A method, system, device and terminal for discriminating sedimentary environments of lacustrine fine-grained sedimentary rocks

Abstract

The present invention belongs to the technical field of oil and gas exploration, and discloses a method, system, device and terminal for discriminating the sedimentary environment of fine-grained sedimentary rocks. By means of the multi-scale and multi-view micropore identification technology, the microscopic structural characteristics of fine-grained sedimentary rocks are statistically analyzed. The field emission environmental scanning electron microscope is used to continuously take photos of the microscopic structure of fine-grained rocks by successive movement, and the taken photos are sequentially spliced. After being identified and processed by software, the microscopic geometric characteristics and arrangement characteristics of the particles are obtained. According to the microscopic geometric characteristics and arrangement characteristics of the particles, the sedimentary environment of fine-grained sedimentary rocks is identified. Starting from two aspects, namely the microscopic sedimentary structure and the particle morphology of fine-grained sedimentary rocks, the present invention explores the coupling relationship between the structural characteristics of sedimentary rocks and the sedimentary environment at the microscopic scale, realizes the scientific classification and optimization of fine-grained rocks at the microscopic scale, provides a method for discriminating the sedimentary environment relying on the microstructural characteristics of rocks, has important practical significance for the fine characterization of fine-grained rocks, and better serves the development evaluation of oil and gas.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration, and particularly relates to a method, system, device and terminal for discriminating the sedimentary environment of fine-grained sedimentary rocks. Background Art

[0002] At present, fine-grained sedimentary rocks are regarded as important source rocks for unconventional oil and gas resources, and have characteristics such as fine grain size, complex structure, and strong heterogeneity. The formation of fine-grained sedimentary rocks undergoes geological evolution processes such as sedimentation and diagenesis, and their macroscopic structural characteristics and microscopic morphological characteristics are far more complex than those of other rocks. First, the particle size of fine-grained rocks is small, and it is difficult to accurately distinguish with the naked eye; moreover, the sedimentary structural characteristics of fine-grained sedimentary rocks vary widely, and the diagenetic process strongly transforms the sedimentary particles; finally, even fine-grained rocks with similar macroscopic structural characteristics have ever-changing microscopic morphological characteristics. Therefore, relying solely on macroscopic classification methods (such as the "ternary" classification method of mineral composition, color structure classification method, genetic classification method, etc.) cannot fully depict the true properties of fine-grained sedimentary rocks.

[0003] The macroscopic structural characteristics and color properties of fine-grained rocks are manifestations of their microscopic structures, and the macroscopic properties of rocks are controlled by microscopic structural characteristics. Conducting a systematic study on the microscopic structure of fine-grained particles is a process from internal mechanisms to external manifestations. After a series of water flow transportation and re-deposition of fine-grained sediments, there may be certain specific microstructures within the sedimentary unit, which retain the characteristics of primary tissues (i.e., those formed during or shortly after sedimentation) or secondary tissues (i.e., those formed before evolution), and can be used to infer and reconstruct the original sedimentary conditions of the old environment.

[0004] Through the above analysis, the problems and defects of the existing technology are as follows: Macroscopic classification methods including the "ternary" classification method of mineral composition, color structure classification method, genetic classification method, etc. cannot fully depict the true properties of fine-grained sedimentary rocks. The microscopic structure of fine-grained sedimentary rocks is closely related to the sedimentary environment, but there is currently no research on precisely discriminating the sedimentary environment from the perspectives of particle size, shape, and arrangement degree. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention provides a method, system, device and terminal for discriminating the sedimentary environment of fine-grained sedimentary rocks, and particularly relates to a method, system, medium, device and terminal for discriminating the sedimentary environment of fine-grained sedimentary rocks based on the microstructural characteristics of continental rocks.

[0006] The present invention is implemented as follows. A method for discriminating the sedimentary environment of fine-grained sedimentary rocks, the method for discriminating the sedimentary environment of fine-grained sedimentary rocks includes:

[0007] Successively move and continuously take microscopic structure photos of fine-grained rock using a field emission environmental scanning electron microscope, and successively splice the taken photos with the help of multi-scale and multi-field of view. Use micropore identification technology; identify and process through software to count the particle size, morphological characteristics, and particle arrangement structure of fine-grained sedimentary rock, and obtain the microscopic geometric characteristics and arrangement characteristics of particles; based on the microscopic geometric characteristics and arrangement characteristics of particles, identify the sedimentary environment of fine-grained sedimentary rock; finely characterize the morphology and arrangement characteristics of particles from a special perspective of the microstructure to reflect the internal manifestations of the sedimentary environment and sedimentary process.

[0008] Furthermore, the method for discriminating the sedimentary environment of the fine-grained sedimentary rock includes the following steps:

[0009] Step 1, splicing and identification of FE-SEM photos;

[0010] Step 2, using ImageJ software to depict the microstructure characteristic parameters of particles;

[0011] Step 3, identifying the sedimentary microstructure.

[0012] Furthermore, the splicing and identification of FE-SEM photos in Step 1 include:

[0013] Splice the scanning electron micrographs taken at the beginning and end into a photo that can reflect the overall microscopic characteristics of the sedimentary rock, and perform particle identification work; use ImageJ software to perform gray-scale processing on the identified image to obtain a digital image composed of black and white two colors, and the black area represents the area of the particles.

[0014] The digital image is composed of a series of pixel points with different gray values. The pixel point values of the black part are 0, and the pixel point values of the white part are 255, which is represented by a discrete function matrix f(x,y):

[0015]

[0016] In the formula, a and b represent the row and column numbers of the pixel point in the corresponding pixel matrix in the whole image, and n and m represent the number of rows and columns of the pixel points included in the image.

