WO2024119528A1 - 一种岩心样品分析方法、系统、电子设备及存储介质 - Google Patents

一种岩心样品分析方法、系统、电子设备及存储介质 Download PDF

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WO2024119528A1
WO2024119528A1 PCT/CN2022/138665 CN2022138665W WO2024119528A1 WO 2024119528 A1 WO2024119528 A1 WO 2024119528A1 CN 2022138665 W CN2022138665 W CN 2022138665W WO 2024119528 A1 WO2024119528 A1 WO 2024119528A1
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organic matter
core sample
small core
content
meter
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French (fr)
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朱光有
陈志勇
曹颖辉
马德波
乔占峰
黄士鹏
范俊佳
陈玮岩
倪云燕
郑剑锋
李秋芬
李闯
张明
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Petrochina Co Ltd
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Petrochina Co Ltd
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
    • G01N15/088—Investigating volume, surface area, size or distribution of pores; Porosimetry
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
    • G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
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    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
    • G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
    • G01N23/046—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material using tomography, e.g. computed tomography [CT]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/22—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material
    • G01N23/223—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material by irradiating the sample with X-rays or gamma-rays and by measuring X-ray fluorescence
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    • G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2223/00—Investigating materials by wave or particle radiation
    • G01N2223/07—Investigating materials by wave or particle radiation secondary emission
    • G01N2223/076—X-ray fluorescence
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2223/00—Investigating materials by wave or particle radiation
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    • G01N2223/616—Specific applications or type of materials earth materials
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    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection

Definitions

  • the present invention relates to the technical field of petroleum logging, and in particular to a core sample analysis method, system, electronic equipment and storage medium.
  • well logging data is usually used to determine geophysical parameters.
  • the geophysical properties of rock formations such as electrochemical properties, electrical conductivity, acoustic properties, radioactivity, etc. are used to identify oil layers, gas layers, rock layers, and water layers, and to specifically determine the location, lithology, organic matter abundance, and maturity of oil reservoirs.
  • Well logging data can only indirectly and conditionally reflect the geological characteristics of rock formations.
  • coring operations are usually required, and the cores obtained are sampled and analyzed using a variety of experimental instruments and methods to determine the key parameters of the reservoir.
  • the object of the present invention is to provide a method and device for efficiently and accurately analyzing core samples without destroying the core samples, thereby determining key parameters required for oil and gas exploration.
  • the present invention provides the following four technical solutions.
  • the present invention provides a core sample analysis method, wherein the method comprises:
  • volume content of organic matter i.e., the volume ratio of organic matter to the volume of the small core sample
  • porosity i.e., the volume ratio of pores to the volume of the small core sample
  • volume content of inorganic minerals i.e., the volume ratio of inorganic minerals to the volume of the small core sample
  • the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed are determined.
  • the present invention provides a core sample analysis system, wherein the system comprises:
  • Large core data acquisition module used to obtain dual-energy spiral CT scans of meter-scale large cores to be analyzed; determine at least three small core samples from the meter-scale large cores to be analyzed; wherein the dual-energy spiral CT scans include low-energy CT scans and high-energy CT scans;
  • Small core data acquisition module used to obtain XRF scans of surface characteristic areas of each small core sample and micrometer CT scans of each small core sample;
  • Small core parameter determination module used to determine the organic matter volume content (i.e., the volume ratio of organic matter volume to small core sample), porosity (i.e., the volume ratio of pores to small core sample) and inorganic mineral volume content (i.e., the volume ratio of inorganic mineral volume to small core sample) of each small core sample by using the micron CT scan image of each small core sample and the XRF scan image of the surface characteristic area;
  • organic matter volume content i.e., the volume ratio of organic matter volume to small core sample
  • porosity i.e., the volume ratio of pores to small core sample
  • inorganic mineral volume content i.e., the volume ratio of inorganic mineral volume to small core sample
  • Large core parameter determination module used to determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample.
  • the present invention provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of a core sample analysis method when executing the program.
  • the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the core sample analysis method when executed by a processor.
  • the technical solution provided by the present invention can determine the organic matter volume content distribution, porosity distribution, inorganic mineral volume content distribution and other parameters of meter-scale large cores on the basis of obtaining cores on site at the exploration site without destroying the standard meter-scale large cores of the formation, greatly improving the accuracy of oil and gas reservoir evaluation description and providing a reference basis for exploration and exploitation.
  • the technical solution provided by the present invention accelerates the analysis speed of cores after on-site coring, improves the analysis efficiency, and greatly improves the analysis accuracy without destroying the cores.
  • Figure 1 is a density curve diagram.
  • FIG. 2 is a graph showing relative atomic number.
  • FIG. 3 is a schematic diagram showing the analysis of inorganic minerals according to the present invention.
  • Figure 4 is a schematic diagram of micron CT extraction of organic matter (cyan represents organic matter).
  • FIG. 5 is a three-dimensional structure diagram of connected pores in a micrometer CT core and a pore distribution calculation calculated by the digital core technology according to an embodiment of the present invention.
  • a specific embodiment of the present invention provides a core sample analysis method, wherein the method comprises:
  • Step S1 Obtain a dual-energy spiral CT scan of a meter-sized large rock core to be analyzed; determine at least three small core samples from the meter-sized large rock core to be analyzed; wherein the dual-energy spiral CT scan includes a low-energy CT scan and a high-energy CT scan;
  • Step S2 obtaining an XRF scan of a surface characteristic region of each small core sample and a micrometer CT scan of each small core sample;
  • Step S3 using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area, respectively, the organic matter volume content (i.e., the volume ratio of the organic matter volume to the small core sample), the porosity (i.e., the volume ratio of the pores to the small core sample) and the inorganic mineral volume content (i.e., the volume ratio of the inorganic mineral volume to the small core sample) of each small core sample are determined;
  • Step S4 Based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample, determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • the core sample is composed of organic matter, pores and inorganic minerals, that is, for a certain core sample, the sum of the volume content of organic matter, porosity and volume content of inorganic minerals is 1.
  • the small core sample is of centimeter or millimeter scale.
  • the XRF scan image of the small core sample is a image obtained by scanning with microbeam X-ray fluorescence analysis.
