Method for characterizing oil inclusion abundance based on laser confocal scanning technology

Abstract

This invention discloses a method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology in the field of geological exploration and oil and gas development. The specific steps are as follows: Step 1: Preview reservoir inclusion slices and calibrate the development field of oil-bearing inclusions; Step 2: Full-spectrum scanning to calibrate the field of view and determine the spectral characteristics of oil-bearing inclusions; Step 3: Laser confocal scanning of the field of view, reconstructing the three-dimensional structure of oil-bearing inclusions in each field of view and calculating the volume; Step 4: Applying the spectral characteristics of oil-bearing inclusions from Step 2 to classify the oil-bearing inclusion stages, and combining the oil-bearing inclusion volume from Step 3 to calculate the total volume of oil-bearing inclusions in different stages, using the volume of oil-bearing inclusions in different stages to characterize the abundance. This invention utilizes laser confocal microscopy, laser confocal scanning technology, and spectral scanning technology to distinguish the stages of oil-bearing inclusions based on their spectral characteristics and to represent the abundance by the volume of oil-bearing inclusions, thus achieving the characterization of the abundance of oil-bearing inclusions in different stages.

Description

Technical Field

[0001] This invention belongs to the field of geological exploration and oil and gas development, specifically a method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology. Background Technology

[0002] Oil inclusions are fossil records of hydrocarbon accumulation formed when crude oil is trapped within mineral lattice defects or fractures during migration and accumulation. They are widely distributed in present-day and ancient oil reservoirs. These inclusions provide researchers with crucial information about hydrocarbon generation, migration, and accumulation processes; therefore, accurate identification and quantitative characterization of oil-bearing inclusions are of great significance in oil and gas exploration and development.

[0003] Traditional methods for characterizing the abundance of oil inclusions primarily rely on conventional fluorescence microscopy and ultraviolet-excited fluorescence techniques. In this approach, researchers typically select multiple fields of view within a reservoir thin section, counting the total number of mineral grains and the number of grains containing oil inclusions in each field of view. Subsequently, the abundance of oil inclusions is approximated by calculating the ratio of oil inclusion grains to the total number of grains, i.e., the oil inclusion abundance index (GOI).

[0004] However, this method has significant limitations. First, the random selection of the field of view can lead to bias and instability in the results. Second, GOI can only reflect the total abundance of oil inclusions, but cannot distinguish and quantify oil inclusions from different phases. Therefore, this invention proposes a method for characterizing the abundance of oil inclusions based on laser confocal scanning technology to solve the above problems. Summary of the Invention

[0005] This invention proposes a method for characterizing the abundance of oil inclusions based on laser confocal scanning technology. By using a laser confocal microscope and applying laser confocal scanning and spectral scanning technologies, the abundance of oil inclusions is represented by distinguishing the phases based on their spectral characteristics and by using the volume of oil inclusions. This method enables the characterization of the abundance of oil inclusions at different phases.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows: a method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology, the specific steps of which are as follows:

[0007] Step 1: Preview reservoir inclusion slices and mark the development field of oil-bearing inclusions.

[0008] Step 2: Full-spectrum scanning to calibrate the field of view and determine the spectral characteristics of oil-bearing inclusions.

[0009] Step 3: Use laser confocal scanning to reconstruct the three-dimensional structure of oil inclusions in each field of view and calculate their volume.

[0010] Step 4: Apply the spectral characteristics of oil inclusions from Step 2 to classify the oil inclusion phases, and combine the oil inclusion volume from Step 3 to calculate the total volume of oil inclusions in different phases, using the volume of oil inclusions in different phases to characterize the abundance.

[0011] The above solution achieved the following beneficial effects:

[0012] 1. The method of this invention significantly improves the accuracy and precision of oil inclusion abundance characterization. Through laser confocal scanning technology, high-resolution and high-sensitivity image data can be acquired, enabling precise identification and localization of oil inclusions. Simultaneously, combining this with full-spectrum scanning technology allows for the determination of the spectral characteristics of oil inclusions, further improving the accuracy of abundance characterization.

