Method and device for identifying diagenetic alteration degree of carbonate rock

Abstract

The present application relates to the technical field of petroleum and natural gas geological exploration and rock analysis, and discloses a method and device for identifying the diagenetic alteration degree of carbonate rocks. The method comprises the following steps: collecting a cathodoluminescence image of a carbonate rock thin section and performing quantitative analysis to divide mineral regions with different luminescence characteristics; performing laser ablation surface scanning in the regions to obtain a two-dimensional content distribution map; achieving accurate pixel-level alignment of the cathodoluminescence image and the element distribution map by using three-level progressive registration; calculating a multi-dimensional comprehensive alteration index by fusing the cathodoluminescence parameters and the element geochemical indicators for each pixel point based on the registered image; and dividing the diagenetic alteration degree into grades according to the index. The device comprises a cathodoluminescence imaging module, a laser element surface scanning module, an image registration module, a data processing and fusion module, and an evaluation output module. By pixel-level fusion of the fabric information and the geochemical fingerprint, the present application realizes fine and quantitative evaluation of the diagenetic alteration degree of carbonate rocks.

Description

Technical Field

[0001] This invention relates to the field of petroleum and natural gas geological exploration and rock analysis technology, and in particular to a method and apparatus for determining the degree of diagenetic alteration of carbonate rocks. Background Technology

[0002] Carbonate rocks are an important type of oil and gas reservoir, accounting for about 50% of global oil and gas reserves. After deposition, carbonate rocks have undergone multiple phases and types of diagenesis, including cementation, dissolution, dolomitization, and hydrothermal alteration, which have led to the modification of the original sedimentary structure, the complexity of the pore structure, and the large changes in reservoir properties. The degree of diagenetic alteration directly affects the reservoir quality and exploration evaluation conclusions. Therefore, accurate quantitative identification of the degree of diagenetic alteration of carbonate rocks has important theoretical and engineering significance. At present, the identification of the degree of diagenetic alteration of carbonate rocks mainly relies on the following technical means: (1) Polarized light microscopy observation: By observing mineral morphology, cement generation, replacement phenomena, etc., the alteration type and intensity can be determined. However, this method relies on experience judgment, is highly subjective, and is difficult to quantify. (2) Cathodoluminescence (CL) analysis: Cathodoluminescence is a luminescent phenomenon produced by the direct bombardment of the material surface by an electron beam. It is mainly used in the study of sedimentary rock reservoir diagenesis, especially the study of carbonate rock diagenesis. Its effect is more intuitive than conventional petrological and rock chemical analysis. However, current research on the luminescence properties of carbonate minerals using cathodoluminescence methods is still limited to visual identification and description, and cannot achieve quantitative expression. (3) Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) point analysis: It can obtain the elemental and isotopic composition of mineral micro-regions, but the spatial coverage is limited, making it difficult to reflect the distribution characteristics and trends of elements in two-dimensional space. The results obtained by traditional whole-rock analysis are average values ​​of multiple structural components, which are not representative. (4) Laser surface scanning imaging: In recent years, laser surface scanning imaging technology has been developed, which can reduce the detection limit to below 10⁻⁹ and improve the spatial resolution of images from ≥5μm to ≤1μm. However, in the existing technology, laser surface scanning imaging is mainly used for the visualization of elemental distribution and has not been systematically linked with the quantitative evaluation of the degree of diagenesis and alteration. Existing patents include: a method for tracing diagenetic fluids in carbonate reservoirs (CN118533949A), which achieves refined tracing of diagenetic fluids through petrological characteristics and laser surface scanning imaging characteristics; a method and system for identifying the source of diagenetic fluids based on micro-area in-situ elemental distribution (CN201910538155.3), which combines cathodoluminescence and elemental distribution to identify the source of fluids; and a quantitative analysis method for cathodoluminescence images of carbonate minerals (CN202211609049), which realizes quantitative analysis of cathodoluminescence images. However, the above-mentioned existing technologies have the following common technical defects: (1) Single information dimension: Existing technologies either only use CL qualitative analysis, or only use LA-ICP-MS point analysis, or only use laser surface scanning imaging, failing to realize the systematic combination of CL image quantitative analysis and LA-ICP-MS surface scanning imaging, making it difficult to comprehensively characterize the complex characteristics of diagenetic alteration.(2) Low data fusion: Even when studies use both CL and LA-ICP-MS, CL is often used for point selection and LA-ICP-MS for point analysis. The two are not strictly corresponding in space, resulting in fragmented information and making it difficult to establish a quantitative correspondence between CL characteristics and elemental geochemical characteristics. (3) Lack of standardized quantitative identification methods for alteration degree: Currently, the judgment of diagenetic alteration degree mainly relies on petrological observation and empirical judgment, lacking a quantitative and standardized evaluation system based on multimodal data. Therefore, developing a device and method that can combine laser elemental surface scanning and cathodoluminescence to achieve quantitative identification of carbonate rock diagenetic alteration degree has important theoretical significance and engineering application value. Summary of the Invention

[0003] To achieve the above objectives, the present invention adopts the following technical solution: One aspect of the present invention provides a method for determining the degree of diagenetic alteration of carbonate rocks, comprising the following steps: Carbonate rock samples were cut, ground, polished, thin-sectioned, and collected using a cathodoluminescence analyzer to obtain high-resolution RGB format cathodoluminescence images. The cathodoluminescence images were decomposed into RGB channels, K-means clustering, pixel proportion and brightness mean were calculated, and relative luminescence intensity index was calculated to obtain the mineral region classification with different luminescence characteristics and their relative content, luminescence color and intensity parameters. Based on the identified representative regions, laser and ICP-MS parameters were set, and signals of Mg, Fe, Mn, Sr, Ba, U, Th, and rare earth elements were collected. Quantitative correction was performed using NIST SRM 610 / 612 as an external standard and Ca as an internal standard. Two-dimensional content distribution maps of each element were obtained through surface scanning with an inductively coupled plasma mass spectrometer. The representative regions, identified by K-means clustering analysis, included mineral regions with different cathodoluminescence characteristics, such as calcite cements of different generations and regions with different degrees of alteration. These regions were used to guide the selection of areas for elemental surface scanning with the inductively coupled plasma mass spectrometer. The cathodoluminescence images and the two-dimensional content distribution maps of each element were registered in three levels: primary microscopic positioning based on at least three reference points, secondary spatial relationship calculation based on mineral structural feature points, and tertiary pixel-level fine registration based on maximizing grayscale consistency or minimizing grayscale difference. This resulted in pixel-aligned image pairs in the same spatial coordinate system with a registration accuracy better than one pixel. A multi-dimensional comprehensive alteration index was calculated for each pixel in the image pair. Based on the value of the multi-dimensional comprehensive alteration index, the degree of diagenetic alteration of the carbonate rock samples was classified, and a diagenetic alteration degree evaluation report was output.

[0004] In another aspect, the present invention provides an apparatus for determining the degree of diagenetic alteration of carbonate rocks, comprising: The cathodoluminescence imaging module is used to irradiate carbonate rock thin section samples with cathodoluminescence under standard working conditions and acquire high-resolution cathodoluminescence images. The laser elemental surface scanning module is used to perform laser surface scanning in a selected area and simultaneously acquire two-dimensional distribution data of Mg, Fe, Mn, Sr, Ba, U, Th and rare earth elements; The image registration module is used to spatially register the cathodoluminescence image with the two-dimensional content distribution map of each element, so as to achieve dual-modal data alignment of the same region and the same pixel; The data processing and fusion module is used to perform RGB color space decomposition and cluster analysis on cathodoluminescence images to extract luminescence feature parameters; perform spatial interpolation and image processing on elemental surface scan data to generate a two-dimensional elemental distribution map; and fuse the cathodoluminescence feature parameters and elemental content data in the registered spatial coordinates to construct a multi-dimensional comprehensive alteration index. The evaluation output module is used to classify and identify the degree of diagenetic alteration of carbonate rock samples based on the comprehensive alteration index, and output an alteration degree evaluation report. Attached Figure Description

[0005] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of the method for determining the degree of diagenetic alteration of carbonate rocks provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram illustrating the principle of the method for determining the degree of diagenetic alteration of carbonate rocks provided in Embodiment 1 of the present invention. Figure 3 This is a process diagram of obtaining mineral regional classifications with different luminescence characteristics and their relative contents, luminescence color and intensity parameters provided in Embodiment 2 of the present invention; Figure 4 This is a process diagram of obtaining the two-dimensional content distribution map of each element provided in Embodiment 6 of the present invention; Figure 5 This is a diagram illustrating the process of three-level registration between the cathodic emission image and the two-dimensional content distribution map of each element provided in Embodiment 8 of the present invention; Figure 6 This is a schematic diagram of the device for identifying the degree of diagenetic alteration of carbonate rocks provided in Embodiment 13 of the present invention; Figure 7 A block diagram of the electronic device provided by the present invention; Figure 8 A block diagram of a computer-readable storage medium provided for this invention; Figure 9This is a schematic diagram of the overall structure of the device for determining the degree of diagenetic alteration of carbonate rocks provided in Embodiment 13 of the present invention. Figure 10 This is a schematic diagram of the device for determining the degree of diagenetic alteration of carbonate rocks provided in Embodiment 13 of the present invention; Figure 11 This is a diagram showing the K-means clustering analysis results in this embodiment of the invention, identifying mineral regions with different luminescent characteristics; Figure 12 This is a superimposed image of the CL image and the two-dimensional content distribution map of each element in an embodiment of the present invention. Figure 13 This is a spatial distribution map of the Comprehensive Alteration Index (CAI) and an alteration degree classification map in an embodiment of the present invention.

[0006] Reference numerals: 1. Cathode ray emission imaging module; 2. Laser elemental scanning module; 3. Image registration module; 4. Data processing and fusion module; 5. Evaluation output module; 6. Central processing unit / microprocessor / main control chip; 7. Storage medium; 8. Data bus; 9. Input / output bus / external bus / device bus; 10. Display; 11. Input / output device; 12. Computer-readable instructions; 13. Non-transitory computer-readable storage medium. Detailed Implementation

[0007] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0008] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0009] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0010] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0011] The present invention provides a method for identifying the degree of diagenetic alteration of carbonate rocks. This method quantitatively identifies the degree of diagenetic alteration of carbonate rocks, including: acquiring cathodoluminescence images of thin sections prepared from carbonate rock samples; analyzing the cathodoluminescence images to obtain the corresponding relative luminescence intensity index; quantitatively analyzing the relative luminescence intensity index of the cathodoluminescence images to obtain a two-dimensional content distribution map of each element within the luminescent characteristic mineral region; employing a three-level progressive registration method, using at least three reference points for microscopic positioning, and calculating the spatial transformation relationship based on the common mineral structure feature points in the cathodoluminescence images and the two-dimensional content distribution maps of each element to achieve pixel-level fine alignment; calculating a multi-dimensional comprehensive alteration index for each pixel in the pixel-level finely aligned cathodoluminescence images and the two-dimensional content distribution maps of each element; classifying the degree of diagenetic alteration of the carbonate rock samples according to the value of the multi-dimensional comprehensive alteration index, and outputting a diagenetic alteration degree evaluation report. To address the technical problems of existing technologies, such as limited information dimensions, low data integration, and lack of standardized methods for quantitatively identifying alteration levels, this research aims to achieve a refined and quantitative evaluation of the degree of diagenetic alteration in carbonate rocks.

