are determined for each block partition, enabling automated filling of the physical property parameters of the geological model, further improving modeling efficiency and ensuring modeling accuracy.

[0053] According to an embodiment of this application, based on the boundary location information used to represent the extent of a land parcel in the basic geological attribute data, multiple modified geological units are divided into multiple land parcel partitions, including: determining the land parcel edges of the multiple land parcel partitions and the respective extents of the multiple land parcel partitions based on the boundary location information; for a first modified geological unit that differs from the boundary location information, dividing the first modified geological unit into a land parcel partition corresponding to the extent to which the modified geological unit belongs; for a second modified geological unit that has the same boundary location information, determining the land parcel partition to which the modified geological unit belongs based on the positional relationship between the second modified geological unit and the edges of the multiple land parcels.

[0054] In this embodiment, the edge of a land parcel can be understood as the geometric boundary line used to divide multiple land parcel zones. The range corresponding to each land parcel zone can be the spatial area enclosed by the geometric boundary line of the land parcel zone. Different land parcel zones can be used to represent different geological blocks, such as rock masses of different ages, tectonic units separated by fault zones, etc.

[0055] The first modified geological unit is used to represent a geological unit in which the spatial location of a node in a 3D mesh model is explicitly located within a certain block partition and does not directly intersect or overlap with the boundary of the block partition. For the first modified geological unit, it can be directly assigned to the block partition corresponding to the range to which the modified geological unit belongs based on its coordinate position. Specifically, the nodes of the 3D mesh model can be iterated, and the ray casting method can be used to determine whether the node is located within different block partitions. If it is located within a block partition, it is assigned to the block partition corresponding to the range to which the modified geological unit belongs.

[0056] The second modified geological unit is used to represent a geological unit whose node in the 3D mesh model is located exactly on the edge of a plot within a plot partition, i.e., its location information is the same as or coincides with the boundary location information. For the second modified geological unit, the positional relationship between the second modified geological unit and multiple plot edges can be determined by calculating the distance from the node to each plot edge. By determining the positional relationship between the unit center and each block, the plot partition to which the modified geological unit belongs can be determined.

[0057] According to embodiments of this application, based on the boundary location information of the land parcel, multiple modified geological units are divided into land parcel zones. Using the edges of these zones and their respective corresponding ranges, first modified geological units with different boundary location information are directly assigned to the land parcel zone corresponding to their assigned range. Second modified geological units with the same boundary location information are assigned to land parcel zones based on their positional relationship with the land parcel edges. This solves the problem of ambiguous assignment of modified geological units at land parcel boundaries and the problem of false smoothing of physical property parameters due to insufficient data resolution, ensuring accurate characterization of abrupt changes in mechanical properties at land parcel boundaries.

[0058] According to an embodiment of this application, the basic geological attribute data includes the seismic wave velocity of each of multiple sampling points in a three-dimensional mesh model of the target area; the geological attribute data also includes the category of each of the multiple sampling points, which includes regular sampling points and low-velocity sampling points; the category of the sampling points is determined by the following method: based on a preset seismic wave velocity threshold and the wave velocity of each of the multiple sampling points, the multiple sampling points are divided into low-velocity sampling points and regular sampling points, wherein the seismic wave velocity of the low-velocity sampling points is less than the velocity threshold, and the seismic wave velocity of the regular sampling points is greater than or equal to the velocity threshold.

[0059] In this embodiment, the sampling point can be understood as a regularized grid node corresponding to the region of the three-dimensional grid model. The seismic wave velocity data of the sampling point comes from the regional seismic wave velocity model, such as a high-resolution three-dimensional wave velocity structure model, which is obtained by mapping to each grid node through a grid search algorithm.

[0060] Multiple sampling points can be divided into low-velocity sampling points and regular sampling points based on a preset seismic wave velocity threshold and the individual seismic wave velocities of each sampling point. The preset seismic wave velocity threshold can be understood as a criterion for identifying anomalies, typically determined based on the statistical characteristics of the regional background seismic wave velocity field. For example, the preset seismic wave velocity threshold can be the mean of the background seismic wave velocity minus one or two standard deviations, or an empirical value can be set based on known structural features of the target area.

[0061] For example, low-velocity sampling points typically correspond to anomalous structures in the lithospheric structure, such as partially melted zones, fluid-rich zones, or high-temperature weak layers. Conventional sampling points correspond to normal crust or lithospheric media.

[0062] According to the embodiments of this application, by pre-setting seismic wave velocity thresholds, it is possible to identify and discretize the spatial distribution of anomalies, transforming the continuous seismic wave velocity field into node classification information with clear geological significance. This provides basic geological attribute data support for the geometric delineation of anomalies and the assignment of block zoning values, avoiding the uncertainty of manual interpretation.

