Semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning

Abstract

The invention relates to a semi-quantitative fluid inclusion analysis method based on three-dimensional CT (Computed Tomography) scanning, which is applied to the technical field of geological mineral detection and comprises the following steps: acquiring sample data of a sample to be analyzed; performing sample preparation on the to-be-analyzed sample based on the sample data to generate a target sample; performing three-dimensional CT scanning processing on the target sample to generate three-dimensional cross-sectional image data; performing image preprocessing on the three-dimensional cross-sectional image data to generate processed three-dimensional data; extracting a three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain three-dimensional data of the fluid inclusion; performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation and analysis data; and generating a fluid inclusion analysis result based on the fluid inclusion three-dimensional data and the computational analysis data. The method has the effect of comprehensively and accurately analyzing the fluid inclusion.

Description

Technical Field

[0001] The present application relates to the technical field of geological mineral detection, and in particular to a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning. Background Art

[0002] Fluid inclusions are tiny fluid samples captured during the formation of minerals. Their composition and properties are of great significance for the study of geological history, mineralization processes and resource exploration.

[0003] Traditional analysis methods primarily rely on two-dimensional microscopy, Raman spectroscopy, cryo-thermometry, or traditional CT scanning. However, these methods all have drawbacks. For example, two-dimensional microscopy involves observing inclusion slices using a polarizing microscope or a hot / cold stage and manually measuring the gas-liquid ratio. This can lead to distorted cavity morphology, large dimensional errors, and an inability to resolve fluid distribution characteristics. Raman spectroscopy, which uses Raman spectroscopy to analyze the chemical composition of fluid inclusions, can only analyze local regions and cannot obtain information on their overall distribution. Cryo-thermometry measures the phase transition temperatures of fluid inclusions during freezing and heating to infer their formation conditions, but this requires sample destruction and cannot fully reflect the three-dimensional characteristics of the inclusions. Traditional CT scanning, however, lacks sufficient resolution to identify micron-scale inclusion details and can only provide qualitative morphological descriptions. Therefore, a technology that can comprehensively and accurately analyze fluid inclusions is urgently needed. Summary of the Invention

[0004] In order to comprehensively and accurately analyze fluid inclusions, the present application provides a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning.

[0005] In a first aspect, the present application provides a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning, which adopts the following technical solutions:

[0006] A semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning, comprising:

[0007] Obtaining sample data of a sample to be analyzed;

[0008] Performing sample preparation on the sample to be analyzed based on the sample data to generate a target sample;

[0009] Performing a three-dimensional CT scan on the target sample to generate three-dimensional tomographic image data;

[0010] performing image preprocessing on the three-dimensional tomographic image data to generate processed three-dimensional data;

[0011] Extracting the three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain three-dimensional data of the fluid inclusion;

[0012] performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation analysis data;

[0013] Fluid inclusion analysis results are generated based on the fluid inclusion three-dimensional data and the computational analysis data.

[0014] By adopting the above technical solution, after obtaining the sample to be analyzed, the sample to be analyzed is controlled according to the sample data to generate a target sample that is more convenient for scanning and analysis. Then, the target sample is three-dimensionally scanned using three-dimensional CT technology, and the three-dimensional tomographic image data obtained by the scan is preprocessed to highlight the inclusion information therein to obtain processed three-dimensional data. Then, three-dimensional features of the fluid inclusions in the processed three-dimensional data are extracted to determine the detailed three-dimensional data of the fluid inclusions. The fluid inclusions are analyzed to obtain analysis data of the fluid inclusions in the target sample, so as to generate analysis results that can fully display the fluid inclusion information, thereby enabling comprehensive and accurate analysis of the fluid inclusions.

[0015] Optionally, preparing the sample to be analyzed based on the sample data to generate a target sample includes:

[0016] Determining whether the size of the sample to be analyzed meets the scanning conditions based on the sample data;

[0017] If the size of the sample to be analyzed does not meet the scanning conditions, the sample to be analyzed is segmented and cleaned based on the preset scanning conditions and the sample data to generate a target sample;

[0018] If the size of the sample to be analyzed meets the scanning conditions, the sample to be analyzed is cleaned, and the cleaned sample to be analyzed is used as the target sample.

[0019] Optionally, performing three-dimensional CT scanning on the target sample to generate three-dimensional tomographic image data includes:

[0020] A high-resolution micro-CT system with a resolution of 1 μm is used to perform a 360° rotational three-dimensional CT scan on the target sample to generate three-dimensional tomographic image data. The scanning parameters of the high-resolution micro-CT system are: tube voltage of 100-200 kV, tube current of 100-300 μA, aluminum filter thickness of 0.5-2 mm, and exposure time of 0.5-2 s / frame.

