Full-diameter coal rock component quantitative identification method and device based on CT (Computed Tomography) scanning

Abstract

The invention relates to a full-diameter coal rock component quantitative identification method and device based on CT scanning, and the method comprises the steps: carrying out the CT image three-dimensional reconstruction of CT scanning images of different end faces of a dry coal sample and a coal sample saturated with a contrast agent, and obtaining a dry coal sample data body and a saturated coal sample data body; comparing the dry coal sample data body with the saturated coal sample data body, and segmenting and removing hole fractures and minerals to obtain a coal CT (Computed Tomography) data body; performing organic matter component comparison on the coal CT data body, and determining gray value ranges of different macroscopic coal and rock components in the organic matter components; and counting corresponding pixel points based on the gray value range of each macroscopic coal rock component, depicting the distribution of the corresponding pixel points in a three-dimensional space, and calculating the corresponding content. According to the method, the content of the macroscopic coal rock components in the coal sample can be quantitatively represented, the spatial distribution rule of different macroscopic coal rock components can be shown, and on the basis, the relation between the coal reservoir pore fracture development and the macroscopic coal rock components can be further analyzed by combining the segmented pore fractures in the coal.

Description

Technical Field

[0001] The invention relates to a method and a device for quantitatively identifying full-diameter coal and rock components based on CT scanning. Background Art

[0002] The development of cracks in coal is significantly controlled by different macroscopic coal rock components and is one of the important indicators for evaluating the sweet spots of coalbed methane development. In the prior art, the distribution of different macroscopic coal rock components in coal samples is usually distinguished directly by the naked eye. However, only the cross section of a sample can be observed, and the identification result is inaccurate. At the same time, this method has a certain degree of subjectivity. In addition, in the prior art, optical microscopes or scanning electron microscopes are often used to observe the development of pores and cracks in different macroscopic coal rock components, and it is difficult to observe the three-dimensional distribution characteristics of different pores and cracks in macroscopic coal rock components. Therefore, it is necessary to use advanced instruments to quantitatively characterize the macroscopic coal rock components in coal and to finely characterize their spatial distribution laws. Summary of the invention

[0003] In order to quantitatively characterize the content of different macroscopic coal and rock components in coal samples and show the spatial distribution law of different macroscopic coal and rock components, the present invention proposes a method and device for quantitatively identifying coal and rock components based on CT scanning of the full diameter. The technical solution proposed by the present invention is as follows:

[0004] In a first aspect, the present invention provides a method for quantitatively identifying coal and rock components based on full-diameter CT scanning, comprising:

[0005] The CT scan images of different end faces of the dry coal sample and the coal sample saturated with contrast agent are respectively reconstructed in three dimensions to obtain a dry coal sample data volume and a saturated coal sample data volume;

[0006] By comparing the dry coal sample data volume with the saturated coal sample data volume, the pores, cracks and minerals are segmented and removed to obtain the coal CT data volume;

[0007] Comparing the organic matter components of the coal CT data volume to determine the gray value range of different macroscopic coal rock components in the organic matter components;

[0008] Based on the gray value range of each macroscopic coal rock component, the corresponding pixel points are counted to characterize their distribution in three-dimensional space and calculate the corresponding content.

[0009] In one or some embodiments, the step of comparing the dry coal sample data volume with the saturated coal sample data volume, segmenting and removing pores, cracks and minerals to obtain the coal CT data volume includes:

[0010] After aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image;

[0011] Threshold segmentation and top hat segmentation are performed on the difference image to obtain pores, cracks and minerals in the difference image, and the minerals and pores, cracks are removed from the difference image to obtain a coal CT data volume.

[0012] In one or some embodiments, before subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain the difference image, the method further includes:

[0013] After aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, the dry coal sample data volume is subjected to filtering and sharpening processing to obtain a processed dry coal sample data volume.

[0014] In one or some embodiments, the step of subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image includes:

[0015] The processed dry coal sample data volume is subtracted from the saturated coal sample data volume to obtain the difference image.

[0016] In one or some embodiments, the organic matter component includes a bright component and a dark component; and the step of comparing the organic matter components of the coal CT data volume to determine the gray value range of different macroscopic coal rock components in the organic matter component includes:

[0017] The bright component and the dark component of the organic component in the coal CT data volume are compared, and the gray value range of different macroscopic coal rock components is determined according to the density difference between the bright component and the dark component.

