Fault zone internal structure area calculation method, device, equipment, medium and product

Abstract

The invention discloses a fault zone internal structure area calculation method, and relates to the technical field of petroleum geology. According to a preset proportional scale, gray processing and calibration are carried out on the casting body sheet image, and an optimized fault zone is determined; particle gap filling is carried out on the optimized fault zone, and the internal structure area of the fault zone is determined; based on a preset threshold value, obtaining all particles corresponding to the internal structure area of the fault zone; and determining the internal structure area of the fault zone based on the area of each particle. According to the method, the internal structure area of the fault zone can be quantitatively and accurately calculated.

Description

Technical Field

[0001] This application relates to the technical field of petroleum geology, and particularly to a method, device, equipment, medium and product for calculating the area of the internal structure of a fault zone. Background Art

[0002] A fault is a deformation product of crustal rock masses under tectonic stress and is the most common tectonic form. Its existence may affect the migration and preservation of underground oil and gas. Its interior consists of a "binary" structure composed of a fault core and a fracture zone. In the past, the characterization of faults has mainly been qualitative analysis, without a quantitative characterization method. This qualitative description is greatly affected by subjective factors, which may affect the judgment of its nature, restricting scholars from further studying the impact of faults on the migration and preservation of oil and gas, and thus affecting the decision-making evaluation of oil and gas exploration and development.

[0003] In the past, it was only possible to qualitatively analyze the internal structure of the fault zone or select particles within the fault zone for semi-quantitative analysis, which was very time-consuming and laborious; through a microscope, it was found that many matrix particles could not be quantitatively analyzed, and the selection of particles for analysis by humans had a certain degree of subjectivity, and the accuracy of particle size statistical software was also limited, resulting in inaccurate calculation of the structural area inside the fault zone. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, equipment, medium and product for calculating the area of the internal structure of a fault zone, which can accurately calculate the structural area inside the fault zone quantitatively.

[0005] To achieve the above purpose, the present application provides the following solutions.

[0006] In a first aspect, the present application provides a method for calculating the area of the internal structure of a fault zone, including: obtaining a thin section image of a casting; performing gray-scale processing and calibration on the thin section image of the casting according to a preset scale to determine an optimized fault zone; filling the particle voids in the optimized fault zone to determine the internal structure area of the fault zone; obtaining all particles corresponding to the internal structure area of the fault zone based on a preset threshold; and determining the internal structure area of the fault zone based on the area of each particle.

[0007] Further, performing gray-scale processing and calibration on the thin section image of the casting according to a preset scale to determine an optimized fault zone specifically includes: dividing the boundary between the host rock and the fault zone in the thin section image of the casting; removing the background of the boundary between the host rock and the fault zone to determine the target fault zone; and performing gray-scale processing and calibration on the target fault zone based on a preset scale to determine the optimized fault zone.

[0008] Further, based on a preset scale, perform grayscale processing and calibration on the target fault zone to determine the optimized fault zone, specifically including: obtaining the 8-bit instruction in Type under the Image instruction in the image processing software; based on the 8-bit instruction, converting the target fault zone into a monochrome image with 256 levels of gray, and determining the target fault zone after grayscale processing; determining the preset scale based on the line tool in the image processing software; and calibrating the target fault zone after grayscale processing based on the preset scale to determine the optimized fault zone.

[0009] Further, perform particle void filling on the optimized fault zone to determine the internal structure area of the fault zone, specifically including: determining the Fill Holes instruction in Binary based on the Process instruction in the image processing software; performing binarization processing on the optimized fault zone based on the Fill Holes instruction to complete the particle void filling of the optimized fault zone; and using the optimized fault zone after particle void filling as the internal structure area of the fault zone.

[0010] Further, based on a preset threshold, obtain all the particles corresponding to the internal structure area of the fault zone, specifically including: obtaining the Threshold instruction in Adjust under the Image instruction in the image processing software; and determining all the particles corresponding to the internal structure area of the fault zone based on the Threshold instruction and the preset threshold.

[0011] Further, before determining the internal structure area of the fault zone based on the area of each particle, it further includes: encoding each particle and determining the area of each particle; and performing weighted summation on the area of each particle based on the area of each particle and the number of encodings to obtain the internal structure area of the fault zone.