[0021] Optionally, performing image preprocessing on the three-dimensional tomographic image data to generate processed three-dimensional data includes:

[0022] performing denoising and contrast enhancement processing on the three-dimensional tomographic image data;

[0023] The denoising process uses a non-local mean filtering algorithm to remove noise from the three-dimensional tomographic image data and retain edge details of the target sample;

[0024] The contrast enhancement processing is based on Hounsfield Unit, the dynamic range is adjusted to 500-5000HU, and the window position is adjusted to 1000-3000HU to highlight the grayscale difference between the fluid inclusions and the mineral matrix in the target sample;

[0025] The three-dimensional tomographic image data that has undergone the denoising process and the contrast enhancement process is used as processed three-dimensional data.

[0026] Optionally, extracting the three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain the three-dimensional fluid inclusion data includes:

[0027] performing threshold segmentation and morphological optimization processing on the processed three-dimensional data;

[0028] The threshold segmentation uses the Otsu algorithm to automatically determine the threshold range, segmenting the fluid inclusion area in the processed three-dimensional data to generate a binary three-dimensional matrix;

[0029] Morphological optimization performs an opening operation on the binarized three-dimensional matrix to remove isolated noise points in the fluid inclusion region, and performs a closing operation on the binarized three-dimensional matrix to fill internal holes in the fluid inclusion region in the processed three-dimensional data, retaining connected regions with a size greater than 1 μm³, to obtain fluid inclusion three-dimensional data.

[0030] Optionally, the opening operation is used to remove isolated noise points with a size less than 1 μm³ in the fluid inclusion region in the processed three-dimensional data, and the closing operation is used to fill internal pores with a porosity less than 5% in the fluid inclusion region in the processed three-dimensional data.

[0031] Optionally, performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation and analysis data includes:

[0032] Acquiring actual sample data of the target sample;

[0033] determining the inclusion size of the fluid inclusion region based on the three-dimensional fluid inclusion data;

[0034] Calculating the spatial distribution density of the fluid inclusion region based on the inclusion size and the actual sample data;

[0035] Calculating the aspect ratio and curvature radius of the fluid inclusion region based on the three-dimensional data of the fluid inclusion;

[0036] The inclusion size, the spatial distribution density, the body aspect ratio and the curvature radius are used as calculation and analysis data.

[0037] Optionally, generating the fluid inclusion analysis results based on the fluid inclusion three-dimensional data and the computational analysis data includes:

[0038] generating a three-dimensional distribution map based on the three-dimensional data of the fluid inclusion;

[0039] Performing data annotation on the three-dimensional distribution map based on the calculated and analyzed data to generate an annotated three-dimensional distribution map;

[0040] generating a statistical data table and a semi-quantitative analysis report based on the annotated three-dimensional distribution graph;

[0041] The annotated three-dimensional distribution graph, the statistical data table and the semi-quantitative analysis report are bound together to generate fluid inclusion analysis results.

[0042] In summary, this application includes at least one of the following beneficial technical effects:

[0043] After obtaining the sample to be analyzed, the sample to be analyzed is controlled according to the sample data to generate a target sample that is more convenient for scanning and analysis. Then, the target sample is three-dimensionally scanned using three-dimensional CT technology, and the three-dimensional tomographic image data obtained by the scan is preprocessed to highlight the inclusion information therein to obtain processed three-dimensional data. Then, three-dimensional features of the fluid inclusions in the processed three-dimensional data are extracted to determine the detailed three-dimensional data of the fluid inclusions. The fluid inclusions are analyzed to obtain the analysis data of the fluid inclusions in the target sample, so as to generate analysis results that can fully display the fluid inclusion information, thereby enabling a comprehensive and accurate analysis of the fluid inclusions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning provided in an embodiment of the present application.

[0045] Figure 2 This is a schematic diagram of the results of extracting and analyzing the three-dimensional data of fluid inclusions provided in the embodiments of the present application. DETAILED DESCRIPTION

[0046] The present application is further described in detail below with reference to the accompanying drawings.

[0047] The present application provides a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning. This method can be performed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be, but is not limited to, a smartphone, a tablet computer, or a desktop computer.

[0048] Figure 1 A schematic flow chart of a semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning provided in an embodiment of the present application.