[0017] Furthermore, using ImageJ software to depict the microstructure characteristic parameters of particles in Step 2 includes:

[0018] Use ImageJ image processing software to import the identified image into the image processing software to obtain a numerical image with black and white tones; combine Matlab mathematical analysis software to calculate complex shape parameters, and the shape parameters include particle size, flatness, convexity, and perimeter angularity index. The directional arrangement characteristics of particles are reflected by the "structural orientation entropy" and the particle preferred direction distribution map.

[0019] (1) Diameter of the particle

[0020] The equivalent circle diameter D is adopted as the diameter of the particle; the equivalent circle diameter is the diameter of a circle with the same area as the circle, and the calculation formula is as follows: S As the diameter of the particle; the equivalent circle diameter is the diameter of a circle with the same area as the circle, and the calculation formula is as follows:

[0021]

[0022] (2) Flatness of the particle

[0023] For irregular particles, the shape of the particle is represented by the flatness ratio:

[0024] F = b / t;

[0025] In the formula, F is the flatness ratio; t is the thickness of the particle, which is the distance between the parallel planes of the particle; b is the width of the particle, the shortest distance between another parallel plane, perpendicular to the parallel plane; the flatness of fine-grained sediment particles is usually greater than 1, and the larger the value, the more sheet-like the particle tends to be.

[0026] (3) Angularity of the particle

[0027] The calculation formula of the perimeter angularity index is as follows:

[0028]

[0029] In the formula, Perimeter c is the perimeter of the convex surface of the particle, and Perimeter e is the perimeter of the equivalent ellipse of the particle; the perimeter angularity index of fine-grained sediment particles is greater than 1, and the larger the value, the more developed the edges of the particle are, the more irregular the shape tends to be, and the stronger the angularity.

[0030] (4) Roundness

[0031] Roundness represents the degree to which the shape of an object resembles a circle. The specific formula for roundness is:

[0032]

[0033] (5) Simple shape index

[0034] The shape factor is usually used to characterize the shape of a three-dimensional object. Based on the relationship between the surface area, volume and the power of the diameter of the particle, the simple particle shape index characterizes the shape of a two-dimensional object, as follows:

[0035]

[0036] In the formula, L is the perimeter and A is the area of the particle. The simple particle shape index has nothing to do with the particle size. The value of a circle is the smallest (SC = 1), and as the particle approaches the aspect ratio (the ratio of the long axis to the short axis) increases, the shape index will gradually increase.

[0037] The arrangement characteristic parameters of particles are calculated by means of structural orientation entropy, as follows:

[0038]

[0039] In the formula, E di is the particle arrangement entropy, representing the particle orientation fractal dimension value; E pd is the particle size entropy, representing the particle size fractal dimension value; E bi is the pore arrangement entropy, representing the pore orientation fractal dimension value; The larger the value, the higher the degree of arrangement disorder is proved, the more chaotic and random the arrangement is, without obvious rules, and the more unstable the system is; on the contrary, it indicates that the degree of disorder is lower, the arrangement is more oriented, the system is more stable.

[0040] Furthermore, the specific operation process of the ImageJ image processing software is as follows:

[0041] (1) Gray-scale transformation: Import the target picture into the software and perform gray-scale transformation on the picture;

[0042] (2) Gray-scale threshold setting: Adjust the threshold of the picture according to the gray-scale value of the picture, so that the complete geometric shape of the particle size appears in the picture, keep the threshold concentrated in a stable range, and extract the particles according to the threshold;

[0043] (3) Picture denoising: Adopt the method of automatic denoising;

[0044] (4) Obtaining geometric parameters: After denoising processing, calculate the geometric parameters of the particles and select the items to be measured; the items to be calculated include the centroid coordinates (X, Y), axis length ratio, area, perimeter, equivalent ellipse perimeter, convexity of Objects, and calibrate and count the particles;

[0045] (5) Exporting data: Export and convert the data, and output all the data and save it in an Excel table. Use the formula to convert the measurement results to obtain the true geometric information of the particles.

[0046] Furthermore, the sedimentary micro-structure identification indexes in step three include:

[0047] Analyze the particle size, geometric shape and arrangement structure characteristics of continental fine-grained rocks in the deep lake - semi-deep lake facies, shallow lake facies and delta front subfacies under different sedimentary backgrounds.

[0048] Among them, the particle size of the fine-grained rock in the deep lake - semi-deep lake subfacies is distributed in the range of 0.18 - 13 μm, concentrated in the range of 1 - 4 μm, with an average value of 2.81 μm; the particle size of the fine-grained rock in the shallow lake subfacies is distributed in the range of 0.25 - 16 μm, concentrated in the range of 1 - 6 μm, with an average value of 5.01 μm; the particle size of the fine-grained rock developed in the delta front subfacies is distributed in the range of 0.24 - 36 μm, concentrated in the range of 2 - 14 μm, with an average value of 12.75 μm.

[0049] The distribution ranges of the flatness, roundness, perimeter angularity index, and simple shape index of the fine-grained rock particles in the deep lake - semi-deep lake subfacies are 1.87 - 3.30, 0.62 - 0.72, 1.28 - 1.50, and 1.32 - 1.59. The distribution ranges of the flatness, roundness, perimeter angularity index, and simple shape index of the fine-grained rock particles in the shallow lake subfacies are 1.85 - 3.54, 0.60 - 0.75, 1.30 - 1.61, and 1.25 - 1.45. While the distribution ranges of the flatness, roundness, perimeter angularity index, and simple shape index of the fine-grained rock particles in the delta front subfacies are 1.60 - 2.70, 0.63 - 0.75, 1.35 - 1.64, and 1.42 - 1.73.