  • the micron CT scan image of the small core sample is an image obtained by dual-energy scanning using a micron X-ray microscope.
  • the dual-energy spiral CT scan image of the meter-scale large core to be analyzed is an image obtained by scanning the dual-energy spiral CT with a standard sample.
  • step S3 using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area, respectively, to determine the organic matter volume content, porosity and inorganic mineral volume content of each small core sample includes:
  • Step S31 using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area, respectively determine the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample;
  • Step S32 based on the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample, respectively determine the organic matter volume content, porosity and inorganic mineral volume content of each small core sample;
  • step S31 the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample are determined by the following method:
  • Step S311 determining organic matter, pores and inorganic minerals in the surface characteristic region of the small core sample based on the micron CT scan image and XRF scan image of the surface characteristic region of the small core sample;
  • Step S312 Based on the micron CT scanning image features of organic matter, micron CT scanning image features of pores and micron CT scanning image features of inorganic minerals in the surface characteristic area of the small core sample, organic matter extraction, pore extraction and inorganic mineral extraction are performed in the micron CT scanning image of the small core sample to determine the organic matter distribution, porosity distribution and inorganic mineral distribution of the small core sample;
  • step S312 based on the grayscale of the micron CT scan image of organic matter, the grayscale of the micron CT scan image of pores, and the grayscale of the micron CT scan image of inorganic minerals in the surface characteristic area of the small core sample, organic matter extraction, pore extraction, and inorganic mineral extraction can be performed in the micron CT scan image of the small core sample to determine the organic matter distribution, porosity distribution, and inorganic mineral distribution of the small core sample;
  • step S311 the organic matter, pores and inorganic minerals in the surface characteristic area of the small core sample are preliminarily determined based on the micron CT scan image of the surface characteristic area of the small core sample, and then the components of the organic matter, pores and inorganic minerals in the preliminarily determined surface characteristic area of the small core sample are identified using the XRF scan image of the surface characteristic area of the small core sample, and then the organic matter, pores and inorganic minerals in the surface characteristic area of the small core sample are corrected, so as to accurately determine the organic matter, pores and inorganic minerals in the surface characteristic area of the small core sample.
  • step S4 based on the dual-energy spiral CT scan of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample, determines the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed, including:
  • Step S41 based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, determining the first CT characterization value and the second CT characterization value of each layer of the meter-scale large core to be analyzed; wherein the first CT characterization value is the CT characterization value corresponding to the low-energy CT scan image in the dual-energy spiral CT scan image, and the second CT characterization value is the CT characterization value corresponding to the high-energy CT scan image in the dual-energy spiral CT scan image;
  • Step S42 based on the volume content of organic matter, porosity and volume content of inorganic minerals of each small core sample, in combination with the first CT characterization value and the second CT characterization value of each layer corresponding to each small core sample in the meter-scale large core to be analyzed, respectively determine the contribution capacity of organic matter per unit volume content to the first CT characterization value, the contribution capacity of pores per unit volume content to the first CT characterization value, the contribution capacity of inorganic minerals per unit volume content to the first CT characterization value, the contribution capacity of organic matter per unit volume content to the second CT characterization value, the contribution capacity of pores per unit volume content to the second CT characterization value and the contribution capacity of inorganic minerals per unit volume content to the second CT characterization value;
  • Step S43 based on the first CT characterization value and the second CT characterization value of each layer of the meter-scale large core to be analyzed, combined with the contribution capacity of organic matter per unit volume content to the first CT characterization value, the contribution capacity of pores per unit volume content to the first CT characterization value, the contribution capacity of inorganic minerals per unit volume content to the first CT characterization value, the contribution capacity of organic matter per unit volume content to the second CT characterization value, the contribution capacity of pores per unit volume content to the second CT characterization value, and the contribution capacity of inorganic minerals per unit volume content to the second CT characterization value, determine the volume content of organic matter and/or the porosity and/or the volume content of inorganic minerals of each layer of the meter-scale large core to be analyzed, so as to achieve the determination of the volume content distribution of organic matter and/or the porosity distribution and/or the volume content distribution of inorganic minerals of the meter-scale large core to be analyzed;
  • step S42 the contribution capacity of organic matter per unit volume to the first CT characterization value, the contribution capacity of pores per unit volume to the first CT characterization value, the contribution capacity of inorganic minerals per unit volume to the first CT characterization value, the contribution capacity of organic matter per unit volume to the second CT characterization value, the contribution capacity of pores per unit volume to the second CT characterization value, and the contribution capacity of inorganic minerals per unit volume to the second CT characterization value respectively satisfy:
  • CT x X 1 ⁇ V 1 + X 2 ⁇ V 2 + X 3 ⁇ V 3
  • CT Y Y 1 ⁇ V 1 +Y 2 ⁇ V 2 +Y 3 ⁇ V 3
  • CT x is the first CT characterization value
  • X 1 is the contribution of organic matter per unit volume to the first CT characterization value
  • V 1 is the volume content of organic matter
  • X 2 is the contribution of pores per unit volume to the first CT characterization value
  • V 2 is the porosity
  • X 3 is the contribution of inorganic minerals per unit volume to the first CT characterization value
  • V 3 is the volume content of inorganic minerals
  • CT Y is the second CT characterization value
  • Y 1 is the contribution of organic matter per unit volume to the second CT characterization value
  • Y 2 is the contribution of pores per unit volume to the second CT characterization value
  • Y 3 is the contribution of inorganic minerals per unit volume to the second CT characterization value
  • the first CT characterization value can characterize the relative atomic number
  • the second CT characterization value can characterize the average density
  • the first CT characterization value is a grayscale value
  • the second CT characterization value is a grayscale value
  • the first CT characterization value is a relative atomic number
  • the second CT characterization value is an average density
  • the method further comprises: using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area to respectively determine the organic carbon content of each small core sample;
  • organic carbon content of each small core sample was determined by the following method:
  • the organic matter in the surface characteristic area of the small core sample is determined;
  • the organic matter in the micron CT scanning image of the small core sample is extracted, and then the volume of the organic matter in the small core sample is determined in combination with the volume of the small core sample;
  • Micrometer CT scans of organic matter from small core samples were used to determine the density of organic matter
  • the volume, density and carbon mass content of organic matter are used together with the mass of the small core sample to determine the organic carbon content (TOC) of the small core sample.
