Method, device, equipment and medium for determining porosity of carbonate rock thin section
By processing carbonate rock thin section image data using a pore identification model, generating a pore distribution heat map, and combining it with experimental data for correction, the problem of low efficiency and poor accuracy in porosity calculation in traditional methods is solved, achieving efficient and accurate porosity determination.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2025-12-12
- Publication Date
- 2026-07-03
AI Technical Summary
Traditional methods for calculating the porosity of carbonate rock thin sections are inefficient and inaccurate, making it difficult to meet the needs of large-scale exploration data. Furthermore, they are susceptible to interference from impurities and fractures, and cannot accurately distinguish between effective and ineffective porosity.
A pore identification model (such as a CNN model) is used to process carbonate rock thin section image data to generate a pore distribution heat map. Porosity is calculated by combining the total effective pore area with the total area of the thin section, and the calculation accuracy is improved by combining core experiments and well logging data.
It enables accurate calculation of the porosity of carbonate rock thin sections, improves analysis and processing efficiency, meets the batch image data processing needs of large-scale exploration, and shortens the analysis time to the second level.
Smart Images
Figure CN122335950A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of oil and gas reservoir exploration and development technology, specifically to a method, apparatus, equipment, medium and product for determining the porosity of carbonate rock thin sections. Background Technology
[0002] In traditional methods, porosity is mostly estimated by geologists through manual observation of images of carbonate rock thin sections and combined with core experimental data, or indirectly calculated through a single well logging curve.
[0003] However, traditional methods rely on manual identification by geologists, which is inefficient and makes it difficult to meet the needs of large-scale exploration data. Furthermore, these methods are susceptible to interference from impurities and fractures, making it impossible to accurately distinguish between effective and ineffective pores. This results in low porosity calculation accuracy, with calculation errors often exceeding 15%. Summary of the Invention
[0004] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for determining the porosity of carbonate rock thin sections, in order to solve the technical defects of low processing efficiency and poor porosity calculation accuracy of existing technologies for carbonate rock thin sections.
[0005] To achieve the above objectives, the first aspect of this application provides a method for determining the porosity of carbonate rock thin sections, the method comprising: Acquire thin section image data of carbonate rocks from the target well; Based on the pore identification model, a pore distribution thermogram corresponding to a carbonate rock thin section is obtained from the thin section image data. The total effective pore area is determined based on the pore distribution thermogram. The porosity of carbonate rock thin sections is determined based on the total effective pore area and the total area of the thin sections.
[0006] In this embodiment of the application, acquiring thin section image data of carbonate rock thin sections of the target well includes: Acquire initial thin section image data of carbonate rock thin sections from the target well; The initial thin section image data is processed to remove scanning noise in order to obtain thin section image data of carbonate rock thin sections of the target well.
[0007] In this embodiment, the porosity of the carbonate rock thin section is determined based on the total effective pore area and the total area of the thin section, including determining the porosity according to the following formula:
[0008] In the formula, Indicates the porosity of thin sections of carbonate rocks. Represents the total effective pore area. This represents the total area of the thin sheet.
[0009] In this embodiment of the application, the method further includes: Obtain core experimental data from the target well, including experimental porosity. When the deviation between the porosity of the carbonate rock thin section and the experimental porosity is not within the preset porosity deviation range, the porosity of the carbonate rock thin section is corrected.
[0010] In this embodiment of the application, the method further includes: Acquire logging data for the target well, including logging porosity. Based on the porosity of carbonate rock thin sections and well logging porosity, determine the error rate between the porosity of carbonate rock thin sections and well logging porosity. The porosity of carbonate rock thin sections is corrected when the error rate is not within the preset error rate range.
[0011] In this embodiment of the application, the porosity correction of carbonate rock thin sections includes: The model parameters of the pore identification model are updated, and the porosity of the carbonate rock thin section is obtained again based on the updated pore identification model.
[0012] In this embodiment of the application, the aperture recognition model is a CNN model.
[0013] The second aspect of this application provides a device for determining the porosity of carbonate rock thin sections, the device comprising: The first acquisition module is used to acquire thin section image data of carbonate rock thin sections of the target well; The module is used to obtain a thermal map of pore distribution corresponding to a carbonate rock thin section based on the pore identification model and the thin section image data. The first determining module is used to determine the total effective pore area based on the pore distribution thermal map; The second determining module is used to determine the porosity of the carbonate rock thin section based on the total effective pore area and the total area of the thin section.