[0063] According to an embodiment of this application, the land parcel zoning further includes anomaly zoning; the anomaly zoning is determined by: determining the wave velocity anomaly region from the three-dimensional mesh model based on the location of at least one low-velocity sampling point; determining the anomalous geological unit belonging to the seismic wave velocity anomaly region from the multiple modified geological units based on the correspondence between the three-dimensional mesh model and multiple modified geological units, and determining the anomaly zoning based on at least one anomalous geological unit.

[0064] In this embodiment, the basic geological attribute data may also include the distribution data of local anomalies in the lithospheric structure of the target area. The distribution data of local anomalies in the lithospheric structure can be determined in the following way: using a high-resolution three-dimensional seismic wave velocity structure model of the lithospheric region, by setting a reasonable velocity threshold, and combining it with a pre-constructed three-dimensional mesh model, a mesh search algorithm is used to systematically traverse all nodes of the three-dimensional mesh model, accurately identify and extract the set of nodes whose seismic wave velocity values ​​are lower than the set threshold, and delineate the continuous spatial distribution range of low-velocity anomalies in the lithospheric region through discrete regularized node forms.

[0065] Anomaly zoning can be understood as the zoning of crustal material blocks corresponding to anomalies in seismic wave velocity, typically corresponding to local anomalies within the lithosphere. Based on the location of low-velocity sampling points, anomaly regions in seismic wave velocity are determined from the 3D mesh model. Anomaly regions in seismic wave velocity can be understood as the spatial extent of the set of low-velocity sampling points; by accurately determining the spatial location of these low-velocity sampling points, anomaly regions can be precisely located in the model.

[0066] Based on the correspondence between a 3D mesh model and multiple modified geological units, anomalous geological units belonging to seismic wave velocity anomaly regions are identified from these modified geological units. Anomaly zones are then determined based on at least one anomalous geological unit. An anomalous geological unit represents a modified geological unit belonging to a seismic wave velocity anomaly region. The node information of the 3D mesh model of the seismic wave velocity anomaly region can be mapped to the modified geological units using a mesh search method. Based on the direct correspondence between the nodes of the 3D mesh model and the modified geological units, it is determined whether all nodes of the modified geological unit are located within the velocity anomaly region, or whether the center point of the modified geological unit falls within the velocity anomaly region, thus determining whether the modified geological unit belongs to the anomalous geological unit category. The set of units identified as anomalous geological units forms at least one anomalous geological unit, thus defining the anomalous zone.

[0067] According to embodiments of this application, seismic wave velocity anomaly regions are determined through discrete low-velocity sampling points. Based on the correspondence between a three-dimensional mesh model and multiple modified geological units, anomalous geological units and anomaly zones are determined. Anomaly zones, as a supplement to block zoning, utilize the local characteristics of the spatial distribution of geophysical anomalies. Seismic wave velocity anomaly regions are determined based on low-velocity sampling points, precisely focusing computational resources on these regions. Through localization, the number of interpolation mesh nodes is significantly reduced, lowering memory usage and computational complexity. While improving computational efficiency, refined mesh reconstruction of anomaly morphology is achieved, enhancing the implementation efficiency of geophysical anomalies in the three-dimensional mesh model.

[0068] According to embodiments of this application, the simulation parameters of each of the multiple land parcel partitions include simulation parameters of the first modified geological unit and simulation parameters of the second modified geological unit in the land parcel partition. Based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, the physical property parameters of each of the multiple land parcel partitions are fitted to obtain the simulation parameters of each of the multiple land parcel partitions, including: for each second modified geological unit, determining the physical property parameters of the land parcel partition to which the second modified geological unit is located; using the mean of the physical property parameters within the land parcel partition as the simulation parameters of the second modified geological unit; for each first modified geological unit, based on the boundary location information of the land parcel partition to which the first modified geological unit belongs, the simulation parameters of the second modified geological unit, and the location of the first modified geological unit, using an interpolation algorithm to determine the simulation parameters of the first modified geological unit.

[0069] Figure 3 A schematic diagram illustrating the determination of simulation parameters according to an embodiment of this application is shown.

[0070] like Figure 3As shown, plot A and plot B are adjacent and have the same boundary location information. The physical property parameter of the first modified geological unit I310 in plot A is 10, and the physical property parameter of the first modified geological unit II320 in plot A is 40. The physical property parameter of the first modified geological unit III330 in plot B is 100, and the physical property parameter of the first modified geological unit IV340 in plot B is 200.

[0071] For a second modified geological unit located on an adjacent boundary, the target plot where the center point of the second modified geological unit is located can be determined, and the values ​​of the physical property parameters of the second modified geological unit can be modified to the average value of the physical property parameters of multiple first modified geological units within the target plot.