[0012] Example 1: As Figure 1 As shown, this embodiment of the invention provides a method for determining the degree of diagenetic alteration of carbonate rocks, comprising the following steps: Step S100: The carbonate rock sample is cut, ground, polished, thin-sectioned, and acquired by a cathodoluminescence analyzer to obtain a high-resolution RGB format cathodoluminescence image; Step S200: The cathodoluminescence image is decomposed into RGB channels, K-means clustering, pixel ratio and brightness mean calculation, and relative luminescence intensity index calculation to obtain the mineral region classification with different luminescence characteristics and their relative content, luminescence color and intensity parameters. Step S300: Based on the identified representative regions, set the laser and ICP-MS parameters, collect signals of Mg, Fe, Mn, Sr, Ba, U, Th, and rare earth elements, and perform quantitative correction using NIST SRM 610 / 612 as the external standard and Ca as the internal standard. After surface scanning by inductively coupled plasma mass spectrometry, obtain a two-dimensional content distribution map of each element. Among them, the representative regions are mineral regions with different cathodoluminescence characteristics identified by K-means clustering analysis, such as calcite cements of different generations, regions with different degrees of alteration, etc., which are used to guide the selection of regions for elemental surface scanning by inductively coupled plasma mass spectrometry. Step S400: The cathodoluminescence image and the two-dimensional content distribution map of each element are registered in three levels: primary microscopic positioning based on at least three reference points, secondary spatial relationship calculation based on mineral structure feature points, and tertiary pixel-level fine registration based on maximizing grayscale consistency or minimizing grayscale difference, to obtain pixel-aligned image pairs in the same spatial coordinate system with a registration accuracy better than one pixel; a multi-dimensional comprehensive alteration index is calculated for each pixel of the image pair; based on the value of the multi-dimensional comprehensive alteration index, the degree of diagenetic alteration of the carbonate rock sample is classified into levels, and a diagenetic alteration degree evaluation report is output.

[0013] Among them, cathodoluminescence images are color digital images acquired under standard operating conditions, with a voltage of 15.2–15.6 kV and a current of 220–230 μA. These images can intuitively reflect the luminescence color and brightness of minerals with different degrees of diagenetic alteration in carbonate rocks: typically, fresh or weakly altered calcite emits a bright orange-red to red hue, while strongly altered or Mn-rich calcite emits a brighter luminescence. 2＋The region glows bright orange-yellow to yellow-green, which can be used to preliminarily distinguish the intensity of alteration. Traditional CL image acquisition parameters are inconsistent, leading to incomparable luminescence intensities from different batches or laboratories, making it impossible to establish a unified standard for alteration identification. This embodiment, by fixing the parameter range, ensures that the relative luminescence intensity index has cross-sample repeatability. Conventional methods only use grayscale images, losing the subtle red-yellow-green color difference caused by changes in the Mn / Fe ratio, making it difficult to distinguish between weak and moderate alteration regions. High-resolution RGB images retain complete three-channel chromaticity information, providing an input vector for K-means clustering to automatically separate different alteration generations. Under standard conditions of 15.2-15.6kV voltage, 220-230μA current, 0.003mbar vacuum, and 4ms exposure time, high-resolution RGB format cathodoluminescence images, rather than grayscale format, are acquired, distinguishing between fresh / weakly altered calcite (bright orange-red to red) and strongly altered / Mn-rich calcite. 2＋ The chromaticity differences across regions (bright orange-yellow to yellow-green) were fully recorded and reproducibly acquired. The relative luminescence intensity index (CLintensity) was calculated as: the sum of the average RGB three-channel luminance values ​​in each cluster multiplied by the percentage of pixels in that cluster. This index quantitatively expresses the luminescence intensity of mineral regions with different alteration degrees; the higher the alteration degree, the greater the luminescence intensity of Mn. 2＋ Changes in activator content often lead to shifts in luminescence intensity. By comparing the index values ​​of different regions, the original carbonate components and later alteration products can be semi-quantitatively distinguished. Mineral regions with different luminescence characteristics are classified, along with their relative contents, luminescence color, and intensity parameters. K-means clustering groups pixels with similar RGB values ​​in the CL image into one category. Each category corresponds to a mineral region with a specific luminescence characteristic, such as primary calcite, early cement, and late altered calcite. The output includes: relative contents: the area proportion of this type of region, reflecting the mineral abundance at different diagenetic alteration stages; luminescence color and intensity: the RGB mean of this type of region, indicating the direction of change in the Mn / Fe ratio during alteration. These parameters together constitute a quantitative index set for identifying the degree of alteration. A two-dimensional content distribution map refers to the concentration distribution image of each element (Mg, Fe, Mn, Sr, Ba, U, Th, and rare earth elements) on the sample plane generated after internal standard Ca correction of LA-ICP-MS surface scan data. Among the elements, Mn, Fe, and Sr are particularly sensitive to diagenetic alteration: Mn enrichment is often accompanied by alteration under reducing conditions, Fe indicates changes in redox environment, and Sr can reflect whether the original seawater information has been modified by later fluids. By comparing the two-dimensional distribution map with the CL image, the element migration characteristics of the alteration zone can be identified. Mineral regions with different cathodoluminescence characteristics are the actual spatial locations of minerals corresponding to different luminescence categories identified in step S200 cluster analysis. For example: bright red areas, low Mn / Fe ratio, often represent unaltered or weakly altered calcite in the early diagenetic stage; orange-yellow areas, medium Mn / Fe ratio, represent medium alteration areas; dark brown or non-luminescent areas, high Fe...2＋ Quenching luminescence represents alteration products under strong reducing conditions; the region is a direct spatial carrier for identifying differences in the degree of diagenetic alteration. The selected area for elemental surface scanning of inductively coupled plasma mass spectrometry (ICP-MS) refers to using mineral regions with different luminescence characteristics obtained in step S200 as spatial constraints to precisely set the scanning range of LA-ICP-MS surface scanning, for example, performing high-resolution scanning only on a certain luminescence color region or transition zone; avoiding uniform scanning of indifferent regions, but focusing on target mineral domains with different degrees of alteration to obtain the elemental two-dimensional distribution data that best reflects the diagenetic alteration gradient, such as from primary to strong alteration, thereby improving identification efficiency and specificity. Image pairs refer to the cathode emission image and the two-dimensional content distribution image of each element, which are aligned pixel by pixel in the same spatial coordinate system after three-level registration in step S400. For example, the CL image is paired with the Mn element distribution map. By superimposing or observing the image pairs side by side, the element content at the pixel position corresponding to a certain emission feature, such as bright orange, such as the Mn / Ca ratio, can be accurately determined. Pixel-level alignment is the basis for realizing the joint identification of the degree of alteration by emission and elements, and avoids misjudgment caused by spatial misalignment.

[0014] In the above embodiments, the principle is referenced in the appendix. Figure 2The sample preparation and cathodoluminescence image acquisition technology in this embodiment ensures high-fidelity recording of mineral luminescence characteristics. High-resolution RGB format images provide the original data foundation for subsequent mineral regional classification, preserving the luminescence differences in carbonate rock regions with different alteration degrees. Image processing algorithms achieve zonal quantitative analysis of luminescence characteristics. RGB channel decomposition enhances the ability to identify color differences, K-means clustering automatically distinguishes mineral regions with different luminescence characteristics, and pixel ratio and average brightness calculation provide the spatial distribution ratio and relative luminescence intensity data of each region. The relative luminescence intensity index further quantifies the diagenetic alteration information of the minerals; thus, accurate segmentation and parameterization of luminescence characteristics of carbonate rock regions with different alteration degrees are achieved. Trace element surface scanning analysis technology selects representative analysis areas based on cathodoluminescence characteristics, avoiding the limitations of random sampling. Quantitative correction using laser and ICP-MS combined with NIST SRM 610 / 612 external standards and Ca internal standards ensures accurate detection of key diagenetic indicator elements such as Mg, Fe, Mn, and Sr. Two-dimensional elemental distribution maps reveal the elemental migration patterns in different alteration regions, and together with cathodoluminescence data, they form a basis for elemental geochemical identification of alteration degree. Multi-level registration technology ensures precise spatial matching between cathodoluminescence images and elemental distribution maps. Microscopic positioning and structural feature point calculation solve the deformation problem at both macroscopic and microscopic scales. The grayscale consistency or difference minimization optimization algorithm achieves sub-pixel-level registration accuracy, allowing the pixel-level correspondence of image pairs to be used for multi-parameter comprehensive calculations. The calculation of a multi-dimensional comprehensive alteration index further integrates luminescence characteristics and elemental distribution information, forming a unified quantitative index of diagenetic alteration, ultimately classifying alteration levels and outputting an evaluation report.

[0015] In summary, this embodiment achieves an objective and quantitative evaluation of the degree of diagenetic alteration of carbonate rocks through the synergistic analysis of cathodoluminescence characteristics and trace element distribution, improving the accuracy and reliability of identification. This embodiment also utilizes cathodoluminescence images to provide textural information on mineral growth generations and alteration history, as well as laser elemental surface scan data, and geochemical fingerprint information on the chemical composition of alteration fluids. This achieves the complementary advantages of both textural and geochemical dual-modal information, enabling more accurate differentiation of the superimposed effects of different stages and types of diagenetic alteration. LA-ICP-MS surface scan has a spatial resolution of 1~5μm, while CL images have pixel-level resolution. After registration, a fine correspondence between mineral textural and elemental geochemistry is achieved at the micrometer scale, revealing alteration heterogeneity at the microscale. This shift from qualitative description in traditional methods to multi-dimensional comprehensive index quantitative evaluation results in objective and repeatable results, eliminating the subjectivity of human judgment. A standardized system covering the entire process from sample preparation, CL image acquisition and quantitative analysis, LA-ICP-MS surface scanning parameter optimization, image registration and fusion, to alteration index calculation and classification, is provided, exhibiting strong operability and scalability. A systematic device integrating CL imaging, LA-ICP-MS surface scanning, image registration, data fusion, and evaluation output was designed, realizing an automated process from data acquisition to result output. The comprehensive alteration index can be directly used for carbonate reservoir evaluation, providing quantitative basis for favorable reservoir prediction and exploration sweet spot selection.

