Quantitative characterization method of pitch optical structure based on reflectivity and roughness
By combining polarizing microscopy and atomic force microscopy, the optical structure of pyrophoric pitch was refined into six types, solving the problem of quantitative characterization of the optical structure of pyrophoric pitch and achieving more reliable applicability to geological samples.
Patent Information
- Application Number
- CN202110551133.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-05-20
- Publication Date
- 2025-11-21
- Estimated Expiration
- 2041-05-20
AI Technical Summary
Existing technologies lack quantitative methods for characterizing the optical structure of pitch, especially for irregular mosaic and fibrous structures, which have not been studied for their reflectivity and roughness. This results in insufficiently refined optical structure classification of geological samples, which lacks geological significance.
Using a combination of polarizing microscopy and atomic force microscopy, photomicrographs were taken in unpolarized reflected light, single-polarized reflected light, and orthogonal reflected light modes. Reflectivity and roughness parameters were calculated by combining a microspectrophotometer and an atomic force microscope, and the optical structure of pyrophoric pitch was refined into six types.
It achieves quantitative characterization of the optical structure of tar pitch, with more reliable results, applicable to geological samples, providing stronger applicability to geological samples, and enabling more precise classification of optical structure types.
Smart Images
Figure CN114544619B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of energy materials and organic petrology, specifically to a quantitative characterization method for the optical structure of pitch based on reflectivity and roughness. Background Technology
[0002] Strongly anisotropic (intermediate phase) pitch has a complex and diverse optical structure, and different optical structures have specific geological significance, such as indicating differences in crude oil precursors and influencing maturity identification. Existing measurement methods classify measurement results into mosaic and streamline types according to morphology, and further into fine, medium, and coarse categories according to scale, totaling six categories. This classification method has limited application in geology and lacks quantitative characteristics (as shown in Table 1).
[0003] The optical structures involved in actual geological samples are more complex and diverse, such as irregular mosaics and fibrous structures. The reflectivity and roughness of these optical structures have not been studied, and there is a lack of measurement methods and classification schemes based on quantitative characterization. Furthermore, their origins and geological significance are unclear.
[0004]
[0005] Table 1 Classification of optical structures of tar pitch in existing technologies Summary of the Invention
[0006] This invention addresses the technical problems of the aforementioned measurement methods for the optical structure of tar pitch, which involve rough division and lack of quantitative characteristics, and the lack of research on the reflectivity and roughness of irregular mosaic, fibrous, and other structures. It provides a quantitative characterization method for the optical structure of tar pitch based on reflectivity and roughness, which divides the structure according to quantitative parameters, resulting in more reliable results and greater applicability to geological samples.
[0007] To address the aforementioned technical problems, this invention provides a method for quantitative characterization of the optical structure of pitch based on reflectivity and roughness, characterized by comprising the following steps:
[0008] S1: Collect rock samples containing pitch, prepare thin sections, and polish them with polishing fluid to obtain smooth surfaces of pitch containing different optical structures;
[0009] S2: Using a polarizing microscope in unpolarized reflected light, single-polarized reflected light, and orthogonal reflected light modes, select the field of view of different optical structures described in S1 and take micrographs to screen the optical structure photographs.
[0010] S3: Draw six optical structure models, namely, uniform to slight mosaic, fine mosaic, irregular mosaic, sphere, streamline and fiber.
[0011] S4: Perform multiple reflectance tests using different optical structure models described in the microspectrophotometer, and plot the reflectance frequency distribution diagram to calculate reflectance and roughness.
[0012] Specifically, in step S4,
[0013] For uniform to light mosaic and fine mosaic, the maximum and minimum reflectance difference Dmax-min is calculated based on the maximum reflectance BRmax, minimum reflectance BRmin, and mean reflectance BRavg measured in the reflectance distribution map.