  • organic carbon content TOC is determined by the following formula:
  • TOC is the organic carbon content
  • m C is the total organic carbon mass
  • m O is the total mass of organic matter
  • m 2 is the mass of the core sample to be analyzed
  • ⁇ O is the density of organic matter
  • V O is the volume of organic matter
  • W OC is the mass content of carbon element in organic matter
  • the density of organic matter can be determined by conventional methods using the micron CT scan of organic matter in the small core sample; for example, the density of organic matter can be determined by combining the average grayscale of the micron CT scan of organic matter in the small core sample with the grayscale of the micron CT scan of the standard sample.
  • the method further comprises: using the micron CT scans of each small core sample and the XRF scans of the surface characteristic areas, combined with the dual-energy spiral CT scans of the meter-scale large core to be analyzed and the volume content distribution of organic matter in the meter-scale large core to be analyzed, to determine the distribution of organic carbon content in the meter-scale large core to be analyzed;
  • the distribution of organic carbon content in the meter-scale large core to be analyzed is determined to include:
  • the density of organic matter was determined using micrometer CT scans of organic matter in each small core sample
  • the average density of each layer of the meter-scale large core to be analyzed is determined by using the dual-energy spiral CT scan image of the meter-scale large core to be analyzed;
  • the organic carbon content of each layer of the meter-scale large core to be analyzed is determined by using the density and carbon mass content of organic matter, combined with the average density and organic volume content of each layer of the meter-scale large core to be analyzed;
  • organic carbon content of each layer of the meter-scale core to be analyzed is determined by the following formula:
  • the density of organic matter can be determined by using the micron CT scan of organic matter in the small core sample in a conventional manner; for example, the density of organic matter can be determined by combining the average grayscale of the micron CT scan of organic matter in the small core sample with the grayscale of the micron CT scan of the standard sample;
  • the average density of each layer of the meter-scale large rock core to be analyzed is determined by using the dual-energy spiral CT scan image of the meter-scale large rock core to be analyzed, and the conventional method can be used; for example, the average grayscale of the high-energy CT scan image in the dual-energy spiral CT scan image of each layer of the meter-scale large rock core to be analyzed is combined with the grayscale of the CT scan image of the standard sample to determine the average density of each layer of the meter-scale large rock core to be analyzed.
  • the method further includes: determining the type of organic matter using the micron CT scans of each small core sample and the XRF scans of the surface characteristic areas;
  • the type of organic matter is determined by the ratio of the number of oxygen and carbon atoms in the organic matter
  • the ratio of oxygen and carbon atoms in organic matter can be determined by the following formula:
  • R OC is the ratio of oxygen to carbon atoms in organic matter
  • W OO is the mass content of oxygen in organic matter
  • W OC is the mass content of carbon in organic matter
  • the ratio of oxygen to carbon atoms when the organic matter type is type I kerogen is less than the ratio of oxygen to carbon atoms when the organic matter type is type II kerogen, which is less than the ratio of oxygen to carbon atoms when the organic matter type is type III kerogen.
  • the type of organic matter is determined by the ratio of the number of hydrogen and carbon atoms in the organic matter
  • the ratio of hydrogen and carbon atoms in organic matter can be determined by the following formula:
  • R OC is the ratio of hydrogen to carbon atoms in organic matter
  • W OH is the mass content of hydrogen in organic matter
  • W OC is the mass content of carbon in organic matter
  • the ratio of the number of hydrogen and carbon atoms when the organic matter type is type I kerogen and the ratio of the number of hydrogen and carbon atoms when the organic matter type is type II kerogen are greater than the ratio of the number of hydrogen and carbon atoms when the organic matter type is type III kerogen.
  • the method further comprises: determining the maturity of organic matter using micron CT scans of each small core sample and XRF scans of characteristic areas of the surface layer;
  • organic matter maturity is determined in the following way:
  • Z0 is the average atomic number of organic matter
  • fi is the ratio of the number of electrons that the i-th component element of organic matter contributes to the organic matter
  • Zi is the atomic number of the i-th component element of organic matter
  • n i is the number of atoms of the i-th component element of organic matter
  • N is the total number of components of organic matter
  • A is a coefficient, which is usually 3.2;
  • determining the vitrinite reflectance of the organic matter includes:
  • the relationship between the vitrinite reflectance of the organic matter and the average atomic number can be determined by fitting the vitrinite reflectance of the standard sample and the average atomic number;
  • the vitrinite reflectance of organic matter is determined by using the relationship between the vitrinite reflectance of organic matter and the average atomic number;
  • the method further comprises:
  • Whether it is a source rock is determined based on the maturity of organic matter.
  • the method further comprises: determining the inorganic mineral composition using the micron CT scans of each small core sample and the XRF scans of the surface characteristic areas;
  • the inorganic mineral composition was determined by:
  • the elemental composition and content of each element of each inorganic mineral are determined; based on the elemental composition and content of each element of each inorganic mineral, the mineral types of each inorganic mineral are determined;
  • various inorganic minerals are extracted from the micron CT scanning images of each small core sample, and then the proportion of various inorganic minerals in the inorganic minerals is determined;
  • inorganic mineral composition determines (the mineral types of inorganic minerals and the proportion of each type of inorganic mineral are determined).
  • the method further comprises:
  • the pore size, pore distribution characteristics and effective porosity (ratio of connected pore volume to core volume) of each small core sample were determined.
  • the embodiment of the present invention also provides a specific implementation of a core sample analysis system, which is used to implement the above core sample analysis method embodiment.
  • the system includes:
  • the large core data acquisition module 21 is used to obtain a dual-energy spiral CT scan image of a meter-scale large core to be analyzed; determine at least three small core samples from the meter-scale large core to be analyzed; wherein the dual-energy spiral CT scan image includes a low-energy CT scan image and a high-energy CT scan image;
  • Small core data acquisition module 22 used to obtain XRF scans of surface characteristic areas of each small core sample and micrometer CT scans of each small core sample;
  • Small core parameter determination module 23 used to determine the organic matter volume content (i.e., the volume ratio of organic matter volume to small core sample), porosity (i.e., the volume ratio of pores to small core sample) and inorganic mineral volume content (i.e., the volume ratio of inorganic mineral volume to small core sample) of each small core sample by using the micron CT scan image of each small core sample and the XRF scan image of the surface characteristic area;
  • organic matter volume content i.e., the volume ratio of organic matter volume to small core sample
  • porosity i.e., the volume ratio of pores to small core sample
  • inorganic mineral volume content i.e., the volume ratio of inorganic mineral volume to small core sample
  • Large core parameter determination module 24 used to determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample.