[0016] Example 2: As Figure 3 As shown, based on Example 1, the process of obtaining the mineral region classification and its relative content, luminescence color and intensity parameters of different luminescence characteristics in step S200 of this embodiment of the invention specifically includes the following steps: Step S201: Decompose the cathode luminescence image into three monochromatic channels: red, green, and blue, and calculate the RGB component value of each pixel; Step S202: Use the K-means clustering algorithm to perform cluster analysis on the image pixels, and group pixels with similar luminescence characteristics into the same category. Each category corresponds to a mineral region with a luminescence characteristic, such as calcite cement from different generations, regions with different degrees of alteration, etc. Step S203: Calculate the pixel percentage of each category as the relative content parameter of that mineral in the sample; calculate the average brightness of the R, G, and B channels in each category to quantitatively characterize the luminous color and luminous intensity of that mineral; calculate the relative luminous intensity index according to the formula. ; in, , , The average RGB brightness value for a certain category. For the number of pixels in this category, This represents the total number of pixels in the image.

[0017] The three monochrome channels (red, green, and blue) refer to separating the high-resolution RGB cathodoluminescence image into three independent grayscale images: red, green, and blue. The brightness value of each channel records the luminescence intensity of the mineral in that wavelength band. When identifying the degree of diagenetic alteration, the color difference of minerals with different alteration degrees—weak alteration tends to be reddish, and strong alteration tends to be yellowish-green—is reflected by the brightness ratio of the three channels. After decomposition, the color information of each pixel is used for quantitative calculation, thereby distinguishing the alteration level. The RGB component values ​​refer to the specific values ​​of the red (R), green (G), and blue (B) channels of each pixel in the image, ranging from 0 to 255. The component values ​​together determine the luminescence color and brightness of the mineral region. When identifying the degree of alteration, the Mn / Fe ratio of the original carbonate composition and the alteration products of different stages is different, causing the ratio of R, G, and B component values ​​to change. For example, the R value in the weak alteration area is significantly higher than the G and B values, while the G value in the strong alteration area is relatively higher, which can quantitatively distinguish the strength of alteration. Pixels with similar luminescence characteristics refer to a group of pixels whose R, G, and B component values ​​are close to each other in the RGB color space, corresponding to areas where minerals exhibit consistent color and brightness under cathodic luminescence. Pixels are spatially continuous, forming mineral regions of the same type, such as cements of the same generation or zones of the same alteration degree. When identifying the degree of diagenetic alteration, clustering can group pixels with consistent luminescence characteristics into one category, automatically identifying the spatial distribution of different alteration levels. A mineral region refers to a two-dimensional spatial range composed of connected pixels with similar luminescence characteristics, corresponding to a certain type of carbonate mineral or a product of the same diagenetic stage in a thin section sample, such as primary calcite, early cements, late-altered calcite, or non-luminescent areas under strong reducing conditions. Each mineral region represents a specific diagenetic alteration stage or alteration intensity and is the basic spatial unit for identifying the degree of alteration. The relative abundance parameter refers to the percentage of pixels in a certain mineral region out of the total number of pixels in the image, i.e., the area proportion of the mineral within the analytical field of view. This parameter directly reflects the abundance of minerals with different alteration degrees in the sample: a high proportion of weakly altered areas indicates that the overall alteration of the sample is weak, while a high proportion of strongly altered areas indicates strong alteration, providing spatial statistical basis for the quantitative evaluation of the degree of diagenetic alteration. The mean brightness refers to the average brightness of the red, green, and blue channels of all pixels within a certain mineral region. These three means collectively characterize the average luminous color and average luminous intensity of that mineral. When identifying the degree of alteration, the relative magnitude of the mean brightness reflects the difference in the Mn / Fe ratio: R_mean is highest when the Mn / Fe ratio is low (weak alteration); R_mean decreases and G_mean increases when the Mn / Fe ratio is medium (medium alteration); and R_mean decreases and G_mean increases when the Mn / Fe ratio is high. 2＋(Quenching luminescence) all three means are very low. Luminescence color refers to the chromaticity determined by the ratio of R_mean, G_mean, and B_mean, such as bright red, orange-yellow, or yellow-green; luminescence intensity refers to the overall level of the three luminance means, quantified by the relative luminescence intensity index; in identifying the degree of diagenetic alteration, luminescence color indicates the activity of the activator Mn during alteration. 2＋ With quencher Fe 2＋ The relative concentration change and the luminescence intensity reflect the total luminescence output; the combination of the two can distinguish the primary components, early diagenetic cement, late alteration products and the non-luminescent zone quenched by iron under reducing conditions, thus achieving a semi-quantitative to quantitative classification of alteration level.

[0018] In the above embodiments, this embodiment achieves quantitative characterization of the microluminescence properties of minerals by decomposing the RGB three-channel components of the cathodoluminescence image and calculating pixel-level spectral features. The K-means clustering algorithm automatically classifies pixels with similar spectral features, accurately distinguishing mineral phases with different degrees of diagenetic alteration, such as identifying the orange luminescent area of ​​unaltered calcite and the dark blue luminescent area of ​​strongly altered regions. The calculation of the pixel proportion of each category establishes mineral phase abundance parameters, providing a quantitative indicator for the spatial distribution of alteration intensity. The calculation of the average brightness of the RGB channels constructs a standardized description system for mineral luminescence properties, solving the subjectivity problem of traditional visual interpretation. The relative luminescence intensity index integrates both luminescence intensity and regional area information through normalization. The parameter is negatively correlated with the degree of alteration of carbonate rocks; when the degree of alteration increases, leading to more lattice defects, the index value shows a systematic decrease. This embodiment establishes a numerical correspondence between cathodoluminescence characteristics and the degree of diagenetic alteration, providing a traceable quantitative criterion for reservoir quality evaluation.

[0019] Example 3: Based on Example 2, step S202 of this embodiment of the invention performs cluster analysis on image pixels, specifically including the following steps: Step S2021: Input the RGB component values ​​of each pixel into the K-means clustering algorithm, set the number of clusters, randomly select initial cluster centers, calculate the Euclidean distance between the RGB component values ​​of each pixel and each cluster center, assign the pixel to the nearest cluster center, update the cluster center to the average of the RGB component values ​​of all pixels in the current category, repeat the iteration until the cluster centers no longer change, output the category label of each pixel, and realize the initial division of luminescent pixels of different alteration degrees of carbonate rocks; Step S2022: Traverse the category labels of all pixels, count the total number of pixels in each category, and remove noise categories with a pixel count lower than a preset threshold; sort the remaining categories according to their RGB mean from the red end representing weak alteration to the yellow-green end representing strong alteration, to obtain multiple stable pixel categories, each pixel category corresponding to a set of luminescent features of a carbonate rock diagenetic alteration degree. Step S2023: Perform eight-neighbor connectivity analysis on all pixels of each pixel category, merge spatially adjacent pixels of the same category into the same connected region, and remove isolated connected regions with an area smaller than the preset minimum area; output each remaining connected region as a mineral region, which is identified as a classification unit with a specific diagenetic alteration level, and used to quantitatively calculate the alteration degree parameter.

[0020] The number of cluster categories refers to the pre-defined target number of categories in the K-means algorithm, corresponding to the expected number of different diagenetic alteration levels in the carbonate rock sample. Based on the visible color differences in cathodoluminescence images, such as bright red, orange-red, orange-yellow, yellow-green, and dark brown, the number of cluster categories is set to 3 to 5, representing alteration levels of weak, moderate, strong, and quenched (no luminescence), respectively. The initial cluster centers refer to the RGB component value combinations of several randomly selected pixels at the beginning of the clustering iteration; each combination serves as the initial representative color for a category. The initial values ​​are updated through subsequent iterations, eventually converging to the actual average luminescence color of mineral regions with different alteration levels. The selection of initial cluster centers affects the convergence speed but does not change the final classification result, ensuring the objective distinction between different alteration levels. Euclidean distance refers to the geometric distance between the RGB component values ​​(R, G, B) of each pixel and a cluster center (Rc, Gc, Bc). This distance measures the similarity between the pixel's luminescence characteristics and the standard color of the alteration level represented by the cluster center; a smaller distance indicates that the pixel's luminescence color is closer to the corresponding alteration level. The category label is an integer assigned to each pixel by the clustering algorithm to identify the cluster to which the pixel belongs. Each category label corresponds to a specific diagenetic alteration level, such as label 1 representing a weakly altered bright red area, label 2 representing a moderately altered orange-yellow area, and label 3 representing a strongly altered yellow-green area. The labels realize the mapping from a continuous color space to a discrete alteration level space. Different alteration levels of luminescent pixels refer to the differences in luminescence between different alteration levels in cathodoluminescence images of carbonate rocks due to the presence of Mn during diagenetic alteration. 2＋ Fe 2＋ Pixel units exhibiting varying luminescence colors and intensities due to changes in the content of activators and quenchers; weakly etched pixels show high R values ​​and low G / B values; moderately etched pixels show decreased R values ​​and increased G values; strongly etched or Fe-rich pixels exhibit... 2＋Pixels are generally low in brightness or have a yellowish-green tint; a pixel is the smallest analytical unit for classifying alteration levels. Noise categories refer to clusters with fewer pixels than a preset threshold, such as those less than 0.1% of the total image pixels. These categories are usually caused by random noise during image acquisition, surface scratches on thin sections, or abnormal luminescence points, and do not represent the actual altered mineral areas of carbonate rocks. Removing noise categories can prevent non-alteration information from being misclassified as alteration levels, improving identification accuracy. The red end of weak alteration refers to regions in the RGB color space where the red channel brightness is significantly higher than the green and blue channels, corresponding to mineral areas in carbonate rocks with low or no diagenetic alteration, such as primary calcite or early cement. Its characteristics are Rmean >> Gmean ≈ Bmean, with a bright orange-red to red luminescence color, reflecting a low Mn / Fe ratio and fewer lattice defects. The yellowish-green end of strong alteration refers to regions in the RGB color space where the green channel brightness is relatively high, the red channel brightness is low, and the blue channel brightness is lowest, corresponding to strongly altered carbonate rocks or areas rich in Mn. 2＋ Mineral regions, such as late-altered calcite, are characterized by Gmean > Rmean > Bmean, with luminescence colors ranging from yellowish-green to yellowish-orange, reflecting a moderate Mn / Fe ratio and a high lattice defect density. Stable pixel categories refer to those with sufficient pixel count, convergent RGB mean values, and no change with initial clustering values ​​after noise removal and sorting by alteration sequence. Each stable pixel category has a defined RGB mean range, such as Rmean 180-220, Gmean 120-160, Bmean 60-100, and a spatial distribution pattern, reliably representing a degree of diagenetic alteration and used for quantitative calculations of relative content, luminescence intensity, and alteration index.

[0021] In the above embodiments, this embodiment uses the K-means clustering algorithm to perform initial partitioning based on pixel-level RGB components, achieving objective classification of cathodoluminescence characteristics of carbonate rocks and effectively avoiding errors from manually delineating alteration zones. The number of categories is set and cluster centers are iteratively optimized to ensure the algorithm can adaptively identify typical luminescence patterns of different alteration intensities. A noise category filtering mechanism eliminates abnormal interference during image acquisition, retaining statistically significant effective alteration feature categories. A category sequence is established according to the RGB mean, constructing a standardized spectral gradient from weak to strong alteration, forming an ordered classification system corresponding to the degree of diagenetic alteration. Eight-neighborhood connectivity analysis integrates discrete pixels into continuous geological units, accurately reflecting the spatial distribution characteristics of alteration areas. Area threshold filtering removes pseudo-anomaly areas caused by local noise or imaging defects, ensuring that the final output mineral regions are all geologically significant. Automatic extraction of connected components establishes the topological structure of alteration zones, providing basic units for calculating regionalized alteration parameters. This embodiment realizes the transformation from pixel-level spectral features to geologically significant alteration zones, forming a spatial classification framework that can quantitatively characterize the intensity of diagenetic alteration of carbonate rocks.