[0014] For irregular mosaics, spheres, streamlines, and fibers, the light and dark areas of the optical structure are divided. Based on the mean reflectance of the dark area BRlr, the mean reflectance of the bright area BRhr, and the mean reflectance Bravg measured in the reflectance distribution map, the reflectance difference between the bright and dark areas Dhr-lr is calculated.
[0015] Specifically, the thin film is made into a target with a diameter of less than 15 mm, and an atomic force microscope is used to obtain a three-dimensional morphology image of the tar pitch surface.
[0016] Specifically, the average roughness Ra and root mean square roughness Rq are automatically calculated from the three-dimensional topography image.
[0017] Specifically, in step S4, the number of test points for multiple reflectivity tests is 50.
[0018] Specifically, in step S1, rock samples containing tar pitch are collected, and the samples used are rock cores.
[0019] Compared with the prior art, the present invention achieves the following technical effects:
[0020] This invention presents a quantitative characterization method for the optical structure of pitch ash based on reflectivity and roughness. Building upon morphological and dimensional classifications, it refines the optical structure of pitch ash into six distinct structures. Using microspectrophotometry and atomic force microscopy imaging, the reflectivity and roughness parameters of each optical structure are calculated, enabling quantitative characterization. This classification scheme overcomes the limitations of simplistic, artificial morphological and dimensional classifications in the energy materials field. Classification based on quantitative parameters yields more reliable results and greater applicability to geological samples. Attached Figure Description
[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0022] Figure 1 This is a flowchart of the detection method in this scheme;
[0023] Figure 2 Photographs of light reflected from pitch pyroth with six different optical structures;
[0024] Figure 3 Histograms of frequency distribution of pyroth reflection for six optical structures;
[0025] Figure 4 The atomic force microscope morphology features of six different optical structures of pitch;
[0026] Figure 5 This represents the relationship between the surface roughness and reflectivity range of tar pitch. Detailed Implementation
[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] This invention provides a quantitative characterization method for the optical structure of pyrophoric asphalt based on reflectivity and roughness. The method classifies the asphalt according to quantitative parameters, resulting in more reliable results and greater applicability to geological samples.
[0029] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0030] like Figure 1-5 As shown, this invention provides a quantitative characterization method for the optical structure of tar pitch based on reflectivity and roughness. Using microspectrophotometer and atomic force microscope imaging, the original optical structure of tar pitch is refined into six additional optical structures based on morphology and size classification. The reflectivity and roughness parameters of different optical structures are calculated, providing a quantitative characterization of the optical structure and further indicating the properties of crude oil. Specifically, it includes the following steps (e.g.) Figure 1 As shown):
[0031] S1: Collect rock samples containing pitch, prepare thin sections, and polish them with polishing fluid to obtain smooth surfaces of pitch containing different optical structures;
[0032] S2: Using a polarizing microscope in unpolarized reflected light, single-polarized reflected light, and crossed reflected light modes, select the field of view of the different optical structures described in S1 and take photomicrographs. Select the optical structure photographs (e.g., ...). Figure 2 (as shown);
[0033] S3: Based on the characteristics of different optical structures in the optical structure photographs, six optical structure models were drawn, namely, uniform to slight mosaic, fine mosaic, irregular mosaic, small sphere, streamline and fiber optical structures.
[0034] S4: Multiple reflectance tests were conducted using different optical structure models described in the microspectrophotometer. In this scheme, 50 test points were selected, and a reflectance frequency distribution map was plotted to calculate reflectance and roughness (e.g., ...). Figure 3 (As shown).
[0035] Specifically, in the above scheme, for uniform to slight mosaic and fine mosaic, the maximum and minimum reflectance difference Dmax-min is calculated based on the maximum reflectance BRmax, minimum reflectance BRmin, and mean reflectance BRavg measured in the reflectance distribution map.
