Three-dimensional modeling method and rendering method for dynamically inserting hidden fault into geologic body

Abstract

The invention relates to the technical field of three-dimensional modeling technologies of geologic bodies, and discloses a three-dimensional modeling method and rendering method for dynamically inserting a hidden fault into a geologic body, and the modeling method comprises the steps: carrying out the preprocessing of geologic body data based on the geologic body feature analysis and fault recognition algorithm, and carrying out the fault simulation through a dynamic insertion algorithm, fault simulation data are obtained; obtaining a fault insertion starting point in the fault simulation data, constructing an insertion model according to the fault insertion starting point, inserting faults to two sides respectively, and obtaining fault insertion track data; setting model parameters according to fault insertion trajectory data, and limiting the simulation range of a dynamic insertion algorithm; and under the criterion that the matching degree of the fault insertion trajectory and the geologic body data is the highest, on the basis of the geologic body structure model and the fault kinematic model, searching optimal fault parameters, and performing fault insertion correction on the geologic body. According to the invention, the accuracy and efficiency of geologic body modeling can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of three-dimensional modeling of geological bodies, and in particular to a three-dimensional modeling method and a rendering method for dynamically inserting a concealed fault into a geological body. Background Art

[0002] Existing 3D modeling technologies for geological bodies face many challenges when dealing with hidden faults. Traditional modeling methods often rely on limited geological data and empirical judgments, making it difficult to accurately simulate the dynamic insertion process of faults and their impact on the structure of geological bodies. In addition, these methods are inefficient when processing large-scale geological data, and it is difficult to achieve real-time rendering and detailed display, which limits their application in complex geological environments. In terms of technical principles, many existing methods rely on static fault models and lack in-depth analysis of fault kinematics and dynamic changes in geological body structure, resulting in deviations between modeling results and actual geological conditions.

[0003] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: the existing modeling method cannot effectively deal with the dynamic insertion problem of hidden faults, resulting in the inability to accurately simulate the impact of faults on the structure of geological bodies; the prior art is inefficient when processing large-scale geological data and it is difficult to meet the needs of real-time rendering and high-precision modeling; in addition, the prior art lacks effective algorithm support in fault identification and parameter optimization, which limits the modeling accuracy and reliability. Summary of the invention

[0004] The embodiment of the present invention aims to provide a three-dimensional modeling method and a rendering method for dynamically inserting a hidden fault into a geological body, so as to solve the technical problems raised in the prior art.

[0005] The embodiment of the present invention solves the technical problem by adopting the following technical solution:

[0006] In a first aspect, a three-dimensional modeling method for dynamically inserting a hidden fault into a geological body is provided, comprising:

[0007] Based on geological body feature analysis and fault identification algorithm, the geological body data is preprocessed, and then the dynamic insertion algorithm is used to simulate the fault to obtain the fault simulation data;

[0008] Obtain the fault insertion starting point in the fault simulation data, build an insertion model based on the fault insertion starting point, insert faults to both sides respectively, and obtain fault insertion trajectory data; set model parameters based on the fault insertion trajectory data to limit the simulation range of the dynamic insertion algorithm;

[0009] Under the criterion of the highest matching degree between the fault insertion trajectory and the geological body data, the optimal fault parameters are searched based on the geological body structure model and the fault kinematic model, and the fault insertion correction is performed on the geological body.

[0010] Furthermore, the geological body feature analysis is performed using Fourier transform; the mathematical model of the fault identification algorithm is:

[0011]

[0012] Among them, f(x) is the geological body data function, and F(x) is the Fourier transform result.

[0013] Furthermore, the preprocessing of the geological body data includes:

[0014] The geological body data with window function applied is used as input data, the fault position of the current stage is estimated according to the fault simulation results of the previous stage, and the optimal window function parameters are selected according to the position and geological body data characteristics;

[0015] Obtaining a corresponding window function according to the window function parameters, and obtaining an amplitude-frequency response curve according to the shape of the window function;

[0016] According to the amplitude-frequency response curve, the coefficient of the FIR filter is designed by the least square method; the geological body data is filtered by the FIR filter, and then the fault identification coefficient of the window function corresponding to the window function parameter is used to identify the fault of the geological body data.

