Method, apparatus and system for threshold interference analysis of microscopic multiphase flow images

Abstract

This application relates to the field of oil and gas field development technology, specifically to a method, apparatus, system, and storage medium for threshold interference analysis of microscopic multiphase flow images. Based on a first image of a microscopic visualization model obtained from a water-drive simulation experiment, this patent utilizes the characteristics of color channels to set multiple thresholds. Then, a mask is generated using multiple judgment matrices based on these thresholds to obtain a second image. The second image is then grayscaled and further processed. This effectively avoids inaccurate extraction results, ultimately improving the precision of experimental image processing, reducing experimental errors, and enhancing the accuracy of the results.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, and specifically to a method, apparatus, system and storage medium for threshold interference analysis of microscopic multiphase flow images. Background Technology

[0002] Threshold interference resistance analysis of microscopic multiphase flow images plays a crucial role in oil and gas field development. It can improve the accuracy, reliability and repeatability of image analysis results, thereby providing a solid data foundation for various decision-making processes.

[0003] Existing analysis methods often suffer from problems such as threshold segmentation having certain errors, complex image colors causing incorrect recognition results, and scattered target regions causing inaccurate recognition results. Summary of the Invention

[0004] The purpose of this application is to provide a method for analyzing microscopic multiphase flow images against threshold interference, in order to solve the problems of insufficient image analysis accuracy, difficulty in overcoming interference, and large errors in the prior art.

[0005] To achieve the above objectives, the first aspect of this application provides a method for threshold interference analysis of microscopic multiphase flow images, comprising:

[0006] The first image of the microscopic visualization model in the water drive simulation experiment was acquired. In the process of water drive, simulated formation water stained with blue medium was used as the displacing phase and saturated crude oil was used as the displaced phase.

[0007] N blue thresholds are set based on the blue color channel, where N is a natural number;

[0008] For each blue threshold, the pixels of each first image are judged based on the blue threshold to generate a first logical matrix corresponding to the blue threshold;

[0009] Generate a mask based on the entire first logic matrix;

[0010] The second image corresponding to the mask is converted to grayscale, and the area of ​​gravel transport is determined based on the processed second image.

[0011] In this embodiment of the application, for each blue threshold, judging each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold includes: selecting the area affected by the blue medium in the first image to determine the target area; and for each blue threshold, judging the pixels of the target area based on the blue threshold to generate a first logical matrix corresponding to the blue threshold.

[0012] In this embodiment of the application, for each blue threshold, judging each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold further includes: for each blue threshold, determining pixels that meet preset conditions as blue pixels and pixels that do not meet preset conditions as non-blue pixels, wherein a preset condition is met when the B value is greater than the blue threshold and both the R value and the G value are less than the blue threshold; and for each blue threshold, generating a first logical matrix corresponding to the blue threshold based on the judgment results of all pixels of each first image.

[0013] In this embodiment of the application, the process of grayscale processing of the second image corresponding to the mask and determining the gravel transport area based on the processed second image includes: grayscale processing of the second image, determining a first threshold and a second threshold by statistical analysis of grayscale values; grayscale processing of the second image based on the first threshold and the second threshold and performing logical judgment, determining a second logic matrix based on the judgment result; and determining the gravel transport area through the second logic matrix.

[0014] In this embodiment, grayscale processing of the second image and determination of a first threshold and a second threshold by statistical analysis of grayscale values ​​include: statistical analysis of the grayscale values ​​of blue pixels in the grayscale processed second image; determination of the first threshold and the second threshold based on the grayscale value statistical results, such that the grayscale values ​​of low-grayscale blue pixels in the grayscale processed second image are less than the first threshold, and the grayscale values ​​of high-grayscale blue pixels are greater than the second threshold; grayscale processing of the second image based on the first threshold and the second threshold and logical judgment, and determination of the second logic matrix based on the judgment results include: grayscale processing of the second image, obtaining the regions where high-grayscale blue pixels and low-grayscale blue pixels are located in the grayscale processed second image based on the first threshold and the second threshold, and determining the second logic matrix.

[0015] In this embodiment of the application, the first image of the microscopic visualization model in the water flooding simulation experiment is acquired. The water flooding simulation operation, which uses simulated formation water stained with blue medium as the displacing phase and formation crude oil as the displaced phase, includes: filling the microscopic visualization model with transparent glass beads and interstitial sand; saturating the model with simulated formation water; saturating the model with formation crude oil; and finally performing the water flooding simulation operation using simulated formation water stained with methylene blue. Real-time image acquisition of the microscopic visualization model during the experiment is performed; and the acquired images are preprocessed to determine the first image.

