Oil and gas field three-dimensional geological modeling and visualization method and system, electronic equipment and storage medium

Abstract

The invention belongs to the field of oil and gas field geological modeling, and discloses an oil and gas field three-dimensional geological modeling and visualization method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining a geological map of a to-be-modeled region, and collecting geological data of an oil and gas field through a ground penetrating radar, the geological data comprising rock stratum data and soil data; preprocessing the geological map and the geological data to obtain preprocessed data, and fusing the preprocessed data to obtain a three-dimensional geological data set; based on the three-dimensional geological data set, constructing a three-dimensional geological model of the oil and gas field by using a finite element method and a deep learning technology; and displaying the three-dimensional geologic model through an AR technology to complete visualization of the model. Key problems in the prior art can be effectively solved, powerful technical support is provided for efficient exploration and development of oil and gas fields, and important practical application value and wide market prospects are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field geological modeling, and particularly relates to a three-dimensional geological modeling and visualization method, system, electronic device and storage medium for oil and gas fields. Background Art

[0002] With the increasing scarcity of global oil and gas resources and the continuous increase in the difficulty of exploration and development, the efficient exploration and development of oil and gas fields have become one of the core challenges in the energy industry. Although traditional two-dimensional geological modeling methods have played an important role in early exploration, they have obvious limitations in describing complex geological structures, dynamic prediction, and multidisciplinary collaboration. Two-dimensional modeling methods usually can only display geological profiles or planar information, and it is difficult to accurately reflect the three-dimensional geological characteristics of oil and gas fields, such as faults, folds, lithological changes, and fluid distributions. In addition, the two-dimensional modeling has insufficient capabilities in data integration and dynamic simulation, resulting in its gradually limited application in modern oil and gas field development.

[0003] In recent years, with the rapid development of computer technology, numerical simulation methods, and artificial intelligence technology, three-dimensional geological modeling and visualization technology has gradually become an important tool for oil and gas field exploration and development. Three-dimensional modeling can comprehensively and intuitively display the geological structure of oil and gas fields, providing a scientific basis for drilling path optimization, reservoir prediction, and resource assessment. However, the existing three-dimensional modeling technologies still have many deficiencies. First, the multi-source data fusion ability is limited, and geological, geophysical, and geochemical data from different sources are often difficult to be efficiently integrated, resulting in insufficient modeling accuracy. Second, the existing modeling methods have low computational efficiency when dealing with complex geological bodies, and it is difficult to meet the rapid modeling requirements of large-scale oil and gas fields. In addition, the visualization effect of three-dimensional models still needs to be improved, especially in dynamic display and multi-attribute overlay, and the existing technologies are difficult to meet the actual application requirements.

[0004] In summary, developing an efficient, accurate, and reliable three-dimensional geological modeling and visualization method is of great significance for improving the exploration and development efficiency of oil and gas fields, reducing development costs, and increasing resource utilization. Based on this background, the present patent technology proposes an innovative three-dimensional geological modeling and visualization method, aiming to solve the key problems in the existing technology and provide strong technical support for the efficient development of oil and gas fields. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a three-dimensional geological modeling and visualization method for oil and gas fields, and the method includes:

[0006] Obtain geological maps of the area to be modeled, and collect geological data of the oil and gas field by using ground penetrating radar, where the geological data includes rock layer data and soil data;

[0007] Preprocess the geological maps and geological data to obtain preprocessed data, and fuse the preprocessed data to obtain a three-dimensional geological dataset;

[0008] Based on the three-dimensional geological dataset, use the finite element method and deep learning technology to construct a three-dimensional geological model of the oil and gas field;

[0009] Display the three-dimensional geological model through AR technology to complete the visualization of the model.

[0010] Preferably, the preprocessing method includes:

[0011] Perform denoising processing on the geological maps and geological data using Gaussian filtering to obtain denoised images and denoised geological data;

[0012] Use the Sobel operator to enhance the edges of the denoised image, and unify the scales and projection methods of the enhanced images with different scales and projection methods to obtain processed geological maps;

[0013] Perform systematic error correction on the denoised geological data, use Kriging interpolation to fill in the missing data, and perform standardization processing on the corrected and filled geological data to obtain processed geological data.