[0017] Furthermore, the optimal window function parameters are window function parameters corresponding to the minimum error under different geological body characteristics.

[0018] Further, obtaining the fault insertion starting point in the fault simulation data includes:

[0019] The geological body data is subjected to the operations of feature extraction, fault identification and fault position estimation to obtain the fault position of the fault domain;

[0020] Search for the maximum fault position of each geological body as the position of each fault, perform curve fitting on the fault positions of multiple adjacent geological bodies in sections, and calculate the relative deviation of each fault in the curve fitting results and the average deviation of the faults in the section;

[0021] The fault segment with the smallest average deviation is taken as the segment target, and the fault position is selected according to the relative deviation threshold. The fault domain feature information of each selected fault position is extracted, and the most significant feature is selected as the starting point of fault insertion.

[0022] Furthermore, the parameter range of the fault insertion model is:

[0023] P={(x,y,z)∣x∈[x1,x2],y∈[y1,y2],z∈[z1,z2]}

[0024] Among them, the coordinates of the starting point of fault insertion are (x1, y1, z1), x1, y1, z1 are the minimum coordinate values ​​of the geological body data, and x2, y2, z2 are the maximum coordinate values ​​of the geological body data.

[0025] Furthermore, the fault insertion correction of the geological body includes: dividing each geological body data into multiple segments along the fault insertion direction according to the geological body data, first obtaining the geological body structure before and after the central fault parameter adjustment according to the difference in geological body data before and after the fault insertion, and then obtaining the geological body structure and fault insertion position before and after the adjustment of other fault parameters.

[0026] In a second aspect of the present invention, a three-dimensional modeling and rendering method for dynamically inserting a hidden fault into a geological body is provided, comprising:

[0027] Acquire fault simulation data obtained by a three-dimensional modeling method of dynamically inserting a hidden fault into a geological body;

[0028] Based on the three-dimensional grid division method, the fault simulation data is divided into multiple data blocks with uniform structures;

[0029] According to the viewpoint position, the CPU is used to load the corresponding data blocks into the memory in real time, and the geological blocks to be rendered are loaded into the GPU's video memory;

[0030] Based on the GPU parallel computing platform, GPU stream processors are used to build multi-resolution LOD models in parallel to render geological bodies.

[0031] Furthermore, the three-dimensional grid-based division method divides the fault simulation data into multiple data blocks with uniform structures, including: according to a preset data block density threshold, using a three-dimensional grid division method to divide the fault simulation data layer by layer to obtain each sub-block, and merging adjacent sub-blocks according to the number of data points in adjacent sub-blocks until a total sub-block point threshold is reached to obtain multiple data blocks.

[0032] Furthermore, the method of loading corresponding data blocks into the memory in real time by using the CPU according to the viewpoint position, and loading the geological blocks to be rendered into the display memory of the GPU, includes:

[0033] Calculate the address of the geological body data block file to be loaded into the memory and cache data according to the current viewpoint position; construct the memory and cache data using a linked list data structure, and initialize the loading of cache and memory geological body block data;

[0034] When the viewpoint changes, determine the type of viewpoint movement and update the memory data; calculate the cache update threshold, determine whether to clear useless data in the cache and whether to load external memory data into the cache, and perform the required clearing or loading operations.

[0035] The above-mentioned embodiments of the present invention have at least the following beneficial effects: the three-dimensional modeling method of the present invention for dynamically inserting a hidden fault into a geological body can improve the accuracy and efficiency of geological body modeling. By combining the preprocessing steps based on geological body feature analysis and fault identification algorithm with the dynamic insertion algorithm for fault simulation, the insertion trajectory of the fault and the changes in the geological body structure can be simulated more accurately. In addition, by obtaining the starting point of the fault insertion in the fault simulation data and constructing an insertion model, the insertion position and direction of the fault can be accurately controlled, thereby obtaining a modeling result that is more in line with the actual geological conditions.