[0072] For example, if the center point of the second modified geological unit 350 located at the boundary is located in block partition A, and the average value of the physical property parameters of multiple first modified geological units in block partition A is 18, then the physical property parameter value of the second modified geological unit 350 is set to 18.

[0073] The plot partition contains multiple first-corrected geological units. For a first-corrected geological unit located within plot partition A, the simulation parameters within the plot partition are calculated using an interpolation algorithm based on its distance from the adjacent boundary. For example, for the simulation parameters within plot partition A, spatial interpolation of physical property parameters is performed between the first-corrected geological unit I310 and the second-corrected geological unit II320 of plot partition A. That is, the simulation parameters of plot partition A are obtained through spatial interpolation, and the values ​​of these simulation parameters smoothly transition between 10 and 40.

[0074] Similarly, for the simulation parameters within plot partition B, spatial interpolation of physical property parameters is performed between the first modified geological unit III330 and the first modified geological unit IV340 of plot partition B. That is, the simulation parameters of plot partition B are obtained through spatial interpolation, and the values ​​of these simulation parameters smoothly transition between 100 and 200.

[0075] In this embodiment, simulation parameters can be understood as lithospheric physical property parameters used for numerical simulation calculations, including but not limited to elastic modulus, density, viscosity coefficient, and thermal conductivity. These physical property parameters are prior physical property values ​​corresponding to each block partition, and are typically determined based on experimental petrological data or geophysical observation inversion results.

[0076] The spatial location of the second modified geological unit coincides with the boundary of the land parcel, thus connecting multiple adjacent land parcel sub-regions. The boundary locations between adjacent sub-regions exhibit abrupt changes in physical properties due to differences in their respective physical property parameters. Directly using interpolation algorithms to fit these physical property parameters at these locations would result in smoothing of the physical property parameters at the land parcel boundaries. Therefore, for the second modified geological unit, by determining the land parcel sub-region where the center of the second modified geological unit is located, the mean value of the physical property parameters of the corresponding land parcels is calculated, and this mean value is used as the simulation parameter for the second modified geological unit.

[0077] The first modified geological unit uses the boundary location information of its constituent land parcels as constraints and physical property parameters within the first modified geological unit as known control points to calculate and determine the simulation parameters of the first modified geological unit using interpolation algorithms. These interpolation algorithms include, but are not limited to, inverse distance weighted interpolation, radial basis function interpolation, or Kriging interpolation.

[0078] According to embodiments of this application, by distinguishing between different assignment strategies for the first modified geological unit representing the interior of a block partition and the second modified geological unit representing the boundary of the block partition, a reasonable transition of physical property parameters at the block boundary is achieved. This avoids smoothing the block boundary, ensures abrupt changes in physical properties at the block boundary, and guarantees the continuity and smoothness of the parameter field within the block. This accurately characterizes the lateral discontinuities in the lithospheric mechanical properties, effectively avoiding the problem of false homogenization of physical property parameters at the block boundary due to limited resolution of observational data, and ensuring that the simulated parameter values ​​can truly reflect the spatial abrupt changes in the Earth's deep structure.

[0079] According to an embodiment of this application, based on the depth data in the basic geological attribute data used to represent topographic elevation and crustal stratification, multiple initial geological units are remapped to obtain multiple modified geological units, including: determining the edge shape and internal structure of the target area based on elevation and depth data, wherein the edge shape is determined according to the topographic elevation and the internal structure is determined according to the crustal stratification depth data; and remapping the multiple initial geological units based on the edge shape and internal structure to obtain modified geological units corresponding to the multiple initial geological units respectively.

[0080] In this embodiment, the edge shape of the target area is determined based on the terrain elevation. The edge shape can be understood as the geometric morphology of the model's surface, as depicted by terrain elevation data, such as undulating features like mountain peaks, valleys, and steep slopes, which determines the spatial distribution of the upper boundary of the three-dimensional model. The internal structure of the target area is determined based on crustal layering. The internal structure can be understood as the layered geometric framework within the model, determined by data from the interfaces of various crustal layers, which can be used to reflect the interface undulations and thickness variations between different crustal layers.

[0081] Multiple initial geological units can be remapped based on their edge shapes to obtain corrected geological units corresponding to each initial unit. Specifically, elevation data can be used to interpolate the elevation values ​​at each grid node, mapping the vertical coordinates of the initial regularized grid nodes to the actual topographic relief surface. The corrected geological units are then used to conform to the surface geometry. For areas with significant local topographic abrupt changes, an adaptive grid refinement technique based on topographic gradient control can be employed to smooth the local topography.