[0014] Preferably, the fusion method includes:

[0015] Register the processed geological maps and the processed geological data spatially to obtain registered geological maps and registered geological data;

[0016] Extract the key features from the registered geological maps and the registered geological data, and use the weighted average fusion method to fuse the key features to obtain the three-dimensional geological dataset.

[0017] Preferably, the method for constructing the three-dimensional geological model includes:

[0018] Discretize the three-dimensional geological dataset into finite element meshes, and set physical equations describing the mechanical behavior of rock formations based on geomechanics;

[0019] Set the boundary conditions and initial conditions of the model according to the three-dimensional geological dataset, and based on the boundary conditions and the initial conditions, use the finite element method to solve the physical equations to obtain the mechanical parameters of the rock formations;

[0020] Convert the three-dimensional geological dataset into a multi-dimensional tensor, construct a deep learning model and use the converted data to train the model to obtain a feature extraction model;

[0021] Extract the features in the 3D geological data using the feature extraction model, and fuse the features with the mechanical parameters to obtain the fused data;

[0022] Construct the 3D geological model based on the fused data.

[0023] The present invention also provides a 3D geological modeling and visualization system for oil and gas fields, which is used to implement the method described in any one of the above, including: a data acquisition module, a data processing module, a model construction module, and a model display module;

[0024] The data acquisition module is used to obtain the geological maps of the area to be modeled and collect the geological data of the oil and gas field using a ground penetrating radar, and the geological data includes rock layer data and soil data;

[0025] The data processing module is used to preprocess the geological maps and the geological data to obtain the preprocessed data, and fuse the preprocessed data to obtain a 3D geological data set;

[0026] The model construction module constructs a 3D geological model of the oil and gas field based on the 3D geological data set using the finite element method and deep learning technology;

[0027] The model display module is used to display the 3D geological model through AR technology to complete the visualization of the model.

[0028] Preferably, in the data processing module, the preprocessing process includes:

[0029] Perform denoising processing on the geological maps and the geological data using Gaussian filtering to obtain the denoised image and the denoised geological data;

[0030] Use the Sobel operator to enhance the edges of the denoised image, and unify the scales and projection methods of the enhanced images with different scales and projection methods to obtain the processed geological maps;

[0031] Perform systematic error correction on the denoised geological data, fill in the missing data using Kriging interpolation, and perform standardization processing on the corrected and filled geological data to obtain the processed geological data.

[0032] Preferably, in the data processing module, the fusion process includes:

[0033] Register the processed geological maps and the processed geological data spatially to obtain the registered geological maps and the registered geological data;

[0034] Extract the key features from the registered geological maps and the registered geological data, and use the weighted average fusion method to fuse the key features to obtain the three-dimensional geological data set.

[0035] Preferably, the working process of the model construction module includes:

[0036] Discretize the three-dimensional geological data set into finite element meshes, and set physical equations describing the mechanical behavior of rock formations based on geomechanics;

[0037] Set the boundary conditions and initial conditions of the model according to the three-dimensional geological data set. Based on the boundary conditions and the initial conditions, use the finite element method to solve the physical equations to obtain the mechanical parameters of the rock formations;

[0038] Convert the three-dimensional geological data set into a multi-dimensional tensor, construct a deep learning model and use the converted data to train the model to obtain a feature extraction model;

[0039] Use the feature extraction model to extract the features in the three-dimensional geological data, and fuse the features with the mechanical parameters to obtain the fused data;

[0040] Construct the three-dimensional geological model based on the fused data.

[0041] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the oil and gas field three-dimensional geological modeling and visualization method according to any one of claims 1 to 4.

[0042] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed, it implements the oil and gas field three-dimensional geological modeling and visualization method according to any one of claims 1 to 4.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] Through the multi-source data fusion technology, the present invention can efficiently integrate the geological, geophysical, and geochemical data of oil and gas fields, solve the problem of insufficient data integration ability in traditional modeling methods, and significantly improve the accuracy and reliability of the three-dimensional geological model; secondly, the visualization technology of the present invention can display the shape, attributes, and dynamic changes of the geological model in an intuitive and vivid manner; finally, through the model verification and optimization steps, the present invention ensures a high degree of consistency between the modeling results and the actual data. This verification mechanism not only improves the credibility of the model but also provides reliable technical support for subsequent development plan adjustment.