[0036] Furthermore, the three-dimensional modeling and rendering method of the present invention can effectively process large-scale geological data and realize high-quality real-time rendering. By dividing the fault simulation data into multiple uniformly structured data blocks based on the three-dimensional grid division method, and utilizing the collaborative work of the CPU and the GPU, the geological blocks can be quickly loaded and rendered, thereby improving the rendering efficiency. At the same time, by utilizing the GPU parallel computing platform to construct a multi-resolution LOD model, the rendering details can be dynamically adjusted according to different viewpoints and distances, the visual effect can be optimized, and the three-dimensional display of the geological body can be made more realistic and intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] One or more embodiments are exemplarily described by the figures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0038] Figure 1 It is a schematic flow chart of the three-dimensional modeling method of dynamically inserting a hidden fault into a geological body provided by the present invention;

[0039] Figure 2 It is a flow chart of the three-dimensional modeling and rendering method of the dynamic insertion of a hidden fault into a geological body provided by the present invention;

[0040] Figure 3 The schematic diagram schematically shows the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to facilitate the understanding of the present invention, the present invention is described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as "connecting" another element, it can be directly on another element, or there can be one or more centered elements therebetween. The orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "upper end", "lower end", "top" and "bottom" used in this specification is based on the orientation or positional relationship shown in the accompanying drawings, only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0042] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0043] Combine the following Figure 1 , the three-dimensional modeling method 100 for dynamically inserting a hidden fault into a geological body provided in an embodiment of the present application is described in detail through a specific embodiment.

[0044] Figure 1 The figure is a flow chart of a three-dimensional modeling method for dynamically inserting a hidden fault into a geological body provided by the present invention. The three-dimensional modeling method for dynamically inserting a hidden fault into a geological body provided by one embodiment of the present invention comprises:

[0045] Step 101, based on geological body feature analysis and fault identification algorithm, preprocessing geological body data, and then using dynamic insertion algorithm to simulate faults to obtain fault simulation data;

[0046] Step 102, obtaining the fault insertion starting point in the fault simulation data, constructing an insertion model according to the fault insertion starting point, inserting faults to both sides respectively, and obtaining fault insertion trajectory data; setting model parameters according to the fault insertion trajectory data, and limiting the simulation range of the dynamic insertion algorithm;

[0047] Step 103, under the criterion of the highest matching degree between the fault insertion trajectory and the geological body data, based on the geological body structure model and the fault kinematic model, search for the best fault parameters and perform fault insertion correction on the geological body.

[0048] It should be noted that this method first pre-processes the geological body data based on geological body feature analysis and fault identification algorithm, which is a key step in the modeling process. Through this step, potential faults in the geological body can be identified and provide an accurate data basis for subsequent fault simulation.

[0049] Specifically, geological body feature analysis usually uses mathematical methods such as Fourier transform to convert geological body data into frequency domain to facilitate analysis and identification of fault features. Fault identification algorithms determine the location and characteristics of faults based on specific patterns in geological body data, such as discontinuities or abnormal changes. In this process, specific algorithm parameters may need to be set, such as the window size of Fourier transform, the threshold of fault identification, etc., to ensure the accuracy of the analysis results.

[0050] Preferably, in order to improve the efficiency and accuracy of preprocessing, an adaptive algorithm can be used to dynamically adjust the parameters of Fourier transform, or machine learning technology can be used to optimize the fault identification algorithm. In addition, parallel computing technology can be used to accelerate the data processing process, or cloud computing resources can be used to process large-scale geological data.

[0051] In some embodiments, the geological body feature analysis is performed using Fourier transform; the mathematical model of the fault identification algorithm is:

[0052]

[0053] Among them, f(x) is the geological body data function, and F(x) is the Fourier transform result.

[0054] It should be noted that the geological body feature analysis in this embodiment uses Fourier transform, which is a commonly used mathematical tool for converting geological body data from the time domain to the frequency domain in order to better identify and analyze fault features in the geological body.

[0055] Specifically, the Fourier transform result F(x) is obtained by combining the geological volume data function f(x) with the Fourier transform kernel e -2πix In this process, it is necessary to select a suitable window function to process the geological data to reduce spectrum leakage and improve frequency resolution. The selection and parameter setting of the window function have an important influence on the result of Fourier transform, which may include the type of window function, such as Hanning window, Hamming window, etc., length and shape.

[0056] Preferably, in order to improve the efficiency and accuracy of Fourier transform, a fast Fourier transform FFT algorithm can be used to reduce the amount of calculation. In addition, an adaptive window function technology can be introduced to dynamically adjust the parameters of the window function according to the characteristics of the geological body data to obtain a more accurate frequency response. In the mathematical model of the fault identification algorithm, it is also possible to consider introducing a regularization term to suppress the influence of noise and outliers and improve the accuracy and robustness of fault identification. These improvements help to improve the performance and reliability of the overall modeling process.