[0013] 2. The method of this invention enables the reconstruction of the three-dimensional structure and volume calculation of oil-bearing inclusions. Through laser confocal scanning technology, the three-dimensional structural information of oil-bearing inclusions can be obtained, and their volume can then be calculated using mathematical algorithms. This breakthrough allows researchers to more intuitively understand the distribution and scale of oil-bearing inclusions in reservoirs, providing a more reliable geological basis for oil and gas exploration and development.

[0014] 3. The method of this invention, combining the spectral characteristics and volumetric data of oil inclusions, can effectively classify the phases of oil inclusions. By comprehensively analyzing factors such as geological background, sedimentary environment, and hydrocarbon accumulation process, researchers can gain a deeper understanding of the formation and evolution history of oil inclusions in different phases, revealing the patterns of hydrocarbon generation, migration, and accumulation. This has significant practical implications for guiding oil and gas exploration and development, helping to improve exploration success rates and reduce development risks.

[0015] 4. The method of this invention is also characterized by its simplicity, high efficiency, and speed. Laser confocal scanning technology boasts a high level of automation and intelligence, significantly reducing manual intervention and errors, and improving the efficiency of data processing and analysis. This enables researchers to obtain abundance information of oil-bearing inclusions more quickly, providing timely and accurate support for oil and gas exploration and development.

[0016] In summary, the method of this invention demonstrates significant advantages in improving characterization accuracy, achieving three-dimensional structural reconstruction and volume calculation, revealing the laws governing hydrocarbon generation and migration, and offering simple and efficient operation. It not only plays a crucial role in promoting oil and gas exploration and development but also helps improve exploration efficiency and development benefits.

[0017] Furthermore, the method for previewing reservoir inclusion slides in step one is as follows: the reservoir inclusion slides are rapidly previewed using bright-field laser confocal microscopy (EPI) and ultraviolet-excited fluorescence (DIA).

[0018] Beneficial Effects: Bright-field microscopy (EPI) preview allows researchers to clearly observe the overall structure and morphological characteristics of reservoir inclusions, providing an intuitive visual reference for subsequent calibration and facilitating the rapid identification of areas with significant oil inclusion development, thus aiding in detailed analysis. The application of ultraviolet-excited fluorescence (DIA) mode enables oil inclusions to fluoresce, making them more prominently displayed. This technology significantly improves the accuracy and efficiency of oil inclusion identification, reducing the possibility of missed or false detections. Fluorescence preview allows for more accurate calibration of the areas where oil inclusions develop, providing a reliable basis for subsequent spectral scanning and volumetric calculations. Laser confocal microscopy, with its high resolution and sensitivity, can capture the fine structure and compositional variations of reservoir inclusions, helping researchers gain a deeper understanding of reservoir characteristics and properties, and providing more accurate geological data for subsequent oil and gas exploration and development.

[0019] Furthermore, in step one, the number of calibrated fields of view is greater than or equal to ten.

[0020] Beneficial Effects: Increasing the number of calibration horizons helps improve the representativeness of oil inclusion development characteristics. By calibrating multiple horizons, a more comprehensive understanding of oil inclusion development at different locations and under different conditions within the reservoir can be achieved. This helps reduce misjudgments or biases caused by local features, improving the accuracy and reliability of the overall analysis. Calibration of multiple horizons helps reveal the spatial variation patterns of oil inclusion development. Different horizons may represent different geological environments, sedimentary conditions, and hydrocarbon accumulation processes within the reservoir. By comparing and analyzing the characteristics of oil inclusions in these horizons, the variation patterns in their spatial distribution, size, and morphology can be revealed, further understanding the distribution and evolution patterns of oil and gas reservoirs. Calibration of multiple horizons also increases the sample size for data analysis, improving the stability and reliability of statistical results. More horizon data means more observation points and information sources, helping to reduce the influence of random errors and accidental factors, making the analysis results closer to the true situation.

[0021] Furthermore, the criteria for defining the field of view in step one are: the defined oil inclusions are larger than the unselected oil inclusions, and the inclusions within the field of view are distributed in groups or densely in the host mineral grains or in linear and banded distributions along the secondary micro-fractures that cut through the mineral grains.