[0050] The fine-grained rock particles developed in the deep lake - semi-deep lake subfacies have a relatively wide value distribution range, with values in the range of 0.780 - 0.901 and an average value of 0.852; in the shallow lake subfacies the values are in the range of 0.814 - 0.956 and an average value of 0.905; in the delta front subfacies the values are distributed in the interval of 0.915 - 0.964 and an average value of 0.943. The degree of oriented arrangement of the fine-grained rock particles in the deep lake - semi-deep lake subfacies is the best; the degree of oriented arrangement of the fine-grained rock particles in the shallow lake subfacies is slightly weaker than that in the deep lake - semi-deep lake subfacies; while the distribution of the fine-grained rock particles in the delta front subfacies is chaotic and without obvious rules.

[0051] Another object of the present invention is to provide a discrimination system for the sedimentary environment of fine-grained sedimentary rock applying the discrimination method for the sedimentary environment of fine-grained sedimentary rock, and the discrimination system for the sedimentary environment of fine-grained sedimentary rock includes:

[0052] A photo stitching module for stitching and identifying FE-SEM photos;

[0053] A characteristic parameter acquisition module for depicting the microstructure characteristic parameters of particles using ImageJ software;

[0054] A structure identification module for identifying sedimentary microstructures.

[0055] Another object of the present invention is to provide a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the method for discriminating the sedimentary environment of fine-grained sedimentary rocks.

[0056] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the method for discriminating the sedimentary environment of fine-grained sedimentary rocks.

[0057] Another object of the present invention is to provide an information data processing terminal for implementing the system for discriminating the sedimentary environment of fine-grained sedimentary rocks.

[0058] Combined with the above technical solutions and the solved technical problems, please analyze the advantages and positive effects of the technical solution to be protected by the present invention from the following aspects:

[0059] First, aiming at the technical problems existing in the above prior art and the difficulty of solving this problem, closely combining the technical solution to be protected by the present invention and the results and data in the R & D process, etc., analyze in detail and profoundly how the technical solution of the present invention solves the technical problems and the creative technical effects brought after solving the problems. The specific description is as follows:

[0060] The present invention uses the multi-scale and multi-view micropore identification technology to statistically analyze the microscopic structural characteristics of fine-grained sedimentary rocks; uses a field emission environmental scanning electron microscope to successively move and continuously take photos of the microscopic structure of fine-grained rocks, and then splices the taken photos in sequence. After identification and processing by software (ImageJ), the multi-scale micropore structure characteristics can be observed comprehensively. The new image analysis technology of the present invention is more comprehensive and intuitive than the local observation under the scanning electron microscope. After splicing and processing multiple (8×8) fine-grained rock microstructural images, to a certain extent, it avoids the randomness of position selection in the traditional observation method, reduces the insufficient global understanding of the pore structure of fine-grained rocks and the error caused by the selection of the sample observation position, and can present the microscopic structural morphology of fine-grained sedimentary rocks with multi-scale and multi-order on one image, providing a new idea for the quantitative characterization and qualitative analysis of the microscopic structure.

[0061] The present invention uses the ImageJ image processing software to import the identified image into the image processing software to obtain a black-and-white tonal numerical image. This software can easily obtain basic geometric parameters such as the number, perimeter, area, major and minor diameters of particles, and can also segment, count, classify, etc. the target image.

[0062] Second, considering the technical solution as a whole or from the perspective of the product, the technical effects and advantages of the technical solution to be protected by the present invention are specifically described as follows:

[0063] Starting from two aspects, namely the microscopic sedimentary structure and morphological characteristics of fine-grained sedimentary rocks, the present invention explores the coupling relationship between the structural characteristics of sedimentary rocks and the sedimentary environment at the microscopic scale, realizes the scientific classification and optimization of fine-grained rocks at the microscopic scale, provides a method for discriminating the sedimentary environment of fine-grained rocks relying on the microstructural characteristics of rocks, has important practical significance for the fine characterization of fine-grained rocks, and can better serve the development and evaluation of oil and gas.

[0064] Third, as the creative auxiliary evidence of the claims of the present invention, it is also reflected in the following important aspects:

[0065] The technical solution of the present invention fills the technical gaps at home and abroad in the industry:

[0066] Before the present invention, many scholars distinguished the sedimentary environment of fine-grained rocks from the macroscopic structure, color and composition of fine-grained rocks. However, this method is not very accurate and it is difficult to conduct refined research. The present invention proposes a method for discriminating the sedimentary environment of fine-grained rocks from a new perspective of the morphological characteristics and arrangement structure of microstructural particles, which has innovative value technically and scientific value theoretically. Brief Description of the Drawings

[0067] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments of the present invention. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0068] Figure 1 It is a flowchart of the method for discriminating the sedimentary environment of continental fine-grained sedimentary rocks provided by the embodiments of the present invention;

[0069] Figure 2 It is a schematic diagram of the principle of the method for discriminating the sedimentary environment of continental fine-grained sedimentary rocks provided by the embodiments of the present invention;

[0070] Figure 3 It is a schematic diagram of the multi-scale multi-view field stitching technology and particle recognition provided by the embodiments of the present invention;

[0071] Figure 4 It is a distribution diagram of the dominant direction provided by the embodiments of the present invention;

[0072] Figure 5 It is a columnar and box diagram of the particle size distribution of fine-grained rocks under different sedimentary backgrounds provided by the embodiments of the present invention;

[0073] Figure 6It is a histogram of the particle shape parameters of fine-grained rock under different deposition environments provided by the embodiments of the present invention;

[0074] Figure 7 It is a box plot of the directional entropy of particle structure under different deposition environments provided by the embodiments of the present invention;

[0075] Figure 8 It is a comprehensive diagram of the microstructure analysis of fine-grained rock Kath#1 provided by the embodiments of the present invention;

[0076] Figure 9 It is a comprehensive diagram of the microstructure analysis of fine-grained rock Kath#2 provided by the embodiments of the present invention;

[0077] Figure 10 It is a comprehensive diagram of the microstructure analysis of fine-grained rock Kath#3 provided by the embodiments of the present invention. Detailed implementation manners

[0078] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] Aiming at the problems existing in the prior art, the present invention provides a method, system, device and terminal for discriminating the deposition environment of fine-grained sedimentary rock, and the present invention will be described in detail below with reference to the accompanying drawings.