[0018] In one or some embodiments, the gray value range of different macroscopic coal rock components is determined according to the density difference between the bright component and the dark component, including:

[0019] According to the density difference between the bright component and the dark component, the watershed algorithm is used to identify the gray boundary range between different macro coal and rock components;

[0020] The end faces of the coal samples are cut and polished in sequence, and after each cutting and polishing, the end faces are photographed with a high-definition camera. The photos of different end faces are calibrated and segmented using a preset image processing method, and the area proportions of macroscopic coal and rock components on different end faces are counted, and the average area ratio is calculated to obtain the local macroscopic coal and rock component proportions;

[0021] The grayscale boundary range of each macroscopic coal rock component is calibrated based on the proportion of the local macroscopic coal rock component to obtain the grayscale value range of different macroscopic coal rock components.

[0022] In one or some embodiments, the grayscale boundary range of the local macroscopic coal rock component based on the proportion of each macroscopic coal rock component is calibrated to obtain the grayscale value range of different macroscopic coal rock components, including:

[0023] Adjust the grayscale value threshold of the grayscale boundary range of each macroscopic coal rock component, and calculate the overall macroscopic coal rock component proportion of the adjusted different macroscopic coal rock components until the overall macroscopic coal rock component proportion is equal to the local macroscopic coal rock component proportion.

[0024] In one or some embodiments, the CT scan images of different end surfaces of the dry coal sample and the coal sample saturated with contrast agent are obtained by the following method;

[0025] The coal sample to be scanned is dried in a vacuum drying oven until the weight of the coal sample remains unchanged to obtain a dry coal sample, and different end faces of the dry coal sample are CT scanned to obtain a CT scan image of the dry coal sample;

[0026] saturating the dry coal sample after CT scanning with a contrast agent in a pressure saturation device to obtain a coal sample saturated with a contrast agent;

[0027] The different end faces of the coal sample with contrast agent are subjected to CT scanning to obtain a CT scanning image of the coal sample saturated with contrast agent; wherein the scanning parameters of the coal sample with contrast agent are consistent with the scanning parameters of the dry coal sample.

[0028] In one or some embodiments, when performing CT scanning on a dry coal sample, the X-ray tube voltage is set to 110-130 kV, the current is 80-120 μA, and the number of CT images is 1400-1600.

[0029] In one or some embodiments, the saturated contrast agent is a mixed solution of potassium iodide and sodium chloride, wherein the concentration of potassium iodide is 1.4-1.6 mol / L, and the concentration of sodium chloride is 0.9-1.1 mol / L.

[0030] In a second aspect, the present invention provides a device for quantitatively identifying coal and rock components based on full-diameter CT scanning, comprising:

[0031] A three-dimensional reconstruction module is used to perform three-dimensional reconstruction of CT images of CT scan images of different end surfaces of a dry coal sample and a coal sample saturated with contrast agent, respectively, to obtain a dry coal sample data volume and a saturated coal sample data volume;

[0032] A comparison module is used to compare the dry coal sample data volume and the saturated coal sample data volume, segment and remove pores, cracks and minerals to obtain a coal CT data volume;

[0033] A calculation module, used for comparing the organic components of the coal CT data volume, and determining the gray value range of different macroscopic coal and rock components in the organic components;

[0034] The characterization module is used to count the corresponding pixel points based on the gray value range of each macro coal rock component, characterize its distribution in three-dimensional space and calculate the corresponding content.

[0035] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for quantitatively identifying full-diameter coal and rock components based on CT scanning as described in the first aspect.

[0036] In a fourth aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0037] Memory, used to store computer programs;

[0038] The processor is used to implement the method for quantitatively identifying the full-diameter coal and rock components based on CT scanning as described in the first aspect when executing the program stored in the memory.

[0039] Based on the above technical solution, the beneficial effects of the present invention compared with the prior art are as follows:

[0040] The method for quantitatively identifying coal rock components based on full-diameter CT scanning provided by the present invention performs CT scanning on different end faces of dry coal samples and coal samples saturated with contrast agents, and performs three-dimensional reconstruction of CT images based on CT scanning pictures of different end faces to obtain dry coal sample data bodies and saturated coal sample data bodies; by comparing the dry coal sample data body and the saturated coal sample data body, pores, cracks and minerals are segmented and removed to obtain the coal CT data body after removing pores, cracks and minerals; the organic components of the coal CT data body are compared, and the gray value range of different macroscopic coal rock components in the organic component is determined; based on the gray value range of each macroscopic coal rock component, the corresponding pixel points are counted, and its distribution in three-dimensional space is depicted and the corresponding content is calculated. Through CT identification, the content of macroscopic coal rock components in the coal sample can be quantitatively characterized, so it is more accurate and objective. At the same time, the spatial distribution law of different macroscopic coal rock components can be displayed, and based on this, the relationship between the development of coal reservoir pores and cracks and macroscopic coal rock components can be further analyzed in combination with the aforementioned segmented coal pores and cracks.