[0022] Beneficial Effects: The standardized criteria ensure that the selected field of view contains relatively high levels of oil inclusion development, allowing researchers to focus more intently on representative and typical oil inclusions, thus revealing more accurately the patterns of hydrocarbon generation, migration, and accumulation. By comparing the calibrated field of view with unselected fields, the differences and characteristics of oil inclusion development can be more clearly identified, facilitating in-depth investigation of the factors and conditions influencing oil inclusion development and further deepening our understanding of hydrocarbon reservoir formation and distribution. This calibrated field of view standard also helps improve the accuracy and reliability of data analysis. Because the selected field of view contains high levels of oil inclusion development, the acquired data and information are more representative and credible, more accurately reflecting the characteristics and properties of the reservoir.

[0023] Furthermore, in step two, when determining the spectral characteristics of oil-bearing inclusions, the spectral scanning parameters are pre-optimized. These parameters include, but are not limited to, the spectral mode, scanning range, and scanning interval. At the same time, the correlation between different spectral characteristics and the composition, formation environment, and evolutionary history of the oil-bearing inclusions must be considered.

[0024] Beneficial Effects: In-depth analysis of the correlation between spectral characteristics and the composition of oil-bearing inclusions allows for more accurate identification of different types of oil-bearing inclusions, helping to reveal the composition and properties of oil and gas reservoirs and providing crucial information for subsequent exploration and development. Considering the relationship between spectral characteristics and the formation environment of oil-bearing inclusions helps to understand the sedimentary conditions and environmental factors such as temperature and pressure involved in inclusion formation. This information is essential for revealing the processes of hydrocarbon generation and migration, and helps to better predict the distribution and scale of oil and gas reservoirs. Analyzing the connection between spectral characteristics and the evolutionary history of oil-bearing inclusions can reveal the changes in inclusions throughout geological history, including key events such as hydrocarbon charging and dissipation. This helps researchers gain a deeper understanding of the evolutionary history of oil and gas reservoirs and provides a more comprehensive geological background for oil and gas exploration and development.

[0025] Furthermore, in step three, the field-of-view laser confocal scanning of the oil-containing inclusions employs three-dimensional stereo scanning.

[0026] Beneficial Effects: 3D scanning can acquire three-dimensional spatial information of oil-bearing inclusions. Compared with traditional 2D scanning, it can more comprehensively reflect the morphology and distribution characteristics of inclusions, helping to more accurately assess the abundance of inclusions and the potential of oil and gas reservoirs. The multi-point scanning function in the software allows the software to automatically scan multiple calibrated fields of view sequentially, reducing manual operation steps and time. This not only improves work efficiency but also reduces human error, enhancing data consistency and reliability. The results of 3D and multi-point scanning can be visualized through 3D reconstruction and other methods, enabling researchers to more intuitively understand the distribution and morphology of oil and gas reservoirs, providing more intuitive guidance for exploration and development.

[0027] Furthermore, during laser confocal scanning in step three, the scanning parameters are pre-optimized, including but not limited to laser power and scanning speed.

[0028] Beneficial effects: Optimizing laser power ensures high-quality images during scanning. Appropriate laser power improves image contrast and clarity, allowing for better visualization of the detailed features of oil-containing inclusions. Simultaneously, it avoids damage to the sample from excessively high laser power, ensuring the accuracy and reliability of the experiment. Adjusting the scanning speed can improve scanning efficiency while maintaining image quality. Faster scanning speeds can shorten experimental cycles and reduce time costs. However, excessively fast scanning speeds may lead to a decrease in image quality; therefore, it is necessary to select an appropriate scanning speed while ensuring image quality.

[0029] Furthermore, in step three, the volume of the oil-containing inclusions is calculated using a mathematical algorithm, which includes, but is not limited to, image processing algorithms, three-dimensional reconstruction techniques, pixel counting methods, or volume integration methods.