[0022] Example 4: Based on Example 3, the process of performing eight-neighbor connectivity analysis on all pixels of each pixel category in step S2023 of this embodiment of the invention specifically includes the following steps: Step S20231: Perform eight-neighbor connectivity analysis on all pixels with the same category label in each pixel category: Traverse each pixel in the category and check whether the pixels in its eight adjacent directions (up, down, left, right, upper left, upper right, lower left, and lower right) have the same category label. Pixels with the same label and connected by the eight-neighbor path are grouped into the same connected component. Repeat until all pixels in the category are assigned to a certain connected component, and aggregate discrete pixels of the same etch degree level into spatially continuous etch region units. Step S20232: Count the number of pixels contained in each connected region, use the value as the area parameter of the connected region, compare the area parameter with the preset minimum area threshold, if the area of ​​the connected region is less than the preset threshold, the connected region is determined to be an isolated noise region and removed from the subsequent analysis, only the connected regions with an area greater than or equal to the threshold are retained to ensure that the mineral regions participating in the alteration degree identification have a statistically significant spatial scale. Step S20233: Output each connected component retained after area filtering as a mineral region. Each mineral region is assigned the alteration level attribute of its original pixel category, such as weak alteration, moderate alteration, strong alteration, or quenched non-luminescent region. Record the boundary coordinates, total number of pixels, and average RGB component value of the region to complete the conversion from pixel-level clustering results to spatial classification units with clear diagenetic alteration levels. This is used to calculate the relative content parameters and luminescence intensity parameters of each alteration level.

[0023] In the above embodiments, this embodiment aggregates discrete pixels into spatially continuous alteration region units based on eight-neighbor connectivity analysis, eliminating pixel-level classification discreteness caused by spectral mixing or noise, and ensuring that the spatial continuity of the alteration region conforms to the actual distribution characteristics of the geological body. Isolated noise regions are eliminated through area threshold screening, effectively suppressing interference from small-area pseudo-alteration regions caused by image noise or classification errors, retaining statistically significant mineral regions, and improving the reliability of alteration degree identification. The boundary coordinates and average RGB component values ​​of the mineral regions are output, quantifying the spatial distribution range and spectral characteristics of each alteration level, providing a data foundation for calculating relative content parameters and luminescence intensity parameters, and realizing the conversion from pixel-level classification to regional alteration intensity assessment. The alteration level attributes of the original pixel categories are retained, ensuring that the spatial aggregation process does not change the original classification results of mineral alteration intensity, so that the final output region units strictly correspond to the diagenetic alteration levels, meeting the needs of quantitative analysis of carbonate rock alteration degree.

[0024] Example 5: Based on Example 4, the process of using the numerical value as the area parameter of the connected component in step S20232 of this embodiment of the invention specifically includes the following steps: Step S202321: Traverse the coordinates of each pixel in the current connected component. Starting from the first pixel, increment the counter by one for each pixel visited. Count all pixels belonging to the connected component point by point until there are no more uncounted pixels in the connected component, and obtain the total number of pixels in the connected component. Step S202322: Assign the total number of pixels of the connected region to the area parameter of the connected region. The value of the area parameter directly represents the two-dimensional spatial range covered by the alteration grade mineral region in the thin section field of view. The larger the area parameter, the wider the area occupied by the alteration grade region in the sample, and vice versa. Specifically, an area parameter variable corresponding to the current connected domain is defined. The data type of the area parameter variable is integer, and the initial value is zero. It is used to store the quantitative value of the size of the two-dimensional spatial range covered by the connected domain. The total number of pixels in the connected domain is obtained as a numerical value. The numerical value is written into the defined area parameter variable through the assignment operator, completing the mapping from pixel count to area parameter. This allows the spatial scale of the connected domain to be quantitatively recorded in the form of pixel count. The area parameter, as the core attribute value of the connected domain, is used for two calculations: first, the area parameters of all connected domains under the same alteration level are accumulated to obtain the total area ratio of this alteration level; second, the area parameters of connected domains with different alteration levels are compared horizontally. The larger the area parameter of the connected domain, the more extensive the development of the alteration level region in the carbonate rock sample, and the more significant the control effect on the overall diagenetic alteration degree of the sample. This realizes the quantitative identification from the scale of local connected domains to the macroscopic alteration degree. Step S202323: Assign the area parameter of each connected domain to its corresponding alteration level category: weak alteration, moderate alteration, strong alteration, or quenched non-luminescent region; sum the area parameters of all connected domains under the same alteration level to obtain the total area ratio of the alteration level; a high total area ratio of weak alteration indicates that the original components of the sample are well preserved, while a high total area ratio of strong alteration indicates that the sample has undergone strong fluid alteration, thus realizing the quantitative identification of the overall diagenetic alteration degree of carbonate rocks from the area parameters of connected domains.

[0025] In the above embodiments, this embodiment uses a pixel-level traversal connected domain area measurement method to ensure accurate quantification of the spatial coverage of the alteration region. The pixel-by-pixel counting mechanism eliminates the subjective error of traditional visual estimation methods, transforming the two-dimensional distribution characteristics of the alteration region into calculable discrete values, providing basic data support for subsequent statistical analysis. Secondly, the mapping relationship between area parameters and alteration levels establishes a quantitative bridge between microstructure and macroscopic features. By classifying the connected domain area into specific alteration level categories, the classification and statistics of alteration regions with different intensities are realized. The mapping relationship directly reflects the intensity of the alteration fluid's effect; the larger the cumulative value of the area parameter in a strongly altered region, the wider the penetration range of the fluid's alteration effect in the sample. The multi-level area parameter analysis framework realizes three-dimensional analysis of diagenetic alteration. The cumulative area of ​​the same alteration level reflects the spatial proportion of a specific alteration intensity, while cross-category comparison reveals the relative development degree of different alteration intensities. It can accurately distinguish the alteration morphology of samples; for example, a high proportion of weak alteration indicates that the original structure is well preserved, while samples dominated by strong alteration reflect strong alteration by deep fluids.

[0026] In summary, this embodiment establishes a complete quantitative chain from microscopic pixel statistics to macroscopic alteration identification. The area parameter, as a core intermediate variable, not only preserves the geometric characteristics of the connected domains but also transforms them into a geologically significant alteration degree index through hierarchical classification and statistical analysis, providing a repeatable and verifiable quantitative standard for the study of carbonate rock diagenesis.

[0027] Example 6: As Figure 4 As shown, based on Example 1, the process of obtaining the two-dimensional content distribution map of each element in step S300 of this embodiment of the invention specifically includes the following steps: Step S301: Based on the representative regions determined by the cluster analysis of the cathodic emission images, set the laser wavelength, beam diameter, scanning speed, laser frequency, and energy density of the laser ablation system; at the same time, set the RF power, cooling gas flow rate, auxiliary gas flow rate, carrier gas flow rate, and time-resolved data acquisition mode of the inductively coupled plasma mass spectrometer to complete the instrument parameter configuration for the area scan analysis. Step S302: Perform line scanning or raster scanning in the selected representative area, and simultaneously collect the signal intensity of magnesium, iron, manganese, strontium, barium, uranium, thorium and all rare earth elements to obtain the original signal intensity distribution data of each element in the scanning area. Step S303: Using glass standard material as an external standard and calcium as an internal standard element, quantitatively correct the signal intensity of each element collected, and generate a two-dimensional content distribution map of each element in the carbonate rock sample plane, which is used to register with the cathodoluminescence image and identify the degree of diagenetic alteration.

[0028] Among them, representative regions identified by CL image clustering analysis, including mineral development areas with different luminescent characteristics, were used to acquire high-resolution elemental surface scan data by setting LA-ICP-MS surface scan parameters: (1) Laser ablation system parameter settings: laser wavelength 193nm, preferred beam spot diameter 4~44μm, selected according to spatial resolution requirements, scanning speed 4~10μm / s, laser frequency 6~10Hz, energy density 6~10J / cm 2 ; (2) ICP-MS parameter settings: RF power 1200~1500W, cooling gas flow rate 13~15L / min (Ar), auxiliary gas flow rate 0.8~1.2L / min (Ar), carrier gas flow rate 0.8~1.0L / min (He), data acquisition mode is time resolution mode; (3) Perform line scanning or raster scanning within the selected area and simultaneously acquire the signal intensity of the following elements: Mg, Fe, Mn, Sr, Ba, U, Th and rare earth elements (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu); (4) Using NISTSRM610 / 612 glass standard material as external standard and Ca as internal standard element, quantitative correction of element signal intensity is performed to generate two-dimensional content distribution map of each element.

[0029] In the above embodiments, the optimized configuration of the laser ablation system and inductively coupled plasma mass spectrometer parameters ensures that the spatial resolution and detection sensitivity of trace elements meet the requirements of micro-area analysis. The representative regions determined by the cathodoluminescence image clustering analysis provide geologically significant target areas for elemental surface scanning, avoiding data redundancy caused by blind scanning. The line scanning or raster scanning mode combined with the multi-element synchronous acquisition strategy enables the synchronous in-situ detection of major elements such as magnesium and iron, and trace elements such as uranium and thorium. The original signal intensity distribution data directly reflects the occurrence state of elements in mineral micro-areas, providing a data basis for distinguishing primary sedimentary components from the superposition of later diagenetic fluids. The instrument drift and matrix effect are eliminated by the external standard and internal standard joint correction method, and the generated two-dimensional content distribution map has quantitative characteristics. Spatial registration with the cathodoluminescence image can establish the correspondence between elemental geochemical zoning and cathodoluminescence rings, clarify the migration law of active elements such as iron and manganese and the anomaly of rare earth element distribution patterns, and thus quantify the modification intensity of diagenetic events such as cementation and dissolution on the original components.

[0030] In summary, this embodiment, through the coupled analysis of micro-area elemental distribution and cathodoluminescence characteristics, overcomes the limitations of traditional bulk phase analysis in identifying the superposition of multiple phases of diagenetic fluids, and provides a high-precision geochemical evidence chain for the reconstruction of carbonate rock diagenetic sequences.