[0041] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0042] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a schematic diagram of the process of a method for quantitatively identifying full-diameter coal and rock components based on CT scanning provided by an embodiment of the present invention;

[0045] Figure 2 is a flow chart of fracture and mineral segmentation; wherein a is the sample image of the saturated contrast agent solution aligned with the conventional dry sample, b is the image of the dry sample after AD filtering and sharpening, c is the difference image obtained by subtracting the dry sample from the wet sample, d is the segmentation effect diagram of the conventional dry sample, and e is the segmentation effect diagram of the difference image;

[0046] Figure 3 It is a flow chart of macroscopic coal-rock component segmentation; wherein a is the original CT image of conventional dry sample, b is the image of conventional dry sample after AD filtering, c is the image of conventional dry sample after filtering and sharpening, and d is the coal-rock component segmentation effect diagram;

[0047] Figure 4 It is the gray value distribution map of different macro coal and rock components in CT images;

[0048] Figure 5 It is a schematic diagram of the structure of a device for quantitatively identifying full-diameter coal and rock components based on CT scanning provided by an embodiment of the present invention;

[0049] Figure 6 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0051] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0052] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0053] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] The inventor discovered during work that in the prior art, the distribution of different macroscopic coal rock components in a coal sample is usually distinguished directly by the naked eye, but this method can only observe the cross section of a sample. At the same time, this method has a certain degree of subjectivity. In addition, in the prior art, an optical microscope or a scanning electron microscope is often used to observe the development of pores and fissures in different macroscopic coal rock components. It is difficult to observe the three-dimensional distribution characteristics of different pores and fissures in the macroscopic coal rock components, which cannot meet the inventor's expectations. Therefore, it is necessary to quantitatively characterize the macroscopic coal rock components in coal with the help of advanced instruments, and to finely characterize their spatial distribution laws. After further research and development, the inventor made the present invention.

[0055] Embodiment 1

[0056] Before quantitatively characterizing the macroscopic coal rock components of the coal sample, the coal sample to be scanned needs to be processed to obtain a dry coal sample and a coal sample saturated with contrast agent, and the two coal samples are scanned to obtain corresponding CT scan images. In one embodiment, the CT scan images of different end surfaces of the dry coal sample and the coal sample saturated with contrast agent are obtained in the following manner;

[0057] (1) drying the coal sample to be scanned in a vacuum drying oven until the weight of the coal sample remains unchanged to obtain a dry coal sample, and performing CT scanning on different end surfaces of the dry coal sample to obtain a CT scan image of the dry coal sample;

[0058] The present invention places a coal sample with a diameter of 2.5 cm and a height of 5 cm into a vacuum drying oven, and evacuates the sample to a vacuum degree of 1Mpa, then sets the temperature to 105 degrees Celsius, and dries the sample for at least 24 hours until the weight of the coal sample does not change, thereby obtaining a dry coal sample. When performing a CT scan on the dry coal sample, the X-ray tube voltage is set to 110-130kV, the current is 80-120μA, and the number of CT photos is 1400-1600. The present invention first evacuates the X-ray tube and heats the tube, and then places the coal sample in the sample holder to start the rays; sets the X-ray tube voltage to 120KV, the current to 100μA, and the exposure value to 1, and performs a CT scan on the dry coal sample, with the number of CT photos being 1500, as shown in FIG. Figure 2 Figure d shows an example of a CT image of a dry coal sample obtained by scanning.

[0059] (2) saturating the dry coal sample after CT scanning with a contrast agent in a pressure saturation device to obtain a coal sample saturated with a contrast agent;

[0060] The saturated contrast agent is a mixed solution of potassium iodide and sodium chloride, wherein the concentration of potassium iodide is 1.4-1.6 mol / L, and the concentration of sodium chloride is 0.9-1.1 mol / L. In the embodiment of the present invention, the X-ray attenuation solution is a mixed solution of potassium iodide and sodium chloride, wherein the concentration of potassium iodide is 1.5 mol / L, and the concentration of sodium chloride is 1 mol / L; the dry coal sample is completely immersed in the X-ray attenuation solution, and placed in a vacuum box, and the vacuum is drawn until no bubbles are generated, the air in the coal sample is extracted, and the solution is completely saturated into the pores and cracks in the coal based on the imbibition mechanism, and the coal sample is taken out to obtain a coal sample saturated with the contrast agent.

[0061] (3) Performing CT scanning on different end faces of the coal sample saturated with the contrast agent to obtain a CT scan image of the coal sample saturated with the contrast agent; wherein the scanning parameters of the coal sample saturated with the contrast agent are consistent with the scanning parameters of the dry coal sample.