[0030] Beneficial Effects: Employing mathematical algorithms can significantly improve the accuracy and precision of volume calculations. These carefully designed and validated algorithms can accurately process image data, extract the three-dimensional structural information of oil-bearing inclusions, and calculate accurate volume values ​​accordingly. Compared to traditional manual measurement or approximate estimation methods, mathematical algorithms can greatly reduce errors and biases, improving the reliability of calculation results. Simultaneously, the algorithms also reduce interference from human factors, lowering the risk of operational errors.

[0031] Furthermore, in step four, when dividing the oil-bearing inclusions into different phases, the geological background, sedimentary environment, and hydrocarbon accumulation process should be considered to comprehensively analyze the correspondence between spectral characteristics and phases.

[0032] Beneficial effects: While spectral characteristics can provide important information about the composition and formation environment of inclusions, accurate determination of inclusion periods may be difficult based solely on spectral data. By combining information such as geological background, sedimentary environment, and hydrocarbon accumulation process, spectral data can be interpreted and corrected in greater depth, improving the accuracy of inclusion period classification.

[0033] Furthermore, in step four, when calculating the total volume of oil-bearing inclusions in different phases, statistical analysis methods are used to compare the differences in the volume distribution of inclusions in different phases, thereby revealing the laws governing oil and gas generation, migration, and accumulation.

[0034] Beneficial Effects: Statistical analysis methods allow for a more precise and systematic assessment of the volumetric distribution characteristics of oil-bearing inclusions from different phases. This enables the processing of large amounts of data and the extraction of key information regarding hydrocarbon generation, migration, and accumulation. By comparing the size and distribution patterns of inclusions from different phases, a comprehensive understanding of the evolutionary history and distribution patterns of hydrocarbons in reservoirs can be achieved. Furthermore, it contributes to a deeper understanding of reservoir geological characteristics and hydrocarbon reservoir formation mechanisms. By comparing the spectral characteristics and volumetric distribution differences of inclusions from different phases, the hydrocarbon evolution processes under different geological periods and environmental conditions within the reservoir can be inferred, helping to reveal the formation and evolution history of hydrocarbon reservoirs and providing a more comprehensive geological background and basis for oil and gas exploration and development. Attached Figure Description

[0035] Figure 1 This is a flowchart of an embodiment of the method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology according to the present invention.

[0036] Figure 2 Fluorescent image of oil-containing inclusions in SY1.

[0037] Figure 3 The image shows the spectral distribution characteristics of oil inclusions in SY1.

[0038] Figure 4 The main peak wavelength (λ) of the oil inclusions in SY1 max ) and red-green quotient (Q 650 / 500 (Related image)

[0039] Figure 5 This is a three-dimensional volume reconstruction of the SY1 rock skeleton and oil-bearing inclusions. Detailed Implementation

[0040] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0041] The following detailed description illustrates the specific implementation method:

[0042] Example 1, basically as shown in the appendix Figure 1 As shown: The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology includes the following specific steps:

[0043] Step 1: Preview reservoir inclusion slides and identify the developmental field of view for oil-bearing inclusions. The preview method for reservoir inclusion slides is as follows: Rapid preview of reservoir inclusion slides is performed using bright-field laser confocal microscopy (EPI) and ultraviolet-excited fluorescence (DIA). The number of identified fields of view should be greater than or equal to ten. Identified oil-bearing inclusions should be larger than unselected oil-bearing inclusions, and the inclusions within the field of view should be clustered or densely distributed within the host mineral grains, or distributed linearly or in bands along secondary microfractures that cut through the mineral grains.

[0044] Step 2: Full-spectrum scanning to calibrate the field of view and determine the spectral characteristics of oil inclusions. When determining the spectral characteristics of oil inclusions, the spectral scanning parameters are optimized in advance. The parameters include, but are not limited to, the spectral mode, scanning range, and scanning interval. At the same time, the correlation between different spectral characteristics and the composition, formation environment, and evolutionary history of oil inclusions must be considered.

[0045] Step 3: Laser confocal scanning of the field of view reconstructs the 3D structure of oil inclusions in each field of view and calculates their volume. During laser confocal scanning, scanning parameters are pre-optimized, including but not limited to laser power and scanning speed; laser confocal scanning employs 3D stereo scanning. Mathematical algorithms are used to calculate the volume of oil inclusions, including but not limited to image processing algorithms, 3D reconstruction techniques, pixel counting methods, or volume integration methods.