[0031] Example 7: Based on Example 6, the process of generating a two-dimensional content distribution map of each element in the plane of the carbonate rock sample in step S303 of this embodiment of the invention specifically includes the following steps: Step S3031: Within the selected representative area, the laser beam spot is moved point by point using line scanning or raster scanning. At each scanning point, the mass spectrometry signal intensity values ​​of magnesium, iron, manganese, strontium, barium, uranium, thorium, and all rare earth elements are recorded simultaneously. The spatial coordinates of each scanning point are also recorded. The signal intensity values ​​of all scanning points are arranged in the scanning order to form the original signal intensity distribution data, preserving the spatial distribution information of element content in different alteration levels. Step S3032: Divide the original signal intensity value of each element collected at each scanning point by the internal standard signal intensity value of calcium at the same point to obtain the signal intensity ratio of each element relative to calcium; at the same time, measure the signal intensity of the same element in the glass standard material to establish an external standard calibration curve; substitute the relative signal intensity ratio of each scanning point into the external standard calibration curve to calculate the semi-quantitative content value of each element at the scanning point, thus completing the preliminary conversion from original signal intensity to element content; Step S3033: Rearrange the semi-quantitative content values ​​of all scanning points according to the original spatial coordinates. After background subtraction and instrument drift correction, generate a two-dimensional content distribution map of each element in the carbonate rock sample plane. Among them, the content distribution of manganese, iron, and strontium, which are sensitive elements of diagenetic alteration, directly reflects the difference in element migration between weak and strong alteration areas. This is used to register with cathodoluminescence images and identify the degree of diagenetic alteration.

[0032] The mass spectrometry signal intensity value refers to the ion count rate of specific elements, such as magnesium, iron, manganese, and strontium, detected by the inductively coupled plasma mass spectrometer at each scanning point. The intensity value directly reflects the relative level of element content at that point. When determining the degree of diagenetic alteration, weakly altered areas often maintain lower manganese signals and higher strontium signals, while strongly altered areas show significantly increased manganese signals and decreased strontium signals. The change in signal intensity value quantitatively records the intensity of alteration fluid's modification of the original carbonate rock. The spatial coordinate position refers to the two-dimensional coordinates (X, Y) of each laser scanning point on the thin section plane, automatically recorded by the scanning system. This coordinate system maps each mass spectrometry signal intensity value to a specific microscopic region on the sample. When determining the degree of diagenetic alteration, the spatial coordinates allow for precise localization of element content differences between regions of different alteration levels, such as the bright red weakly altered area and the yellow-green strongly altered area, avoiding information averaging caused by mixed sampling. Spatial distribution information refers to the two-dimensional distribution pattern formed by arranging the elemental signal intensity values ​​of all scanning points according to their spatial coordinates. This information describes the enrichment or depletion locations of various elements on the plane of the carbonate rock sample. When identifying the degree of diagenetic alteration, the enrichment areas of elements such as manganese and iron are spatially highly consistent with the strong alteration areas, yellow-green or brownish-dark areas in the cathodoluminescence image, while the enrichment areas of strontium correspond to the weak alteration areas or bright red areas. The spatial distribution information provides intuitive geochemical evidence for alteration zoning. The internal standard signal intensity value of calcium refers to the mass spectrometry signal intensity of calcium collected synchronously at each scanning point, serving as the main component of the carbonate rock. Since the calcium content in carbonate rocks is relatively stable, using it as an internal standard can correct signal drift caused by laser energy fluctuations, sample thickness differences, etc. When identifying the degree of diagenetic alteration, dividing the signals of other elements by the calcium signal eliminates interference from non-alteration factors, making the manganese / calcium and iron / calcium ratios between different scanning points comparable, thus accurately reflecting the relative enrichment or depletion of elements during the alteration process. Glass reference materials refer to NIST SRM 610 / 612 standard glass slides with known accurate content of each element. In LA-ICP-MS analysis, the signal intensity of the glass reference materials is measured under the same conditions to establish the correspondence between signal intensity and actual content. When identifying the degree of diagenetic alteration, glass reference materials provide an absolute quantitative benchmark, allowing cross-sample comparison of the content of alteration-sensitive elements such as manganese, iron, and strontium in different samples and batches, laying the foundation for establishing a unified standard for alteration degree grading. External standard calibration curves refer to the content-intensity relationship curves established through linear regression, with the known content of each element in the glass reference material as the x-axis and the measured signal intensity as the y-axis. Substituting the signal intensity of unknown samples into this curve allows for the calculation of semi-quantitative content of elements. When identifying the degree of diagenetic alteration, external standard calibration curves convert the original signal intensity into content values ​​with geochemical significance, such as manganese content ranging from 50 ppm to 500 ppm, transforming the elemental differences between weak and strong alteration from high and low signal levels into absolute concentration differences, improving the objectivity and repeatability of the identification.Semi-quantitative content values ​​refer to the approximate concentrations of each element at the scanning point after internal standard correction and external standard curve conversion, typically expressed in ppm or μg / g. While these values ​​do not achieve complete quantitative precision, they are sufficient to reliably distinguish the order-of-magnitude differences in element content between different alteration grades. When assessing the degree of diagenetic alteration, semi-quantitative content values ​​can be directly used to set thresholds: for example, manganese content <100ppm indicates weak alteration, 100-300ppm indicates moderate alteration, and >300ppm indicates strong alteration, thus achieving a leap from qualitative observation to quantitative classification. Element migration differences refer to the spatial distribution changes caused by the influx or extrusion of chemical components, particularly manganese, iron, strontium, and barium, from the original carbonate rocks during diagenetic alteration. When determining the degree of diagenetic alteration, weakly altered areas retain original marine characteristics or are low in manganese and high in strontium, while strongly altered areas show the superposition of exogenous fluids or are high in manganese, low in strontium, and locally enriched in iron. By comparing the spatial differentiation patterns of manganese, iron, and strontium in the two-dimensional content distribution map with the luminescence color partitioning of the cathodoluminescence image, the action path and alteration intensity of the alteration fluid can be traced, providing elemental geochemical evidence for the comprehensive identification of the degree of diagenetic alteration.

[0033] In the above embodiments, this embodiment uses line scanning or raster scanning to acquire the elemental distribution data of the entire sample surface. By simultaneously recording spatial coordinates and mass spectrometry signal intensity, the original spatial distribution information of elemental content in different alteration regions is preserved, providing basic data support for establishing a two-dimensional content distribution map and ensuring that the element migration trajectory required for alteration degree identification is spatially traceable. Through dual data processing of calcium element internal standard correction and external standard material calibration, the original signal intensity is converted into a semi-quantitative content value, effectively eliminating instrument fluctuations and matrix effect interference, making the content differences of alteration-sensitive elements such as manganese, iron, and strontium comparable between weak and strong alteration areas, and establishing a standardized data foundation for quantitative identification of alteration degree. Through spatial coordinate reconstruction and background subtraction processing, the semi-quantitative data is converted into a two-dimensional content distribution map. The distribution characteristics of manganese, iron, and strontium directly reflect the element migration law in the alteration process. The registration of their spatial differentiation patterns with cathodoluminescence image features can establish a correspondence between elemental geochemical behavior and alteration degree, providing a multi-dimensional evidence chain for the objective identification of carbonate rock diagenetic alteration degree. A quantitative characterization of the migration of microscopic elements to macroscopic alteration zones was achieved.

[0034] Example 8: As Figure 5 As shown, based on Example 1, the process of three-level registration between the cathodoluminescence image and the two-dimensional content distribution map of each element in step S400 of this embodiment of the invention specifically includes the following steps: Step S401: Before acquiring cathodoluminescence images and elemental surface scanning, mark at least three reference points on the thin slice and record their coordinates under the microscope to complete the first-level microscopic positioning. Among them, reference points, such as marked points at the corners of thin sections or distinctive mineral grains in the sample; Step S402: Identify common mineral structure feature points in the cathodoluminescence image and the two-dimensional content distribution map of each element, establish mineral structure feature point pairs and calculate the initial spatial transformation relationship to complete the secondary feature point matching; Among them, mineral structural features include mineral boundaries, cementation zones, and the edges of dissolution pores; Step S403: Based on the initial spatial transformation relationship, by maximizing the consistency of the gray-level distribution of the two images or minimizing the sum of squares of the gray-level differences of each pixel, pixel-level fine registration is performed on the two images, so that the cathodic emission image and the two-dimensional content distribution map of each element are aligned in the same spatial coordinate system, with a registration accuracy better than one pixel, and an image pair for identifying the degree of diagenetic alteration of carbonate rocks is obtained.

[0035] In the above embodiments, the primary microscopic positioning of the reference point ensures that the cathodoluminescence images and elemental surface scan data acquired by different imaging devices have a unified spatial reference system, eliminating systematic errors introduced by mechanical displacement between devices and sample stage movement; the use of physical marker points combined with microscope coordinate recording achieves initial spatial correlation of cross-modal imaging data. Secondary matching of mineral structure feature points uses microscopic morphological features commonly found in carbonate rocks, such as mineral boundaries and cement zoning, as registration markers to overcome the image contrast inversion problem caused by differences in signal sources between different imaging technologies; feature point pairs established based on mineralogical features can accurately derive affine transformation parameters between images, providing an initial transformation matrix for subsequent pixel-level registration. Pixel-level fine registration, based on a grayscale distribution optimization algorithm, eliminates the sub-pixel-level deviations remaining in the first two stages and corrects local deformations through nonlinear transformation; it ensures that cathodoluminescence information and elemental distribution data correspond one-to-one in space, providing an accurate co-location basis for the coupled analysis of the diagenetic fluid domain and elemental migration path in carbonate rocks; the final acquired images can accurately reflect the changes in elemental diffusion gradients at mineral alteration boundaries, the elemental zoning characteristics of cement zoning, and other microscopic evidence of diagenetic alteration.

[0036] Example 9: Based on Example 8, the pixel-level fine registration process for two images in step S403 of this embodiment of the invention specifically includes the following steps: Step S4031: Based on the initial spatial transformation relationship, place the cathodic emission image and the two-dimensional content distribution map of each element in the same spatial coordinate system, and perform coordinate transformation on the two-dimensional content distribution map of each element to initially align it with the cathodic emission image. Step S4032: Calculate the gray level difference of each pair of pixels in the overlapping area of ​​the two images, sum the squares of the gray level differences of all pixels to obtain the overall matching error; or calculate the probability density function of the gray level distribution of the two images and their joint distribution to obtain the mutual information and quantify the alignment degree of the two images. Step S4033: Iteratively adjust the spatial transformation parameters to minimize the sum of squared grayscale differences or maximize the mutual information until the transformation parameters converge; output the final transformed two-dimensional content distribution map of each element, which is precisely aligned with the cathodoluminescence image at the pixel level, with a registration accuracy better than one pixel, to obtain an image pair for identifying the degree of diagenetic alteration of carbonate rocks.

[0037] In the above embodiments, Example 10: Based on Example 1, the following parameters are calculated for each pixel using the registered cathodic emission image data and elemental surface scan data provided in this embodiment of the invention: The cathode luminescence intensity parameter is CLintensity. Cathode emission color parameters, R / G ratio, B / G ratio, etc.; Elemental content parameters: Fe, Mn, Sr, Ba, U, Th content (μg / g); Characteristic element ratios: Mn / Sr ratio, Fe / Sr ratio, U / Th ratio, total rare earth elements ∑REE; Alteration-sensitive element combination index: ASCI = (Fe + Mn) / (Ca + Mg); Calculate the Comprehensive Alteration Index (CAI) using the following formula: ; ; In the formula, the norm of each index represents the normalization process, which is the normalization process by dividing the measured value of each index by the standard value of that index in the unaltered reference region. For the weighting coefficients, satisfying The weighting coefficients are determined by principal component analysis or analytic hierarchy process; the larger the CAI value, the stronger the degree of diagenetic alteration.