[0012] In a second aspect, a computing device for the internal structure area of a fault zone is provided, including: an acquisition module for acquiring a thin section image of a casting; a setting module for performing grayscale processing and calibration on the thin section image of the casting according to a preset scale to determine an optimized fault zone; a filling module for performing particle void filling on the optimized fault zone to determine the internal structure area of the fault zone; a determination module for obtaining all the particles corresponding to the internal structure area of the fault zone based on a preset threshold; and a calculation module for determining the internal structure area of the fault zone based on the area of each particle.

[0013] In a third aspect, a computer device is provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method for calculating the area of the internal structure of the fault zone described in the first aspect.

[0014] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, it implements the method for calculating the area of the internal structure of the fault zone described in the first aspect.

[0015] In a fifth aspect, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, it implements the method for calculating the area of the internal structure of the fault zone described in the first aspect.

[0016] According to the specific embodiments provided in this application, the following technical effects are disclosed in this application as follows.

[0017] In this application, by obtaining the thin section image of the casting, and according to the preset scale, performing gray processing and calibration on the thin section image of the casting to determine the optimized fault zone, so that the image quality of the optimized fault zone is more conducive to accurately identifying and analyzing the fault zone. Then, filling the particle voids in the optimized fault zone, determining the area of the internal structure of the fault zone, and obtaining all the particles corresponding to the area of the internal structure of the fault zone based on a preset threshold. Finally, based on the area of each particle, the area of the internal structure of the fault zone is determined. The accurate acquisition of the area of the entire internal structure of the fault zone is efficiently realized. This application can quantitatively solve the problem of inaccurate calculation of the internal structure area of the fault zone caused by qualitative analysis in the past, avoiding the errors caused by external factors such as only being able to qualitatively analyze the internal structure of the fault zone or selecting particles in the fault zone for semi-quantitative analysis in the past, which is beneficial to further analyzing the characteristics of the internal structure of the fault and has practical significance for guiding oil and gas exploration and development. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a schematic flowchart of a method for calculating the area of the internal structure of a fault zone provided in an embodiment of the present application.

[0020] Figure 2 It is a schematic diagram of a selected fault zone in an embodiment of the present application.

[0021] Figure 3Schematic diagram of removing the parent rock background in the embodiments of the present application.

[0022] Figure 4 Schematic diagram of grayscale processing in the embodiments of the present application.

[0023] Figure 5 Schematic diagram of filling particle voids in the embodiments of the present application.

[0024] Figure 6 Schematic diagram of selecting particles by adjusting the threshold in the embodiments of the present application.

[0025] Figure 7 Schematic diagram of numbering particles and calculating their areas in the embodiments of the present application.

[0026] Figure 8 Structural block diagram of a device for calculating the area of the internal structure of a fault zone provided in the embodiments of the present application. Detailed implementation manners

[0027] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0028] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0029] As Figure 1 shown, the present application provides a method for calculating the area of the internal structure of a fault zone, including step 101-step 105.

[0030] Step 101: Obtain a thin section image of the casting.

[0031] Step 102: According to a preset scale, perform grayscale processing and calibration on the thin section image of the casting to determine the optimized fault zone.

[0032] Step 103: Fill the particle voids in the optimized fault zone to determine the area of the internal structure of the fault zone.

[0033] Step 104: Based on a preset threshold, obtain all the particles corresponding to the area of the internal structure of the fault zone.

[0034] Among them, the general range of the preset threshold is 0 - 255 gray values, which is specifically adjusted according to the mineral composition. The preset threshold actually used in this implementation is 80 - 150 gray values. Specifically, first obtain the initial threshold through the Otsu algorithm, and then, in combination with the research objective (particle / pore identification) and the image gray histogram, fine-tune it up and down by 20 units within the general range; the preset threshold needs to be located at the trough of the gray distribution of mineral particles and voids, and at the same time, verify through standard samples to ensure that the area calculation error ≤ 5%.

[0035] Step 105: Determine the internal structure area of the fault zone based on the area of each particle.

[0036] In some embodiments, step 102 specifically includes steps 201 - 202.

[0037] Step 201: Divide the boundary between the parent rock and the fault zone in the thin section image of the casting; remove the background of the boundary between the parent rock and the fault zone to determine the target fault zone.

[0038] Step 202: Based on the preset scale, perform gray processing and calibration on the target fault zone to determine the optimized fault zone.