[0045] In summary, the present invention has significant advantages in improving modeling accuracy, optimizing calculation efficiency, enhancing visualization effects, and improving decision-making support capabilities. It can effectively solve the key problems in the prior art, provide strong technical support for the efficient exploration and development of oil and gas fields, and has important practical application value and broad market prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1 is a schematic flowchart of the method according to an embodiment of the present invention;

[0048] Figure 2 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

[0049] Description of the reference numerals:

[0050] 1010, processor; 1020, memory; 1030, input / output interface; 1040, communication interface; 1050, bus. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the ordinary meaning understood by those of ordinary skill in the art in the field to which the present disclosure belongs. The "first", "second" and similar terms used in the embodiments of the present disclosure do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or items appearing before this term cover the elements or items listed after this term and their equivalents, without excluding other elements or items. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "up", "down", "left", "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0053] Example 1

[0054] In this example, as Figure 1 shown, a three-dimensional geological modeling and visualization method for oil and gas fields, the method comprising:

[0055] S1. Obtain geological maps of the area to be modeled, and use ground penetrating radar to collect geological data of the oil and gas field, the geological data including rock formation data and soil data.

[0056] S2. Preprocess the geological maps and geological data to obtain preprocessed data, and fuse the preprocessed data to obtain a three-dimensional geological data set.

[0057] The preprocessing method includes: performing denoising processing on the geological maps and geological data using Gaussian filtering to obtain a denoised image and denoised geological data; using the Sobel operator to enhance the edges of the denoised image, and unifying the scales and projection methods of the enhanced images with different scales and projection methods to obtain a processed geological map; performing systematic error correction on the denoised geological data, filling in missing data using Kriging interpolation, and performing standardization processing on the corrected and filled geological data to obtain processed geological data.

[0058] In this example, Gaussian filtering is used to perform denoising processing on the geological maps and geological data to obtain a denoised image and denoised geological data. The formula for Gaussian filtering is:

[0059]

[0060] where G(x, y) represents the value of the Gaussian filter at (x, y), and σ is the standard deviation; the Sobel operator is used to enhance the edges of the denoised image to highlight the boundaries of geological structures. The formula for the Sobel operator is:

[0061]

[0062] where G x represents the gradient operator in the horizontal direction, and G y represents the gradient operator in the vertical direction; then, the scales and projection methods of the enhanced images with different scales and projection methods are unified to obtain a processed geological map. Then, systematic error correction is performed on the geological data collected by the ground penetrating radar, such as time zero correction, velocity correction, etc. For missing data points, Kriging interpolation is used for interpolation to fill in the data gaps. The formula for Kriging interpolation is:

[0063]

[0064] where represents the estimated value at point s0, and λi denotes the weight coefficient, and \(z(s i ) represents the observed value at the known point \(s i . The geological data is standardized to have the same dimension and range, facilitating subsequent fusion and modeling.

[0065] The fusion method includes: registering the processed geological map and the processed geological data spatially to obtain the registered geological map and the registered geological data; extracting the key features from the registered geological map and the registered geological data, and using the weighted average fusion method to fuse the key features to obtain a three-dimensional geological dataset.

[0066] In this embodiment, the preprocessed geological map and geological data are registered spatially to ensure that they are in the same coordinate system; the key features in the geological map and geological data are extracted, such as formation interfaces, faults, porosity, permeability, etc.; the geological map and geological data are fused using methods such as weighted average or neural network to obtain a three-dimensional geological dataset. The formula for weighted average is:

[0067] D 融合 =\(\alpha D 图件 +(1 - \alpha)D 数据

[0068] where \(D 融合 represents the fused data, \(D 图件 represents the geological map, \(D 数据 represents the geological data, and \(\alpha\) represents the weight coefficient, which is usually determined according to the reliability and importance of the data.

[0069] S3. Based on the three-dimensional geological dataset, use the finite element method and deep learning technology to construct a three-dimensional geological model of the oil and gas field.