[0038] In the above embodiments, the cathodoluminescence intensity and color parameters of this embodiment can effectively identify mineral phase transition regions in carbonate rocks that have been altered by diagenetic fluids; a decrease in CL intensity usually corresponds to calcite recrystallization or dolomitization, while changes in R / G and B / G ratios reflect the doping effect of trace elements and can indicate changes in redox conditions of the diagenetic environment. Elemental content parameters Fe, Mn, Sr, Ba, U, Th, and characteristic element ratios Mn / Sr, Fe / Sr, and U / Th can quantitatively characterize the geochemical characteristics of different diagenetic fluids; Fe and Mn enrichment indicates the action of reducing fluids, Sr depletion reflects the dissolution of original carbonate minerals, and changes in the U / Th ratio are related to the degree of oxidation of the diagenetic environment; the total rare earth element (∑REE) can be used to determine the fluid source and migration path. The alteration-sensitive element combination index (ASCI) quantitatively evaluates the degree of substitution of divalent metal elements during diagenesis using (Fe+Mn) / (Ca+Mg). The ratio shows a significant increasing trend during alteration processes such as dolomitization and ferrodotization, which can effectively distinguish the original sedimentary components from secondary rock minerals.

[0039] In summary, the Comprehensive Alteration Index (CAI) of this embodiment overcomes the limitations of a single index by weighted fusion of multi-source geochemical and optical features; normalization eliminates dimensional differences among parameters, and the weighting coefficients are determined by principal component analysis or hierarchical analysis to ensure that the parameters most sensitive to diagenetic alteration of carbonate rocks receive a higher contribution; finally, the CAI value can quantitatively characterize the alteration intensity of a single pixel and reveal the dominant migration channels of diagenetic fluids and the location of alteration fronts based on spatial distribution patterns; thus providing high-resolution quantitative evidence for carbonate reservoir quality evaluation and diagenetic history reconstruction.

[0040] Example 11: Based on Example 1, this embodiment of the invention classifies the degree of diagenetic alteration of carbonate rock samples into the following levels according to the Comprehensive Alteration Index (CAI): Weak alteration: CAI < 1.5, indicating that the sample retains relatively original sedimentary texture and geochemical characteristics, and the degree of diagenetic alteration is relatively weak; Moderate alteration: 1.5≤CAI<2.5, indicating that the sample has undergone moderate diagenetic alteration, with some original fabric destroyed and elements redistributed to a moderate degree; Strong alteration: CAI≥2.5 indicates that the sample has undergone strong diagenetic alteration, the original sedimentary fabric has been severely modified, and elements have undergone significant migration and redistribution.

[0041] In the above embodiments, the CAI threshold range setting is based on a comprehensive alteration index calculated using multi-parameter weighting, converting continuous variables into discrete alteration intensity levels. 1.5 serves as the upper limit for weak alteration, reflecting that the original sedimentary fabric is basically preserved and elements have not undergone significant migration. 2.5 serves as the lower limit for strong alteration, corresponding to significant alteration of mineral phase transformation and element redistribution. The range division eliminates subjective judgment biases based on a single indicator through the quantitative integration of geochemical and optical characteristics. A weak alteration level indicates that diagenetic fluid activity has not significantly altered the original sedimentary characteristics, the cathodoluminescence structure is well preserved, and the element distribution pattern is consistent with the original characteristics of the sedimentary environment. A moderate alteration level indicates that diagenetic fluid activity has triggered local recrystallization and element diffusion rebalancing; cathodoluminescence shows partial destruction of zonal structures, and the ratios of sensitive elements deviate but do not reach extreme values. Strong alteration grades correspond to intense modification by diagenetic fluids, with large-scale phase transitions in the original mineral facies, complete reorganization of cathodoluminescent fabrics, and obvious secondary enrichment or depletion characteristics in element distribution patterns. The classification system can effectively correlate diagenetic alteration intensity with reservoir property changes, providing an objective quantitative benchmark for evaluating the quality of carbonate reservoirs. The classification results can directly guide the prediction of favorable reservoir zones and the reconstruction of diagenetic evolution sequences.

[0042] Example 12: Based on Example 1, this embodiment of the invention outputs a diagenetic alteration degree evaluation report containing the following content: Cathodoluminescence images and cluster analysis results (distribution map of mineral regions with different luminescence characteristics); Two-dimensional distribution map of key elements (Fe, Mn, Sr, Mn / Sr, etc.); Spatial distribution map of the comprehensive alteration index (CAI); Overall grading conclusions regarding the degree of alteration of the sample; Optional: Establish a chart relating alteration degree to reservoir properties (porosity, permeability).

[0043] In the above embodiments, the cathodoluminescence images and cluster analysis results of this embodiment intuitively display the distribution of mineral regions with different luminescence characteristics, effectively identifying the spatial configuration relationship between primary sedimentary fabrics and secondary rock minerals; the maps can locate the boundaries of cement generations, dissolution cavities, and recrystallization regions in carbonate rocks. Two-dimensional distribution maps of key elements reveal the spatial differentiation patterns of sensitive indicators such as Fe, Mn, Sr, and the Mn / Sr ratio, quantitatively characterizing the element migration paths caused by diagenetic fluid activity; Mn-enriched areas indicate the range of reducing fluid activity, Sr-depleted zones reflect the dissolution intensity of primary carbonate minerals, and areas with abnormally high Mn / Sr values ​​mark the position of diagenetic alteration fronts. The spatial distribution map of the comprehensive alteration index (CAI) quantitatively characterizes the alteration intensity at different locations of the sample with pixel-level precision by weighted fusion of optical and geochemical parameters; high CAI value regions have a strict spatial correspondence with cathodoluminescence structural destruction areas and elemental anomaly areas, accurately delineating advantageous channels for diagenetic alteration. The overall alteration severity grading conclusions are based on the CAI threshold classification standard, summarizing multi-parameter quantitative analysis at the microscale into a clear alteration intensity level evaluation. The conclusions support the analysis of reservoir heterogeneity genesis, distinguishing between primary sedimentary control and diagenetic alteration-dominated reservoir space evolution patterns. A correlation chart between alteration severity and reservoir properties establishes a quantitative response relationship between diagenetic alteration intensity and porosity and permeability, revealing the property variation patterns of secondary porosity development zones or tight cementation zones corresponding to strongly altered areas. This correlation provides data support for predicting the distribution of high-quality reservoirs and the division of diagenetic facies zones.

[0044] In summary, the evaluation report of this embodiment achieves cross-scale integration of microscopic alteration characteristics and macroscopic reservoir evaluation, forming a complete technical chain from mineral fabric identification and element migration analysis to reservoir performance prediction, providing a scientific basis for carbonate oil and gas exploration and development decisions.

[0045] Example 13: As Figure 6 As shown, based on Examples 1-12, the device for determining the degree of diagenetic alteration of carbonate rocks provided in this embodiment of the invention includes: Cathodoluminescence imaging module 1 includes a cathodoluminescence instrument and an image acquisition unit, which is used to irradiate carbonate rock thin section samples with cathodoluminescence under standard working conditions and acquire high-resolution cathodoluminescence images. The laser elemental surface scanning module 2 includes a laser ablation system and an inductively coupled plasma mass spectrometer (LA-ICP-MS), which is used to perform laser surface scanning in a selected area and simultaneously acquire two-dimensional distribution data of elements such as Mg, Fe, Mn, Sr, Ba, U, Th and rare earth element REE. Image registration module 3 is electrically connected to the cathodoluminescence imaging module and the laser element surface scanning module. It is used to spatially register the cathodoluminescence image with the two-dimensional content distribution map of each element, so as to realize the dual-modal data alignment of the same region and the same pixel. The data processing and fusion module 4 includes an image processing unit and a data fusion unit, which are used to perform RGB color space decomposition and cluster analysis on the cathodic emission image to extract emission feature parameters; perform spatial interpolation and image processing on the element surface scan data to generate a two-dimensional element distribution map; and fuse the cathodic emission feature parameters and element content data in the registered spatial coordinates to construct a multi-dimensional comprehensive alteration index. Evaluation output module 5 is used to classify and identify the degree of diagenetic alteration of carbonate rock samples based on the comprehensive alteration index and output an alteration degree evaluation report.

[0046] In this embodiment, the principle reference Figure 9 and Figure 10 .

[0047] Specific structural design and parameters of the device 1. Cathode-emitting imaging module The cathodoluminescence imaging module includes a cathodoluminescence analyzer and an image acquisition unit.

[0048] Cathodoluminescence analyzer parameters: Model: CL8200 MK5-2 or equivalent; Electron gun operating voltage: 15.2kV-15.6kV, adjustable; Electron gun operating current: 220μA-230μA, adjustable; Sample chamber vacuum: 0.003mbar; Cold cathode electron source, no need for heated filament; Image acquisition unit parameters: Camera: High-resolution CCD or CMOS digital camera; Pixels: ≥5 megapixels (2592×1944); Exposure time: 4ms (adjustable); Image format: RGB 24-bit color image, saved as TIFF or JPEG format. Working conditions: Sample requirements: 0.05mm thick sheet, surface polished to 10000 mesh; working distance: 15-20mm; scanning method: raster scanning. 2. Laser elemental surface scanning module The laser elemental surface scanning module includes a laser ablation system and an inductively coupled plasma mass spectrometer (LA-ICP-MS).

[0049] Laser ablation system parameters: Laser type: 193nm ArF excimer laser; Laser wavelength: 193nm; Beam diameter: 4~160μm continuously adjustable, optical resolution 1μm; Scanning speed: 4~10μm / s (area scan), adjustable as needed; Laser frequency: 6~10Hz; Energy density: 6~10J / cm² 2 Stability is better than 2%rms; Abrasion method: raster scanning (line scanning line-by-line coverage); ICP-MS parameters: Instrument Model: Agilent 7900 or equivalent quadrupole ICP-MS; RF Power: 1200~1500W; Cooling Gas Flow Rate: 13~15L / min (Ar); Auxiliary Gas Flow Rate: 0.8~1.2L / min (Ar); Carrier Gas Flow Rate: 0.8~1.0L / min (He); Data Acquisition Mode: Time-Resolved Mode (TRA); Dwell Time: 10-50ms per mass number; Number of Acquired Masses (Isotopes): 23 Na、 24 Mg 27 Al、 29 Si、 39 K, 43 Ca, 55 Mn, 57 Fe、 88 Sr、 137 Ba、 238 U、 232 Th, and rare earth element isotopes ( 139 La、 140 Ce、 141 Pr、 146 Nd, 147 Sm、 151 Eu、 158 Gd, 159 Tb, 163 Dy、 165 Ho、 166 Er、 169 Tm、 172 Yb、 175 Lu); Quantitative correction: External standard: NIST SRM 610 / 612 glass standard; Internal standard element: 43 Ca (major element in carbonate matrix); Data processing software: Iolite v4 or equivalent software; 3. Image registration module The image registration module includes an industrial computer, an image acquisition card, and registration algorithm software.