  • the small core sample is of centimeter or millimeter scale.
  • the XRF scan image of the small core sample is a image obtained by scanning with microbeam X-ray fluorescence analysis.
  • the micron CT scan image of the small core sample is an image obtained by dual-energy scanning using a micron X-ray microscope.
  • the dual-energy spiral CT scan image of the meter-scale large core to be analyzed is an image obtained by scanning the dual-energy spiral CT with a standard sample.
  • the small core parameter determination module 23 includes:
  • the first determination submodule 231 is used to determine the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample by using the micron CT scan image of each small core sample and the XRF scan image of the surface characteristic area;
  • the second determination submodule 232 is used to determine the organic matter volume content, porosity and inorganic mineral volume content of each small core sample based on the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample;
  • the first determining submodule 231 includes:
  • Surface characteristic region extraction unit 2311 used to determine organic matter, pores and inorganic minerals in the surface characteristic region of the small core sample based on the micron CT scan image and XRF scan image of the surface characteristic region of the small core sample;
  • Distribution determination unit 2312 is used to extract organic matter, pores and inorganic minerals from the micron CT scan image of the small core sample based on the micron CT scan image features of organic matter, the micron CT scan image features of pores and the micron CT scan image features of inorganic minerals in the surface characteristic area of the small core sample, so as to determine the organic matter distribution, porosity distribution and inorganic mineral distribution of the small core sample.
  • the large core parameter determination module 24 includes:
  • CT characterization value determination submodule 241 used to determine the first CT characterization value and the second CT characterization value of each layer of the meter-level large rock core to be analyzed based on the dual-energy spiral CT scan image of the meter-level large rock core to be analyzed; wherein the first CT characterization value is the CT characterization value corresponding to the low-energy CT scan image in the dual-energy spiral CT scan image, and the second CT characterization value is the CT characterization value corresponding to the high-energy CT scan image in the dual-energy spiral CT scan image;
  • Contribution capacity determination submodule 242 used to determine the contribution capacity of organic matter per unit volume content to the first CT characterization value, the contribution capacity of pores per unit volume content to the first CT characterization value, the contribution capacity of inorganic minerals per unit volume content to the first CT characterization value, the contribution capacity of organic matter per unit volume content to the second CT characterization value, the contribution capacity of pores per unit volume content to the second CT characterization value, and the contribution capacity of inorganic minerals per unit volume content to the second CT characterization value, based on the volume content of organic matter, porosity and volume content of inorganic minerals of each small core sample and in combination with the first CT characterization value and the second CT characterization value of each layer corresponding to each small core sample in the meter-scale large core to be analyzed;
  • Large core parameter determination submodule 243 used to determine the organic matter volume content and/or porosity and/or inorganic mineral volume content of each layer of the meter-scale large core to be analyzed based on the first CT characterization value and the second CT characterization value of each layer of the meter-scale large core to be analyzed, combined with the contribution capacity of unit volume content of organic matter to the first CT characterization value, the contribution capacity of unit volume content of pores to the first CT characterization value, the contribution capacity of unit volume content of inorganic minerals to the first CT characterization value, the contribution capacity of unit volume content of organic matter to the second CT characterization value, the contribution capacity of unit volume content of pores to the second CT characterization value and the contribution capacity of unit volume content of inorganic minerals to the second CT characterization value, so as to determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • the contribution capacity of organic matter per unit volume to the first CT characterization value, the contribution capacity of pores per unit volume to the first CT characterization value, the contribution capacity of inorganic minerals per unit volume to the first CT characterization value, the contribution capacity of organic matter per unit volume to the second CT characterization value, the contribution capacity of pores per unit volume to the second CT characterization value, and the contribution capacity of inorganic minerals per unit volume to the second CT characterization value respectively satisfy:
  • CT x X 1 ⁇ V 1 + X 2 ⁇ V 2 + X 3 ⁇ V 3
  • CT Y Y 1 ⁇ V 1 +Y 2 ⁇ V 2 +Y 3 ⁇ V 3
  • CT x is the first CT characterization value
  • X 1 is the contribution of organic matter per unit volume to the first CT characterization value
  • V 1 is the volume content of organic matter
  • X 2 is the contribution of pores per unit volume to the first CT characterization value
  • V 2 is the porosity
  • X 3 is the contribution of inorganic minerals per unit volume to the first CT characterization value
  • V 3 is the volume content of inorganic minerals
  • CT Y is the second CT characterization value
  • Y 1 is the contribution of organic matter per unit volume to the second CT characterization value
  • Y 2 is the contribution of pores per unit volume to the second CT characterization value
  • Y 3 is the contribution of inorganic minerals per unit volume to the second CT characterization value
  • the first CT characterization value can characterize the relative atomic number
  • the second CT characterization value can characterize the average density
  • the first CT characterization value is a grayscale value
  • the second CT characterization value is a grayscale value
  • the first CT characterization value is a relative atomic number
  • the second CT characterization value is an average density
  • system further comprises:
  • Small core organic carbon content determination module 25 used to determine the organic carbon content of each small core sample using the micron CT scan image of each small core sample and the XRF scan image of the surface characteristic area;
  • the small core organic carbon content determination module 25 is specifically used to determine the organic carbon content of each small core sample in the following manner:
  • the organic matter in the surface characteristic area of the small core sample is determined;
  • the organic matter in the micron CT scanning image of the small core sample is extracted, and then the volume of the organic matter in the small core sample is determined in combination with the volume of the small core sample;
  • Micrometer CT scans of organic matter from small core samples were used to determine the density of organic matter
  • the volume, density and carbon mass content of organic matter are used together with the mass of the small core sample to determine the organic carbon content (TOC) of the small core sample.