[0070] The method for constructing the three-dimensional geological model includes: discretizing the three-dimensional geological dataset into finite element meshes and setting up physical equations describing the mechanical behavior of rock formations based on geomechanics; setting the boundary conditions and initial conditions of the model according to the three-dimensional geological dataset, and using the finite element method to solve the physical equations based on the boundary conditions and initial conditions to obtain the mechanical parameters of the rock formations; converting the three-dimensional geological dataset into a multi-dimensional tensor, constructing a deep learning model and training the model using the converted data to obtain a feature extraction model; using the feature extraction model to extract the features from the three-dimensional geological data and fusing the features with the mechanical parameters to obtain the fused data; constructing a three-dimensional geological model based on the fused data.

[0071] In this embodiment, the three-dimensional geological dataset is discretized into a finite element mesh, and the complex geological structure is divided into multiple finite element units. Each unit can be a tetrahedron, a hexahedron, or other suitable geometric shapes to adapt to the complexity of different geological structures. According to the basic principles of geomechanics, physical equations describing the mechanical behavior of rock formations are set, such as elastic mechanics equations or seepage equations, to describe the response of rock formations under conditions such as pressure, temperature, and fluid flow. According to the geological dataset, the boundary conditions (such as surface pressure, formation pressure) and initial conditions (such as initial temperature, initial pore pressure) of the model are set to ensure the physical rationality of the model. The physical equations are numerically solved by the finite element method to obtain the distribution of mechanical parameters such as stress, strain, and pore pressure of the rock formation.

[0072] The three-dimensional geological dataset is converted into a format suitable for input to a deep learning model, that is, geological maps and geological data are converted into multi-dimensional tensors. A suitable deep learning model (such as a convolutional neural network CNN or a generative adversarial network GAN) is selected, and the model is trained using the geological dataset to learn the patterns in the geological data, such as the distribution of rock formations, the change in porosity, and the identification of abnormal geological structures, to obtain a feature extraction model. The features in the geological data (such as rock formation boundaries, porosity distributions, abnormal areas, etc.) are extracted by the deep learning model, and these features are fused with the mechanical parameters to enhance the expression ability of the model. By adjusting the hyperparameters of the deep learning model (such as learning rate, number of network layers, activation function, etc.), the performance of the model is optimized to enable it to more accurately predict the complex changes in geological structures. The mechanical parameters (such as stress, strain) calculated by the finite element method are fused with the geological features (such as rock formation boundaries, abnormal areas) extracted by the deep learning model to form a unified three-dimensional geological model.

[0073] S4. The three-dimensional geological model is displayed through AR technology to complete the visualization of the model.

[0074] In this embodiment, Unity is used in combination with the ARKit framework to build an augmented reality display environment, including landmarks and planes, and the constructed three-dimensional geological model data is converted into a format suitable for AR devices. Through AR technology, the three-dimensional geological model is projected onto the plane according to the landmarks to complete the visualization of the model.

[0075] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server, etc. The method of this embodiment can also be applied to a distributed scenario, and multiple devices cooperate with each other to complete it. In the case of such a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0076] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, it should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not imply the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention. The actions or steps recited in the claims may be executed in a different order than in the above embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] Embodiment 2

[0078] In this embodiment, an oil and gas field three-dimensional geological modeling and visualization system includes: a data acquisition module, a data processing module, a model construction module, and a model display module.

[0079] The data acquisition module is used to obtain geological maps of the area to be modeled and collect geological data of the oil and gas field using ground-penetrating radar. The geological data includes rock layer data and soil data.

[0080] The data processing module is used to preprocess the geological maps and geological data to obtain preprocessed data, and fuse the preprocessed data to obtain a three-dimensional geological data set.

[0081] In the data processing module, the preprocessing process includes: performing denoising processing on the geological maps and geological data using Gaussian filtering to obtain denoised images and denoised geological data; using the Sobel operator to enhance the edges of the denoised images, and unifying the scales and projection methods of the enhanced images with different scales and projection methods to obtain processed geological maps; correcting the systematic errors of the denoised geological data, filling in the missing data using Kriging interpolation method, and performing standardization processing on the corrected and filled geological data to obtain processed geological data.

[0082] The fusion process includes: registering the processed geological maps and processed geological data in space to obtain registered geological maps and registered geological data; extracting the key features from the registered geological maps and registered geological data, and fusing the key features using a weighted average fusion method to obtain a three-dimensional geological data set.

[0083] The model construction module constructs a three-dimensional geological model of the oil and gas field based on the three-dimensional geological data set using the finite element method and deep learning technology.