[0080] I. Explanation of embodiments. In order to enable those skilled in the art to fully understand how the present invention is specifically implemented, this part is an explanatory embodiment that expands and explains the technical solutions of the claims.

[0081] As shown in Figure 1 the method for discriminating the deposition environment of fine-grained sedimentary rock provided by the embodiments of the present invention includes the following steps:

[0082] S101, statistically analyze the microscopic structure characteristics of fine-grained sedimentary rock by means of multi-scale and multi-view micropore identification technology;

[0083] S102, use a field emission environmental scanning electron microscope to continuously take pictures of the microscopic structure of fine-grained rock by successive movement, and splice the taken pictures in sequence;

[0084] S103, after identification and processing by software, obtain the microscopic geometric characteristics and arrangement characteristics of the particles;

[0085] S104, realize the identification of the deposition environment of fine-grained sedimentary rock according to the microscopic geometric characteristics and arrangement characteristics of the particles.

[0086] As a preferred embodiment, as shown in Figure 2As shown, the method for distinguishing the depositional environment of fine-grained sedimentary rocks provided by the embodiment of the present invention specifically includes the following steps:

[0087] (1) Stitching and identification of FE-SEM images

[0088] Fine-grained rock is highly heterogeneous, and a single SEM photo cannot represent the true microstructural characteristics of the rock. Therefore, the microstructural characteristics of fine-grained sedimentary rock are statistically analyzed with the help of multi-scale and multi-view micropore identification technology. The microstructural photos of fine-grained rock are taken by moving the field emission environmental scanning electron microscope in sequence, and the photos are stitched in sequence. After being processed by software identification (ImageJ), the multi-scale micropore structural characteristics can be observed in all aspects (see Figure 3 a). This new image analysis technology is more comprehensive and intuitive than local observation under a scanning electron microscope. After splicing multiple (8×8) fine-grained rock microstructure images, it can avoid the randomness of position selection in traditional observation methods to a certain extent, reduce the lack of global understanding of fine-grained rock pore structure and the errors caused by sample observation position selection, and can present multi-scale and multi-level fine-grained sedimentary rock microstructure morphology in one image, providing a new idea for quantitative characterization and qualitative analysis of microstructure (see Figure 3 b).

[0089] The scanning electron microscope images taken at the beginning and end are stitched together to form a picture that reflects the overall microscopic features of sedimentary rocks (see Figure 3 c), and on this basis, the particles are identified. The yellow color in the figure is the identified particle shape (see Figure 3 d). Then, the recognized image is processed in grayscale using ImageJ software to obtain a digital image composed of black and white colors, in which the black area represents the area of ​​the particle.

[0090] A digital image is composed of a series of pixels with different gray values. The pixel value of the black part is 0, and the pixel value of the white part is 255. It can be represented by a discrete function matrix f(x,y), as follows:

[0091]

[0092] Where a and b represent the row and column numbers of the pixel points in the entire image, and n and m represent the number of rows and columns of the pixels contained in the image.

[0093] (2) Characterize the microstructural characteristic parameters of particles using ImageJ software

[0094] The recognized image is imported into image processing software to obtain a black-and-white tonal digital image. The ImageJ image processing software developed by the National Institutes of Health is used in the present invention. This software can simply obtain basic geometric parameters such as the number, perimeter, area, major and minor diameters of particles, and can also segment, count, classify, etc. the target image. On this basis, the Matlab mathematical analysis software is combined to calculate complex shape parameters such as particle size, flatness, Fourier shape index, perimeter-based angularity index, etc. The specific formulas are as follows.

[0095] The study of the external morphology of particles in this time is carried out on a two-dimensional scale, and most of the particles are irregular in shape, so the circular area equivalent diameter D S is used as the diameter of the particle.

[0096] (1) Particle diameter

[0097] The circular area equivalent diameter D S is used as the diameter of the particle; the circular equivalent diameter is the diameter of a circle with the same area as the circle, and the calculation formula is as follows:

[0098]

[0099] (2) Particle flatness

[0100] For irregular particles, the shape of the particle is represented by the flat ratio:

[0101] F = b / t;

[0102] In the formula, F is the flat ratio; t is the thickness of the particle, which is the distance between the parallel planes of the particle; b is the width of the particle, which is the shortest distance between another parallel plane and is perpendicular to the parallel plane; the flatness of fine-grained sediment particles is usually greater than 1, and the larger the value, the more sheet-like the particle tends to be.

[0103] (3) Particle angularity

[0104] The calculation formula of the perimeter-based angularity index is as follows:

[0105]

[0106] In the formula, Perimeter c is the perimeter of the convex surface of the particle, and Perimeter e is the perimeter of the equivalent ellipse of the particle; the perimeter-based angularity index of fine-grained sediment particles is greater than 1, and the larger the value, the more developed the edges of the particle are, the more irregular the shape tends to be, and the stronger the angularity.

[0107] (4) Roundness

[0108] Roundness represents the degree to which an object's shape resembles a circle. The specific formula for roundness is as follows:

[0109]

[0110] (5) Simple shape index

[0111] Shape factors are usually used to characterize the shape of three-dimensional objects. Based on the relationship between the surface area, volume, and power of the diameter of particles, the simple particle shape index characterizes the shape of two-dimensional objects, as follows:

[0112]

[0113] In the formula, L is the perimeter and A is the particle area. The simple particle shape index is independent of the particle size. The value is the smallest for a circle (SC = 1), and as the particle approaches an aspect ratio (ratio of long axis to short axis) increases, the shape index gradually increases.