  • organic carbon content TOC is determined by the following formula:
  • TOC is the organic carbon content
  • m C is the total organic carbon mass
  • m O is the total mass of organic matter
  • m 2 is the mass of the core sample to be analyzed
  • ⁇ O is the density of organic matter
  • V O is the volume of organic matter
  • W OC is the mass content of carbon element in organic matter.
  • system further comprises:
  • Organic carbon content distribution determination module 26 used to determine the organic carbon content distribution of the meter-scale large core to be analyzed by using the micron CT scan image of each small core sample and the XRF scan image of the surface characteristic area, combined with the dual-energy spiral CT scan image of the meter-scale large core to be analyzed and the organic matter volume content distribution of the meter-scale large core to be analyzed;
  • the organic carbon content distribution determination module 26 is used to determine the organic carbon content distribution of the meter-scale large core to be analyzed in the following manner:
  • the density of organic matter was determined using micrometer CT scans of organic matter in each small core sample
  • the average density of each layer of the meter-scale large core to be analyzed is determined by using the dual-energy spiral CT scan of the meter-scale large core to be analyzed;
  • the organic carbon content of each layer of the meter-scale large core to be analyzed is determined by using the density and carbon mass content of organic matter, combined with the average density and organic volume content of each layer of the meter-scale large core to be analyzed;
  • organic carbon content of each layer of the meter-scale core to be analyzed is determined by the following formula:
  • system further comprises:
  • Organic matter type determination module 27 used to determine the type of organic matter using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area;
  • the organic matter type determination module 27 is used to determine the organic matter type in the following manner:
  • the type of organic matter is determined by the ratio of the number of oxygen and carbon atoms in the organic matter
  • the ratio of oxygen and carbon atoms in organic matter can be determined by the following formula:
  • R OC is the ratio of oxygen to carbon atoms in organic matter
  • W OO is the mass content of oxygen in organic matter
  • W OC is the mass content of carbon in organic matter
  • the ratio of oxygen to carbon atoms when the organic matter type is type I kerogen is less than the ratio of oxygen to carbon atoms when the organic matter type is type II kerogen, which is less than the ratio of oxygen to carbon atoms when the organic matter type is type III kerogen.
  • the organic matter type determination module 27 is used to determine the organic matter type in the following manner:
  • the type of organic matter is determined by the ratio of the number of hydrogen and carbon atoms in the organic matter
  • the ratio of hydrogen and carbon atoms in organic matter can be determined by the following formula:
  • R OC is the ratio of hydrogen to carbon atoms in organic matter
  • W OH is the mass content of hydrogen in organic matter
  • W OC is the mass content of carbon in organic matter
  • the ratio of the number of hydrogen and carbon atoms when the organic matter type is type I kerogen and the ratio of the number of hydrogen and carbon atoms when the organic matter type is type II kerogen are greater than the ratio of the number of hydrogen and carbon atoms when the organic matter type is type III kerogen.
  • system further comprises:
  • Organic matter maturity determination module 28 used to determine the organic matter maturity using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area;
  • the organic matter maturity determination module 28 is used to determine the organic matter maturity in the following manner:
  • Z0 is the average atomic number of organic matter
  • fi is the ratio of the number of electrons that the i-th component element of organic matter contributes to the organic matter
  • Zi is the atomic number of the i-th component element of organic matter
  • n i is the number of atoms of the i-th component element of organic matter
  • N is the total number of components of organic matter
  • A is a coefficient, which is usually 3.2;
  • the organic matter maturity determination module 28 is used to determine the average atomic number of the organic matter in the following manner:
  • the relationship between the vitrinite reflectance of the organic matter and the average atomic number can be determined by fitting the vitrinite reflectance of the standard sample and the average atomic number;
  • the vitrinite reflectance of organic matter is determined by using the relationship between the vitrinite reflectance of organic matter and the average atomic number;
  • system further comprises:
  • the hydrocarbon source rock determination module 29 is used to determine whether it is a hydrocarbon source rock based on the maturity of organic matter.
  • system further comprises:
  • Inorganic mineral composition determination module 30 used to determine the inorganic mineral composition using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area;
  • the inorganic mineral composition determination module 30 is used to determine the inorganic mineral composition in the following manner:
  • the elemental composition and content of each element of each inorganic mineral are determined; based on the elemental composition and content of each element of each inorganic mineral, the mineral types of each inorganic mineral are determined;
  • various inorganic minerals are extracted from the micron CT scanning images of each small core sample, and then the proportion of various inorganic minerals in the inorganic minerals is determined;
  • inorganic mineral composition determines (the mineral types of inorganic minerals and the proportion of each type of inorganic mineral are determined).
  • system further comprises:
  • Pore parameter determination module 31 used for micron CT scanning images of each small core sample to determine the pore size, pore distribution characteristics and effective porosity (ratio of connected pore volume to core volume) of each small core sample.
  • the embodiment of the present invention also provides a specific implementation of an electronic device capable of implementing all steps in the core sample analysis method in the above embodiment, and the electronic device specifically includes the following contents:
  • the processor, the memory, and the communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between the server-side device and the client device and other related devices; the processor is used to call the computer program in the memory, and when the processor executes the computer program, all the steps in the core sample analysis method in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:
  • Step S1 Obtain a dual-energy spiral CT scan of a meter-sized large rock core to be analyzed; determine at least three small core samples from the meter-sized large rock core to be analyzed; wherein the dual-energy spiral CT scan includes a low-energy CT scan and a high-energy CT scan;
  • Step S2 obtaining an XRF scan of a surface characteristic region of each small core sample and a micrometer CT scan of each small core sample;
  • Step S3 using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area, respectively, the organic matter volume content (i.e., the volume ratio of the organic matter volume to the small core sample), the porosity (i.e., the volume ratio of the pores to the small core sample) and the inorganic mineral volume content (i.e., the volume ratio of the inorganic mineral volume to the small core sample) of each small core sample are determined;
  • Step S4 Based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample, determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • the embodiment of the present invention also provides a computer-readable storage medium capable of implementing all the steps in the core sample analysis method in the above embodiment.
  • the computer-readable storage medium stores a computer program.