[0082] Multiple initial geological units can be remapped based on their internal structure to obtain corrected geological units corresponding to each initial geological unit. Specifically, data on crustal interfaces can be used to interpolate the depth of each interface on the grid nodes. Combined with the established surface boundaries, the depth of grid units with stretched or compressed vertical proportions can be determined, and the vertical units can be mapped to the actual crustal interfaces. The corrected geological units are used to characterize the undulations and thickness distribution of each layer within the crust. For vertical units that cross interfaces, the layer to which such units belong can be determined by judging the positional relationship between the unit's center point and the interface.

[0083] According to embodiments of this application, an automated construction of the geometric framework of a 3D geological model is achieved through a remapping strategy for model elements. Based on a coarsened mesh, topographic elevation and crustal interface undulation data are used to interpolate the elevations of mesh nodes and the interfaces of each internal layer. Coordinate mapping is performed by proportionally stretching or compressing the vertical distance, ensuring that the mesh elements accurately conform to the overall contour of the topographic undulations. The model is layered vertically by judging the spatial topology of the elements in their vertical positions. Based on the spatial gradient of the terrain and the undulation characteristics of key geological interfaces, mesh refinement is performed only in drastically changing local areas, ensuring that the mesh maintains geometric smoothness, continuity, and orthogonality in the vertical direction, effectively avoiding mesh distortion caused by abrupt changes in local terrain or interfaces. Furthermore, in wide areas with relatively gentle topographic and interface undulations, the mesh remains relatively coarse, significantly reducing the overall number of elements and computational degrees of freedom. This significantly enhances the model's ability to finely depict complex near-surface geometries, achieving an organic balance between computational accuracy and operational efficiency.

[0084] According to an embodiment of this application, multiple land parcel partitions and their respective simulation parameters are visualized to obtain a geological model of the target area. This includes: for each land parcel partition, rendering a geological sub-model corresponding to the land parcel partition based on its shape and simulation parameters, wherein the shape of the geological sub-model is determined according to the shape of the land parcel partition, and the color of the geological sub-model is determined according to the simulation parameters of the land parcel partition; and stitching together the multiple geological sub-models based on the positional relationship between the multiple land parcel partitions to obtain a geological model of the target area.

[0085] Based on the shape and simulation parameters of the land parcel partitions, a geological sub-model corresponding to each partition is rendered. The shape of a land parcel partition can be understood as the geometric outline occupied by each partition in three-dimensional space after remapping and partitioning. This shape can be defined by the node coordinates and topological connections of all modified geological units within the partition. By employing scientific visualization techniques, abstract parameter data can be transformed into intuitive graphical representations, resulting in the rendered geological sub-model corresponding to each land parcel partition.

[0086] For example, geometric shapes are constructed by reading the node coordinates of all 3D mesh models within a plot partition, representing different plot partitions. The shape of each plot partition corresponds to its actual physical properties in 3D space. Based on the simulation parameters of each plot partition, a preset color mapping table, such as a gradient from blue to red, maps the simulation parameter values ​​to color values ​​and assigns them to the corresponding geometric shapes to distinguish different plot partitions. For example, low-density areas can be rendered as light colors, high-density areas as dark colors, or high-temperature areas as red and low-temperature areas as blue, thereby achieving an intuitive visualization of the simulation parameter field and rendering a geological sub-model corresponding to the plot partition.

[0087] For example, since each plot partition shares a consistent coordinate system and grid node topology, the grid node coordinates, unit topological connections, and all associated physical property parameters of the nodes and units can be written into a data file. Each plot partition can correspond to one or more data files. By generating a corresponding visualization software format index file, the file path corresponding to each plot partition is recorded according to the logical order of the plot partitions. In this way, all generated data files are integrated. The visualization software can read the visualization software format index file to load and stitch together the data of all plot partitions in parallel, thereby obtaining the geological model of the target area. The geological model contains the geometric shape and physical property parameter distribution information of all plot partitions in the target area.

[0088] Based on the positional relationships between multiple land parcels, multiple geological sub-models are stitched together to obtain the geological model of the target area. The independently rendered geological sub-models can be stitched together according to the actual spatial location of each land parcel, based on their adjacency and coordinate correspondence in three-dimensional space.

[0089] According to the embodiments of this application, a geological model of the target area is constructed. By reading the index file in the visualization software format through visualization software, the data of all partitions can be loaded in parallel. The distributed and stored geological sub-models are combined and reconstructed into a complete three-dimensional geological model for display and analysis. This provides a tool for intuitively observing the distribution of complex geological structures and physical property parameters, which is convenient for model checking, result analysis and achievement display.