[0114] The arrangement characteristic parameters of particles are calculated by means of structural orientation entropy, as follows:

[0115]

[0116] In the formula, E di is the particle arrangement entropy, representing the particle orientation fractal dimension value; E pd is the particle size entropy, representing the particle size fractal dimension value; E bi is the pore arrangement entropy, representing the pore orientation fractal dimension value; The larger the value, the higher the degree of disorder in the arrangement is proved, the more chaotic and random the arrangement is, without obvious rules, and the more unstable the system is; on the contrary, it indicates that the degree of disorder is lower, the arrangement is more oriented, and the system is more stable.

[0117] In the formula, Edi is the particle arrangement entropy (particle orientation fractal dimension value), Epd is the particle size entropy (particle size fractal dimension value), and Ebi is the pore arrangement entropy (pore orientation fractal dimension value). The larger the value the higher the degree of disorder in the arrangement is proved, the more chaotic and random the arrangement is, without obvious rules, and the more unstable the system is; on the contrary, it indicates that the degree of disorder is lower, the arrangement is more oriented, and the system is more stable

[0118] The specific operation process of ImageJ image processing software is as follows:

[0119] a. Gray-scale transformation;

[0120] Import the target image into the software and perform grayscale transformation on the image. The specific operation is as follows: Image - Type - 8 - bit in the menu option bar to transform the image into an 8 - bit grayscale image.

[0121] b. Grayscale threshold setting;

[0122] Adjust the threshold of the image according to the grayscale value of the image so that a complete geometric shape of the particle size appears in the image, keep the threshold concentrated in a stable range, and extract the particles according to the threshold. The specific operation is as follows: Image - Adjust - Threshold in the menu option bar.

[0123] c. Automatic denoising;

[0124] After threshold processing, there are still a large number of noise points in the image. The existence of noise points will reduce the accuracy of particle counting and geometric shape parameters. Therefore, it is necessary to perform denoising processing on the image. Manually correct the image or remove these noise points by filtering and smoothing the image. The automatic denoising method adopted in the present invention is as follows: Process - Noise - Despeckle.

[0125] d. Obtaining geometric parameters;

[0126] After denoising processing, calculate the geometric parameters of the particles, select the items to be measured. The items to be calculated in the present invention include the centroid coordinates (X, Y), axis length ratio, area, perimeter, equivalent elliptical perimeter, convexity, etc. of Objects, and calibrate and count the particles. The specific operation is as follows: Analyze - Set measurement - Analyze particles.

[0127] e. Exporting data;

[0128] Export and convert the data, and output and save all the data in an Excel table. Use the above formula to convert the measurement results to obtain the true geometric information of the particles.

[0129] (3) Sedimentary microstructure identification

[0130] The microstructural characteristics (particle size, shape, arrangement, etc.) of continental fine - grained rocks are closely related to the sedimentary environment. The sedimentary environment is the initial driving force for the arrangement of sediments, which determines the initial accumulation and distribution state of fine - grained sediments, thus affecting the microstructural characteristics of fine - grained rocks. On the basis of the above - mentioned technology, the particle size, geometric shape and arrangement structure characteristics of continental fine - grained rocks under different sedimentary backgrounds (deep - lake - semi - deep - lake facies, shallow - lake facies and delta - front sub - facies) are analyzed. The results show that the fine - grained rocks formed under different sedimentary backgrounds have different microstructural characteristics. The specific parameters are shown in Table 1.

[0131] Table 1 Statistical table of microstructure parameters of continental fine-grained rocks under different sedimentary backgrounds

[0132]

[0133] The distribution map of the advantageous direction provided by the embodiment of the present invention is as shown in Figure 4 ; among them, the distribution map of the advantageous direction of the deep lake - semi-deep lake subfacies is shown in Figure 4 a, the distribution map of the advantageous direction of the shallow lake subfacies is shown in Figure 4 b, and the distribution map of the advantageous direction of the delta front subfacies is shown in Figure 4 c.

[0134] On the basis of the above analysis, the grain size characteristics of fine-grained rock particles under different sedimentary backgrounds were analyzed. The analysis results show that the particle sizes of fine-grained rocks in the deep lake - semi-deep lake subfacies are relatively concentrated, distributed in the range of 0.18 - 13 μm, and mainly concentrated between 1 - 4 μm (see Figure 5 a). The particle size distribution of fine-grained rocks in the shallow lake subfacies is also relatively uniform, and the particle size value is slightly larger than that of the deep lake - deep lake facies, distributed in the range of 0.25 - 16 μm, and mainly distributed between 1 - 6 μm (see Figure 5 b). The particle sizes of fine-grained rocks developed in the delta front subfacies vary greatly, covering the range of 0.24 - 36 μm, and mainly concentrated between 2 - 14 μm (see Figure 5 c). The magnitude of environmental fluid dynamics affects the particle size distribution. The quiet and low-energy water environment in the deep lake - semi-deep lake results in uniform sediment distribution and smaller particle sizes, with an average value of 2.81 μm; compared with the deep lake - semi-deep lake subfacies, the water body where the fine-grained sediments in the shallow lake subfacies are located is shallower, and the sedimentary environment is more active than that of the deep lake facies. Therefore, the particle sizes are slightly larger, with an average value of 5.01 μm. Compared with the deep lake - semi-deep lake subfacies and the shallow lake subfacies, the particle sizes of fine-grained rock particles in the delta front subfacies are relatively larger, the distribution is relatively more dispersed, and the average value is 12.75 μm (see Figure 5 d).