[0057] In some embodiments, the preprocessing of geological volume data includes:

[0058] The geological body data with window function applied is used as input data, the fault position of the current stage is estimated according to the fault simulation results of the previous stage, and the optimal window function parameters are selected according to the position and geological body data characteristics;

[0059] Obtaining a corresponding window function according to the window function parameters, and obtaining an amplitude-frequency response curve according to the shape of the window function;

[0060] According to the amplitude-frequency response curve, the coefficient of the FIR filter is designed by the least square method; the geological body data is filtered by the FIR filter, and then the fault identification coefficient of the window function corresponding to the window function parameter is used to identify the fault of the geological body data.

[0061] Specifically, the window function mentioned in the preprocessing step is a mathematical function used to weight the signal in the frequency domain to reduce edge effects and improve the accuracy of signal analysis. The window function options include Hanning window, Hamming window, Blackman window, etc. Each window function has its specific frequency characteristics and application scenarios. Fault identification depends on the characteristics of geological body data, such as discontinuity or abnormal changes, and the location of the fault is identified by setting algorithm parameters. Parameter settings may involve the width, shape and sensitivity of the window function for fault identification.

[0062] Preferably, in the preprocessing process, an adaptive window function technology can be used to dynamically adjust the parameters of the window function according to the characteristics of the geological body data to obtain the best frequency response. In addition, the fault identification process can be optimized by combining a machine learning algorithm, and the fault characteristics in the geological body data can be identified by training the model. When designing the FIR filter, the coefficients of the filter can be determined by a window function method or a frequency sampling method to achieve effective filtering of the geological body data.

[0063] In some embodiments, the optimal window function parameters are window function parameters corresponding to minimum errors under different geological body characteristics.

[0064] It should be noted that the optimal window function parameters described in this embodiment refer to the window function settings that can minimize errors and most effectively identify faults under different geological body characteristics. This is to optimize the fault identification process by adjusting the parameters of the window function to ensure the accuracy of fault simulation.

[0065] Specifically, the window function parameters include the type, length, shape and smoothness of the window function. These parameters directly affect the frequency domain characteristics of the window function, thereby affecting the accuracy of fault identification. For example, the length of the window function determines the frequency domain resolution, while the shape and smoothness affect the size of the side lobe of the window function, which in turn affects the identification of fault features. In actual operation, the window function parameters that can minimize the error under specific geological body characteristics can be determined through experiments or optimization algorithms.

[0066] Preferably, in order to further improve the accuracy of window function parameter selection, machine learning or artificial intelligence technology can be used to analyze the relationship between different geological body characteristics and window function parameters. Through the training model, the optimal window function parameters under specific geological body conditions can be automatically learned and predicted. In addition, it is also possible to consider introducing a multi-scale analysis method to more comprehensively identify and simulate faults by applying different window function parameters at different scales. The application of these methods can further improve the accuracy and efficiency of fault identification.

[0067] In some embodiments, obtaining the fault insertion starting point in the fault simulation data includes:

[0068] The geological body data is subjected to the operations of feature extraction, fault identification and fault position estimation to obtain the fault position of the fault domain;

[0069] Search for the maximum fault position of each geological body as the position of each fault, perform curve fitting on the fault positions of multiple adjacent geological bodies in sections, and calculate the relative deviation of each fault in the curve fitting results and the average deviation of the faults in the section;

[0070] The fault segment with the smallest average deviation is taken as the segment target, and the fault position is selected according to the relative deviation threshold. The fault domain feature information of each selected fault position is extracted, and the most significant feature is selected as the starting point of fault insertion.

[0071] It should be noted that the process of obtaining the fault insertion starting point in this embodiment is achieved by performing feature extraction, fault identification and fault position estimation operations on geological body data. This step is the key to ensuring the accuracy of fault simulation because it involves accurately locating the position of the fault from complex geological data.