[0014] In this embodiment of the application, the first acquisition module is further configured to: Acquire initial thin section image data of carbonate rock thin sections from the target well; The initial thin section image data is processed to remove scanning noise in order to obtain thin section image data of carbonate rock thin sections of the target well.
[0015] In this embodiment of the application, the first determining module is further configured to determine the porosity according to the following formula:
[0016] In the formula, Indicates the porosity of thin sections of carbonate rocks. Represents the total effective pore area. This represents the total area of the thin sheet.
[0017] In this embodiment of the application, the apparatus further includes: The second acquisition module is used to acquire core experimental data of the target well, wherein the core experimental data includes experimental porosity; The first calibration module is used to calibrate the porosity of carbonate rock thin sections when the deviation between the porosity of the thin sections and the experimental porosity is not within the preset porosity deviation range.
[0018] In this embodiment of the application, the apparatus further includes: The third acquisition module is used to acquire logging data of the target well, including logging porosity. The third determination module is used to determine the error rate between the porosity of the carbonate rock thin section and the well logging porosity based on the porosity of the carbonate rock thin section and the well logging porosity. The second correction module is used to correct the porosity of carbonate rock thin sections when the error rate is not within the preset error rate range.
[0019] A third aspect of this application provides a terminal device, comprising: The memory is configured to store instructions; The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the porosity determination method for carbonate rock thin sections as provided in the first aspect above.
[0020] A fourth aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to perform the porosity determination method for carbonate rock thin sections as described in the first aspect above.
[0021] The fifth aspect of this application provides a computer program product, which includes a computer program that, when executed by a processor, implements the method for determining the porosity of carbonate rock thin sections as provided in the first aspect above.
[0022] The above technical solution involves acquiring thin-section image data of carbonate rock sections from the target well; obtaining a pore distribution heatmap of the corresponding carbonate rock thin section based on a pore identification model and the thin-section image data; determining the total effective pore area based on the pore distribution heatmap; and determining the porosity of the carbonate rock thin section based on the total effective pore area and the total area of the carbonate rock thin section. This embodiment of the application accurately distinguishes effective pores through a pore identification model, improving the efficiency of carbonate rock thin section analysis and processing, thereby meeting the needs of large-scale exploration for processing batch thin-section image data.
[0023] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description
[0024] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings: Figure 1 The schematic diagram illustrates a flow chart of a method for determining the porosity of a carbonate rock thin section according to an embodiment of this application; Figure 2 A schematic diagram of a carbonate rock thin section according to an embodiment of this application is shown; Figure 3 A schematic thermal diagram of pore distribution corresponding to a carbonate rock thin section according to an embodiment of this application is shown. Detailed Implementation
[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0026] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.
[0027] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.
[0028] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.
[0029] Figure 1 The illustration schematically shows a flowchart of a method for determining the porosity of a carbonate rock thin section according to an embodiment of this application. Figure 1 As shown in the embodiments of this application, a method for determining the porosity of carbonate rock thin sections is provided. This method may include the following steps: Step S110: Obtain thin section image data of carbonate rock thin sections from the target well; Step S120: Based on the pore identification model, obtain the pore distribution thermogram corresponding to the carbonate rock thin section according to the thin section image data; Step S130: Determine the total effective pore area based on the pore distribution thermogram; Step S140: Determine the porosity of the carbonate rock thin section based on the total effective pore area and the total area of the thin section.
[0030] In step S110, as Figure 2 As shown, Figure 2 The illustration shows a schematic diagram of a carbonate rock thin section according to an embodiment of this application. The carbonate rock thin section can cover carbonate rock thin section samples with different pore types and burial depths. The thin section image data of the carbonate rock thin section refers to a series of images and related data containing information such as rock microstructure, mineral composition, and pore characteristics obtained by observing, photographing and digitizing a standard thickness (usually 0.03 mm) thin section made from a carbonate rock sample under a polarizing microscope.