[0135] Figure 6Box plot of the average particle size of fine-grained rock samples in the 7th member of the Yanchang Formation in the Ordos Basin. Fine-grained rock particles developed in different sedimentary environments have different shape characteristics. As the hydrodynamic conditions during sedimentation weakened (delta front - shallow lake - deep lake - semi-deep lake), the particle size and angularity decreased, while the flatness increased. However, the overall differences were not obvious. The fine-grained rock particles in the deep lake - semi-deep lake subfacies had a large flatness, weak development of angularity and roundness (1.40, 2.18, 0.66), and the average value of the simple shape index was 1.40; the shape index, angularity, and roundness of the fine-grained rock particles in the shallow lake subfacies were almost the same as those in the deep lake - semi-deep lake subfacies (1.40, 1.41, 0.66, 1.40), except that the flatness was slightly less than that in the deep lake - semi-deep lake subfacies (2.65); while the roundness and angularity of the fine-grained rock particles in the delta front subfacies were larger (0.71, 1.51), the flatness value was slightly lower (1.87), and the simple shape index was 1.57 (see Figure 7 ).

[0136] The fine-grained rock particles developed in the deep lake - semi-deep lake subfacies had a wide value distribution range, with values in the range of 0.780 - 0.901 and an average value of 0.852. In most samples, the degree of particle arrangement orientation was relatively high; in the shallow lake subfacies, the values were in the range of 0.814 - 0.956 and the average value was 0.905, indicating that the arrangement of some particles had directionality; in the delta front subfacies, the values were distributed in the range of 0.915 - 0.964, with an average value of 0.943, showing that most particles were randomly distributed without obvious regularity (see Figure 7 ).

[0137] As the hydrodynamic conditions during sedimentation weakened (delta - shallow lake - deep lake - semi-deep lake subfacies), the particle angularity decreased and the flatness increased. The fine-grained rock particles in the deep lake - semi-deep lake and shallow lake subfacies had a large flatness, small angularity, and weak development of roundness; while the roundness and angularity values of the fine-grained rock particles in the delta front subfacies were larger and the flatness was slightly lower.

[0138] The influence of sedimentation on the microstructure of fine-grained rock was mainly reflected in the particle arrangement. As the water body became shallower during the sedimentation period, the particles gradually increased, that is, the particle arrangement orientation gradually weakened. The fine-grained rock particles in the deep lake - semi-deep lake subfacies had the best degree of directional arrangement; the fine-grained rock particles in the shallow lake subfacies had a slightly weaker degree of directional arrangement than those in the deep lake - semi-deep lake subfacies; while the fine-grained rock particles in the delta front subfacies were randomly distributed without obvious regularity.

[0139] The sedimentary environment discrimination system for fine-grained sedimentary rocks provided by the embodiments of the present invention includes:

[0140] A photo stitching module for stitching and recognizing FE-SEM photos;

[0141] A characteristic parameter acquisition module for characterizing the microstructure characteristic parameters of particles using ImageJ software;

[0142] A structure recognition module for recognizing sedimentary microstructures.

[0143] II. Application embodiments. To prove the creativity and technical value of the technical solution of the present invention, this part is an application embodiment of the technical solution of the claims on specific products or related technologies.

[0144] Example application

[0145] Table 2 is a comprehensive table of the microscopic structure analysis of the 7th member of the Yanchang Formation (1982.85 m) in Well W11 in the Ordos Basin. There is no bioturbation phenomenon in the scanning electron microscope images of the fine-grained rock sample Kath#1, the sedimentary structure is single, and it has a rhythmic bedding with a directional arrangement structure. The particle size distribution under the scanning electron microscope is relatively uniform, mostly concentrated between 0.3 and 2.4 μm (average particle size 1.42 μm), and flaky or platy clay mineral particles are developed, arranged in a chain-like direction. The average values of the roundness, flatness, and perimeter angularity index of the fine-grained rock particles are 0.65, 3.0, and 1.35 respectively, the structural orientation entropy value is 0.8021, and the particle arrangement dominant direction distribution map is a spindle-shaped directional type, proving that the particle microstructure distribution of this sample is relatively compact and the degree of dispersion is small. The fine-grained rock sample was formed in a sedimentary environment of a deep lake - semi-deep lake, the water body was calm, basically not affected by waves, and the anoxic reducing environment was not conducive to the survival of organisms, but the remains of plankton in the water body could be well preserved.

[0146] Table 2 Comprehensive table of microscopic structure analysis of fine-grained rock Kath#1

[0147]

[0148]

[0149] The comprehensive diagram of the microscopic structure analysis of the fine-grained rock Kath#1 provided by the embodiment of the present invention is as Figure 8 shown; among them, the multi-scale multi-view scanning electron microscope stitching photos are shown in Figure 8 a - 8b, and the statistical results are shown in Figure 8 c - 8d.

[0150] Table 3 is the comprehensive table of the microscopic structure analysis of the 7th member of the Yanchang Formation (1683.34 m) in Well W6 in the Ordos Basin. There is no bioturbation phenomenon in the scanning electron microscope images of the fine-grained rock sample Kath#16, and it has a parallel bedding structure with oriented arrangement. Under the scanning electron microscope, the particle size distribution is relatively uniform, mostly concentrated between 0.4 and 4.4 μm (average particle size 1.71 μm), and flaky or platy clay mineral particles are developed, showing a chain-like oriented arrangement. The average values of the roundness, flatness, and perimeter angularity index of the fine-grained rock particles are 0.67, 2.4, and 1.45 respectively, and the structural orientation entropy value is 0.8953. The distribution map of the dominant direction of particle arrangement shows certain orientation characteristics, proving that the particle microstructure distribution of this sample is relatively compact and the degree of dispersion is small. It is proved that the fine-grained rock sample was formed in a shallow lake sedimentary environment, with lake wave action, sufficient oxygen at the bottom of the water, prosperous organisms, close to the provenance, and many types of sedimentary structures. The sediments mainly come from the clastic minerals and suspended clay particles transported and deposited at the lake edge, as well as the remains or excreta of animals and plants.