[0046] Step Four: Apply the spectral characteristics of oil inclusions from Step Two to classify oil inclusion phases. When classifying oil inclusion phases, the geological background, sedimentary environment, and hydrocarbon accumulation process should also be considered to comprehensively analyze the correspondence between spectral characteristics and phases. Combine this with the oil inclusion volume data from Step Three to calculate the total volume of oil inclusions from different phases, using the volume of oil inclusions from different phases to characterize abundance. When calculating the total volume of oil inclusions from different phases, statistical analysis methods should be used to compare the differences in volume distribution of inclusions from different phases, thereby revealing the patterns of hydrocarbon generation, migration, and accumulation.

[0047] The specific implementation process is as follows:

[0048] Step 1: Obtain reservoir inclusion samples through drilling coring or outcrop profiling. Use a laser confocal microscope in bright-field (EPI) mode to quickly scan the inclusion samples and observe the overall distribution and morphological characteristics of the inclusions. Subsequently, switch to ultraviolet-excited fluorescence (DIA) mode to excite the oil-bearing inclusions to emit fluorescence, so as to more clearly identify their presence and location.

[0049] During the preview process, at least ten fields of view (GLs) with the most prominent oil inclusion development are selected for calibration. These GLs typically exhibit high inclusion density and good fluorescence properties, representing the main developmental characteristics of oil inclusions in the reservoir. Furthermore, the inclusions within the GLs must be "clustered or densely distributed within the host mineral grains, or distributed linearly or in bands along secondary microfractures that cut through the mineral grains." Calibration can be performed by marking the location and extent of the selected GLs within the microscope's field of view.

[0050] Step 2: After calibrating the field of view, use the full-spectrum scanning function of the laser confocal microscope to scan each field of view. By adjusting the spectral range of the microscope, spectral data of different oil-bearing inclusions in each field of view are obtained. These data reflect the absorption and reflection characteristics of oil-bearing inclusions to different wavelengths of light, which is key to determining the spectral characteristics of the inclusions.

[0051] When analyzing spectral data, it is necessary to consider the correlation between different spectral characteristics and the composition, formation environment, and evolutionary history of oil inclusions. For example, oil inclusions captured in different charging phases will exhibit different fluorescence spectral characteristics due to differences in the maturity and composition of the captured crude oil, including spectral peak shape and main peak wavelength (λ). max ) and red-green quotient (Q 650 / 500 This will reveal the origin and evolution of inclusions.

[0052] Step 3: After determining the spectral characteristics of the oil inclusions, a detailed scan of the selected field of view is performed using laser confocal 3D scanning technology. During the scanning process, scanning parameters, such as laser power, scanning speed, and scanning resolution, are pre-optimized to ensure high-quality scan data. A multi-point scanning method is adopted, that is, different marked positions of the field of view are automatically scanned sequentially to obtain more comprehensive 3D structural information of the inclusions. Through image processing algorithms and 3D reconstruction technology, a 3D structural model of the oil inclusions in each field of view is reconstructed.

[0053] After obtaining the three-dimensional structural model, mathematical algorithms such as pixel counting or volume integration are used to calculate the volume of oil-bearing inclusions. These algorithms can quantitatively calculate the volume based on the inclusions' occupancy in three-dimensional space, thereby achieving a quantitative characterization of the abundance of oil-bearing inclusions.

[0054] Step Four: After obtaining the spectral characteristics and volume data of oil-bearing inclusions, the inclusions can be classified into different phases based on differences in spectral characteristics. Inclusions of different phases typically have different spectral characteristics, reflecting their formation in different geological periods and environments. In the process of phase classification, it is also necessary to combine information such as geological background, sedimentary environment, and hydrocarbon accumulation process for comprehensive analysis. By comparing the differences in spectral characteristics and volume distribution of inclusions of different phases, the laws governing hydrocarbon generation, migration, and accumulation can be revealed, providing important geological basis for oil and gas exploration and development. Finally, the total volume of oil-bearing inclusions of different phases is calculated, and the abundance is characterized by the volume of oil-bearing inclusions of different phases. This step can be completed through simple volume summation or more complex statistical analysis methods. By comparing the volume of inclusions of different phases, the potential scale and distribution of oil and gas in the reservoir can be further assessed. In summary, the method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology, by combining spectral scanning and three-dimensional reconstruction technology, achieves comprehensive analysis and quantitative characterization of the development characteristics of oil-bearing inclusions in reservoirs, improving the accuracy and efficiency of oil and gas exploration and development.