  • the computer program is executed by a processor, all the steps in the core sample analysis method in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:
  • Step S1 Obtain a dual-energy spiral CT scan of a meter-sized large rock core to be analyzed; determine at least three small core samples from the meter-sized large rock core to be analyzed; wherein the dual-energy spiral CT scan includes a low-energy CT scan and a high-energy CT scan;
  • Step S2 obtaining an XRF scan of a surface characteristic region of each small core sample and a micrometer CT scan of each small core sample;
  • Step S3 using the micron CT scan of each small core sample and the XRF scan of the surface characteristic area, respectively, the organic matter volume content (i.e., the volume ratio of the organic matter volume to the small core sample), the porosity (i.e., the volume ratio of the pores to the small core sample) and the inorganic mineral volume content (i.e., the volume ratio of the inorganic mineral volume to the small core sample) of each small core sample are determined;
  • Step S4 Based on the dual-energy spiral CT scan image of the meter-scale large core to be analyzed, combined with the organic matter volume content, porosity and inorganic mineral volume content of each small core sample, determine the organic matter volume content distribution and/or porosity distribution and/or inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • This embodiment provides a core sample analysis method, which is used to analyze meter-scale cores of oil-producing rocks, and specifically includes:
  • the average density and relative atomic number of different layers in the meter-scale large core to be analyzed will have obvious high and low variations. Based on the average density and relative atomic number of each layer in the meter-scale large core to be analyzed, the typical rock section in the meter-scale large core to be analyzed is determined, and multiple small core samples (centimeter or millimeter level) are determined from the typical rock section.
  • C. Scan the characteristic area of the surface of each small core sample by microbeam X-ray fluorescence analysis (Micro-XRF) to obtain the XRF scan image of the surface characteristic area of each small core sample; perform dual energy scanning on each small core sample by micron X-ray microscope (Micro-CT) to obtain the micron CT scan image of each small core sample.
  • Micro-XRF microbeam X-ray fluorescence analysis
  • Micro-CT micron X-ray microscope
  • the elemental composition and mass fraction of each element in the surface characteristic areas of each small core sample are determined (including main organic elements such as carbon W C , sulfur W S , nitrogen W N , oxygen W O and trace elements such as iron W Fe , copper W Cu , magnesium W Mg , zinc W Zn , molybdenum W Mu , nickel W Ni , mercury W Hg and so on).
  • the organic matter (as shown in FIG. 4 ), pores and inorganic minerals in the surface characteristic areas of each small core sample are determined; based on the micron CT scan features of the organic matter, the micron CT scan features of the pores and the micron CT scan features of the inorganic minerals in the surface characteristic areas of each small core sample, organic matter extraction, pore extraction and inorganic mineral extraction are performed in the micron CT scans of each small core sample to determine the organic matter distribution, porosity distribution and inorganic mineral distribution of each small core sample;
  • the volume of organic matter, the volume of pores and the volume of inorganic minerals in each small core sample are determined in combination with the volume of each small core sample, thereby determining the volume content of organic matter, porosity and volume content of inorganic minerals in each small core sample;
  • the average grayscale of the micrometer CT scan of the organic matter of each small core sample is used to determine the organic matter density (based on the scanned standard sample), mass and relative atomic number (based on the scanned standard sample) of each small core sample, and then the average density and average relative atomic number of the organic matter are determined by weighted average as the organic matter density and organic matter relative atomic number of the meter-scale large core to be analyzed;
  • the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of each small core sample were determined, and then the average carbon mass content, average oxygen mass content, average sulfur mass content and average nitrogen mass content of the organic matter were determined by weighted average as the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of the meter-scale large core to be analyzed.
  • the first CT grayscale value is the CT grayscale value corresponding to the low-energy CT scan in the dual-energy spiral CT scan
  • the second CT grayscale value is the CT grayscale value corresponding to the high-energy CT scan in the dual-energy spiral CT scan
  • the contribution capacity of organic matter per unit volume content to the first CT grayscale value, the contribution capacity of pores per unit volume content to the first CT grayscale value, the contribution capacity of inorganic minerals per unit volume content to the first CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of pores per unit volume content to the second CT grayscale value and the contribution capacity of inorganic minerals per unit volume content to the second CT grayscale value are determined respectively; wherein, the contribution capacity of organic matter per unit volume content to the first CT grayscale value, the contribution capacity of pores per unit volume content to the first CT grayscale value, the contribution capacity of inorganic minerals per unit volume content to the first CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to
  • CT x X 1 ⁇ V 1 + X 2 ⁇ V 2 + X 3 ⁇ V 3
  • CT Y Y 1 ⁇ V 1 +Y 2 ⁇ V 2 +Y 3 ⁇ V 3
  • CT x is the first CT gray value
  • X 1 is the contribution of organic matter per unit volume to the first CT gray value
  • V 1 is the volume content of organic matter
  • X 2 is the contribution of pores per unit volume to the first CT gray value
  • V 2 is the porosity
  • X 3 is the contribution of inorganic minerals per unit volume to the first CT gray value
  • V 3 is the volume content of inorganic minerals
  • CT Y is the second CT gray value
  • Y 1 is the contribution of organic matter per unit volume to the second CT gray value
  • Y 2 is the contribution of pores per unit volume to the second CT gray value
  • Y 3 is the contribution of inorganic minerals per unit volume to the second CT gray value
  • the organic matter volume content, porosity and inorganic mineral volume content of each layer of the meter-scale large core to be analyzed are determined, thereby realizing the determination of organic matter volume content distribution, porosity distribution and inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • the volume, density and carbon mass content of organic matter, combined with the mass of the core sample are used to determine the organic carbon content TOC of each small core sample using the following formula;
  • TOC is the organic carbon content
  • m C is the total organic carbon mass
  • m O is the total mass of organic matter
  • m 2 is the mass of the core sample to be analyzed
  • ⁇ O is the density of organic matter
  • V O is the volume of organic matter
  • W OC is the mass content of carbon element in organic matter.