[0062] The coal sample saturated with contrast agent is subjected to CT scanning under the same scanning conditions as (1), such as Figure 3 Figure a is an example of a CT image of a coal sample saturated with contrast agent obtained by scanning.

[0063] The embodiment of the present invention provides a method for quantitatively identifying coal and rock components based on CT scanning of the entire diameter. Figure 1 As shown, including:

[0064] S101, performing CT image three-dimensional reconstruction on CT scan images of different end surfaces of the dry coal sample and the coal sample saturated with contrast agent, respectively, to obtain a dry coal sample data volume and a saturated coal sample data volume;

[0065] In the present invention, the whole coal sample, i.e., the full-diameter coal sample, is scanned. The full-diameter coal sample refers to the core drilled by a full-diameter core drill bit. The complete structure of the rock is retained during the drilling process, i.e., the diameter of the rock sample is the same as the diameter of the borehole, and has a high accuracy in obtaining the core. The present invention uses the core taken out from the coal seam, without cutting and splitting, and the whole section is used for laboratory analysis and determination of relevant parameters in the form of a columnar core, which can improve the accuracy of the quantitative characterization of macroscopic coal rock components. All the obtained CT scan photos of the dry coal sample are imported into the Vgstudio software for three-dimensional reconstruction of the coal rock to obtain a dry coal sample data body; all the obtained CT scan photos of the coal sample saturated with contrast agent are imported into the Vgstudio software for three-dimensional reconstruction of the coal rock to obtain a saturated coal sample data body.

[0066] S102, by comparing the dry coal sample data volume and the saturated coal sample data volume, segmenting and removing pores, cracks and minerals to obtain a coal CT data volume;

[0067] Through the CT image data volume alignment technology, the dry coal sample data volume and the saturated coal sample data volume are aligned; since the pores and cracks of the saturated contrast agent coal sample are filled with contrast agent, they appear whiter on the CT image than the dry coal sample, while there is no difference in other aspects. Therefore, the pores and cracks developed in the coal sample can be obtained by subtracting the two data volumes, and then the minerals are segmented and removed. The pores and cracks and minerals of the coal sample are segmented and removed to obtain the coal CT data volume containing only organic components.

[0068] S103, performing organic component comparison on the coal CT data volume to determine the gray value range of different macroscopic coal rock components in the organic component;

[0069] The organic matter components in coal are different macroscopic coal rock components. There are differences in the grayscale values ​​of different macroscopic coal rock components. By comparing the organic matter components of the coal CT data body, the grayscale value range of different macroscopic coal rock components in the organic matter components can be determined.

[0070] S104. Count the corresponding pixel points based on the gray value range of each macroscopic coal rock component, characterize its distribution in three-dimensional space and calculate the corresponding content.

[0071] After defining the grayscale value ranges of different macroscopic coal rock components, for each macroscopic coal rock component, the number of pixels in the grayscale value range is counted according to its grayscale value range, so as to determine the area proportion of the macroscopic coal rock component, that is, the content of the macroscopic coal rock component.

[0072] The present invention relates to the field of coalbed methane research, and specifically to a method for quantitatively identifying coal rock components based on full-diameter CT scanning. The present invention provides a method for measuring macroscopic coal rock components in coal, using CT scanning of a full-diameter coal sample, and determining the grayscale value range of different macroscopic coal rock components of the coal sample through the dry coal sample data body and the saturated coal sample data body of the coal sample, and dividing the macroscopic coal rock components in the coal into bright components (mirror coal and bright coal) and dark components (dark coal and silky carbon). Based on the grayscale value range of each macroscopic coal rock component, the corresponding pixel points are statistically analyzed, and their distribution in three-dimensional space is depicted and the corresponding content is calculated, so that the macroscopic coal rock components in the coal are quantitatively characterized, which is more accurate and objective, and the spatial distribution law of the macroscopic coal rock components is finely depicted, which can show the spatial distribution law of different macroscopic coal rock components, and based on this, the relationship between the development of coal reservoir pores and fissures and the macroscopic coal rock components can be further analyzed in combination with the aforementioned segmented coal pores and fissures.

[0073] In one embodiment, the step S102 described above of comparing the dry coal sample data volume and the saturated coal sample data volume, segmenting and removing pores, cracks and minerals to obtain the coal CT data volume includes:

[0074] S1021, after aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, subtract the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image;

[0075] Before obtaining the difference image by subtracting the dry coal sample data volume from the saturated coal sample data volume, the method further includes:

[0076] After aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, the dry coal sample data volume is filtered and sharpened to obtain a processed dry coal sample data volume. The dry coal sample data volume is filtered and sharpened to improve its image comparison.