[0055] For example, a batch of inclusion samples were obtained from a reservoir in an oil field. The purpose was to characterize the abundance of oil-bearing inclusions in these samples using laser confocal scanning technology. (See below:)

[0056] First, the bright-field (EPI) and ultraviolet-excited fluorescence (DIA) functions of a laser confocal microscope were used for rapid preview of reservoir inclusion slides. During the preview, ten such views were selected for calibration because the oil-bearing inclusions were particularly well-developed in certain fields of view. These fields were also numbered during the labeling process, designated as SY1-SYn (n≥10), for easy identification in subsequent work.

[0057] Next, full-spectrum scanning was performed on the ten calibrated fields of view. A laser confocal microscope was used to sequentially perform full-spectrum scanning (Full Spectra) on the fields of view SY1-SYn calibrated in step one, selecting BS20 / 80 mode, setting the wavelength scanning range to 400-700 nm, and the scanning interval to 20 nm. After scanning, the spectral characteristics of oil-containing inclusions within the fields of view SY1-SYn were analyzed to obtain the spectral characteristics of the oil-containing inclusions; taking field SY1 as an example, the inclusions within the field of view were sequentially selected using the software's ROI selection function (as shown in the attached image). Figure 2 The figure shows 1-15, indicating 15 inclusions in the field of view SY1 (the inclusions are numbered sequentially), and the corresponding spectral characteristic curves of the oil-bearing inclusions are obtained (as shown in the attached figure). Figure 3 The numbers 1-15 in the diagram correspond to the attached figures respectively. Figure 2The characteristic curves of inclusions with the same labels in the data were used to derive the spectral characteristic curves and spectral parameter data tables of oil-bearing inclusions. The same method was used to obtain the spectral characteristic curves and spectral parameter data tables of oil-bearing inclusions for other fields of view SY2-SYn.

[0058] Spectral characteristic data of oil inclusions within each field of view were obtained through scanning. These data not only reflect the chemical composition of the oil inclusions but also relate to their formation environment and evolutionary history. Characteristic data include the main peak wavelength (the emission wavelength corresponding to the maximum fluorescence intensity) and the red-green quotient (the ratio of fluorescence intensity at 650 nm to fluorescence intensity at 500 nm). Taking field SY1 as an example, the spectral peak shapes of different oil inclusions were compared, and the main peak wavelength (λ) of each oil inclusion was obtained through calculation and processing of the spectral characteristic curves and data. max ) and red-green quotient (Q 650 / 500 Based on the main peak wavelength (λ) max ) and red-green quotient (Q 650 / 500 The intersection map is used to classify the oil-bearing inclusion phases (as shown in the attached diagram). Figure 4 , which represents the intersection graph of all inclusions in view SY1. Other view SY2-SYn are processed in the same way.

[0059] After obtaining the spectral feature data, a detailed scan of the ten fields of view was performed using laser confocal 3D stereo scanning technology. During the scanning process, scanning parameters, such as laser power and scanning speed, were pre-optimized to ensure high-quality scan data. Using 3D stereo scanning technology, the 3D structure of oil inclusions within each field of view was successfully reconstructed, and their volumes were calculated using mathematical algorithms. Multi-point scanning was applied to sequentially perform 3D stereo scanning on the calibrated fields of view SY1-SYn, reconstructing the 3D structure of oil inclusions within each field of view and calculating their volumes. Taking field of view SY1 as an example, the principal focal plane was first determined, and then the top and bottom surfaces of the Z-axis scan were determined sequentially. The scanning interval thickness was set to ensure that the total number of scanned slices was greater than or equal to 20. After the Z-axis scan was completed, a template was established for the oil inclusions on the principal focal plane by selecting parameters based on the fluorescence range. These parameters were then applied to other focal planes to delineate the range of oil inclusions. The parameters of other focal planes were adjusted until satisfactory results were achieved, and then the 3D volume of the oil inclusions was reconstructed and the volumes calculated (as shown in the attached figure). Figure 5 (This represents a 3D view of all inclusions in the field of view SY1). Simultaneously, the scanned rock skeleton is reconstructed in 3D and its volume is calculated. Other fields of view SY2-SYn are processed using the same method.