[0039] In some embodiments, step 202 specifically includes: Based on the Image instruction in the image processing software, obtain the 8-bit instruction in Type under the Image instruction; based on the 8-bit instruction, convert the target fault zone into a monochromatic image with 256 levels of gray to determine the target fault zone after gray processing; based on the straight line tool in the image processing software, determine the preset scale; based on the preset scale, calibrate the target fault zone after gray processing to determine the optimized fault zone.

[0040] In some embodiments, step 103 specifically includes: Based on the image processing software, according to the Process instruction, determine the Fill Holes instruction in Binary; based on the Fill Holes instruction, perform binary processing on the optimized fault zone to complete the filling of particle voids in the optimized fault zone; use the optimized fault zone with particle voids filled as the internal structure area of the fault zone.

[0041] In some embodiments, step 104 specifically includes: Based on the Image instruction in the image processing software, obtain the Threshold instruction in Adjust under the Image instruction; based on the Threshold instruction and the preset threshold, determine all the particles corresponding to the internal structure area of the fault zone.

[0042] In some embodiments, before step 105, it further includes: encoding each particle and determining the area of each particle; based on the area of each particle and the number of encodings, performing a weighted sum of the areas of each particle to obtain the internal structure area of the fault zone.

[0043] In practical applications, this application is mainly based on the analysis of thin-section images of cast specimens. The specific process steps for analyzing the particle areas corresponding to the thin-section images of cast specimens under a microscope are as follows.

[0044] Step 1, scale setting: Select the thin-section image of the cast specimen for grayscale processing and set the scale to calibrate the proportion, which affects the final result of the internal structure area of the fault zone. The specific operation is to click Open under the File command to select the thin-section photo, select the Line Tool in the toolbar, draw a straight line along the scale on the thin-section image, click Set Scale in Analyze, and in the pop-up dialog box: enter the actual straight-line length of 200 at Known distance, enter the unit of mm at Unit of length, and finally click OK to complete the calibration of the scale setting; click the 8-bit command in Type under the Image command to achieve grayscale processing.

[0045] The specific operation process includes: First, open the thin-section image of the cast specimen, click Open under the File menu, and then select the thin-section photo to be processed to load the thin-section image of the cast specimen that needs to be analyzed. Then draw a scale line, select the Line Tool in the toolbar, and then draw a straight line along the scale with a known length on the image to provide a reference line for subsequent scale setting. Further, set the scale: click the Analyze menu, select Set Scale, and in the pop-up dialog box, enter the actual straight-line length (for example, 200) at Known distance. Enter the unit (for example, mm) at Unit of length. Finally, click OK to complete the calibration of the scale setting. Ensure that the measured values in the thin-section image of the cast specimen correspond to the physical dimensions in the real world, so that all subsequent measurements are based on the correct proportion.

[0046] Converting the thin-section image of the cast specimen into an 8-bit grayscale image includes clicking the Image menu and selecting 8-bit in Type. This reduces color information, simplifies the image processing process, and helps with certain specific types of image analysis (such as threshold segmentation, particle analysis, etc.).

[0047] Step 2, select the fault zone: Precisely divide the boundary between the host rock and the fault zone in the thin-section image of the cast specimen, and only select the boundary of the fault zone. This step also affects the final result, as Figure 2 shown.

[0048] Step 3, remove the parent rock background: according to the selected fault zone boundary, after removing all the parent rocks, change the background color behind the fault zone to highlight the fault zone, which is conducive to better observation of the fault zone processing during steps 5 and 6, such as Figure 3 As shown, the specific operation is to click Clear Outside under the Edit command to remove the parent rock background.

[0049] Among them, when removing the parent rock and background, a very small number of particles may have incomplete gaps, which need to be filled to minimize the error.

[0050] Among them, according to the selected fault zone boundary, after removing all the parent rocks, the background color behind the fault zone is changed to highlight the fault zone, which is conducive to better observing the processing of the fault zone when performing steps 5 and 6.

[0051] Step 4, grayscale processing: grayscale the fault zone as a whole, converting the 256-bit image into an 8-bit image, such as Figure 4 As shown, the specific operation is to click the 8-bit command in Type under the Image command to achieve grayscale processing. When converting an image to 8 bits, it usually means converting it into a monochrome image with 256 levels of gray.