[0077] The step of subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image includes:

[0078] The processed dry coal sample data volume is subtracted from the saturated coal sample data volume to obtain the difference image.

[0079] Align the same sample parts in the dry coal sample data volume and the saturated coal sample data volume, and first perform filtering and sharpening to improve the image contrast, such as Figure 2 In the figure, a is the image of the saturated contrast agent solution sample aligned with the conventional dry sample, and b is the CT image of the dry coal sample after filtering and sharpening. Then, the saturated coal sample data volume is subtracted from the dry coal sample data volume to obtain the following: Figure 2 The CT difference image described in c specifically includes the following steps:

[0080] (1) Use Register images in Avizo software to connect the two data volumes of dry coal sample and coal sample saturated with contrast agent, check the Rigid, Aniso-Scale and Shear options in the Transform column, click Align centers and Align principal axes in turn to pre-align the two data volumes, and then click Apply to complete the alignment of the two data volumes;

[0081] (2) The dry coal sample data volume is filtered based on the Anisotropic Diffusion control, and NbIterations is set to 5 to remove the noise caused by the scanning process. Then the dry coal sample data volume is sharpened using the Unsharp Masking control, and the Edge Size is set to 5 to improve its image contrast ( Figure 3 ac); refer to Figure 3 As shown, a is the original CT image of the conventional dry sample, b is the image of the conventional dry sample after AD filtering, c is the image of the conventional dry sample after filtering and sharpening, and d is the coal rock component segmentation effect diagram.

[0082] (3) Use the Arimetic algorithm to obtain a difference image. First, multiply the grayscale of one of the data by 1.73 to make the grayscale values ​​of the two volume data roughly in the same range. Then subtract the volume data of the saturated solution sample from the volume data of the dry sample to obtain a difference image. Figure 2 As shown in c, the gray in the figure represents organic matter in the coal, the black represents minerals, and the white represents pores and cracks in the coal.

[0083] S1022, performing threshold segmentation and top hat segmentation on the difference image to obtain pores, cracks and minerals in the difference image, and removing the minerals and pores, cracks from the difference image to obtain a coal CT data volume.

[0084] Based on the difference image, the Interactive Thresholding algorithm and the Interactive Top-Hat algorithm are used to perform threshold segmentation and top-hat segmentation on the difference image to obtain the pores and cracks and minerals in the coal, and the minerals and pores and cracks are removed from the data volume. The grayscale values ​​of different components in the CT photo are related to their density. The air in the pores and cracks has a lower density than the coal matrix, and the color displayed in the photo is the darkest. The mineral density is high, and the color displayed in the photo is the whitest. Therefore, the present invention preliminarily segments the pores and cracks and minerals through threshold segmentation, but the segmentation has the problem of under-segmentation of the boundaries of pores and cracks and minerals. Furthermore, the present invention adopts the top-hat segmentation method to calculate the darkest or lightest area within the range of 16 pixel blocks. The darkest area is the pores and cracks, and the lightest area is the mineral. The pores and cracks and minerals preliminarily segmented above are further characterized, and based on this, the boundary areas of pores and cracks, minerals and coal matrix that are difficult to segment by threshold segmentation can be segmented. Refer to Figure 2 As shown, d is the segmentation effect diagram of the conventional dried sample, and e is the segmentation effect diagram of the difference image. The segmentation effect of pores, cracks and minerals in the difference image is stronger than that of the conventional dried sample.

[0085] Since minerals are obviously different from other components in the CT scan image, they can be removed in the difference image, but they can also be directly removed in the CT scan image of the dry coal sample. However, the fissures are not obviously different from other components in the CT scan image, so it is necessary to use contrast agent to fill into the fissures and form a coal sample saturated with contrast agent, and then compare the CT scan image of the coal sample saturated with contrast agent with the CT scan image of the dry coal sample to form a difference image. The fissures can only be segmented in the difference image. In one embodiment, the above step S102, by comparing the dry coal sample data volume and the saturated coal sample data volume, segmenting and removing pores, fissures and minerals to obtain the coal CT data volume, includes:

[0086] S1021', respectively performing threshold segmentation and top hat segmentation on the dry coal sample data volume and the saturated coal sample data volume to obtain minerals in the dry coal sample data volume and the saturated coal sample data volume, and removing the minerals from the dry coal sample data volume and the saturated coal sample data volume to obtain a dry coal sample data volume after removing the minerals and a saturated coal sample data volume after removing the minerals;

[0087] S1022', after aligning the same sample part of the dry coal sample data volume after mineral removal and the saturated coal sample data volume after mineral removal, subtract the dry coal sample data volume after mineral removal from the saturated coal sample data volume after mineral removal to obtain a difference image;

[0088] S1023', performing threshold segmentation and top hat segmentation on the difference image to obtain pores and cracks in the difference image, and removing the pores and cracks from the difference image to obtain a coal CT data volume.