[0060] Finally, based on the spectral characteristic data obtained in step two, and combined with information on geological background, sedimentary environment, and hydrocarbon accumulation process, the oil-bearing inclusions were divided into distinct phases. Then, combining the oil-bearing inclusion volume data calculated in step three, the total volume of oil-bearing inclusions in different phases was calculated. The total volume of oil-bearing inclusions of the same phase within all observation fields was calculated along with the total volume of the rock skeleton, and the ratio of the total volume of oil-bearing inclusions in different phases to the total volume of the rock skeleton was used to characterize the abundance of oil-bearing inclusions in different phases. By comparing the differences in the distribution of inclusion abundance across different phases, the patterns of hydrocarbon generation, migration, and accumulation in this oilfield were revealed.

[0061] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific structures and / or characteristics in the solutions are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the structure of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for characterizing the abundance of oil-bearing inclusions based on laser confocal scanning technology, characterized in that, The specific steps are as follows: Step 1: Preview reservoir inclusion sections and define the development field of oil-bearing inclusions; among which, The criteria for defining the field of view are: the defined oil inclusions are larger than the unselected oil inclusions, and the inclusions within the field of view are distributed in groups or densely in the host mineral grains or in linear and banded distributions along the secondary micro-fractures that cut through the mineral grains; Step 2: Full-spectrum scanning to calibrate the field of view and determine the spectral characteristics of oil-bearing inclusions, including the main peak wavelength and red-green quotient; Step 3: Use laser confocal scanning to reconstruct the 3D structure of oil inclusions in each field of view and calculate their volume; Step 4: Apply the spectral characteristics of oil inclusions from Step 2 to classify oil inclusion phases, and combine them with the oil inclusion volume from Step 3 to calculate the total volume of oil inclusions in different phases. Use the volume of oil inclusions in different phases to characterize the abundance. Calculate the total volume of oil inclusions in the same phase and the total volume of the rock skeleton within all observation fields, and use the ratio of the total volume of oil inclusions in different phases to the total volume of the rock skeleton to characterize the abundance of oil inclusions in different phases. In step four, when dividing the oil-bearing inclusions into different phases, the geological background, sedimentary environment, and hydrocarbon accumulation process should be considered, and the correspondence between spectral characteristics and phases should be comprehensively analyzed. In step four, when calculating the total volume of oil-bearing inclusions in different phases, statistical analysis methods are used to compare the differences in the volume distribution of inclusions in different phases, thereby revealing the laws of oil and gas generation, migration, and accumulation.

2. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... The method for previewing reservoir inclusion slides in step one is as follows: use a laser confocal microscope with bright field and ultraviolet excitation fluorescence to quickly preview the reservoir inclusion slides.

3. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... In step one, the number of calibrated fields of view is greater than or equal to ten.

4. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... In step two, when determining the spectral characteristics of oil inclusions, the spectral scanning parameters are optimized in advance. The parameters include the spectral mode, scanning range and scanning interval. At the same time, the correlation between different spectral characteristics and the composition, formation environment and evolutionary history of oil inclusions should be considered.

5. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... In step three, the field-of-view laser confocal scanning of the oil inclusions uses three-dimensional scanning.

6. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... In step three, during laser confocal scanning, the scanning parameters are pre-optimized, including laser power and scanning speed.

7. The method for characterizing the abundance of oil inclusions based on laser confocal scanning technology according to claim 1, characterized in that... Step 3 calculates the volume of oil-bearing inclusions using mathematical algorithms, including image processing algorithms, 3D reconstruction techniques, pixel counting methods, or volume integration methods.

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