[0090] According to an embodiment of this application, the target area is initialized based on the basic geological data of the target area to obtain the basic geological attribute data of the target area, including: constructing a three-dimensional mesh model for the target area based on the regional range and modeling accuracy requirements of the target area, wherein the three-dimensional mesh model includes multiple sampling points and edges between the multiple sampling points; determining the edge geological attribute data of multiple edge sampling points located at the edges of the three-dimensional mesh model based on the basic geological data; determining the internal geological attribute data of each of the multiple internal sampling points using a spatial interpolation algorithm based on the edge geological attribute data, the positional relationship between the edge sampling points and multiple internal sampling points located inside the three-dimensional mesh model; and using the edge geological attribute data and the internal geological attribute data as the basic geological attribute data.

[0091] In this embodiment, the area can be represented by a latitude and longitude range. The required modeling accuracy can be determined based on a preset grid resolution. A three-dimensional mesh model can be generated based on the latitude and longitude range of the target area and the preset grid resolution. The nodes of the three-dimensional mesh model are then designated as sampling points, and edges connecting these sampling points are determined. The required modeling accuracy determines the mesh density; for example, the horizontal grid spacing and the vertical layer thickness can be determined by considering the spatial resolution of geophysical data and computational resources.

[0092] Edge sampling points can be understood as mesh nodes located on the boundaries of a 3D mesh model, including the upper, lower, and side boundaries. Internal sampling points can be understood as mesh nodes located inside the 3D mesh model that do not directly fall on the model boundaries. Edge geological attribute data can be obtained directly from basic geological data or obtained through interpolation. Based on the edge geological attribute data and the positional relationship between edge sampling points and multiple internal sampling points located within the 3D mesh model, spatial interpolation algorithms are used to determine the internal geological attribute data of each of the multiple internal sampling points. Spatial interpolation algorithms include, but are not limited to, inverse distance weighted interpolation, kriging interpolation, or radial basis function interpolation.

[0093] According to embodiments of this application, an automated construction of a regularized grid node attribute field from discrete basic geological data is achieved through a two-step strategy of first determining the edge geological attribute data and then interpolating the internal geological attribute data of the internal region. By referring to the grid resolution of the geological model required for actual calculation, the optimal sampling interval of the terrain data is determined, and the coordinates of data such as terrain, crustal interface, and seismic wave velocity structure are transformed from latitude, longitude, and depth into rectangular coordinates, thus realizing the regularization of basic geological data storage.

[0094] According to embodiments of this application, the basic geological data and basic geological attribute data include at least one of the following: latitude and longitude data, depth data; the modeling method of the geological model further includes: performing coordinate transformation based on latitude and longitude data and depth data to obtain data in the Cartesian coordinate system corresponding to the basic geological attribute data.

[0095] In this embodiment, latitude and longitude data can be understood as geographic coordinates used to describe points on the Earth's surface, typically expressed in degrees, including longitude and latitude. Depth data is the vertical distance relative to a reference surface, used to characterize the depth of internal interfaces or anomalies within the Earth's crust.

[0096] Coordinate transformation is performed based on latitude, longitude, and depth data to obtain data in a Cartesian coordinate system corresponding to the basic geological attributes. Specifically, the original geographic coordinate system, such as latitude, longitude, and depth, is converted into a Cartesian coordinate system suitable for numerical simulation calculations. When the model's spatial scale reaches hundreds of kilometers, the Earth's curvature has a significant impact on the numerical simulation results. Therefore, the Earth's geometry needs to be considered during the modeling process, approximating the Earth as a sphere or ellipsoid during coordinate transformation.

[0097] In one example, the geocentric Cartesian coordinate system transformation formula under the assumption of a uniform sphere can be used for calculation. Specifically, for a given latitude and longitude coordinate point and depth value, it is mapped to a three-dimensional Cartesian coordinate system with the geocenter as the origin through spherical trigonometry, so that the transformed data can be directly used to construct a three-dimensional mesh model, define the spatial location of nodes, and perform subsequent geometric calculations.

[0098] Coordinate transformation can be achieved through equations (1) to (3):

[0099] X=(r+h)·sinθ·cosφ (1)

[0100] Y=(r+h) ·sinθ·sinφ (2)

[0101] Z = (r + h) · cosθ (3)

[0102] Where X, Y, and Z are the three-dimensional coordinates after coordinate transformation, r is the Earth's radius, which is usually taken as 6371 km, h is the terrain depth or terrain elevation, φ is the longitude, and θ is the covariant latitude, which is obtained by calculating the latitude, θ = 90° - latitude.