[0072] Specifically, feature extraction usually includes statistical analysis and pattern recognition of geological data to identify possible fault features. Fault identification may involve the use of specific algorithms, such as machine learning models, to analyze the extracted features and determine the existence of faults. Fault position estimation requires spatial positioning of the identified fault features, which may involve spatial analysis and modeling of geological data. In this process, parameters that may need to be set include the threshold of feature extraction, the sensitivity of fault identification, and the accuracy of position estimation.

[0073] Preferably, in order to improve the accuracy of the starting point of fault insertion, multi-source data fusion technology can be used to combine multiple data types of geological bodies, such as seismic data, geological exploration data, etc. to improve the accuracy of fault identification. In addition, advanced machine learning algorithms, such as deep learning networks, can be introduced to automatically learn and identify fault features. In terms of fault position estimation, high-precision geographic information system GIS technology can be used to improve positioning accuracy. The introduction of these technologies can further improve the quality and efficiency of fault simulation.

[0074] In some embodiments, the parameter range of the fault insertion model is:

[0075] P={(x,y,z)∣x∈[x1,x2],y∈[y1,y2],z∈[z1,z2]}

[0076] Among them, the coordinates of the starting point of fault insertion are (x1, y1, z1), x1, y1, z1 are the minimum coordinate values ​​of the geological body data, and x2, y2, z2 are the maximum coordinate values ​​of the geological body data.

[0077] It should be noted that the parameter range of the fault insertion model in this embodiment is determined by defining a parameter space, which limits the possible parameter values ​​in the fault insertion process.

[0078] Specifically, the parameter range of the fault insertion model is defined as P = {(x, y, z) | x ∈ [x1, x2], y ∈ [y1, y2], z ∈ [z1, z2]}, where x1, y1, z1 are the minimum coordinate values ​​of the geological data, and x2, y2, z2 are the maximum coordinate values ​​of the geological data. The setting of this parameter space is based on the actual range of the geological data to ensure that the fault insertion simulation is carried out within a reasonable spatial range. In actual operation, the setting of these parameters needs to be determined based on the specific geological data, which may involve statistical analysis of the geological data to determine the minimum and maximum coordinate values ​​of the data.

[0079] Preferably, in order to improve the flexibility and adaptability of fault insertion simulation, an adaptive parameter adjustment mechanism can be considered. For example, the parameter range can be dynamically adjusted according to the real-time feedback during the simulation process to better adapt to the changes in geological body data. In addition, it is also possible to consider introducing multi-scale simulation technology, allowing fault insertion simulation at different spatial scales to adapt to geological body structures of different complexities. The introduction of these technologies can further improve the accuracy and efficiency of the simulation, while increasing the applicability of the model.

[0080] In some embodiments, the fault insertion correction of the geological body includes: dividing each geological body data into multiple segments along the fault insertion direction according to the geological body data, first obtaining the geological body structure before and after the central fault parameter adjustment according to the difference in geological body data before and after the fault insertion, and then obtaining the geological body structure and fault insertion position before and after the adjustment of other fault parameters.

[0081] It should be noted that the fault insertion correction process in this embodiment is a process of segmenting the geological body data along the fault insertion direction and adjusting the geological body structure according to the difference between the geological body data before and after the fault insertion.

[0082] Specifically, fault insertion correction includes dividing the geological body data into multiple segments along the fault insertion direction, which may involve spatial analysis of the geological body data to determine the appropriate segmentation method. The adjustment of the central fault parameters and other fault parameters is based on the changes in the geological body data before and after the fault insertion, which may include changes in the physical properties and structural characteristics of the geological body. In actual operation, the parameters that may need to be set include the granularity of the segmentation, the algorithm and method for adjusting the fault parameters, etc.

[0083] Preferably, in order to improve the accuracy and efficiency of fault insertion correction, advanced numerical simulation techniques, such as finite element analysis or discrete element method, can be used to simulate the impact of fault insertion on the geological body structure. In addition, machine learning algorithms can be introduced to analyze the changes in geological body data before and after fault insertion and automatically adjust fault parameters. In terms of geological body structure adjustment, multi-scale modeling technology can be considered to accurately simulate the changes in geological bodies at different scales.