[0052] The main purpose of grayscale processing of fault zones is to optimize image quality, facilitate more accurate identification and analysis of geological features, and provide convenient conditions for subsequent advanced image processing and data analysis. This method has a wide range of application value in geological exploration, earthquake prediction, and environmental monitoring.

[0053] Step 5, filling the gaps between particles includes: when removing the matrix and background in step 3, a small number of particles may have incomplete gaps, which need to be filled to minimize the error, such as Figure 5 As shown, the specific operation is to click the Fill Holes command in Binary under the Process command to fill the particle gaps.

[0054] Step 6, adjust the threshold to select particles: adjust the color threshold to select all particles in the fault zone to facilitate the subsequent calculation of particle area. Incomplete selection will cause some particles to be ignored, which will affect the final calculation of the cumulative sum of particle area, such as Figure 6As shown, the specific operation is to click on the Threshold instruction in Adjust under the Image instruction. In the pop-up threshold adjustment window, the particles in the fault zone (which will turn red) are clearly contrasted with the background. You can check Dark Background, or drag the slider or directly enter a value to adjust the upper and lower thresholds so that the particle areas of all fault zones are completely covered by red, which means all particles are selected. The specific operations include: Click Image -> Adjust -> Threshold to open the threshold adjustment window. Select whether to check Dark Background according to the characteristics of the image. Adjust the upper and lower threshold sliders or directly enter a value to ensure that the particle areas of all fault zones are completely covered by red. Click Apply to apply the threshold. Filling gaps: Fill the pores inside the particles through Process -> Binary -> Fill Holes.

[0055] Among them, adjusting the color threshold to select all the particles in the fault zone affects the final result.

[0056] It is worth noting that the selection of the threshold is very crucial and directly affects the accuracy of subsequent analysis. If the contrast between the particles and the background is not high, some preprocessing (such as filtering, enhancing contrast, etc.) may need to be carried out first. In terms of the background color, checking Dark Background can help better separate the particles from the background, especially when the background is darker. In the real-time preview, use the real-time preview function in the threshold adjustment window to gradually adjust the threshold until satisfied.

[0057] Step 7, number the particles and calculate the area: Finally, number all the particles selected in Step 6, and calculate the area of each numbered particle one by one and accumulate the sum. As Figure 6 shown, the area of the internal structure of the entire fault zone can be obtained.

[0058] Specifically, S = ∑xi, where S is the accumulated result, ∑ is the summation symbol, i is the index variable, whose value ranges from 1 to n, and the value of n is determined by the final number of particles. xi is the area corresponding to the i-th particle. As Figure 7 shown.

[0059] The beneficial effects of this application are as follows: In the past, only qualitative analysis of the internal structure of the fault zone could be carried out, or semi-quantitative analysis was performed by selecting particles within the fault zone, which was very time-consuming and laborious. Through the microscope, it can be found that many matrix particles cannot be quantitatively analyzed, and the selection of particles for analysis by humans has certain subjectivity, and the accuracy of particle size statistical software also has limitations. However, this application can reduce the errors caused by these external factors and can save a lot of time. In particular, this quantitative method solves the bottleneck problem of only qualitative analysis in the past, which is conducive to further analyzing the characteristics of the internal structure of the fault and has practical significance for guiding oil and gas exploration and development.

[0060] Reference Figure 8 , this application provides a computing device for the area of the internal structure of a fault zone, including: an acquisition module 1 for acquiring a thin section image of a casting; a setting module 2 for performing grayscale processing and calibration on the thin section image of the casting according to a preset scale to determine an optimized fault zone; a filling module 3 for filling the particle voids in the optimized fault zone to determine the area of the internal structure of the fault zone; a determination module 4 for obtaining all the particles corresponding to the area of the internal structure of the fault zone based on a preset threshold; and a calculation module 5 for determining the area of the internal structure of the fault zone based on the area of each particle.

[0061] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, where a computer program is stored in the memory, and when the processor executes the computer program, the above method is implemented.

[0062] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0063] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0064] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of the relevant data need to comply with the relevant regulations.

[0065] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRdM), magnetoresistive random access memory (MRdM), ferroelectric random access memory (FRdM), phase change memory (Phdse Chdnge Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RdM) or external cache memory, etc. By way of illustration and not limitation, RdM can be in various forms, such as static random access memory (Stdtic Random Access Memory, SRdM) or dynamic random access memory (DyndmicRandomAccess Memory, DRdM), etc.