[0049] like Figure 1 As shown, the main process of the method is described as follows (steps S101 to S107):

[0050] Step S101: Acquire sample data of a sample to be analyzed.

[0051] In this embodiment, the sample data of the sample to be analyzed includes the type of rock containing fluid inclusions, the collection time and size, etc. The sample data is recorded and measured by the mining personnel after mining. The sample to be analyzed can be one or more, but when analyzing, only samples of one rock type can be analyzed, so as to avoid inaccurate measurement and analysis caused by the mixing of other types of rock.

[0052] Step S102: preparing the sample to be analyzed based on the sample data to generate a target sample.

[0053] For step S102, determine whether the size of the sample to be analyzed meets the scanning conditions based on the sample data; if the size of the sample to be analyzed does not meet the scanning conditions, the sample to be analyzed is segmented and cleaned based on the preset scanning conditions and sample data to generate a target sample; if the size of the sample to be analyzed meets the scanning conditions, the sample to be analyzed is cleaned, and the cleaned sample to be analyzed is used as the target sample.

[0054] In this embodiment, after obtaining the sample to be analyzed, it is necessary to prepare the sample to be analyzed to obtain a target sample for scanning. Since three-dimensional scanning has certain limitations, if the size of the sample to be analyzed is too large, it may cause inaccurate or incomplete scanning. It is necessary to determine whether the sample to be analyzed needs to be cut according to the size of the sample to be analyzed and the scanning conditions. The scanning condition is that the sample size needs to be a cube of 3 to 10 mm or a regular shape with equivalent size, such as a cylinder, a prism, etc. If the size meets the scanning condition, the sample to be analyzed will be cleaned to remove impurities on the surface, and the cleaned sample to be analyzed will be used as the target sample. If the size does not meet the scanning condition, the sample to be analyzed will be cut according to the size specified by the scanning condition, and after cutting, it will be cleaned to remove impurities on the surface, and at least one frame obtained by cutting and cleaning will be used as the target sample.

[0055] Step S103: Perform a three-dimensional CT scan on the target sample to generate three-dimensional tomographic image data.

[0056] In step S103 , a high-resolution micro-CT system with a resolution of 1 μm is used to perform a 360° rotational three-dimensional CT scan of the target sample to generate three-dimensional tomographic image data. The scanning parameters of the high-resolution micro-CT system are: tube voltage 100-200 kV, tube current 100-300 μA, aluminum filter thickness 0.5-2 mm, and exposure time 0.5-2 s / frame.

[0057] In this embodiment, in order to obtain accurate three-dimensional tomographic image data, it is necessary to use a three-dimensional CT system to perform rotational scanning processing on the target sample, so as to obtain three-dimensional tomographic image data that fully reflects the information of fluid inclusions in the target sample. When scanning, it is necessary to use a high-resolution micro-CT system with a resolution of 1 μm, and set the scanning parameters to tube voltage 100~200 kV, tube current 100~300 μA, aluminum filter thickness 0.5~2 mm and exposure time 0.5~2 s / frame, so as to ensure clear imaging of tiny inclusions in the target sample.

[0058] Step S104: performing image preprocessing on the three-dimensional tomographic image data to generate processed three-dimensional data.

[0059] For step S104, denoising and contrast enhancement are performed on the three-dimensional tomographic image data;

[0060] Denoising uses a non-local mean filtering algorithm to remove noise from the three-dimensional tomographic image data and retain the edge details of the target sample. Contrast enhancement is based on the Hounsfield Unit, with the dynamic range adjusted to 500-5000HU and the window position to 1000-3000HU to highlight the grayscale difference between fluid inclusions and the mineral matrix in the target sample. The three-dimensional tomographic image data that has completed denoising and contrast enhancement is used as the processed three-dimensional data.

[0061] In this embodiment, although the obtained three-dimensional tomographic image data can show the location and imaging of the fluid inclusions, the contrast between it and the ordinary rock mass is not high enough, which still has a certain impact on subsequent processing. Therefore, the three-dimensional tomographic image data needs to be preprocessed to generate clearer and more complete processed three-dimensional data. The specific processing method includes two steps: denoising and contrast enhancement. The denoising process includes using a non-local mean filtering algorithm, i.e., a Non-local Means algorithm, to remove interference noise in the three-dimensional tomographic image data and retain the edge details of the fluid inclusion area in the three-dimensional tomographic image data. The contrast enhancement process includes adjusting the window width to 500-5000 HU and adjusting the window position to 1000-3000 HU based on the Hounsfield Unit (HU) dynamic range, thereby highlighting the grayscale difference information between the fluid inclusion area and the mineral matrix.