[0036] For irregular mosaics, spheres, streamlines, and fibers, the light and dark areas of the optical structure are divided. Based on the mean reflectance of the dark area BRlr, the mean reflectance of the bright area BRhr, and the mean reflectance Bravg measured in the reflectance distribution map, the reflectance difference between the bright and dark areas Dhr-lr is calculated (as shown in Table 2).
[0037] Specifically, in the above scheme, in step S1, the thin film is made into a target with a diameter of less than 15 mm, placed on the sample stage of an atomic force microscope, and imaged using the ScanAsyst Mode. The atomic force microscope is then used to obtain a three-dimensional morphology image of the pyrophoric pitch surface (e.g., ...). Figure 4 (As shown).
[0038] The optical structures of six types of asphalt were refined above, and the reflectivity and roughness of these six optical structures were obtained. The reflectivity and roughness of these optical structures have not been studied in the prior art and are of great significance for the determination of crude oil properties.
[0039] Specifically, to verify the accuracy of the pyrophoric acid reflectivity and roughness of the optical structure delineated by the above method, this scheme verifies the formation of the optical structure by processing existing data. The specific steps are as follows:
[0040] Three-dimensional elevation data of the tar pitch surface was extracted from the existing data. The three-dimensional elevation data was smoothed and the substrate was flattened. Based on the three-dimensional topography, the average roughness Ra and root mean square roughness Rq were automatically calculated (as shown in Table 3).
[0041]
[0042] Table 2. Random reflectivity parameters of pyrophoric asphalt with different optical structures in the Sichuan Basin.
[0043]
[0044] Table 3. Roughness and Reflectivity Parameters of Atomic Force Microscope
[0045] For the above data, respectively fit the correlation between the average roughness Ra or the root mean square roughness Rq and the reflectivity difference Dmax-min or the reflectivity difference Dhr-lr (e.g., Figure 5 As shown in the figure, the optical structure is caused by the different roughnesses resulting from the uneven surface of the tar pitch.
[0046] Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. Furthermore, those skilled in the art will recognize that, based on the ideas of this invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this invention.
Claims
1. A quantitative characterization method for the optical structure of pitch based on reflectivity and roughness, characterized in that, Includes the following steps: S1: Collect rock samples containing pitch, prepare thin sections, and polish them with polishing fluid to obtain smooth surfaces of pitch containing different optical structures; S2: Using a polarizing microscope in unpolarized reflected light, single-polarized reflected light, and orthogonal reflected light modes, select the field of view of different optical structures described in S1 and take micrographs to screen the optical structure photographs. S3: Draw six optical structure models, namely, uniform to slight mosaic, fine mosaic, irregular mosaic, sphere, streamline and fiber. S4: Use the different optical structure models described by the microspectrophotometer to perform multiple reflectance tests, and draw a reflectance frequency distribution diagram to calculate reflectance and roughness; In step S4 For uniform to light mosaic and fine mosaic, the maximum and minimum reflectance difference Dmax-min is calculated based on the maximum reflectance BRmax, minimum reflectance BRmin, and mean reflectance BRavg measured in the reflectance distribution map. For irregular mosaics, spheres, streamlines, and fibers, the light and dark areas of the optical structure are divided. Based on the mean reflectance of the dark area BRlr, the mean reflectance of the bright area BRhr, and the mean reflectance Bravg measured in the reflectance distribution map, the reflectance difference between the bright and dark areas Dhr-lr is calculated.
2. The method according to claim 1, characterized in that, In step S1, the thin film is made into a target with a diameter of less than 15 mm, and an atomic force microscope is used to obtain a three-dimensional morphology image of the tar pitch surface.
3. The method according to claim 2, characterized in that, The average roughness Ra and root mean square roughness Rq are automatically calculated from the three-dimensional topography image.
4. The method according to claim 1, characterized in that, In step S4, the number of test points for multiple reflectivity tests is 50.
5. The method according to claim 1, characterized in that, In step S1, rock samples containing tar pitch are collected, and the samples used are rock cores.