[0066] The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0067] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0068] Specific examples are used in this article to elaborate on the principles and implementation manners of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, based on the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A method for calculating the area of the internal structure of a fault zone, characterized in that Including: Obtain a thin section image of the casting body; According to a preset scale, perform grayscale processing and calibration on the thin section image of the casting body to determine the optimized fault zone; The preset scale is based on clicking Open to select the thin section photo under the File instruction, selecting the straight line tool in the toolbar, drawing a straight line along the scale on the thin section image, clicking Set scale in Analyze, and in the pop-up dialog box: enter the actual straight line length of 200 at Known distance, enter the unit of mm at Unit of length, and finally click OK to complete the calibration scale setting; Perform particle void filling on the optimized fault zone to determine the internal structure area of the fault zone; Based on a preset threshold, obtain all particles corresponding to the internal structure area of the fault zone; Based on the area of each particle, determine the internal structure area of the fault zone, specifically including: encoding each particle and determining the area of each particle; Based on the area of each particle and the number of encoded particles, perform weighted summation on the area of each particle to obtain the internal structure area of the fault zone.

2. The method for calculating the area of the internal structure of the fault zone according to claim 1, characterized in that, According to a preset scale, perform grayscale processing and calibration on the thin section image of the casting body to determine the optimized fault zone, specifically including: Divide the boundary between the host rock and the fault zone in the thin section image of the casting body; Remove the background of the boundary between the host rock and the fault zone to determine the target fault zone; Based on a preset scale, perform grayscale processing and calibration on the target fault zone to determine the optimized fault zone.

3. The method for calculating the area of the internal structure of the fault zone according to claim 2, wherein Based on a preset scale, perform grayscale processing and calibration on the target fault zone to determine the optimized fault zone, specifically including: Based on the Image instruction in the image processing software, obtain the 8-bit instruction in Type under the Image instruction; Based on the 8-bit instruction, convert the target fault zone into a monochromatic image with 256 levels of gray to determine the target fault zone after grayscale processing; Based on the straight line tool in the image processing software, determine the preset scale; Based on the preset scale, calibrate the target fault zone after grayscale processing to determine the optimized fault zone.

4. The method for calculating the area of the internal structure of the fault zone according to claim 1, characterized in that Perform particle void filling on the optimized fault zone to determine the internal structure area of the fault zone, specifically including: Based on the image processing software, according to the Process instruction, determine the Fill Holes instruction in Binary; Based on the Fill Holes instruction, perform binary processing on the optimized fault zone to complete the particle void filling of the optimized fault zone; Take the optimized fault zone after particle void filling as the internal structure area of the fault zone.

5. The method for calculating the area of the internal structure of the fault zone according to claim 1, characterized in that Based on a preset threshold, obtain all particles corresponding to the internal structure area of the fault zone, specifically including: Based on the Image instruction in the image processing software, obtain the Threshold instruction in Adjust under the Image instruction; Based on the Threshold instruction and the preset threshold, determine all particles corresponding to the internal structure area of the fault zone.

6. A calculation device for the area of the internal structure of a fault zone, characterized in that, Including: An acquisition module for obtaining a thin section image of the casting body; A setting module, configured to perform grayscale processing and calibration on the cast thin-section image according to a preset scale, and determine an optimized fault zone; the preset scale is based on the following steps: click Open under the File instruction to select a thin-section photo, select the line tool in the toolbar, draw a straight line along the scale on the thin-section image, click Set scale in Analyze, and in the pop-up dialog box: enter the actual straight-line length of 200 at Known distance, enter the unit of mm at Unit of length, and finally click OK to complete the calibration scale setting; A filling module, configured to fill the particle voids in the optimized fault zone and determine the internal structure area of the fault zone; A determination module, configured to obtain all the particles corresponding to the internal structure area of the fault zone based on a preset threshold; A calculation module, configured to determine the internal structure area of the fault zone based on the area of each particle, specifically including: encoding each particle and determining the area of each particle; Based on the area of each particle and the number of encodings, perform weighted summation on the area of each particle to obtain the internal structure area of the fault zone.

7. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method for calculating the internal structure area of the fault zone according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for calculating the internal structure area of the fault zone according to any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for calculating the internal structure area of the fault zone according to any one of claims 1-5.

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