[0031] In step S120, the thin section image data is input into the pore recognition model. The pore recognition model can automatically segment the effective pore area to obtain a pore distribution heat map corresponding to the carbonate rock thin section. The pore distribution heat map is a visual chart that maps the size, number, or density of pores inside a carbonate rock thin section to their spatial location using color depth. Figure 3 A schematic diagram illustrates a pore distribution thermogram corresponding to a carbonate rock thin section according to an embodiment of this application, such as... Figure 3As shown, the blue area corresponds to the effective porosity region. In one example, this application embodiment can simultaneously input thin-section image data of thousands of carbonate rock thin sections into the porosity recognition model, and the porosity recognition model outputs a pore distribution heat map corresponding to thousands of carbonate rock thin sections, thereby improving the analysis efficiency of carbonate rock thin sections.
[0032] In step S130, the total area of effective pores is determined by the pore distribution heat map that has been segmented into effective pore regions.
[0033] In step S140, the porosity of the carbonate rock thin section can be calculated using the total effective pore area and the total area of the thin section identified in step S130. When the thin section image data is input into the porosity recognition model, the total area of the carbonate rock thin section can also be obtained through the porosity recognition model. In one example, thousands of carbonate rock thin sections are each assigned a corresponding name. For the porosity of these thousands of carbonate rock thin sections, the porosity corresponding to each carbonate rock thin section name is determined.
[0034] This application embodiment acquires thin-section image data of carbonate rock thin sections from a target well; based on a porosity identification model, a pore distribution heatmap corresponding to the carbonate rock thin section is obtained from the thin-section image data; the total effective pore area is determined based on the pore distribution heatmap; and the porosity of the carbonate rock thin section is determined based on the total effective pore area and the total area of the carbonate rock thin section. This application embodiment accurately distinguishes effective pores through a pore identification model, improving the analysis and processing efficiency of carbonate rock thin sections and reducing the analysis time of a single carbonate rock thin section from several hours to seconds, thereby meeting the needs of batch thin-section image data processing in large-scale exploration.
[0035] Furthermore, step S110 may include the following steps: Step S111: Obtain initial thin section image data of carbonate rock thin sections from the target well; Step S112: Remove scanning noise from the initial thin section image data to obtain thin section image data of carbonate rock thin sections of the target well.
[0036] In this embodiment of the application, the initial thin section image data of carbonate rock thin sections need to be preprocessed. Image denoising algorithms (such as Gaussian filtering) are used to remove scanning noise, and contrast stretching and edge sharpening techniques are used to highlight the gray-scale difference between pores and matrix, so as to improve the recognition accuracy of the pore recognition model.
[0037] Further, step S140 includes determining the porosity according to the following formula:
[0038] In the formula, Indicates the porosity of thin sections of carbonate rocks. Represents the total effective pore area. This represents the total area of the thin sheet.
[0039] In this embodiment, the quotient of the total effective pore area and the total area of the thin sheet is used as the porosity of the carbonate rock thin sheet using the above formula.
[0040] Furthermore, embodiments of this application may also include the following steps: Step S210: Obtain core experimental data from the target well, wherein the core experimental data includes experimental porosity; Step S220: If the deviation between the porosity of the carbonate rock thin section and the experimental porosity is not within the preset porosity deviation range, the porosity of the carbonate rock thin section is corrected.
[0041] In steps S210-S220 of this application embodiment, when conducting core experiments on the target well, the obtained core experiment data includes porosity (i.e., experimental porosity). The deviation between the porosity of the carbonate rock thin section and the experimental porosity is determined. If the deviation is not within a preset porosity deviation range, it indicates that the porosity of the carbonate rock thin section obtained using the porosity identification model may be somewhat inaccurate. Therefore, it is necessary to further correct the porosity of the carbonate rock thin section to obtain accurate porosity. As an example, the preset porosity deviation range can be (-5%, 5%). This application embodiment does not specifically limit the preset porosity deviation range.
[0042] Furthermore, embodiments of this application may also include the following steps: Step S310: Obtain logging data of the target well, wherein the logging data includes logging porosity; Step S320: Determine the error rate between the porosity of the carbonate rock thin section and the logging porosity based on the porosity of the carbonate rock thin section; Step S330: Correct the porosity of the carbonate rock thin section if the error rate is not within the preset error rate range.