[0016] In this embodiment of the application, preprocessing the acquired image to determine the first image includes: denoising the acquired image, removing impurity pixels, and determining the first image.

[0017] In this embodiment of the application, N ranges from [1, 254].

[0018] A second aspect of this application provides an apparatus for threshold interference-resistant analysis of microscopic multiphase flow images, comprising:

[0019] The memory is configured to store instructions; and

[0020] A processor configured to retrieve instructions from memory and, when executing instructions, to perform a method for threshold-resistant analysis of microscopic multiphase flow images.

[0021] A third aspect of this application provides an apparatus for threshold interference analysis of microscopic multiphase flow images, comprising:

[0022] A device for threshold interference-resistant analysis of microscopic multiphase flow images;

[0023] Image acquisition device.

[0024] A fourth aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to perform any of the following methods for threshold interference analysis of microscopic multiphase flow images.

[0025] Through the above technical solution, this application uses the characteristics of color channels to process the image of the affected area in the water drive simulation experiment using multiple threshold points, and then eliminates various interferences in the original acquired image to filter out the actual affected pixels, thereby determining the sand and gravel transport area. This allows for better analysis of the images obtained from the water drive simulation experiment, reduces the interference of various errors on statistics, and improves the accuracy of the results.

[0026] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0027] 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:

[0028] Figure 1 The schematic diagram illustrates a flowchart of a method for analyzing microscopic multiphase flow images against threshold interference according to an embodiment of this application;

[0029] Figure 2 This illustration schematically shows the effect of extracting a first image with different blue thresholds in a method for analyzing microscopic multiphase flow images against threshold interference according to an embodiment of this application.

[0030] Figure 3This illustration schematically shows a comparison between a first image and a second image extracted using a mask in a method for analyzing microscopic multiphase flow images against threshold interference according to an embodiment of this application.

[0031] Figure 4 The illustration shows a comparison diagram of the second image before and after processing with a second logic matrix in a microscopic multiphase flow image anti-threshold interference analysis method according to an embodiment of this application. Detailed Implementation

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Figure 1 The illustration schematically shows a flowchart of a method for threshold interference-resistant analysis of microscopic multiphase flow images according to an embodiment of this application. Figure 1 As shown in the embodiments of this application, a method for threshold interference analysis of microscopic multiphase flow images is provided. The method may include the following steps:

[0036] Step 110: Acquire the first image of the microscopic visualization model in the water drive simulation experiment, wherein, during the displacement process, simulated formation water stained with blue medium is used as the displacement phase and formation crude oil is used as the displaced phase to carry out the water drive simulation operation.

[0037] In this embodiment, the application first loads a microscopic visualization model based on the physical properties of the target reservoir and saturates it with simulated formation water stained with blue medium, then saturates it with formation crude oil, and then injects the simulated formation water into the microscopic visualization model to perform water drive simulation operation.

[0038] Specifically, in one optional implementation, a microscopic visualization model can be filled with transparent glass beads of a certain mesh size and interstitial sand to simulate the physical properties of the target reservoir. The vacancies between the transparent glass beads simulate the pores in the formation, while the addition of interstitial sand forms a more complex pore network, improving the realism of the model. Next, the model is saturated with simulated formation water stained with a blue medium. For example, methylene blue is used to stain the simulated formation water and completely saturate the entire model, making the entire field of view uniformly blue. Formation crude oil is then injected into the model to simulate the migration of oil and gas to the reservoir and the saturation process, thus bringing the model to its original oil-bearing state before displacement. Valves are installed at both ends of the model to simulate the injection and production ends during actual displacement operations. By controlling the pressure at both ends, fluid can be initiated under pressure differential. During the displacement process, the methylene blue-stained simulated formation water is used as the displacing phase, and the saturated crude oil is used as the displaced phase, performing a waterflood simulation operation. During the displacement process, it can be observed that as simulated formation water continuously enters the model from the injection end, formation crude oil continuously flows out from the production end. Simultaneously, due to the scouring and transporting effects of the fluid, gravel can also be observed moving within the model and flowing out from the production end. During the displacement process, images of the model are acquired at fixed time intervals.

[0039] A microscopic visualization model was built using glass beads and interstitial sand. Water dyed with blue medium was used as the displacing phase and formation crude oil was used as the displaced phase to simulate water flooding. This effectively simulates the changes in the actual formation environment and the displacement process. At the same time, the addition of dyed medium helps to better demonstrate the role of water flooding and formation changes, which is convenient for image acquisition and analysis.

[0040] Step 120: Set N blue thresholds based on the blue color channel, where N is a natural number.