[0050] Hardware configuration: Industrial PC: Intel Core i7 processor, 32GB RAM, 1TB SSD; Image acquisition card: Supports RGB 24-bit image acquisition; Monitor: 27-inch 4K professional monitor (for image registration and display). Registration algorithm: Feature point matching: SIFT (Scale Invariant Feature Transform) or SURF algorithm; Initial transformation: Affine transformation matrix calculation; Fine registration: Mutual information maximization or least squares matching algorithm; Registration accuracy: better than 1 pixel; 4. Data Processing and Fusion Module The data processing and fusion module includes an image processing unit and a data fusion unit.

[0051] Image processing unit functions include: RGB color space decomposition and channel separation; K-means clustering analysis (the number of clusters K is determined by the elbow method, usually set to 3-8); pixel proportion statistics and RGB brightness mean calculation; image filtering and enhancement (median filtering for noise reduction, contrast enhancement). Data fusion unit functions: spatial interpolation of elemental surface scan data (Kriging or inverse distance weighting); pixel-level overlay of CL image and two-dimensional content distribution map of each element; pixel-by-pixel calculation of the comprehensive alteration index (CAI); and graded coloring of alteration degree. 5. Evaluation Output Module The evaluation output module includes a results visualization unit and a report generation unit.

[0052] Results visualization: Original CL image and cluster analysis results; two-dimensional distribution heatmap of key elements; spatial distribution map of CAI (color scale map); gradation map of alteration degree (color block map). Report generation: Format: PDF / Excel / Word; Content: Method parameters, analysis data, results charts, hierarchical conclusions, and explanations.

[0053] In the above embodiments, the cathodoluminescence imaging module of this embodiment identifies the microstructural features of calcite and dolomite, such as the original growth zoning, cementation generations, and dissolution pores, through cathodoluminescence images acquired under standard operating conditions; the difference in luminescence intensity reflects the presence of Mn in the diagenetic fluid. 2＋ Activator and Fe 2＋The relative content changes of quenchers provide direct evidence of early diagenetic environments; high-resolution imaging can detect secondary enlargement margins and microfractures, aiding in the assessment of pressure solution-recrystallization intensity. The laser elemental surface scanning module uses LA-ICP-MS surface scanning data to quantitatively characterize the spatial variation of the Mg / Ca ratio, identifying the heterogeneous distribution of dolomitization; the covariance relationship of Fe-Mn-Sr elemental assemblages distinguishes between atmospheric freshwater diagenetic environments and burial diagenetic environments, with Sr depletion and Mn enrichment indicating atmospheric freshwater influence, while Sr preservation and Fe enrichment reflect burial conditions; REE distribution patterns, U-Th content, Ce anomalies, Y / Ho ratios, and other characteristics can trace the redox state and origin of diagenetic fluids; anomalous Ba enrichment zones can indicate later hydrothermal alteration events. The image registration module uses a feature-point-based elastic registration algorithm to achieve high-precision spatial alignment, ensuring a strict correspondence between the cathodoluminescence ring boundary and abrupt elemental content change zones, overcoming the limitations of insufficient representativeness in traditional point analysis sampling, and accurately establishing a quantitative relationship between luminescence intensity and elemental content, such as Mn. 2＋ The correspondence between critical content and cathodoluminescence activation threshold was investigated. The data processing and fusion module extracted CL spectral parameters through RGB spatial decomposition and performed multivariate regression analysis with LA-ICP-MS elemental data to construct a nonlinear mapping model between the Fe / (Fe+Mn) ratio and red light emission intensity. A spatial interpolation algorithm transformed discrete point data into a continuous distribution field, generating Mg / (Ca+Mg) contour maps to quantify the diffusion gradient of the dolomite alteration front. A comprehensive alteration index was used to integrate structural modification degree and chemical modification amount, accurately calibrating the alteration intensity from the microscopic to the mesoscopic scale. The evaluation output module, based on an alteration degree classifier built using machine learning, outputs a five-level alteration classification based on multiple indicators such as calcite cathodoluminescence intensity variance, dolomite order index, and ΣREE / Sr ratio, including no alteration, slight alteration, moderate alteration, strong alteration, and complete alteration. The report automatically annotates hydrothermal alteration markers and atmospheric freshwater interaction indicators to ensure the accuracy of the genetic analysis.

[0054] In summary, this embodiment, through the dual constraints of microstructure and geochemical data, elevates traditional qualitative description to quantitative evaluation, significantly improving the identification accuracy of multi-stage and superimposed diagenetic alteration, and has unique advantages, especially in distinguishing complex diagenetic sequences such as burial-dissolution-cementation cycles and tectonic-hydrothermal superimposed alteration.

[0055] Figure 7 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0056] The electronic device may include a central processing unit / microprocessor / main control chip 6; and a storage medium 7 coupled to the central processing unit / microprocessor / main control chip 6 and storing computer-executable instructions therein for performing the steps of various methods of embodiments of the present invention when executed by the processor.

[0057] The central processing unit / microprocessor / main control chip 6 may include, but is not limited to, one or more processors or microprocessors.

[0058] Storage medium 7 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0059] In addition, the electronic device may include (but is not limited to) a data bus 8, an input / output bus / external bus / device bus 9, a display 10, and input / output devices 11 (e.g., keyboard, mouse, speaker, etc.).

[0060] The central processing unit / microprocessor / main control chip 6 can communicate with external devices (10, 11, etc.) via wired or wireless networks (not shown) through the input / output bus / external bus / device bus 8.

[0061] The storage medium 7 may also store at least one computer-executable instruction for performing the steps of various functions and / or methods in the embodiments described herein when run by the central processing unit / microprocessor / main control chip 6.

[0062] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0063] Figure 8 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0064] like Figure 8As shown, instructions, such as computer-readable instructions 12, are stored on the non-transitory computer-readable storage medium 13. When the computer-readable instructions 12 are executed by a processor, the various methods described above can be performed. The non-transitory computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 13 can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions 12 stored on the non-transitory computer-readable storage medium 13, the various methods described above can be performed.

[0065] The application effects of the present invention will be further described below in conjunction with specific applications.

[0066] Specific application example 1: Ordovician carbonate rocks in a well in the Tarim Basin: This embodiment uses an Ordovician carbonate reservoir sample from a well in the Tarim Basin as an example to illustrate the specific application of the method of the present invention.

[0067] 1. Overview of the study area and sample selection The Ordovician carbonate rocks in the Tarim Basin are important oil and gas reservoirs within the basin, having undergone multiple phases of tectonic-hydrothermal activity and intense diagenetic alteration. Samples from the study area, originating from the Yijianfang Formation of the Ordovician system in a well, consist of sparry sandstone and micritic limestone, buried at a depth of approximately 5500 m. These samples have experienced multiple diagenetic events, including atmospheric water dissolution during the early diagenetic period, burial cementation during the middle diagenetic period, and late-stage hydrothermal alteration.

[0068] Representative core samples were selected, cut into 0.05mm thick CL-specific thin slices, and the surface was polished to 10,000 mesh.

[0069] 2. Cathodoluminescence image acquisition and quantitative analysis The thin film was placed in a cathodoluminescence analyzer, and CL images were acquired under the following working conditions: voltage 15.5kV, current 225μA, vacuum degree 0.003mbar, exposure time 4ms, and image resolution 2592×1944 pixels.

[0070] CL image features: The sample exhibits a distinct cathodic emission ring structure, and three regions with different emission characteristics can be identified: Region A (dark red glow): represents early cementation, with low glow intensity; Region B (orange-red luminescence): Represents mid-stage buried cement, with moderate luminescence intensity; Region C (bright yellow luminescence): Represents a late-stage hydrothermal alteration region with high luminescence intensity. RGB color decomposition and cluster analysis: Import the CL image into the image processing system and perform RGB three-channel separation.

[0071] Table 1 shows the statistical results:

[0072] The K-means clustering algorithm (K=3) was used to classify the pixels of the CL image. The clustering results were highly consistent with the three regions that can be identified by the naked eye, and the classification accuracy was >95%.

[0073] 3. LA-ICP-MS area scan data acquisition LA-ICP-MS area scanning was performed on three representative regions (one 200μm×200μm scanning area from each region) identified by CL image clustering analysis.

[0074] Area scanning parameters: Beam spot diameter: 10 μm; Scanning speed: 6 μm / s; Laser frequency: 8 Hz; Energy density: 8 J / cm² 2 Scan range: 200μm × 200μm (per region); Scanning method: raster scan (X-direction line scan, Y-direction step 10μm); Collected elements include: Mg, Fe, Mn, Sr, Ba, U, Th and 14 rare earth elements; Quantitative correction: using NIST SRM 612 as the external standard, with... 43 Using Ca as an internal standard, the signal intensity of each element is quantitatively converted to generate a two-dimensional content distribution map of each element.

[0075] Table 2. Surface scan results (representative data for the region):

[0076] The results of the area scan show that: Region A (dark red glow) has Mn / Sr = 1.73 and Fe / Sr = 6.76, belonging to a weak alteration region; Region B (orange-red glow) has Mn / Sr = 9.26 and Fe / Sr = 40.53, belonging to the medium alteration region; Region C (bright yellow glow) has Mn / Sr=51.19, Fe / Sr=212.38, and U / Th=1.85, belonging to a strongly altered region.

[0077] 4. Image registration and fusion The CL image was then registered with the two-dimensional content distribution map of each element at three levels. First-level registration (microscopic positioning): Set three gold particle reference points at the corner of the slice and record their coordinates to ensure that CL image acquisition and LA-ICP-MS surface scanning are performed in the same coordinate system.

[0078] Secondary registration (feature point matching): Identify 5 common feature points (edges of dissolution pores) in the CL image and Fe element surface scan, establish feature point pairs, and calculate the affine transformation matrix.

[0079] Three-level registration (pixel-level fine registration): Based on the initial transformation matrix, a mutual information maximization algorithm is used for fine registration, achieving a registration accuracy of 0.8 pixels (better than 1 pixel), realizing pixel-level spatial alignment between the CL image and the surface scan images of elements such as Fe, Mn, and Sr.

[0080] After registration, a ternary correlation database of "CL luminescence feature ↔ element content ↔ spatial location" was established at the pixel level, containing approximately 10... 6 Data points.

[0081] 5. Calculation of the Comprehensive Alteration Index (CAI) Using unaltered limestone (standard values ​​for the unaltered zone in the study area) as a reference, the indicators were normalized. Reference values: CL_intensity_ref=0.20, Mn / Sr_ref=0.19, Fe / Sr_ref=0.95, U / Th_ref=0.25, ASCI_ref=0.08.