[0151] Table 3 Comprehensive Table of Microscopic Structure Analysis of Fine-Grained Rock Kath#2

[0152]

[0153] The comprehensive diagram of the microscopic structure analysis of the fine-grained rock Kath#2 provided by the embodiment of the present invention is as Figure 9 shown; among them, the multi-scale multi-view scanning electron microscope mosaic photos are shown in Figure 9 a - 9b, and the statistical results are shown in Figure 9 c - 9d.

[0154] Table 4 is the comprehensive table of the microscopic structure analysis of the 7th member of the Yanchang Formation (1418.82 m) in Well W2 in the Ordos Basin. In the scanning electron microscope images of the fine-grained rock sample Kath#3, the particles are randomly distributed and there is no obvious microscopic aggregation phenomenon. Under the scanning electron microscope, the particle size distribution is relatively uniform, mostly concentrated between 1.0 and 9.2 μm (average particle size 2.52 μm). The average values of the roundness, flatness, and perimeter angularity index of the fine-grained rock particles are 0.71, 2.0, and 1.40 respectively, and the structural orientation entropy value is 0.9751. The distribution map of the dominant direction of particle arrangement is of a random type, the particle distribution is relatively dispersed, and the degree of dispersion is large. It is proved that the fine-grained rock sample was formed in a delta sedimentary environment, the water environment is relatively active, and the particle size is affected by transportation, deposition and other effects. The sediments mainly come from the clastic minerals and suspended clay particles transported and deposited at the lake edge, etc.

[0155] Table 4 Comprehensive Diagram of Microscopic Structure Analysis of Fine-Grained Rock Kath#3

[0156]

[0157] The comprehensive diagram of the microscopic structure analysis of the fine-grained rock Kath#3 provided by the embodiment of the present invention is asFigure 10 as shown; among which, the multi-scale and multi-field-of-view scanning electron microscope stitching photos are shown in Figure 10 a to 10b, and the statistical results are shown in Figure 10 c to 10d.

[0158] It should be noted that the embodiments of the present invention can be implemented through hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those of ordinary skill in the art can understand that the above devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and their modules of the present invention can be implemented by hardware circuits of programmable hardware devices such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above hardware circuits and software, such as firmware.

[0159] As described above, only the specific embodiments of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A method for distinguishing the sedimentary environment of fine-grained sedimentary rocks. It is characterized in that The method for distinguishing the depositional environment of the fine-grained sedimentary rock comprises: Use a field emission environmental scanning electron microscope to continuously take photos of the microstructure of fine-grained rocks, and stitch the photos in sequence with the help of multi-scale and multi-viewing fields; use software identification and recognition to count the grain size, morphological characteristics and grain arrangement structure of fine-grained sedimentary rocks, and obtain the microscopic geometric characteristics and arrangement characteristics of the grains; based on the microscopic geometric characteristics and arrangement characteristics of the grains, the sedimentary environment of fine-grained sedimentary rocks can be identified; from the special perspective of microstructure, the morphology and arrangement characteristics of the grains are finely characterized to reflect the intrinsic performance of the sedimentary environment and sedimentary process; The method for distinguishing the depositional environment of fine-grained sedimentary rocks comprises the following steps: Step 1: stitching and identification of FE-SEM photos; Step 2, using ImageJ software to characterize the microstructural characteristic parameters of the particles; Step three, identifying the deposited microstructure; The identification of the deposited microstructure comprises: The sedimentary environment is the initial driving force for sediment arrangement, which determines the initial accumulation and distribution state of fine-grained sediments, thereby affecting the microstructural characteristics of fine-grained rocks. The sedimentary environment includes deep lake-semi-deep lake phase, shallow lake phase and delta front subphase. By analyzing the grain size, grain size characteristics, geometric shape and arrangement structure characteristics of terrestrial fine-grained rock particles under different sedimentary backgrounds, the microstructural characteristics of fine-grained rocks formed under different sedimentary backgrounds are obtained.

2. The method for determining the depositional environment of fine-grained sedimentary rocks according to claim 1, It is characterized in that The stitching and identification of the FE-SEM photos in step 1 include: The scanning electron microscope images taken at the beginning and end are stitched together into a picture that can reflect the overall microscopic features of the sedimentary rock, and the particles are identified; the identified image is gray-scaled using ImageJ software to obtain a digital image composed of black and white colors, with the black area representing the area of ​​the particle; A digital image is composed of a series of pixels with different gray values. The pixel value of the black part is 0, and the pixel value of the white part is 255. It is represented by a discrete function matrix f(x,y): Where a and b represent the row and column numbers of the pixel points in the entire image, and n and m represent the number of rows and columns of the pixels in the image.

3. The method for determining the depositional environment of fine-grained sedimentary rocks according to claim 1, It is characterized in that The microstructural characteristic parameters of the particles described in step 2 using ImageJ software include: ImageJ image processing software is used to import the recognized image into the image processing software to obtain a digitized image in black and white tones; Matlab mathematical analysis software is used to calculate complex shape parameters, including particle size, flatness, Fourier shape index, and perimeter angularity index; (1) Particle diameter Adopt the equivalent diameter D of the circular area S as the diameter of the particle; the equivalent circular diameter is the diameter of a circle with the same area as the circle, and the calculation formula is as follows: (2) Flatness of particles For irregular particles, the shape of the particle is expressed by the flatness ratio: F = b / t; In the formula, F is the flatness ratio; t is the thickness of the particle, which is the distance between the parallel planes of the particle; b is the width of the particle, which is the shortest distance between another pair of parallel planes and is perpendicular to the parallel planes; the flatness of fine-grained sediment particles is usually greater than 1, and the larger the value, the more sheet-like the particles tend to be; (3) Angularity of particles The calculation formula for the perimeter angularity index is as follows: wherein, Perimeter c is the perimeter of the convex surface of the particle, and Perimeter e is the perimeter of the equivalent ellipse of the particle; the perimeter angularity index of the fine-grained sediment particles is greater than 1, and the larger the value, the more developed the edges of the particles are, the more irregular the shape tends to be, and the stronger the angularity is; (4) Roundness Roundness represents the degree to which the shape of an object resembles a circle. The specific formula for roundness is: (5) Simple shape index Shape factors are usually used to characterize the shape of three-dimensional objects. Based on the relationship between the surface area, volume, and power of the diameter of the particles, the simple particle shape index characterizes the shape of two-dimensional objects, as follows: In the formula, L is the perimeter and A is the particle area; the simple particle shape index is independent of the particle size. The value of a circle is the smallest, SC = 1. As the particle approaches the aspect ratio (the ratio of the long axis to the short axis), the shape index will gradually increase; The arrangement characteristic parameters of particles are calculated by means of structural orientation entropy, specifically as follows: where, E di is the entropy of particle arrangement, representing the value of the particle orientation fractal dimension; E pd is the entropy of particle size, representing the value of the particle size fractal dimension; E bi is the entropy of pore arrangement, representing the value of the pore orientation fractal dimension; The larger the value, the higher the degree of disorder in the arrangement, indicating that the arrangement is more chaotic, without obvious rules, and the system is more unstable; on the contrary, it indicates that the degree of disorder is lower, the arrangement is more oriented, and the system is more stable.