[0041] In this embodiment of the application, since the dye used is blue, in order to accurately obtain the affected area, it is necessary to set a blue threshold based on the blue color channel so as to extract blue pixels.

[0042] Specifically, in one optional implementation, the RGB color channel can be used. Since the range of RGB values ​​is 0-255, 254 blue threshold points (1-254) are selected. That is, the value of N can range from [1, 254]. Setting multiple threshold points based on the blue color channel helps to identify various pixels with different staining conditions, making the statistics more complete and accurate.

[0043] Step 130: For each blue threshold, judge each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold.

[0044] In this embodiment, blue pixels are identified and extracted based on a blue threshold, and the extraction results are then statistically analyzed to generate a first logical matrix. Meanwhile, since the number of blue thresholds set in step 120 may not be 1, each blue threshold needs to be used to judge all pixels in the first image.

[0045] Specifically, for an embodiment that uses RGB color channels and selects 254 blue threshold points, based on the characteristic that the B channel value of each blue pixel in the RGB color space should be greater than the R channel value and the G channel value, all pixels are judged with B values ​​from 1 to 254, thereby generating a total of 254 first logical matrices.

[0046] Please refer to the following: Figure 2 . Figure 2 The illustration schematically demonstrates the effect of extracting blue pixels from a first image using different blue thresholds in a method for analyzing microscopic multiphase flow images according to an embodiment of this application. It can be observed that the number of blue pixels extracted varies with different blue threshold settings; using multiple thresholds for judgment and extraction can improve the extraction effect. Judging pixels in the first image based on different thresholds and generating a first logical matrix for each pixel is beneficial for extracting all blue pixels.

[0047] Step 140: Generate a mask based on the entire first logic matrix.

[0048] In this embodiment of the application, there may be more than one first logical matrix, and the extraction results of different blue threshold points are not completely the same. Therefore, it is necessary to use all the first logical matrices to process the first image and generate a mask to obtain the second image.

[0049] Specifically, in one optional implementation, a logical OR operation needs to be performed on the 254 first logical matrices corresponding to the 254 blue thresholds to generate a mask with the same resolution as the first image. For example, suppose an image resolution is 1000. 1000, then the mask size is 1000. 1000. The mask is a 0 / 1 matrix. If the mask value of a pixel at a given position is 0, the pixel is discarded; otherwise, it is retained.

[0050] Please refer to the following: Figure 3 . Figure 3 The illustration schematically shows a comparison between a first image and a second image extracted using a mask in a method for analyzing microscopic multiphase flow images against threshold interference according to an embodiment of this application. It can be seen that extracting the first image using a mask generated by performing a logical OR operation on all logical matrices can extract as many blue pixels with varying coloring states as possible. Generating a mask based on the entire first logical matrix allows for individual, threshold-based judgment of all pixels in the image, ensuring the completeness of the extraction results.

[0051] Step 150: Perform grayscale processing on the second image corresponding to the mask, and determine the gravel transport area based on the processed second image.

[0052] In this embodiment, a preliminary extraction can be performed based on the mask to obtain the corresponding second image. Then, the second image is grayscaled, and the brightness information of the pixels is used to segment the cleaned area and the oil, water and sand area and obtain the grayscale value features respectively. The second image is then further processed to obtain the accurate sand and gravel transport area.

[0053] Specifically, in one optional implementation, a mask is used to process the first image to obtain a second image. The extracted region in the second image includes channels cleaned by formation water and areas where oil, water, and sand mix, with brightness differences between the two regions. Grayscale processing of the second image reveals the brightness information of the pixels, and then the grayscale values ​​of all pixels are statistically analyzed to obtain a grayscale threshold for region segmentation. A judgment matrix is ​​generated using the grayscale threshold, and logical judgments are performed on the grayscale-processed second image to determine the accurate area of ​​sand and gravel transport.

[0054] Please refer to the following: Figure 4 . Figure 4 This illustration schematically shows a comparison of the second image before and after processing with a second logic matrix in a method for analyzing microscopic multiphase flow images against threshold interference according to an embodiment of this application. It can be seen that the use of the second logic matrix improves the recognition accuracy, enabling effective separation of interfering pixels. By masking the first image and then utilizing grayscale processing and further segmentation statistics, the different regions represented by different blue pixels can be accurately separated, and other interferences can be eliminated, resulting in more accurate extraction of the gravel transport area.

[0055] Simulated formation water stained with blue medium was used to perform water flooding on the model. Pixels were extracted multiple times using different judgment matrices under different thresholds. Grayscale processing and different grayscale thresholds were used to improve the extraction accuracy, which can better obtain the area of ​​gravel migration and improve the effect of quantitative and qualitative analysis of parameters in the crude oil displacement experiment of the microscopic visualization model.