[0082] Principal component analysis was used to determine the weight coefficients. Principal component analysis was performed on five regional samples (including the unaltered region). The contribution rate of the first principal component was 78.5%. The loading coefficients of each index were normalized to obtain the weights: w1=0.20, w2=0.25, w3=0.25, w4=0.15, w5=0.15.

[0083] Overall CAI calculation for the sample (weighted average of the three regions): Region A (35.2%): CAI_A = 0.20 × 1.60 + 0.25 × 9.11 + 0.25 × 7.12 + 0.15 × 1.28 + 0.15 × 4.50 = 4.28 Region B (42.8%): CAI_B = 0.20 × 2.90 + 0.25 × 48.74 + 0.25 × 42.66 + 0.15 × 2.72 + 0.15 × 14.75 = 24.23 Region C (22.0%): CAI_C = 0.20 × 4.75 + 0.25 × 269.42 + 0.25 × 223.56 + 0.15 × 7.40 + 0.15 × 69.75 = 127.85 The overall weighted average CAI of the sample is calculated as follows: CAI = 0.352 × 4.28 + 0.428 × 24.23 + 0.220 × 127.85 = 39.72 6. Identification of the degree of diagenetic alteration The degree of alteration of the samples was graded based on the CAI value: CAI=39.72≥2.5, judged as "strong alteration" level.

[0084] Further, the three regions are further divided into different areas for identification: Region A: CAI = 4.28 (>2.5), strong alteration Region B: CAI = 24.23 (>2.5), strong alteration Region C: CAI = 127.85 (>2.5), strong alteration This indicates that the sample as a whole underwent intense diagenetic alteration, but the degree of alteration showed obvious spatial heterogeneity—the degree of alteration in region C (bright yellow luminescent area) was much higher than that in regions A and B, reflecting the channel-like alteration characteristics of late-stage hydrothermal fluids.

[0085] 7. Correlation Analysis between Alteration Degree and Reservoir Properties The alteration degree identification results of this invention are correlated with the existing reservoir physical property data (porosity, permeability) in the study area:

[0086] The results show that strongly altered samples have higher porosity and permeability, indicating that diagenetic alteration (especially late-stage dissolution and hydrothermal alteration) has a significant improving effect on reservoir properties. The correlation coefficient between the comprehensive alteration index (CAI) of this invention and reservoir porosity is 0.82, and the correlation coefficient with permeability is 0.76, showing a good positive correlation.

[0087] 8. Conclusion This embodiment successfully applied the apparatus and method of the present invention to quantitatively identify the degree of diagenetic alteration in Ordovician carbonate rock samples from the Tarim Basin: Quantitative analysis of CL images identified three mineral regions with different luminescent characteristics; LA-ICP-MS surface scanning revealed the two-dimensional distribution patterns of alteration-sensitive elements such as Fe, Mn, and Sr; Image registration achieves pixel-level spatial correlation between CL features and element content; The overall alteration index (CAI) is 39.72, indicating strong alteration. The degree of alteration showed a good positive correlation with reservoir properties, verifying the effectiveness of the method of the present invention.

[0088] Specific application example 2: Parameter adaptation for different carbonate rock types 1. Limestone sample Thin section thickness: 0.05 mm; CL operating voltage: 15.2 kV, current: 220 μA; LA-ICP-MS surface scan spot size: 10-20 μm; Key elements of interest: Fe, Mn, Sr, Mg (Fe / Mn and Mn / Sr ratios are sensitive indicators of limestone alteration). 2. Dolomite sample Thin film thickness: 0.05mm; CL operating voltage: 15.5kV, current: 225μA (the luminescence intensity of dolomite CL is usually lower than that of calcite, so the parameters need to be appropriately increased); LA-ICP-MS surface scanning spot size: 15-25μm; Key elements to watch: Fe, Mn, Sr, Mg, Ca / Mg ratio (changes in Mg content indicate the degree of dolomitization). 3. Hydrothermal altered carbonate rocks Thin film thickness: 0.05 mm; CL operating voltage: 15.6 kV, current: 230 μA (high luminescence intensity in hydrothermal alteration regions, overexposure must be avoided); LA-ICP-MS surface scan spot size: 5-10 μm (higher resolution to capture details of alteration veins); Key elements of interest: Fe, Mn, Ba, U, Th, REE (U / Th ratio and REE distribution pattern are characteristic fingerprints of hydrothermal fluids) 4. General Quality Control Requirements At least three parallel thin-slice samples should be prepared for each sample, with a relative deviation of key parameters ≤10%; the instrument should be standardized and calibrated using a standard luminescent material before CL image acquisition; sensitivity tuning should be performed before LA-ICP-MS area scanning to ensure oxide yield (CeO). ＋ / Ce ＋ )≤2%, double charge yield (Ce 2＋ / Ce ＋ The error margin should be ≤2%; after image registration, a visual inspection should be performed, and if the registration error exceeds 2 pixels, the image should be re-registered; when calculating the comprehensive alteration index (CAI), the reference value for unaltered images should be taken from samples of the same stratum, lithology, and clearly unaltered nature in the study area.

[0089] Figure 11 This is a diagram showing the K-means clustering analysis results in this embodiment of the invention, identifying mineral regions with different luminescent characteristics; Figure 12 This is a superimposed image of the CL image and the two-dimensional content distribution map of each element in an embodiment of the present invention. Figure 13 This is a spatial distribution map of the Comprehensive Alteration Index (CAI) and an alteration degree classification map in an embodiment of the present invention.

[0090] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0093] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0094] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the degree of diagenetic alteration of carbonate rocks, characterized in that, Includes the following steps: Cathodoluminescence images of thin section samples of carbonate rocks were acquired; The cathodoluminescence image was quantitatively analyzed to obtain the relative luminescence intensity index, and mineral regions with different luminescence characteristics were divided according to the index. Laser ablation inductively coupled plasma mass spectrometry was performed within the mineral region to obtain a two-dimensional content distribution map of each element. A three-level progressive registration is adopted, based on at least three reference points for microscopic positioning, and the spatial transformation relationship is calculated using the common mineral structure feature points between the cathodoluminescence image and the two-dimensional content distribution map of each element, so that the two can achieve pixel-level fine alignment. For the registered image, a multi-dimensional comprehensive alteration index based on cathodoluminescence parameters and elemental geochemical parameters is calculated pixel by pixel; Based on the value of the multidimensional comprehensive alteration index, the degree of diagenetic alteration of carbonate rock samples is classified into levels, and an evaluation report is generated.

2. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, Carbonate rock samples were cut, ground, polished, thin-sectioned, and collected using a cathodoluminescence analyzer to obtain high-resolution RGB format cathodoluminescence images. The cathodoluminescence images were decomposed into RGB channels, K-means clustering, pixel proportion and brightness mean were calculated, and relative luminescence intensity index was calculated to obtain the mineral region classification with different luminescence characteristics and their relative content, luminescence color and intensity parameters.

3. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, Based on the identified representative regions, laser and ICP-MS parameters were set, and signals of Mg, Fe, Mn, Sr, Ba, U, Th and rare earth elements were collected. Quantitative correction was performed using NISTSRM 610 / 612 as an external standard and Ca as an internal standard. After surface scanning with an inductively coupled plasma mass spectrometer, two-dimensional content distribution maps of each element were obtained.

4. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 3, characterized in that, in, Representative regions were identified by K-means clustering analysis as mineral regions with different cathodic emission characteristics.

5. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, The cathodoluminescence image and the two-dimensional content distribution map of each element are registered in three levels: primary microscopic positioning based on at least three reference points, secondary spatial relationship calculation based on mineral structural feature points, and tertiary pixel-level fine registration based on maximizing gray-level consistency or minimizing gray-level difference. This results in pixel-aligned image pairs in the same spatial coordinate system with a registration accuracy better than one pixel. For each pixel of the image pair, a multi-dimensional comprehensive alteration index is calculated.

6. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 5, characterized in that, The process of registering the cathodoluminescence image with the two-dimensional content distribution map of each element through three levels includes the following steps: Before acquiring cathodoluminescence images and elemental surface scanning images, at least three reference points are marked on the thin slide and their coordinates under the microscope are recorded to complete the first-level microscopic positioning. Common mineral structure feature points are identified in cathodoluminescence images and two-dimensional content distribution maps of various elements. Mineral structure feature point pairs are established and the initial spatial transformation relationship is calculated to complete the secondary feature point matching. Based on the initial spatial transformation relationship, pixel-level fine registration is performed on the two images by maximizing the consistency of gray-level distribution or minimizing the sum of squares of gray-level differences of each pixel. This enables the cathodoluminescence image and the two-dimensional content distribution map of each element to achieve pixel alignment in the same spatial coordinate system, with a registration accuracy better than one pixel, resulting in an image pair for identifying the degree of diagenetic alteration of carbonate rocks.

7. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, Calculate the Comprehensive Alteration Index (CAI) using the following formula: ； ； In the formula, the norm of each index represents the normalization process, which is the normalization process by dividing the measured value of each index by the standard value of that index in the unaltered reference region. For the weighting coefficients, satisfying The weighting coefficients are determined by principal component analysis or analytic hierarchy process; the larger the CAI value, the stronger the degree of diagenetic alteration.

8. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, Based on the Comprehensive Alteration Index (CAI), the degree of diagenetic alteration of carbonate rock samples is classified into the following levels: Weak alteration: CAI < 1.5, indicating that the sample retains relatively original sedimentary texture and geochemical characteristics; Moderate alteration. Alteration: 1.5≤CAI<2.5 indicates that the sample has undergone moderate diagenetic alteration; Strong alteration: CAI≥2.5 indicates that the sample has undergone strong diagenetic alteration.

9. The method for determining the degree of diagenetic alteration of carbonate rocks as described in claim 1, characterized in that, The output includes a diagenetic alteration degree evaluation report containing the following: cathodoluminescence images and cluster analysis results; two-dimensional distribution maps of key elements; spatial distribution map of the comprehensive alteration index (CAI); and overall alteration degree classification conclusions for the sample.

10. An apparatus for determining the degree of diagenetic alteration of carbonate rocks, used to implement the method according to any one of claims 1 to 9, characterized in that, include: Cathodoluminescence imaging module (1) is used to acquire high-resolution cathodoluminescence images of carbonate rock thin section samples; The laser element surface scanning module (2) is used to perform laser surface scanning in a selected area and simultaneously collect two-dimensional distribution data of Mg, Fe, Mn, Sr, Ba, U, Th and rare earth elements; The image registration module (3) is electrically connected to the cathode luminescence imaging module (1) and the laser element surface scanning module (2) and is used to spatially register the cathode luminescence image with the two-dimensional content distribution map of each element to achieve pixel-level alignment. The data processing and fusion module (4) is used to perform quantitative analysis on the cathodic emission image to extract emission characteristic parameters, process the element surface scan data to generate a two-dimensional element distribution map, and fuse the two to calculate a multi-dimensional comprehensive alteration index. The evaluation output module (5) is used to classify the degree of alteration according to the comprehensive alteration index and output an evaluation report.

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