[0084] The workflow of the model construction module includes: discretizing the three-dimensional geological data set into a finite element mesh and setting up physical equations describing the mechanical behavior of rock formations based on geomechanics; setting the boundary conditions and initial conditions of the model according to the three-dimensional geological data set, and using the finite element method to solve the physical equations based on the boundary conditions and initial conditions to obtain the mechanical parameters of the rock formations; converting the three-dimensional geological data set into a multi-dimensional tensor, constructing a deep learning model and training the model using the converted data to obtain a feature extraction model; using the feature extraction model to extract features from the three-dimensional geological data and fusing the features with the mechanical parameters to obtain fused data; constructing a three-dimensional geological model based on the fused data.

[0085] The model display module is used to display the three-dimensional geological model through AR technology to complete the visualization of the model.

[0086] The system of the above embodiment is used to implement the corresponding oil and gas field three-dimensional geological modeling and visualization method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0087] It should be noted that the above oil and gas field three-dimensional geological modeling and visualization system is embodied in the form of functional units. The term "module" here can be implemented in software and / or hardware forms, and no specific limitation is made thereto.

[0088] For example, the "module" can be a software program, a hardware circuit, or a combination of both that implements the above functions. The hardware circuit may include an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a proprietary processor, or a group of processors, etc.) for executing one or more software or firmware programs, a memory, a merged logic circuit, and / or other suitable components that support the described functions.

[0089] Embodiment III

[0090] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the oil and gas field three-dimensional geological modeling and visualization method described in any of the above embodiments.

[0091] Figure 2FIG. 0 shows a more specific schematic diagram of the hardware structure of the electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. Among them, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other inside the device through the bus 1050.

[0092] The processor 1010 may be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0093] The memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0094] The input / output interface 1030 is used to connect to an input / output module to implement information input and output. The input / output module may be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Among them, the input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0095] The communication interface 1040 is used to connect to a communication module (not shown in the figure) to implement communication interaction between this device and other devices. Among them, the communication module may implement communication in a wired manner (such as USB (Universal Serial Bus), network cable, etc.) or in a wireless manner (such as mobile network, WIFI (Wireless Fidelity), Bluetooth, etc.).

[0096] The bus 1050 includes a path for transmitting information between various components of the device (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0097] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device may also only include the components necessary to implement the solution of the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0098] The system of the above embodiment is used to implement the corresponding oil and gas field three-dimensional geological modeling and visualization method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0099] Embodiment 4

[0100] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the oil and gas field three-dimensional geological modeling and visualization method as described in any of the above embodiments.

[0101] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0102] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to execute the oil and gas field three-dimensional geological modeling and visualization method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0103] Those of ordinary skill in the art should understand that: Any discussion of the above embodiments is exemplary only and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; Under the concept of the present disclosure, 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 variations in different aspects of the embodiments of the present disclosure as described above. For the sake of brevity, they are not provided in detail.

[0104] In addition, for simplicity of explanation and discussion, and in order not to make the embodiments of the present disclosure difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Further, the devices may be shown in block diagram form in order to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of such block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure are to be implemented (i.e., these details should be entirely within the understanding of those skilled in the art). In cases where specific details (such as circuits) are set forth to describe exemplary embodiments of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure can be implemented without these specific details or with variations of these specific details. Accordingly, these descriptions should be considered illustrative rather than restrictive.

[0105] Although the present disclosure has been described in connection with specific embodiments of the present disclosure, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0106] Therefore, the units of the examples described in the embodiments of the present application can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0107] The embodiments of the present disclosure are intended to cover all such alternatives, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the embodiments of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A three-dimensional geological modeling and visualization method for oil and gas fields, characterized in that, The method includes: Obtaining geological maps of the area to be modeled, and collecting geological data of the oil and gas field using ground penetrating radar, where the geological data includes rock formation data and soil data; Preprocessing the geological maps and the geological data to obtain preprocessed data, and fusing the preprocessed data to obtain a three-dimensional geological data set; Based on the three-dimensional geological data set, using the finite element method and deep learning technology to construct a three-dimensional geological model of the oil and gas field; Displaying the three-dimensional geological model through AR technology to complete the visualization of the model.