[0084] The above-mentioned various embodiments of the present invention have the following beneficial effects: the three-dimensional modeling method of the present invention for dynamically inserting a hidden fault into a geological body can solve the accuracy and efficiency problems existing in traditional geological body modeling. By preprocessing the geological body data using geological body feature analysis and fault recognition algorithms, the position and morphology of the fault can be more accurately identified and simulated. The application of the dynamic insertion algorithm makes the fault simulation more flexible and realistic, and setting the model parameters by using the fault insertion trajectory data can limit the simulation range and improve the calculation efficiency. In addition, by searching for the optimal fault parameters under the criterion of the highest matching degree between the fault insertion trajectory and the geological body data, the geological body can be accurately corrected by fault insertion, thereby obtaining a three-dimensional model that is more in line with the actual geological conditions.

[0085] Further, the technical solution proposed in the present invention can optimize the processing flow of geological body data. For example, by performing geological body feature analysis through Fourier transform, the intrinsic characteristics of geological body data can be understood more deeply. The application of window function and the design of FIR filter in the preprocessing step can improve the accuracy of fault identification. The accurate acquisition of the starting point of fault insertion and the construction of fault insertion model can ensure the accuracy and controllability of the fault insertion process. The combined use of these technologies can not only improve the accuracy of modeling, but also improve the automation and intelligence level of the modeling process while ensuring the quality of modeling.

[0086] Please also read Figure 2 , Figure 2 2 is a flow chart of a three-dimensional modeling and rendering method 200 for dynamically inserting a hidden fault into a geological body provided by the present invention, comprising:

[0087] Step 201, obtaining fault simulation data obtained by a three-dimensional modeling method of dynamically inserting a hidden fault into a geological body;

[0088] Step 202, based on a three-dimensional grid partitioning method, the fault simulation data is divided into a plurality of data blocks with uniform structures;

[0089] Step 203, according to the viewpoint position, the CPU is used to load the corresponding data block into the memory in real time, and the geological block to be rendered is loaded into the display memory of the GPU;

[0090] Step 204, based on the GPU parallel computing platform, using the GPU stream processor to construct a multi-resolution LOD model in parallel and render the geological body.

[0091] Specifically, obtaining fault simulation data is the starting point of the rendering process, which usually involves reading the geological volume data corrected by fault insertion from a database or file system. The three-dimensional grid division method is used to divide this data into multiple uniformly structured data blocks, which helps to improve the efficiency of data processing and rendering. The viewpoint position is considered to ensure that the rendered geological volume blocks match the user's perspective and improve the real-time and accuracy of the rendering. In this process, the parameters that may need to be set include the size of the data block, the accuracy of the grid division, the update frequency of the viewpoint, etc.

[0092] Preferably, in order to further improve the efficiency and quality of rendering, the hierarchical detail LOD technology can be used to dynamically adjust the detail level of the rendering according to the viewpoint distance. In addition, multi-threading or multi-process technology can be introduced to accelerate the loading and processing of data blocks. In terms of GPU rendering, the shader program and rendering pipeline can be optimized to fully utilize the parallel computing power of the GPU. The introduction of these technologies can make the rendering of geological bodies more efficient and realistic, while improving the user experience.

[0093] In some embodiments, the three-dimensional grid division method is used to divide the fault simulation data into multiple data blocks with uniform structures, including: according to a preset data block density threshold, a three-dimensional grid division method is used to divide the fault simulation data layer by layer to obtain sub-blocks, and adjacent sub-blocks are merged according to the number of data points in adjacent sub-blocks until the total number of sub-block points reaches a threshold value to obtain multiple data blocks.

[0094] It should be noted that the 3D meshing method in this embodiment is to effectively organize the fault simulation data into uniformly structured data blocks for subsequent rendering processing. This method ensures that each data block remains consistent in size and complexity by dividing the data layer by layer, thereby improving the efficiency and quality of rendering.

[0095] Specifically, the 3D meshing method involves segmenting the fault simulation data according to a preset data block density threshold. This usually includes determining the size, shape, and distribution of the data block, and how to optimize these parameters based on the characteristics of the data. The merging of data blocks is based on the number of data points in adjacent sub-blocks. The final data block is formed by merging adjacent sub-blocks to reach the total number of sub-block points. In this process, the parameters that may need to be set include the minimum and maximum size of the data block, the merging threshold, the segmentation accuracy, etc.