  • the organic carbon content of each layer of the meter-scale large core to be analyzed is determined by the following formula:
  • J. Determine the average atomic number of organic matter based on the elemental composition and the content of each element of the organic matter in the meter-scale large core to be analyzed; obtain the relationship between the vitrinite reflectance of organic matter and the average atomic number; based on the average atomic number of organic matter, determine the vitrinite reflectance of organic matter using the relationship between the vitrinite reflectance of organic matter and the average atomic number; wherein the average atomic number of organic matter is determined by the following formula: Wherein, Z0 is the average atomic number of organic matter; fi is the ratio of the number of electrons that the i-th component element of organic matter contributes to the organic matter; Zi is the atomic number of the i-th component element of organic matter; ni is the number of atoms of the i-th component element of the organic matter phase; N is the total number of components of organic matter; A is the coefficient, which is 3.2;
  • Whether it is a source rock is determined based on the maturity of organic matter.
  • various inorganic minerals in the surface characteristic area are determined based on the micron CT scan and XRF scan of the surface characteristic area.
  • Various minerals in the micron CT scan are extracted based on the micron CT scan characteristics of various minerals in the surface characteristic area to determine the distribution of inorganic minerals (as shown in Figure 3).
  • This embodiment provides a core sample analysis method, which is used to analyze meter-scale cores of reservoirs, and specifically includes:
  • A. Perform dual-energy spiral CT scanning with standard samples on the meter-scale large core to be analyzed in the reservoir to obtain the dual-energy spiral CT scanning image of each layer of the meter-scale large core to be analyzed; and determine the relative atomic number and average density of each layer of the meter-scale large core to be analyzed based on the dual-energy spiral CT scanning image of the meter-scale large core to be analyzed; wherein the relative atomic number is the CT characterization value corresponding to the low-energy CT scanning image in the dual-energy spiral CT scanning image, and the average density is the CT characterization value corresponding to the high-energy CT scanning image in the dual-energy spiral CT scanning image.
  • the typical rock section in the meter-scale large core to be analyzed is determined, and multiple small core samples (centimeter or millimeter level) are determined from the typical rock section.
  • C. Scan the characteristic area of the surface of each small core sample by microbeam X-ray fluorescence analysis (Micro-XRF) to obtain the XRF scan image of the surface characteristic area of each small core sample; perform dual energy scanning on each small core sample by micron X-ray microscope (Micro-CT) to obtain the micron CT scan image of each small core sample.
  • Micro-XRF microbeam X-ray fluorescence analysis
  • Micro-CT micron X-ray microscope
  • the elemental composition and mass fraction of each element in the surface characteristic areas of each small core sample are determined (including main organic elements such as carbon W C , sulfur W S , nitrogen W N , oxygen W O and trace elements such as iron W Fe , copper W Cu , magnesium W Mg , zinc W Zn , molybdenum W Mu , nickel W Ni , mercury W Hg and so on).
  • the volume of organic matter, the volume of pores and the volume of inorganic minerals in each small core sample are determined in combination with the volume of each small core sample, thereby determining the volume content of organic matter, porosity and volume content of inorganic minerals in each small core sample;
  • the average grayscale of the micrometer CT scan of the organic matter of each small core sample is used to determine the organic matter density (based on the scanned standard sample), mass and relative atomic number (based on the scanned standard sample) of each small core sample, and then the average density and average relative atomic number of the organic matter are determined by weighted average as the organic matter density and organic matter relative atomic number of the meter-scale large core to be analyzed;
  • the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of each small core sample were determined, and then the average carbon mass content, average oxygen mass content, average sulfur mass content and average nitrogen mass content of the organic matter were determined by weighted average as the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of the meter-scale large core to be analyzed.
  • CT x X 1 ⁇ V 1 + X 2 ⁇ V 2 + X 3 ⁇ V 3
  • CT Y Y 1 ⁇ V 1 +Y 2 ⁇ V 2 +Y 3 ⁇ V 3
  • CT x is the relative atomic number
  • X 1 is the contribution of organic matter per unit volume to the relative atomic number
  • V 1 is the volume content of organic matter
  • X 2 is the contribution of pores per unit volume to the relative atomic number
  • V 2 is the porosity
  • X 3 is the contribution of inorganic minerals per unit volume to the relative atomic number
  • V 3 is the volume content of inorganic minerals
  • CT Y is the average density
  • Y 1 is the contribution of organic matter per unit volume to the average density
  • Y 2 is the contribution of pores per unit volume to the average density
  • Y 3 is the contribution of inorganic minerals per unit volume to the average density
  • the volume content of organic matter and/or the porosity and/or the volume content of inorganic minerals per unit volume of each layer of the meter-scale large core to be analyzed are determined, thereby achieving the determination of the volume content distribution of organic matter and/or the porosity distribution and/or the volume content distribution of inorganic minerals of the meter-scale large core to be analyzed.
  • F. Determine the average atomic number of the organic matter based on the elemental composition and the content of each element of the organic matter in the meter-scale large core to be analyzed; obtain the relationship between the vitrinite reflectance of the organic matter and the average atomic number; based on the average atomic number of the organic matter, determine the vitrinite reflectance of the organic matter using the relationship between the vitrinite reflectance of the organic matter and the average atomic number; wherein the average atomic number of the organic matter is determined by the following formula: In the formula, Z0 is the average atomic number of organic matter; fi is the ratio of the number of electrons contributing to the i-th component of organic matter in organic matter; Zi is the atomic number of the i-th component of organic matter; ni is the number of atoms of the i-th component of the organic matter phase; N is the total number of components of organic matter; A is the coefficient, which is 3.2.
  • the rock phase in the surface characteristic area is determined based on the micron CT scan and XRF scan of the surface characteristic area; the elemental composition and the content of each element of the rock phase (including the content of trace elements such as iron, copper, magnesium, zinc, molybdenum, nickel, and mercury) are determined based on the XRF scan of the rock phase in the surface characteristic area; the mineral composition is determined based on the elemental composition and the content of each element of the rock phase; based on the CT scan characteristics of each type of mineral in the surface characteristic area, the various minerals in the CT scan are extracted to determine the mineral distribution.
  • various inorganic minerals in the surface characteristic area are determined based on the micron CT scan and XRF scan of the surface characteristic area.
  • Various minerals in the micron CT scan are extracted based on the micron CT scan characteristics of various minerals in the surface characteristic area to determine the distribution of inorganic minerals (as shown in Figure 3).