[0103] In another example, vector coordinate transformation can be used to convert the east-west, north-south, and vertical velocity components of the local geodetic coordinate system of the geodetic velocity field to the X, Y, and Z directions in the global Cartesian coordinate system with the geocenter as the origin. Based on the spatial coordinates of the boundary grid nodes in the 3D mesh model, the least squares interpolation method is used to map the discrete station velocities into a continuous horizontal velocity constraint field for the boundary nodes of the geological model. For deep boundaries such as the bottom of the lithosphere, due to the lack of direct kinematic observation constraints, simplified vertical uniform velocity or displacement boundary conditions are used to achieve reasonable constraints on the geological model boundaries while ensuring computational stability.

[0104] Vector transformation from spherical coordinates to Cartesian coordinates can be achieved using equation (4):

[0105] (4)

[0106] in, , , The velocity components are in the Cartesian coordinate system. , , These are the local radial, southward, and eastward velocity components in spherical coordinates, respectively.

[0107] According to the embodiments of this application, the spatial benchmark unification and standardization of multi-source heterogeneous basic geological data is realized, enabling observation data from different sources and different coordinate systems to be integrated and used under the same geometric framework. This lays the coordinate foundation for the generation of three-dimensional mesh models, interface interpolation, and assignment of physical property parameters, avoiding data misalignment and model distortion caused by inconsistencies in coordinate systems.

[0108] Based on the above-mentioned geological modeling method, this application also provides a geological modeling apparatus. The following will combine... Figure 4 The device is described in detail.

[0109] Figure 4 A structural block diagram of a modeling apparatus for a geological model according to an embodiment of this application is shown.

[0110] like Figure 4 As shown, the geological modeling device 400 of this embodiment includes an initialization module 410, a remapping module 420, a partitioning module 430, a fitting module 440, and a processing module 450.

[0111] The initialization module 410 is used to initialize the target area based on the basic geological data of the target area, thereby obtaining basic geological attribute data of the target area. The basic geological attribute data includes the geological attribute data of multiple sampling points within the target area. In one embodiment, the initialization module 410 can be used to execute the operation S210 described above, which will not be repeated here.

[0112] The remapping module 420 is used to remap multiple initial geological units based on the depth data representing topographic elevation and crustal stratification in the basic geological attribute data, resulting in multiple corrected geological units. The initial geological units are obtained by dividing the target area based on a preset granularity, where the area is determined according to the longitude and latitude in the basic geological attribute data. The remapping module 420 can be used to execute the operation S220 described above, which will not be repeated here.

[0113] The partitioning module 430 is used to divide the multiple modified geological units into multiple plot partitions based on the boundary location information representing the plot extent in the basic geological attribute data. The partitioning module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0114] The fitting module 440 is used to fit the physical property parameters of each of the multiple land parcel partitions based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, so as to obtain the simulation parameters of each of the multiple land parcel partitions. The fitting module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0115] Processing module 450 is used to visualize the multiple plot partitions and their respective simulation parameters to obtain a geological model of the target area. Processing module 450 can be used to perform the operation S250 described above, which will not be repeated here.

[0116] According to an embodiment of this application, the partitioning module 430 includes: a range determination submodule, a first partitioning submodule, and a second partitioning submodule.

[0117] The scope determination submodule is used to determine the boundaries of multiple land parcel zones and the corresponding scope of each land parcel zone based on the boundary location information.

[0118] The first sub-module is used to divide the first modified geological unit, which is different from the boundary location information, into the plot partition corresponding to the range to which the modified geological unit belongs.

[0119] The second partitioning submodule is used to determine the plot partition to which the modified geological unit belongs by means of the positional relationship between the second modified geological unit and the edges of multiple plots, based on the second modified geological unit with the same boundary location information.

[0120] According to an embodiment of this application, the fitting module 440 includes: a first determining submodule, a calculation submodule, and a second determining submodule.

[0121] The first determination submodule is used to determine the physical property parameters of the block partition where the second modified geological unit is located for each second modified geological unit.

[0122] The calculation submodule is used to use the mean value of the physical property parameters within the plot partition as the simulation parameters of the second modified geological unit.

[0123] The second determination submodule is used to determine the simulation parameters of each first corrected geological unit based on the boundary location information of the block partition to which the first corrected geological unit belongs, the simulation parameters of the second corrected geological unit, and the location of the first corrected geological unit, using an interpolation algorithm.

[0124] According to an embodiment of this application, the remapping module 420 includes a third determining submodule and a remapping submodule.

[0125] The third determination submodule is used to determine the edge shape and internal structure of the target area based on depth data. The edge shape is determined based on the terrain elevation, and the internal structure is determined based on the crustal layer depth data.

[0126] The remapping submodule is used to remap multiple initial geological units based on edge shape and internal structure to obtain corrected geological units corresponding to the multiple initial geological units respectively.