[0096] Preferably, in order to further improve the rendering efficiency of data blocks, a spatial partitioning algorithm, such as an octree or a quadtree, can be used to optimize the organizational structure of the data blocks. In addition, it is possible to consider introducing an adaptive grid partitioning technology to dynamically adjust the size and number of data blocks according to the local complexity of the data. When merging adjacent sub-blocks, error analysis can be introduced to ensure that the merging operation does not have a negative impact on the rendering result.

[0097] In some embodiments, the method of loading corresponding data blocks into memory in real time using the CPU according to the viewpoint position, and loading the geological blocks to be rendered into the display memory of the GPU, includes:

[0098] Calculate the address of the geological body data block file to be loaded into the memory and cache data according to the current viewpoint position; construct the memory and cache data using a linked list data structure, and initialize the loading of cache and memory geological body block data;

[0099] When the viewpoint changes, determine the type of viewpoint movement and update the memory data; calculate the cache update threshold, determine whether to clear useless data in the cache and whether to load external memory data into the cache, and perform the required clearing or loading operations.

[0100] Specifically, the address of the geological data block file to be loaded into the memory and cached data is calculated according to the current viewpoint position, which involves determining the spatial relationship between the user's perspective and the geological data, and how to select the data blocks to be loaded based on this relationship. The construction of the linked list data structure is used to manage memory and cache data, which helps to organize and access data blocks efficiently.

[0101] Furthermore, when the viewpoint changes, the memory data needs to be updated, which may involve loading, unloading and replacing data blocks. In this process, the parameters that may need to be set include the detection frequency of viewpoint updates, the loading and unloading strategies of data blocks, and the management strategies of memory and cache.

[0102] Preferably, in order to improve the efficiency of data processing and rendering, a prediction algorithm can be used to predict the changing trend of the user's perspective, so as to load and render the corresponding data blocks in advance. In addition, data pre-fetching technology can be introduced to pre-load the data blocks that may be needed according to the user's interaction mode and historical data.

[0103] Furthermore, in terms of memory and cache management, intelligent cache replacement algorithms, such as the least recently used (LRU) algorithm, can be used to optimize the storage and replacement of data blocks. The introduction of these technologies can make the processing of viewpoint positions more efficient and intelligent, thereby improving the user experience.

[0104] It should be particularly noted that the three-dimensional modeling and rendering method 200 for dynamically inserting a hidden fault into a geological body provided in an embodiment of the present invention only shows the part related to the technical problem to be solved by the embodiment of the present invention. It can be understood that the three-dimensional modeling and rendering method 200 for dynamically inserting a hidden fault into a geological body provided in an embodiment of the present invention also includes other steps for realizing the functions of the three-dimensional modeling and rendering method 200 for dynamically inserting a hidden fault into a geological body, which will not be repeated here one by one.

[0105] Reference below Figure 3 , which shows a schematic diagram of a structure 300 of an electronic device suitable for implementing some embodiments of the present invention. The electronic devices in some embodiments of the present invention may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0106] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0107] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0108] Furthermore, the storage medium of the embodiment of the present application stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present invention as above, which are not provided in detail for the sake of simplicity. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A three-dimensional modeling method for dynamically inserting a hidden fault into a geological body, characterized in that: The steps include: Based on geological body feature analysis and fault identification algorithm, the geological body data is preprocessed, and then the dynamic insertion algorithm is used to simulate the fault to obtain the fault simulation data; Obtain the fault insertion starting point in the fault simulation data, build an insertion model according to the fault insertion starting point, insert faults to both sides respectively, and obtain fault insertion trajectory data; The model parameters are set according to the fault insertion trajectory data to limit the simulation range of the dynamic insertion algorithm; Under the criterion of the highest matching degree between the fault insertion trajectory and the geological body data, the optimal fault parameters are searched based on the geological body structure model and the fault kinematic model, and the fault insertion correction is performed on the geological body.

2. The three-dimensional modeling method of dynamically inserting a hidden fault into a geological body according to claim 1, characterized in that: The geological body feature analysis is performed using Fourier transform; the mathematical model of the fault identification algorithm is: Among them, f(x) is the geological body data function, and F(x) is the Fourier transform result.