[0043] In steps S310-S330 of this embodiment, the logging data of the target well also includes porosity (logging porosity). The error rate between the porosity of the carbonate rock thin section and the logging porosity is determined. If the error rate is not within a preset error rate range, it indicates that the porosity of the carbonate rock thin section obtained using the porosity identification model may be somewhat inaccurate. Therefore, it is necessary to further correct the porosity of the carbonate rock thin section to obtain accurate porosity. As an example, the preset error rate range can be (-5%, 5%). This embodiment does not specifically limit the preset error rate range.
[0044] Furthermore, the porosity correction of the carbonate rock thin sections in steps S220 and S330 may include the following steps: Step a: Update the model parameters of the pore identification model, and based on the updated pore identification model, re-obtain the porosity of the carbonate rock thin section.
[0045] In this embodiment, the model parameters of the pore identification model are adjusted. The updated pore identification model outputs an updated pore distribution heatmap corresponding to the carbonate rock thin section. Based on the updated pore distribution heatmap, the updated total effective pore area is re-determined. Then, based on the updated total effective pore area and the total area of the carbonate rock thin section, the updated porosity of the carbonate rock thin section is determined. This embodiment can repeat step a until the deviation is within a preset porosity deviation range and the error rate is within a preset error rate range.
[0046] In this embodiment, the aperture recognition model is a CNN (Convolutional Neural Network) model. The CNN model uses learnable filters to perform sliding convolution on the input data (thin slice image data) to automatically extract local features (such as edges and textures).
[0047] This application also provides a device for determining the porosity of carbonate rock thin sections, the device comprising: The first acquisition module is used to acquire thin section image data of carbonate rock thin sections of the target well; The module is used to obtain a thermal map of pore distribution corresponding to a carbonate rock thin section based on the pore identification model and the thin section image data. The first determining module is used to determine the total effective pore area based on the pore distribution thermal map; The second determining module is used to determine the porosity of the carbonate rock thin section based on the total effective pore area and the total area of the thin section.
[0048] Furthermore, the first acquisition module in this application embodiment is also used for: Acquire initial thin section image data of carbonate rock thin sections from the target well; The initial thin section image data is processed to remove scanning noise in order to obtain thin section image data of carbonate rock thin sections of the target well.
[0049] Furthermore, the first determining module in this embodiment is also used to determine porosity according to the following formula:
[0050] In the formula, Indicates the porosity of thin sections of carbonate rocks. Represents the total effective pore area. This represents the total area of the thin sheet.
[0051] Furthermore, the apparatus in this application embodiment also includes: The second acquisition module is used to acquire core experimental data of the target well, wherein the core experimental data includes experimental porosity; The first calibration module is used to calibrate the porosity of carbonate rock thin sections when the deviation between the porosity of the thin sections and the experimental porosity is not within the preset porosity deviation range.
[0052] Furthermore, the apparatus in this application embodiment also includes: The third acquisition module is used to acquire logging data of the target well, including logging porosity. The third determination module is used to determine the error rate between the porosity of the carbonate rock thin section and the well logging porosity based on the porosity of the carbonate rock thin section and the well logging porosity. The second correction module is used to correct the porosity of carbonate rock thin sections when the error rate is not within the preset error rate range.
[0053] It is understood that the porosity determination device for carbonate rock thin sections provided in this application embodiment can realize each process of the porosity determination method for carbonate rock thin sections in the above embodiment and achieve the same technical effect. To avoid repetition, it will not be described again here.
[0054] This application embodiment also provides a terminal device, including: The memory is configured to store instructions; The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the porosity determination method for carbonate rock thin sections as described above.
[0055] It is understood that the terminal device provided in this application embodiment can realize each process of the method for determining the porosity of carbonate rock thin sections in the above embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.
[0056] This application also provides a machine-readable storage medium storing instructions for causing a machine to perform the porosity determination method for carbonate rock thin sections as described above.
[0057] It is understood that the machine-readable storage medium provided in the embodiments of this application can implement each process of the method for determining the porosity of carbonate rock thin sections in the above embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.
[0058] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the porosity determination method for carbonate rock thin sections as described above.
[0059] It is understood that the computer program product provided in this application embodiment can implement each process of the method for determining the porosity of carbonate rock thin sections in the above embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.