[0089] The implementation principle of removing minerals and pores and cracks in this method is similar to that of removing minerals and pores and cracks from the difference image, and will not be repeated here.

[0090] In one embodiment, the organic matter component includes a light component and a dark component; the organic matter component comparison of the coal CT data volume described in step S103 to determine the gray value range of different macroscopic coal rock components in the organic matter component includes:

[0091] S1031. Compare the bright components and dark components of the organic components in the coal CT data volume, and determine the gray value range of different macroscopic coal rock components according to the density difference between the bright components and the dark components.

[0092] In one embodiment, the grayscale value range of different macroscopic coal rock components is determined according to the density difference between the bright component and the dark component in S1031, including:

[0093] S201, using a watershed algorithm to identify the grayscale boundary range between different macroscopic coal and rock components according to the density difference between the bright component and the dark component;

[0094] The organic matter components in coal are different macroscopic coal rock components. The organic matter components in coal include light components (mirror coal and bright coal) and different dark components (dark coal and silky charcoal). There are differences in the grayscale values ​​of different components, which is reflected in the different shades of color in the photo. The present invention uses a watershed algorithm to calculate the difference in grayscale values ​​of adjacent pixel blocks. When the difference is large, it is the boundary of different macroscopic coal rock components. The present invention uses a watershed algorithm to identify the grayscale boundary range between mirror coal + bright coal and dark coal + silky charcoal, that is, the grayscale boundary range between different macroscopic coal rock components. Refer to Figure 3 and Figure 4 As shown, Figure 4 The grayscale value distribution of different macroscopic coal rock components in the CT image of the coal sample numbered Hr-1 shows that there are differences in the grayscale values ​​of the bright components (mirror coal and bright coal) and the dark components.

[0095] S202, cutting and polishing the end faces of the coal sample in sequence, taking photos of the end faces with a high-definition camera after each cutting and polishing, calibrating and segmenting the photos of different end faces with a preset image processing method, and statistically analyzing the area proportions of macroscopic coal and rock components on different end faces, and calculating the average area ratio to obtain the local macroscopic coal and rock component proportions;

[0096] For each end-face photo, a preset image method is used to identify different macroscopic coal-rock components in the photo, and different macroscopic coal-rock components are calibrated and segmented and their area ratios are calculated. For each macroscopic coal-rock component, the average value of the area ratio of the macroscopic coal-rock component in all end-face photos is calculated to obtain the local macroscopic coal-rock component ratio of the macroscopic coal-rock component. In the present invention, Image J software is used to identify different macroscopic coal-rock components in the photo and calculate their area ratios. After different macroscopic coal-rock components are segmented by the image J software, the area ratio can be calculated again with the help of the built-in function of the image J software. The present invention determines the grayscale value thresholds of the bright and dark components in the coal CT data volume by determining the area ratios of the macroscopic coal-rock components of different end faces in the coal sample through photographic technology.

[0097] S203. Calibrate the grayscale boundary range of each macroscopic coal rock component based on the proportion of the local macroscopic coal rock component to obtain the grayscale value range of different macroscopic coal rock components.

[0098] The area proportion calculated by S202 can be considered as the proportion of different macroscopic coal-rock components in the coal sample, so as to constrain the exact grayscale boundary between mirror coal + bright coal and dark coal + silky carbon in the CT image, so that the proportion of the macroscopic coal-rock components in the CT image after segmentation is equal to the value of the macroscopic coal-rock components calculated by Image J.

[0099] Since the density of bright components (mirror coal and bright coal) is lower than that of dark components (dark coal and silky carbon), the former is darker in CT images; the present invention uses a high-definition camera to take pictures at different end faces of the coal sample, and then uses imageJ to distinguish different components on the photos and calculate the area proportion of different components, so as to represent the local macroscopic coal rock component proportion; based on the CT image difference of the aforementioned macroscopic coal rock components, the grayscale value threshold range between different components is preliminarily determined; the local macroscopic coal rock component proportion and the overall macroscopic coal rock component proportion of the coal sample measured by CT should be consistent, so as to determine the threshold of the grayscale value between different macroscopic coal rock components. The present invention cuts and polishes the end face of the coal sample in sequence, takes pictures of the end face with a high-definition camera after each cutting and polishing, and uses image J software to segment different macroscopic coal rock components to obtain experimental data. The present invention utilizes CT to scan the whole coal sample, and through the dry data volume of the coal sample and the coal sample saturated with contrast agent, combined with the corresponding experimental data, the macroscopic coal rock components in the coal are divided into bright components (mirror coal and bright coal) and dark components (dark coal and silky carbon), so as to realize quantitative characterization of the content of macroscopic coal rock components in the coal sample, which is more accurate and objective, and at the same time can show the spatial distribution law of different macroscopic coal rock components.