[0056] In one embodiment, for each blue threshold, judging each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold includes: selecting the area affected by the blue medium in the first image to determine the target area; and for each blue threshold, judging the pixels of the target area based on the blue threshold to generate a first logical matrix corresponding to the blue threshold.

[0057] This application focuses on the area in the first image that is stained by the blue medium, i.e., the water-driven area, and therefore selects the stained area for pixel acquisition.

[0058] In this embodiment of the application, for each blue threshold, judging each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold further includes: for each blue threshold, determining pixels that meet preset conditions as blue pixels and pixels that do not meet preset conditions as non-blue pixels, wherein a preset condition is met when the B value is greater than the blue threshold and both the R value and the G value are less than the blue threshold; and for each blue threshold, generating a first logical matrix corresponding to the blue threshold based on the judgment results of all pixels of each first image.

[0059] This application determines the color of a pixel based on its RGB values. According to the RGB color definition, the color is blue when the B value is greater than a certain value and both the R and G values ​​are less than a certain value. This characteristic is the condition for determining the pixel color in this application.

[0060] In this embodiment of the application, the second image corresponding to the mask is converted to grayscale, and the area of ​​gravel transport is determined based on the processed second image, including:

[0061] The second image is converted to grayscale, and the first threshold and the second threshold are determined by statistical analysis of the grayscale values.

[0062] The second image is grayscaled based on the first threshold and the second threshold, and a logical judgment is made. The second logical matrix is ​​determined based on the judgment result.

[0063] The area of ​​gravel transport is determined by the second logical matrix.

[0064] This application processes a first image using a mask to generate a second image. The second image can be subdivided into three regions: a region with high erosion intensity, a region reflecting glass beads, and a region containing a mixture of oil, water, and sand. The area of ​​sand transport that needs to be statistically analyzed can be obtained by subtracting the regions reflecting glass beads and the region containing the mixture of oil, water, and sand from the second image. By statistically analyzing the grayscale values ​​corresponding to the blue pixels in these two types of regions, two thresholds can be determined. Using these two thresholds, the grayscale-processed second image is further processed to determine the second logical matrix, thereby determining the sand transport area.

[0065] In this embodiment of the application, the second image is converted to grayscale, and the first threshold and the second threshold are determined by statistically analyzing the grayscale values, including:

[0066] Statistical analysis of the grayscale values ​​of blue pixels in the second image after grayscale conversion;

[0067] Based on the statistical results of grayscale values, a first threshold and a second threshold are determined, such that the grayscale values ​​of low-grayscale blue pixels in the grayscaled second image are less than the first threshold, and the grayscale values ​​of high-grayscale blue pixels are greater than the second threshold. The second image is then grayscaled based on the first and second thresholds, and logical judgments are performed. Based on the judgment results, a second logical matrix is ​​determined, including:

[0068] The second image is converted to grayscale. Based on the first threshold and the second threshold, the regions where high grayscale blue pixels and low grayscale blue pixels are located in the grayscale second image are obtained, and the second logical matrix is ​​determined.

[0069] Understandably, due to the translucency of glass beads, the blue brightness in the reflective areas is higher, resulting in a larger grayscale value. Conversely, the blue brightness and grayscale value are lower in the oil-water-sand mixture areas due to oil and sand interference. Therefore, a first threshold is determined by statistically analyzing the grayscale values ​​of blue pixels in the darker oil-water-sand mixture areas, and a second threshold is determined by statistically analyzing the grayscale values ​​of blue pixels in the brighter reflective areas of the glass beads. Using the first and second thresholds, a second logical matrix that accurately locates the oil-water-sand mixture areas and the reflective areas of the glass beads can be obtained in the grayscale-processed second image.

[0070] In this embodiment of the application, the first image of the microscopic visualization model in the water flooding simulation experiment is acquired. The water flooding simulation operation, which uses simulated formation water stained with blue medium as the displacing phase and formation crude oil as the displaced phase, includes: filling the microscopic visualization model with transparent glass beads and interstitial sand, saturating the model with simulated formation water, saturating the model with formation crude oil, and finally using simulated formation water stained with methylene blue to perform the water flooding simulation operation.

[0071] Real-time image acquisition is performed on the microscopic visualization model during the experiment; the acquired images are preprocessed to determine the first image.

[0072] In this embodiment of the application, preprocessing the acquired image to determine the first image includes: denoising the acquired image, removing impurity pixels, and determining the first image.

[0073] In this embodiment of the application, N ranges from [1, 254].