[0127] According to an embodiment of this application, the processing module 450 includes a rendering submodule and a splicing submodule.

[0128] The rendering submodule is used to render a geological sub-model corresponding to each plot partition based on the shape and simulation parameters of the plot partition. The shape of the geological sub-model is determined according to the shape of the plot partition, and the color of the geological sub-model is determined according to the simulation parameters of the plot partition.

[0129] The stitching submodule is used to stitch together multiple geological sub-models based on the positional relationship between multiple plot partitions to obtain a geological model of the target area.

[0130] According to an embodiment of this application, the initialization module 410 includes: a construction submodule, a fourth determination submodule, a fifth determination submodule, and a classification submodule.

[0131] The construction submodule is used to build a 3D mesh model for the target area based on the area range and modeling accuracy requirements of the target area. The 3D mesh model includes multiple sampling points and the edges between the multiple sampling points.

[0132] The fourth determination submodule is used to determine the edge geological attribute data of multiple edge sampling points located at the edge of the three-dimensional mesh model based on the basic geological data.

[0133] The fifth determination submodule is used to determine the internal geological attribute data of each of the multiple internal sampling points based on the edge geological attribute data and the positional relationship between the edge sampling points and multiple internal sampling points located inside the three-dimensional mesh model, using a spatial interpolation algorithm.

[0134] The classification submodule is used to classify marginal geological attribute data and internal geological attribute data as basic geological attribute data.

[0135] According to an embodiment of this application, the geological modeling apparatus 400 further includes a conversion module.

[0136] The transformation module is used to perform coordinate transformation based on latitude, longitude and depth data to obtain data in the Cartesian coordinate system corresponding to the basic geological attribute data.

[0137] According to embodiments of this application, any multiple modules among the initialization module 410, remapping module 420, partitioning module 430, fitting module 440, and processing module 450 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this application, at least one of the initialization module 410, remapping module 420, partitioning module 430, fitting module 440, and processing module 450 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the initialization module 410, remapping module 420, partitioning module 430, fitting module 440, and processing module 450 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0138] Figure 5 A block diagram of an electronic device suitable for implementing a modeling method for geological models according to an embodiment of this application is shown.

[0139] like Figure 5 As shown, an electronic device 500 according to an embodiment of this application includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0140] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 502 and / or RAM 503. It should be noted that the programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0141] According to embodiments of this application, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0142] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0143] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0144] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this application.

[0145] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0146] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0147] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this application embodiment. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0148] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0149] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0150] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

[0151] The embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Without departing from the scope of this application, those skilled in the art can make various substitutions and modifications, all of which should fall within the scope of this application.

Claims

1. A method for modeling a geological model, characterized in that, The method includes: Based on the basic geological data of the target area, the target area is initialized to obtain the basic geological attribute data of the target area, which includes the geological attribute data of multiple sampling points in the target area. Based on the depth data used to represent topographic elevation and crustal stratification in the basic geological attribute data, multiple initial geological units are remapped to obtain multiple corrected geological units. The initial geological units are obtained by dividing the regional range of the target area based on a preset division granularity. The regional range is determined according to the longitude and latitude in the basic geological attribute data. Based on the boundary location information used to represent the extent of the land parcel in the basic geological attribute data, the multiple modified geological units are divided into multiple land parcel partitions; Based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, the physical property parameters of each of the multiple land parcel partitions are fitted to obtain the simulation parameters of each of the multiple land parcel partitions; The geological model of the target area is obtained by visualizing the multiple plot partitions and their respective simulation parameters.

2. The method according to claim 1, characterized in that, The step of dividing multiple modified geological units into multiple land parcel partitions based on the boundary location information used to represent the extent of land parcels in the basic geological attribute data includes: Based on the boundary location information, the edges of the multiple plot partitions and the corresponding ranges of each of the multiple plot partitions are determined; For a first corrected geological unit that differs from the boundary location information, the first corrected geological unit is divided into a plot partition corresponding to the range to which the corrected geological unit belongs; For a second modified geological unit that is identical to the boundary location information, the land parcel zoning to which the modified geological unit belongs is determined by the positional relationship between the second modified geological unit and the edges of the multiple land parcels.

3. The method according to claim 2, characterized in that, The basic geological attribute data includes the seismic wave velocity of each of multiple sampling points in a three-dimensional mesh model of the target area; the geological attribute data also includes the category of each of the multiple sampling points, the category including regular sampling points and low-velocity sampling points. The category of the sampling points is determined in the following way: Based on a preset seismic wave velocity threshold and the seismic wave velocities of the multiple sampling points, the multiple sampling points are divided into low-velocity sampling points and regular sampling points. The seismic wave velocity of the low-velocity sampling points is less than the seismic wave velocity threshold, and the seismic wave velocity of the regular sampling points is greater than or equal to the seismic wave velocity threshold.