[0060] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0061] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0064] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0065] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.
[0066] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.
[0067] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0068] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.
Claims
1. A method of determining porosity of a carbonate rock thin section, characterized by, The method includes: Acquire thin section image data of carbonate rocks from the target well; Based on the pore identification model, a pore distribution thermogram corresponding to the carbonate rock thin section is obtained according to the thin section image data; The total effective pore area is determined based on the aforementioned pore distribution thermogram. The porosity of the carbonate rock sheet is determined based on the total effective pore area and the total sheet area of the carbonate rock sheet.
2. The method of claim 1, wherein, The acquisition of thin section image data of carbonate rocks from the target well includes: Acquire initial thin section image data of carbonate rock thin sections from the target well; The initial thin section image data is processed to remove scanning noise in order to obtain thin section image data of carbonate rock thin sections of the target well.
3. The method of claim 1, wherein, The determination of the porosity of the carbonate rock thin section based on the total effective pore area and the total area of the thin section includes determining the porosity according to the following formula: wherein represents the porosity of the carbonate rock thin section, represents the total area of the effective pores, represents the total area of the thin section.
4. The method according to claim 1, characterized in that, The method further includes: Obtain core experimental data from the target well, wherein the core experimental data includes experimental porosity; If the deviation between the porosity of the carbonate rock thin section and the experimental porosity is not within the preset porosity deviation range, the porosity of the carbonate rock thin section is corrected.
5. The method according to claim 1, characterized in that, The method further includes: Obtain logging data of the target well, wherein the logging data includes logging porosity; Based on the porosity of the carbonate rock thin section and the logging porosity, determine the error rate between the porosity of the carbonate rock thin section and the logging porosity; If the error rate is not within the preset error rate range, the porosity of the carbonate rock sheet is corrected.
6. The method according to claim 4 or 5, characterized in that, The porosity correction of the carbonate rock thin section includes: The model parameters of the pore identification model are updated, and the porosity of the carbonate rock thin section is obtained again based on the updated pore identification model.
7. The method according to claim 1, characterized in that, The pore recognition model is a CNN model.
8. A device for determining the porosity of thin sections of carbonate rock, characterized in that, The device includes: The first acquisition module is used to acquire thin section image data of carbonate rock thin sections of the target well; The module is used to obtain a pore distribution thermogram corresponding to the carbonate rock thin section based on the thin section image data and a pore identification model. The first determining module is used to determine the total effective pore area based on the pore distribution thermal map; The second determining module is used to determine the porosity of the carbonate rock sheet based on the total effective pore area and the total sheet area of the carbonate rock sheet.
9. The apparatus according to claim 8, characterized in that, The first acquisition module is also used for: Acquire initial thin section image data of carbonate rock thin sections from the target well; The initial thin section image data is processed to remove scanning noise in order to obtain thin section image data of carbonate rock thin sections of the target well.
10. The apparatus according to claim 8, characterized in that, The first determining module is further configured to determine the porosity according to the following formula: In the formula, This indicates the porosity of the carbonate rock sheet. This represents the total effective pore area. This represents the total area of the sheet.
11. The apparatus according to claim 8, characterized in that, The device further includes: The second acquisition module is used to acquire core experimental data of the target well, wherein the core experimental data includes experimental porosity; The first correction module is used to correct the porosity of the carbonate rock thin section when the deviation between the porosity of the thin section and the experimental porosity is not within a preset porosity deviation range.
12. The apparatus according to claim 8, characterized in that, The device further includes: The third acquisition module is used to acquire logging data of the target well, wherein the logging data includes logging porosity; The third determining module is used to determine the error rate between the porosity of the carbonate rock thin section and the well logging porosity based on the porosity of the carbonate rock thin section and the well logging porosity. The second correction module is used to correct the porosity of the carbonate rock sheet when the error rate is not within the preset error rate range.
13. A terminal device, characterized in that, include: The memory is configured to store instructions; A processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for determining the porosity of carbonate rock sections according to any one of claims 1 to 7.
14. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the method for determining the porosity of carbonate rock sections according to any one of claims 1 to 7.
15. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method for determining the porosity of carbonate rock thin sections according to any one of claims 1 to 7.