[0062] Step S105 , extracting the three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain three-dimensional data of the fluid inclusion.

[0063] For step S105, threshold segmentation and morphological optimization are performed on the processed three-dimensional data; threshold segmentation uses the Otsu algorithm to automatically determine the threshold range, segmenting the fluid inclusion region in the processed three-dimensional data to generate a binary three-dimensional matrix; morphological optimization performs an opening operation on the binary three-dimensional matrix to remove isolated noise points in the fluid inclusion region, and performs a closing operation on the binary three-dimensional matrix to fill the internal holes in the fluid inclusion region in the processed three-dimensional data, retaining the connected regions with a size greater than 1 μm³, to obtain the fluid inclusion three-dimensional data.

[0064] Furthermore, the opening operation is used to remove isolated noise points with a size less than 1 μm³ in the fluid inclusion region of the processed three-dimensional data, and the closing operation is used to fill the internal pores with a porosity less than 5% in the fluid inclusion region of the processed three-dimensional data.

[0065] In this embodiment, after obtaining the processed 3D data, 3D data extraction of fluid inclusions can be performed on the processed 3D data to obtain the 3D fluid inclusion data. 3D data extraction includes threshold segmentation and morphological optimization. Specifically, the Otsu algorithm is used to automatically determine a threshold range of -500 to 1000 HU, segmenting low-density regions within the processed 3D data, i.e., fluid inclusion regions within the processed 3D data, to generate a binary 3D matrix. Morphological optimization is then used to perform an opening operation on the binary 3D matrix using 3×3 spherical structuring elements to remove isolated noise points with a volume less than 1 μm³ from the processed 3D data. A closing operation using 5×5 cubic structuring elements is then performed to fill internal pores with a porosity of less than 5% within the processed 3D data, retaining effectively connected regions. After processing, the 3D fluid inclusion data is obtained.

[0066] Step S106: perform parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusions to generate calculation and analysis data.

[0067] For step S106, the actual sample data of the target sample is obtained; the inclusion size of the fluid inclusion region is determined based on the three-dimensional fluid inclusion data; the spatial distribution density of the fluid inclusion region is calculated based on the inclusion size and the actual sample data; the body aspect ratio and the curvature radius of the fluid inclusion region are calculated based on the three-dimensional fluid inclusion data; and the inclusion size, spatial distribution density, body aspect ratio and curvature radius are used as calculation and analysis data.

[0068] In this embodiment, the dimensional data of the target sample is measured and the measured dimensional data is used as the actual sample data. Then, the required data is extracted from the three-dimensional data of the fluid inclusion to obtain the inclusion size. According to the total volume of the inclusion area and the volume of the target sample, the percentage of the total volume of the inclusion area to the volume of the target sample is calculated. The obtained percentage is the spatial distribution density of the fluid inclusion area. According to the size of the inclusion, the aspect ratio and curvature radius can also be calculated. All the calculated data are summarized and bound as calculation and analysis data to complete parameter calculation and semi-quantitative analysis.

[0069] Step S107: generating fluid inclusion analysis results based on the fluid inclusion three-dimensional data and the computational analysis data.

[0070] For step S107, a three-dimensional distribution map is generated based on the three-dimensional data of the fluid inclusions; data annotation is performed on the three-dimensional distribution map based on the calculated analysis data to generate an annotated three-dimensional distribution map; a statistical data table and a semi-quantitative analysis report are generated based on the annotated three-dimensional distribution map; and the annotated three-dimensional distribution map, the statistical data table and the semi-quantitative analysis report are bound together to generate the fluid inclusion analysis results.

[0071] In this embodiment, referring to Figure 2, extract and analyze the three-dimensional data of fluid inclusions to obtain a three-dimensional distribution map, and annotate the calculated analysis data on the three-dimensional distribution map to obtain a labeled three-dimensional distribution map with annotation information. Then, summarize and analyze the obtained graph to generate a statistical data table and a semi-quantitative analysis report for reflecting the fluid inclusion area information in the target sample. In order to facilitate subsequent reference and analysis, the annotated three-dimensional distribution map, statistical data table and semi-quantitative analysis report are bound together to obtain the final fluid inclusion analysis results.

[0072] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0073] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application involved in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned application concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions applied for in this application.