[0074] This application provides a device for analyzing the threshold interference resistance of microscopic multiphase flow images, which may include: a memory configured to store instructions; a processor configured to retrieve instructions from the memory and to implement the above-described method for analyzing the threshold interference resistance of microscopic multiphase flow images when executing the instructions.

[0075] This application also provides an apparatus for threshold interference analysis of microscopic multiphase flow images, which may include: a microscopic multiphase flow image threshold interference analysis device; and an image acquisition device.

[0076] This application also provides a machine-readable storage medium storing instructions for causing a machine to perform the above-described method for threshold interference analysis of microscopic multiphase flow images.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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 for analyzing the resistance to threshold interference in microscopic multiphase flow images, characterized in that, The method includes: The first image of the microscopic visualization model in the water drive simulation experiment was acquired. In the process of water drive, simulated formation water stained with blue medium was used as the displacing phase and formation crude oil was used as the displaced phase. N blue thresholds are set based on the blue color channel, where N is a natural number; For each blue threshold, the pixels of each first image are judged based on the blue threshold to generate a first logical matrix corresponding to the blue threshold; Generate a mask based on the entire first logic matrix; The second image corresponding to the mask is converted to grayscale, and the area of ​​gravel transport is determined based on the processed second image.

2. The method according to claim 1, characterized in that, The step of determining each pixel in the first image based on a blue threshold to generate a first logical matrix corresponding to the blue threshold includes: The target area is determined by selecting the region affected by the blue medium in the first image. For each blue threshold, the pixels in the target region are judged based on the blue threshold to generate a first logical matrix corresponding to the blue threshold.

3. The method according to claim 1, characterized in that, The step of determining each pixel of the first image based on the blue threshold to generate a first logical matrix corresponding to the blue threshold further includes: For each blue threshold, pixels that meet the preset conditions are determined as blue pixels, and pixels that do not meet the preset conditions are determined as non-blue pixels. Specifically, when the B value is greater than the blue threshold and both the R value and the G value are less than the blue threshold, it is determined that the preset conditions are met. For each blue threshold, a first logical matrix corresponding to the blue threshold is generated based on the judgment results of all pixels in each first image.

4. The method according to claim 1, characterized in that, The step of performing grayscale processing on the second image corresponding to the mask, and determining the gravel transport area based on the processed second image, includes: The second image is converted to grayscale, and the first threshold and the second threshold are determined by statistical analysis of the grayscale values. The second image is logically judged based on the first threshold and the second threshold, and the second logic matrix is ​​determined based on the judgment result. The gravel transport area is determined by the second logic matrix.

5. The method according to claim 4, characterized in that, The step of performing grayscale processing on the second image and determining the first threshold and the second threshold by statistically analyzing the grayscale values ​​includes: The grayscale values ​​of the blue pixels in the second image after grayscale processing are statistically analyzed. The first threshold and the second threshold are determined based on the grayscale value statistics, so that the grayscale value of low grayscale blue pixels in the grayscale second image is less than the first threshold, and the grayscale value of high grayscale blue pixels is greater than the second threshold. The step of converting the second image to grayscale based on the first threshold and the second threshold, performing logical judgment, and determining the second logical matrix based on the judgment result includes: The second image is converted to grayscale. Based on the first threshold and the second threshold, the regions where high grayscale blue pixels and low grayscale blue pixels are located in the grayscale second image are obtained, and the second logic matrix is ​​determined.

6. The method according to claim 1, characterized in that, The acquisition of the first image of the microscopic visualization model in the water flooding simulation experiment, wherein the water flooding simulation operation, in which simulated formation water stained with blue medium is used as the displacing phase and formation crude oil is used as the displaced phase, includes: The microscopic visualization model was filled with transparent glass beads and interstitial sand, saturated with simulated formation water, saturated with formation crude oil, and finally simulated with water drive using methylene blue-stained simulated formation water. Real-time image acquisition was performed on the microscopic visualization model during the experiment; The acquired image is preprocessed to determine the first image.

7. The method according to claim 1, characterized in that, The range of N is [1, 254].

8. A device for threshold interference-resistant analysis of microscopic multiphase flow images, characterized in that, include: The memory is configured to store instructions; as well as A processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for threshold interference-resistant analysis of microscopic multiphase flow images according to any one of claims 1 to 7.

9. A system for threshold interference analysis of microscopic multiphase flow images, characterized in that, include: An apparatus for threshold interference analysis of microscopic multiphase flow images according to claim 8; An image acquisition device is used to acquire the first image of a microscopic visualization model in a water-drive simulation experiment.

10. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform a method for threshold interference analysis of microscopic multiphase flow images according to any one of claims 1 to 7.

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