4. The method according to claim 3, characterized in that, The land parcel zoning also includes abnormal zoning; The abnormal partitions are determined in the following way: Based on the location of at least one of the low-velocity sampling points, the seismic wave velocity anomaly region is determined from the three-dimensional mesh model; Based on the correspondence between the three-dimensional mesh model and the multiple modified geological units, the abnormal geological units belonging to the seismic wave velocity anomaly region are determined from the multiple modified geological units, and the anomaly zoning is determined based on at least one of the abnormal geological units.

5. The method according to claim 2, characterized in that, The simulation parameters for each of the multiple plot partitions include the simulation parameters of the first modified geological unit in the plot partition and the simulation parameters of the second modified geological unit in the plot partition; The method involves fitting the physical property parameters of each of the multiple land parcel partitions based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, to obtain the simulation parameters of each of the multiple land parcel partitions, including: For each of the second modified geological units, determine the physical property parameters of the block partition where the second modified geological unit is located; The average value of the physical property parameters within the plot partition is used as the simulation parameter of the second modified geological unit; For each of the first corrected geological units, the simulation parameters of the first corrected geological unit are determined by an interpolation algorithm based on the boundary location information of the block partition to which the first corrected geological unit belongs, the simulation parameters of the second corrected geological unit, and the location of the first corrected geological unit.

6. The method according to claim 1, characterized in that, Based on the depth data used to represent topographic elevation and crustal stratification in the basic geological attribute data, multiple initial geological units are remapped to obtain multiple corrected geological units, including: Based on the topographic elevation and crustal layer depth data, the edge shape and internal structure of the target area are determined, wherein the edge shape is determined according to the topographic elevation and the internal structure is determined according to the crustal layer depth data; Based on the edge shape and the internal structure, multiple initial geological units are remapped to obtain modified geological units corresponding to the multiple initial geological units respectively.

7. The method according to claim 1, characterized in that, The step of visualizing the multiple plot partitions and their respective simulation parameters to obtain a geological model of the target area includes: For each plot partition, a geological sub-model corresponding to the plot partition is rendered based on the shape of the plot partition and the simulation parameters of the plot partition. The shape of the geological sub-model is determined according to the shape of the plot partition, and the color of the geological sub-model is determined according to the simulation parameters of the plot partition. Based on the positional relationship between the multiple plots, the multiple geological sub-models are spliced ​​together to obtain the geological model of the target area.

8. The method according to claim 1, characterized in that, The target area is initialized based on its basic geological data to obtain its basic geological attribute data, including: Based on the regional extent and modeling accuracy requirements of the target region, a three-dimensional mesh model for the target region is constructed. The three-dimensional mesh model includes multiple sampling points and edges between the multiple sampling points. Based on the aforementioned basic geological data, the edge geological attribute data of multiple edge sampling points located at the edge of the three-dimensional mesh model are determined; Based on the edge geological attribute data and the positional relationship between the edge sampling point and multiple internal sampling points located inside the three-dimensional mesh model, the internal geological attribute data of each of the multiple internal sampling points is determined using a spatial interpolation algorithm; The marginal geological attribute data and the internal geological attribute data are used as the basic geological attribute data.

9. The method according to claim 1, characterized in that, The basic geological data and the basic geological attribute data include at least one of the following: latitude and longitude data, depth data; The method further includes: Based on the latitude and longitude data and the depth data, coordinate transformation is performed to obtain data in the Cartesian coordinate system corresponding to the basic geological attribute data.

10. A modeling apparatus for a geological model, characterized in that, The device includes: An initialization module is used to initialize the target area based on the basic geological data of the target area, and obtain the basic geological attribute data of the target area, wherein the basic geological attribute data includes the geological attribute data of multiple sampling points in the target area. The remapping module is used to remap multiple initial geological units based on the depth data representing topographic elevation and crustal stratification in the basic geological attribute data to obtain multiple corrected geological units. The initial geological units are obtained by dividing the regional range of the target area based on a preset division granularity. The regional range is determined according to the longitude and latitude in the basic geological attribute data. The partitioning module is used to divide the multiple modified geological units into multiple land parcel partitions based on the boundary location information in the basic geological attribute data that represents the extent of the land parcels. A fitting module is used to fit the physical property parameters of each of the multiple land parcel partitions based on the physical property parameters corresponding to the boundary location information of each of the multiple land parcel partitions, thereby obtaining the simulation parameters of each of the multiple land parcel partitions; and The processing module is used to visualize the multiple plot partitions and their respective simulation parameters to obtain a geological model of the target area.

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