4. The method for discriminating the sedimentary environment of fine-grained sedimentary rocks according to claim 3, characterized in that the specific operation process of the ImageJ image processing software is as follows: (1) Gray-scale transformation: Import the target picture into the software and perform gray-scale transformation on the picture; (2) Gray-scale threshold setting: Adjust the threshold of the picture according to the gray-scale value of the picture so that the complete geometric shape of the particle size appears in the picture, keep the threshold concentrated in a stable range, and extract the particles according to the threshold; (3) Picture denoising: Adopt the method of automatic denoising; (4) Obtaining geometric parameters: After denoising, calculate the geometric parameters of the particles and select the items to be measured; the items to be calculated include the centroid coordinates (X, Y), axis length ratio, area, perimeter, equivalent ellipse perimeter, and convexity of Objects, and calibrate and count the particles; (5) Exporting data: Export and convert the data, and output and save all the data in an Excel table; Use the formula to convert the measurement results to obtain the true geometric information of the particles.

5. The method for discriminating the sedimentary environment of fine-grained sedimentary rocks according to claim 1, characterized in that the sedimentary microstructure identification in step three includes: Analyze the particle size, particle size characteristics, geometric shape, and arrangement structure characteristics of continental fine-grained rocks in the deep lake - semi-deep lake facies, shallow lake facies, and delta front subfacies under different sedimentary backgrounds; Among them, the particle size of the fine-grained rocks in the deep lake - semi-deep lake subfacies is distributed in the range of 0.18 - 13 μm, concentrated in 1 - 4 μm, and the average value is 2.81 μm; the particle size of the fine-grained rocks in the shallow lake subfacies is distributed in the range of 0.25 - 16 μm, concentrated in 1 - 6 μm, and the average value is 5.01 μm; the particle size of the fine-grained rocks developed in the delta front subfacies is distributed in the range of 0.24 - 36 μm, concentrated in 2 - 14 μm, and the average value is 12.75 μm; The distribution ranges of the flatness, roundness, perimeter angularity index, and simple shape index of fine-grained rock particles in the deep lake - semi-deep lake subfacies are 1.87 - 3.30, 0.62 - 0.72, 1.28 - 1.50, and 1.32 - 1.59; those of the fine-grained rock particles in the shallow lake subfacies are 1.85 - 3.54, 0.60 - 0.75, 1.30 - 1.61, and 1.25 - 1.45; while those of the fine-grained rock particles in the delta front subfacies are 1.60 - 2.70, 0.63 - 0.75, 1.35 - 1.64, and 1.42 - 1.73; The distribution range of the E value of the fine-grained rock particles developed in the deep lake - semi-deep lake subfacies is relatively wide, with the E value in the range of 0.780 - 0.901 and an average value of 0.852; in the shallow lake subfacies, the E value is in the range of 0.814 - 0.956 and the average value is 0.905; in the delta front subfacies, the E value is distributed in the range of 0.915 - 0.964 and the average value is 0.943; the degree of directional arrangement of the fine-grained rock particles in the deep lake - semi-deep lake subfacies is the best; the degree of directional arrangement of the fine-grained rock particles in the shallow lake subfacies is slightly weaker than that in the deep lake - semi-deep lake subfacies; while the distribution of the fine-grained rock particles in the delta front subfacies is chaotic and has no obvious pattern; The degree of directional arrangement of the fine-grained rock particles in the deep lake - semi-deep lake subfacies is the best; the degree of directional arrangement of the fine-grained rock particles in the shallow lake subfacies is slightly weaker than that in the deep lake - semi-deep lake subfacies; while the distribution of the fine-grained rock particles in the delta front subfacies is chaotic and has no obvious pattern.

6. A sedimentary environment discrimination system for fine-grained sedimentary rocks applying the sedimentary environment discrimination method of fine-grained sedimentary rocks as described in any one of claims 1 - 5, characterized in that, the sedimentary environment discrimination system for fine-grained sedimentary rocks includes: a photo stitching module for stitching and identifying FE-SEM photos; a characteristic parameter acquisition module for depicting the microstructural characteristic parameters of particles using ImageJ software; a structure identification module for identifying sedimentary microstructures.

7. A computer device, characterized in that, the computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the sedimentary environment discrimination method of fine-grained sedimentary rocks as described in any one of claims 1 - 5.

8. A computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the processor executes the sedimentary environment discrimination method of fine-grained sedimentary rocks as described in any one of claims 1 - 5.

9. An information data processing terminal, characterized in that, the information data processing terminal is used to implement the sedimentary environment discrimination system for fine-grained sedimentary rocks as described in claim 6.

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