Claims

1. A semi-quantitative fluid inclusion analysis method based on three-dimensional CT scanning, characterized in that: include: Obtaining sample data of a sample to be analyzed; Performing sample preparation on the sample to be analyzed based on the sample data to generate a target sample; Performing a three-dimensional CT scan on the target sample to generate three-dimensional tomographic image data; performing image preprocessing on the three-dimensional tomographic image data to generate processed three-dimensional data; Extracting the three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain three-dimensional data of the fluid inclusion; performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation analysis data; Fluid inclusion analysis results are generated based on the fluid inclusion three-dimensional data and the computational analysis data.

2. The method according to claim 1, characterized in that The preparing the sample to be analyzed based on the sample data to generate a target sample comprises: Determining whether the size of the sample to be analyzed meets the scanning conditions based on the sample data; If the size of the sample to be analyzed does not meet the scanning conditions, the sample to be analyzed is segmented and cleaned based on the preset scanning conditions and the sample data to generate a target sample; If the size of the sample to be analyzed meets the scanning conditions, the sample to be analyzed is cleaned, and the cleaned sample to be analyzed is used as the target sample.

3. The method according to claim 1, characterized in that The performing three-dimensional CT scanning on the target sample to generate three-dimensional tomographic image data includes: A high-resolution micro-CT system with a resolution of 1 μm is used to perform a 360° rotational three-dimensional CT scan on the target sample to generate three-dimensional tomographic image data. The scanning parameters of the high-resolution micro-CT system are: tube voltage of 100-200 kV, tube current of 100-300 μA, aluminum filter thickness of 0.5-2 mm, and exposure time of 0.5-2 s / frame.

4. The method according to claim 1, wherein The performing image preprocessing on the three-dimensional tomographic image data to generate processed three-dimensional data includes: performing denoising and contrast enhancement processing on the three-dimensional tomographic image data; The denoising process uses a non-local mean filtering algorithm to remove noise from the three-dimensional tomographic image data and retain edge details of the target sample; The contrast enhancement processing is based on Hounsfield Unit, the dynamic range is adjusted to 500-5000HU, and the window position is adjusted to 1000-3000HU to highlight the grayscale difference between the fluid inclusions and the mineral matrix in the target sample; The three-dimensional tomographic image data that has undergone the denoising process and the contrast enhancement process is used as processed three-dimensional data.

5. The method according to claim 1, wherein Extracting the three-dimensional structure of the fluid inclusion based on the processed three-dimensional data to obtain the three-dimensional data of the fluid inclusion comprises: performing threshold segmentation and morphological optimization processing on the processed three-dimensional data; The threshold segmentation uses the Otsu algorithm to automatically determine the threshold range, segmenting the fluid inclusion area in the processed three-dimensional data to generate a binary three-dimensional matrix; Morphological optimization performs an opening operation on the binarized three-dimensional matrix to remove isolated noise points in the fluid inclusion region, and performs a closing operation on the binarized three-dimensional matrix to fill internal holes in the fluid inclusion region in the processed three-dimensional data, retaining connected regions with a size greater than 1 μm³, to obtain fluid inclusion three-dimensional data.

6. The method according to claim 5, characterized in that The opening operation is used to remove isolated noise points with a size less than 1 μm³ in the fluid inclusion region in the processed three-dimensional data, and the closing operation is used to fill internal pores with a porosity of less than 5% in the fluid inclusion region in the processed three-dimensional data.

7. The method according to claim 5, characterized in that The performing parameter calculation and semi-quantitative analysis on the three-dimensional data of the fluid inclusion to generate calculation analysis data comprises: Acquiring actual sample data of the target sample; determining the inclusion size of the fluid inclusion region based on the three-dimensional fluid inclusion data; Calculating the spatial distribution density of the fluid inclusion region based on the inclusion size and the actual sample data; Calculating the aspect ratio and curvature radius of the fluid inclusion region based on the three-dimensional data of the fluid inclusion; The inclusion size, the spatial distribution density, the body aspect ratio and the curvature radius are used as calculation and analysis data.

8. The method according to claim 7, characterized in that Generating the fluid inclusion analysis results based on the fluid inclusion three-dimensional data and the computational analysis data includes: generating a three-dimensional distribution map based on the three-dimensional data of the fluid inclusion; Performing data annotation on the three-dimensional distribution map based on the calculated and analyzed data to generate an annotated three-dimensional distribution map; generating a statistical data table and a semi-quantitative analysis report based on the annotated three-dimensional distribution graph; The annotated three-dimensional distribution graph, the statistical data table and the semi-quantitative analysis report are bound together to generate fluid inclusion analysis results.

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