[0100] In one embodiment, the grayscale boundary range of the local macroscopic coal rock component based on the proportion of each macroscopic coal rock component described in step S203 is calibrated to obtain the grayscale value range of different macroscopic coal rock components, including:

[0101] Adjust the grayscale value threshold of the grayscale boundary range of each macroscopic coal rock component, and calculate the overall macroscopic coal rock component proportion of the adjusted different macroscopic coal rock components until the overall macroscopic coal rock component proportion is equal to the local macroscopic coal rock component proportion.

[0102] Embodiment 2

[0103] The embodiment of the present invention provides a device for quantitatively identifying coal and rock components based on CT scanning of the entire diameter, referring to Figure 5 As shown, including:

[0104] The three-dimensional reconstruction module 301 is used to perform three-dimensional reconstruction of CT images of CT scan images of different end surfaces of the dry coal sample and the coal sample saturated with contrast agent, respectively, to obtain a dry coal sample data volume and a saturated coal sample data volume;

[0105] A comparison module 302 is used to compare the dry coal sample data volume and the saturated coal sample data volume, segment and remove pores, cracks and minerals to obtain a coal CT data volume;

[0106] The calculation module 303 is used to compare the organic components of the coal CT data volume and determine the gray value range of different macro coal rock components in the organic components;

[0107] The characterization module 304 is used to count the corresponding pixel points based on the gray value range of each macro coal rock component, characterize its distribution in three-dimensional space and calculate the corresponding content.

[0108] The implementation principle and technical effect of the device for quantitatively identifying full-diameter coal and rock components based on CT scanning provided in an embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0109] Embodiment 3

[0110] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for quantitatively identifying full-diameter coal and rock components based on CT scanning as described in any method embodiment is implemented.

[0111] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0112] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0113] Embodiment 4

[0114] An embodiment of the present invention provides an electronic device, referring to Figure 6 As shown, it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114.

[0115] Memory 113, used for storing computer programs;

[0116] The processor 111 is used to implement the method for quantitatively identifying the full-diameter coal and rock components based on CT scanning as described in any of the above-mentioned method embodiments when executing the program stored in the memory 113.

[0117] The implementation principle and technical effect of the electronic device provided by the embodiment of the present invention are similar to those of any of the aforementioned method embodiments, and will not be repeated here.

[0118] The above-mentioned memory 113 can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. The memory 113 has a storage space for program codes for executing any method steps in the above-mentioned method. For example, the storage space for program codes may include various program codes for implementing various steps in the above method respectively. These program codes can be read from or written into one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such computer program products are usually portable or fixed storage units. The storage unit may have a storage segment or storage space arranged similarly to the memory 113 in the above-mentioned electronic device. The program code can be compressed, for example, in an appropriate form. Generally, the storage unit includes a program for executing the method steps according to an embodiment of the present invention, that is, a code that can be read by, for example, a processor 111, and when these codes are run by an electronic device, the electronic device performs the various steps in the method described above.

[0119] In this document, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. The orientation or position relationship indicated by the terms "upper", "lower", etc. is based on the orientation or position relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0120] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict. The present invention is not limited to any single aspect, any single embodiment, or any combination and / or permutation of these aspects and / or embodiments. Each aspect and / or embodiment of the present invention can be used alone, or in combination with one or more other aspects and / or other embodiments.

[0121] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for quantitatively identifying coal and rock components based on full-diameter CT scanning, characterized in that: include: The CT scan images of different end faces of the dry coal sample and the coal sample saturated with contrast agent are respectively reconstructed in three dimensions to obtain a dry coal sample data volume and a saturated coal sample data volume; By comparing the dry coal sample data volume with the saturated coal sample data volume, the pores, cracks and minerals are segmented and removed to obtain the coal CT data volume; Comparing the organic matter components of the coal CT data volume to determine the gray value range of different macroscopic coal rock components in the organic matter components; Based on the gray value range of each macroscopic coal rock component, the corresponding pixel points are counted to characterize their distribution in three-dimensional space and calculate the corresponding content.

2. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 1 is characterized in that: The method of obtaining the coal CT data volume by comparing the dry coal sample data volume and the saturated coal sample data volume, segmenting and removing pores, cracks and minerals, includes: After aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image; Threshold segmentation and top hat segmentation are performed on the difference image to obtain pores, cracks and minerals in the difference image, and the minerals and pores, cracks are removed from the difference image to obtain a coal CT data volume.

3. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 2 is characterized in that: Before obtaining the difference image by subtracting the dry coal sample data volume from the saturated coal sample data volume, the method further includes: After aligning the same sample part of the dry coal sample data volume and the saturated coal sample data volume, the dry coal sample data volume is subjected to filtering and sharpening processing to obtain a processed dry coal sample data volume.

4. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 3 is characterized in that: The step of subtracting the dry coal sample data volume from the saturated coal sample data volume to obtain a difference image includes: The processed dry coal sample data volume is subtracted from the saturated coal sample data volume to obtain the difference image.

5. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 1 is characterized in that: The organic matter components include light components and dark components; the organic matter components of the coal CT data volume are compared to determine the gray value range of different macroscopic coal rock components in the organic matter components, including: The bright component and the dark component of the organic component in the coal CT data volume are compared, and the gray value range of different macroscopic coal rock components is determined according to the density difference between the bright component and the dark component.

6. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 5 is characterized in that: Determining the grayscale value range of different macroscopic coal and rock components according to the density difference between the bright component and the dark component includes: According to the density difference between the bright component and the dark component, the watershed algorithm is used to identify the gray boundary range between different macro coal and rock components; The end faces of the coal samples are cut and polished in sequence, and after each cutting and polishing, the end faces are photographed with a high-definition camera. The photos of different end faces are calibrated and segmented using a preset image processing method, and the area proportions of macroscopic coal and rock components on different end faces are counted, and the average area ratio is calculated to obtain the local macroscopic coal and rock component proportions; The grayscale boundary range of each macroscopic coal rock component is calibrated based on the proportion of the local macroscopic coal rock component to obtain the grayscale value range of different macroscopic coal rock components.

7. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 6 is characterized in that: The grayscale boundary range of the local macroscopic coal rock component based on the proportion of each macroscopic coal rock component is calibrated to obtain the grayscale value range of different macroscopic coal rock components, including: Adjust the grayscale value threshold of the grayscale boundary range of each macroscopic coal rock component, and calculate the overall macroscopic coal rock component proportion of the adjusted different macroscopic coal rock components until the overall macroscopic coal rock component proportion is equal to the local macroscopic coal rock component proportion.

8. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 1 is characterized in that: The CT scan images of different end surfaces of the dry coal sample and the coal sample saturated with contrast agent are obtained by the following method; The coal sample to be scanned is dried in a vacuum drying oven until the weight of the coal sample remains unchanged to obtain a dry coal sample, and different end faces of the dry coal sample are CT scanned to obtain a CT scan image of the dry coal sample; saturating the dry coal sample after CT scanning with a contrast agent in a pressure saturation device to obtain a coal sample saturated with a contrast agent; The different end faces of the coal sample with contrast agent are subjected to CT scanning to obtain a CT scanning image of the coal sample saturated with contrast agent; wherein the scanning parameters of the coal sample with contrast agent are consistent with the scanning parameters of the dry coal sample.

9. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 8 is characterized in that: When performing CT scanning on dry coal samples, the X-ray tube voltage is set to 110-130 kV, the current is 80-120 μA, and the number of CT images is 1400-1600.

10. The method for quantitatively identifying coal and rock components based on full-diameter CT scanning according to claim 8, characterized in that: The saturated contrast agent is a mixed solution of potassium iodide and sodium chloride, wherein the concentration of potassium iodide is 1.4-1.6 mol / L, and the concentration of sodium chloride is 0.9-1.1 mol / L.

11. A device for quantitatively identifying coal and rock components based on CT scanning of the entire diameter, characterized in that: include: A three-dimensional reconstruction module is used to perform three-dimensional reconstruction of CT images of CT scan images of different end surfaces of a dry coal sample and a coal sample saturated with contrast agent, respectively, to obtain a dry coal sample data volume and a saturated coal sample data volume; A comparison module is used to compare the dry coal sample data volume and the saturated coal sample data volume, segment and remove pores, cracks and minerals to obtain a coal CT data volume; A calculation module, used for comparing the organic components of the coal CT data volume, and determining the gray value range of different macroscopic coal and rock components in the organic components; The characterization module is used to count the corresponding pixel points based on the gray value range of each macro coal rock component, characterize its distribution in three-dimensional space and calculate the corresponding content.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for quantitatively identifying full-diameter coal and rock components based on CT scanning as described in any one of claims 1 to 10 is implemented.

13. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the method for quantitatively identifying the full-diameter coal and rock components based on CT scanning as described in any one of claims 1 to 10 when executing the program stored in the memory.

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