3. The three-dimensional modeling method for dynamically inserting a hidden fault into a geological body according to claim 2, characterized in that: The preprocessing of geological body data includes: The geological body data with window function applied is used as input data, the fault position of the current stage is estimated according to the fault simulation results of the previous stage, and the optimal window function parameters are selected according to the position and geological body data characteristics; Obtaining a corresponding window function according to the window function parameters, and obtaining an amplitude-frequency response curve according to the shape of the window function; According to the amplitude-frequency response curve, the coefficient of the FIR filter is designed by the least square method; the geological body data is filtered by the FIR filter, and then the fault identification coefficient of the window function corresponding to the window function parameter is used to identify the fault of the geological body data.

4. The three-dimensional modeling method of dynamically inserting a hidden fault into a geological body according to claim 3, characterized in that: The optimal window function parameters are the window function parameters corresponding to the minimum error under different geological body characteristics.

5. The three-dimensional modeling method of dynamically inserting a hidden fault into a geological body according to claim 1, characterized in that: The step of obtaining a fault insertion starting point in the fault simulation data comprises: The geological body data is subjected to the operations of feature extraction, fault identification and fault position estimation to obtain the fault position of the fault domain; Search for the maximum fault position of each geological body as the position of each fault, perform curve fitting on the fault positions of multiple adjacent geological bodies in sections, and calculate the relative deviation of each fault in the curve fitting results and the average deviation of the faults in the section; The fault segment with the smallest average deviation is taken as the segment target, and the fault position is selected according to the relative deviation threshold. The fault domain feature information of each selected fault position is extracted, and the most significant feature is selected as the starting point of fault insertion.

6. The three-dimensional modeling method of dynamically inserting a hidden fault into a geological body according to claim 1, characterized in that: The parameter range of the fault insertion model is: P={(x,y,z)|x∈[x1,x2],y∈[y1,y2],z∈[z1,z2]} Among them, the coordinates of the starting point of fault insertion are (x1, y1, z1), x1, y1, z1 are the minimum coordinate values ​​of the geological body data, and x2, y2, z2 are the maximum coordinate values ​​of the geological body data.

7. The three-dimensional rendering method for dynamically inserting a hidden fault into a geological body according to claim 1, characterized in that: The fault insertion correction of the geological body includes: dividing each geological body data into multiple sections along the fault insertion direction according to the geological body data, first obtaining the geological body structure before and after the central fault parameter adjustment according to the difference of the geological body data before and after the fault insertion, and then obtaining the geological body structure and fault insertion position before and after the adjustment of other fault parameters.

8. A three-dimensional rendering method for dynamically inserting a hidden fault into a geological body, characterized in that: The steps include: Acquire fault simulation data obtained by the three-dimensional modeling method for dynamically inserting a hidden fault into a geological body according to any one of claims 1 to 7; Based on the three-dimensional grid division method, the fault simulation data is divided into multiple data blocks with uniform structures; According to the viewpoint position, the CPU is used to load the corresponding data blocks into the memory in real time, and the geological blocks to be rendered are loaded into the GPU's video memory; Based on the GPU parallel computing platform, GPU stream processors are used to build multi-resolution LOD models in parallel to render geological bodies.

9. The three-dimensional rendering method for dynamically inserting a hidden fault into a geological body according to claim 8, characterized in that: The method is based on a three-dimensional grid division method to divide the fault simulation data into multiple data blocks with uniform structures, including: according to a preset data block density threshold, using a three-dimensional grid division method to divide the fault simulation data layer by layer to obtain each sub-block, and according to the number of data points in adjacent sub-blocks, merging adjacent sub-blocks until a total point count threshold of the sub-block is reached to obtain multiple data blocks.

10. The three-dimensional rendering method of dynamically inserting a hidden fault into a geological body according to claim 9, characterized in that: According to the viewpoint position, the CPU is used to load the corresponding data block into the memory in real time, and the geological block to be rendered is loaded into the display memory of the GPU, including: Calculate the address of the geological body data block file to be loaded into the memory and cache data according to the current viewpoint position; construct the memory and cache data using a linked list data structure, and initialize the loading of cache and memory geological body block data; When the viewpoint changes, determine the type of viewpoint movement and update the memory data; calculate the cache update threshold, determine whether to clear useless data in the cache and whether to load external memory data into the cache, and perform the required clearing or loading operations.

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