2. The 3D geological modeling and visualization method for oil and gas fields according to claim 1, characterized in that The method of the preprocessing includes: Performing denoising processing on the geological maps and the geological data using Gaussian filtering to obtain denoised images and denoised geological data; Using the Sobel operator to enhance the edges of the denoised images, and unifying the scales and projection methods of the enhanced images with different scales and projection methods to obtain processed geological maps; Performing systematic error correction on the denoised geological data, filling in missing data using Kriging interpolation method, and performing standardization processing on the corrected and filled geological data to obtain processed geological data.

3. The 3D geological modeling and visualization method for oil and gas fields according to claim 2, wherein, The method of the fusion includes: Registering the processed geological maps and the processed geological data spatially to obtain registered geological maps and registered geological data; Extracting key features from the registered geological maps and the registered geological data, and fusing the key features using a weighted average fusion method to obtain the three-dimensional geological data set.

4. The 3D geological modeling and visualization method for oil and gas fields according to claim 1, characterized in that The method of constructing the three-dimensional geological model includes: Discretizing the three-dimensional geological data set into finite element meshes, and setting physical equations describing the mechanical behavior of rock formations based on geomechanics; Setting boundary conditions and initial conditions of the model according to the three-dimensional geological data set, and solving the physical equations using the finite element method based on the boundary conditions and the initial conditions to obtain the mechanical parameters of the rock formations; Converting the three-dimensional geological data set into a multi-dimensional tensor, constructing a deep learning model and training the model using the converted data to obtain a feature extraction model; Extracting features from the three-dimensional geological data using the feature extraction model, and fusing the features with the mechanical parameters to obtain fused data; Constructing the three-dimensional geological model based on the fused data.

5. A three-dimensional geological modeling and visualization system for oil and gas fields, the system being used to implement the method according to any one of claims 1-4, characterized in that, It includes: A data acquisition module, a data processing module, a model construction module, and a model display module; The data acquisition module is used to obtain geological maps of the area to be modeled, and collect geological data of the oil and gas field using ground penetrating radar, where the geological data includes rock formation data and soil data; The data processing module is used to preprocess the geological maps and the geological data to obtain preprocessed data, and fuse the preprocessed data to obtain a three-dimensional geological data set; The model construction module constructs a three-dimensional geological model of the oil and gas field based on the three-dimensional geological data set using the finite element method and deep learning technology; The model display module is used to display the three-dimensional geological model through AR technology to complete the visualization of the model.

6. The 3D geological modeling and visualization system for oil and gas fields according to claim 5, characterized in that, In the data processing module, the preprocessing process includes: The geological map and the geological data are denoised by using Gaussian filtering to obtain the denoised image and the denoised geological data; The Sobel operator is used to enhance the edges of the denoised image, and the enhanced images with different scales and projection methods are unified in terms of scale and projection method to obtain the processed geological map; The systematic error of the denoised geological data is corrected, the Kriging interpolation method is used to fill in the missing data, and the corrected and filled geological data is standardized to obtain the processed geological data.

7. The 3D geological modeling and visualization system for oil and gas fields according to claim 6, wherein, In the data processing module, the fusion process includes: The processed geological map and the processed geological data are registered spatially to obtain the registered geological map and the registered geological data; The key features in the registered geological map and the registered geological data are extracted, and the key features are fused by using a weighted average fusion method to obtain the three-dimensional geological data set.

8. The 3D geological modeling and visualization system for oil and gas fields according to claim 5, characterized in that The working process of the model construction module includes: The three-dimensional geological data set is discretized into finite element meshes, and physical equations describing the mechanical behavior of rock formations are set based on geomechanics; According to the three-dimensional geological data set, the boundary conditions and initial conditions of the model are set, and based on the boundary conditions and the initial conditions, the physical equations are solved by using the finite element method to obtain the mechanical parameters of the rock formations; The three-dimensional geological data set is converted into a multi-dimensional tensor, a deep learning model is constructed, and the model is trained by using the converted data to obtain a feature extraction model; The feature extraction model is used to extract the features in the three-dimensional geological data, and the features are fused with the mechanical parameters to obtain the fused data; The three-dimensional geological model is constructed based on the fused data.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the oil and gas field three-dimensional geological modeling and visualization method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed, it implements the oil and gas field three-dimensional geological modeling and visualization method according to any one of claims 1 to 4.

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