  • This embodiment provides a core sample analysis method, which is used to analyze meter-scale cores of caprocks, and specifically includes:
  • A. Perform dual-energy spiral CT scanning with standard samples on the meter-scale large core to be analyzed in the cap layer to obtain the dual-energy spiral CT scanning image of each layer of the meter-scale large core to be analyzed; and based on the dual-energy spiral CT scanning image of the meter-scale large core to be analyzed, determine the relative atomic number and average density of each layer of the meter-scale large core to be analyzed; wherein the relative atomic number is the CT characterization value corresponding to the low-energy CT scanning image in the dual-energy spiral CT scanning image, and the average density is the CT characterization value corresponding to the high-energy CT scanning image in the dual-energy spiral CT scanning image.
  • the typical rock section in the meter-scale large core to be analyzed is determined, and multiple small core samples (centimeter or millimeter level) are determined from the typical rock section.
  • C. Scan the characteristic area of the surface of each small core sample by microbeam X-ray fluorescence analysis (Micro-XRF) to obtain the XRF scan image of the surface characteristic area of each small core sample; perform dual energy scanning on each small core sample by micron X-ray microscope (Micro-CT) to obtain the micron CT scan image of each small core sample.
  • Micro-XRF microbeam X-ray fluorescence analysis
  • Micro-CT micron X-ray microscope
  • the elemental composition and mass fraction of each element in the surface characteristic areas of each small core sample are determined (including main organic elements such as carbon W C , sulfur W S , nitrogen W N , oxygen W O and trace elements such as iron W Fe , copper W Cu , magnesium W Mg , zinc W Zn , molybdenum W Mu , nickel W Ni , mercury W Hg and so on).
  • the volume of organic matter, the volume of pores and the volume of inorganic minerals in each small core sample are determined in combination with the volume of each small core sample, thereby determining the volume content of organic matter, porosity and volume content of inorganic minerals in each small core sample;
  • the average grayscale of the micron CT scan of the organic matter of each small core sample is used to determine the organic matter density (based on the scanned standard sample), mass and relative atomic number (based on the scanned standard sample) of each small core sample, and then the average density and average relative atomic number of the organic matter are determined by weighted average as the organic matter density and organic matter relative atomic number of the meter-scale large core to be analyzed;
  • the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of each small core sample were determined, and then the average carbon mass content, average oxygen mass content, average sulfur mass content and average nitrogen mass content of the organic matter were determined by weighted average as the mass contents of carbon, oxygen, sulfur and nitrogen in the organic matter of the meter-scale large core to be analyzed.
  • the first CT grayscale value is the CT grayscale value corresponding to the low-energy CT scan in the dual-energy spiral CT scan
  • the second CT grayscale value is the CT grayscale value corresponding to the high-energy CT scan in the dual-energy spiral CT scan
  • the contribution capacity of organic matter per unit volume content to the first CT grayscale value, the contribution capacity of pores per unit volume content to the first CT grayscale value, the contribution capacity of inorganic minerals per unit volume content to the first CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of pores per unit volume content to the second CT grayscale value and the contribution capacity of inorganic minerals per unit volume content to the second CT grayscale value are determined respectively; wherein, the contribution capacity of organic matter per unit volume content to the first CT grayscale value, the contribution capacity of pores per unit volume content to the first CT grayscale value, the contribution capacity of inorganic minerals per unit volume content to the first CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to the second CT grayscale value, the contribution capacity of organic matter per unit volume content to
  • CT x X 1 ⁇ V 1 + X 2 ⁇ V 2 + X 3 ⁇ V 3
  • CT Y Y 1 ⁇ V 1 +Y 2 ⁇ V 2 +Y 3 ⁇ V 3
  • CT x is the first CT gray value
  • X 1 is the contribution of organic matter per unit volume to the first CT gray value
  • V 1 is the volume content of organic matter
  • X 2 is the contribution of pores per unit volume to the first CT gray value
  • V 2 is the porosity
  • X 3 is the contribution of inorganic minerals per unit volume to the first CT gray value
  • V 3 is the volume content of inorganic minerals
  • CT Y is the second CT gray value
  • Y 1 is the contribution of organic matter per unit volume to the second CT gray value
  • Y 2 is the contribution of pores per unit volume to the second CT gray value
  • Y 3 is the contribution of inorganic minerals per unit volume to the second CT gray value
  • the organic matter volume content, porosity and inorganic mineral volume content of each layer of the meter-scale large core to be analyzed are determined, thereby realizing the determination of the organic matter volume content distribution, porosity distribution and inorganic mineral volume content distribution of the meter-scale large core to be analyzed.
  • various inorganic minerals in the surface characteristic area are determined based on the micron CT scan and XRF scan of the surface characteristic area.
  • Various minerals are extracted from the micron CT scan based on the micron CT scan characteristics of various minerals in the surface characteristic area to determine the distribution of inorganic minerals.

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Abstract

本发明提供了一种岩心样品分析方法、系统、电子设备及存储介质。该方法包括：获取待分析米级大岩心的双能量螺旋CT扫描图，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；获取各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图；分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。

Description

一种岩心样品分析方法、系统、电子设备及存储介质 技术领域
本发明涉及石油测井技术领域，特别涉及一种岩心样品分析方法、系统、电子设备及存储介质。
背景技术
在油气田勘探、开发及评价过程中，通常利用测井数据确定地球物理参数。利用岩层的电化学特性、导电特性、声学特性、放射性等地球物理特性识别油层、气层、岩层、水层，并具体确定油藏储层位置、岩性、有机质丰度及成熟度等性质。测井数据仅能间接地、有条件地反映岩层地质特性。为了全面认识油气田的地质面貌、准确确定和评价油气层，通常需要进行取芯作业，将取得的岩心进行制样并采用多种实验仪器利用多种方法进行岩心样品分析实现生储层的关键参数确定。
常规实验室岩心样品分析方法中，通常采用SEM、BSE、EDS、燃烧法等进行微观矿物成分分析和有机质分析，通常采用压汞法、渗流法、驱替法等进行宏观孔隙度、渗透率分析。常规实验室岩心样品分析方法通常流程繁杂费时费工，效率低下。并且常规实验室岩心样品分析方法需要破坏岩心样品，导致分析数据零散，各种性质参数无法在同一区域或同一样品上一一对应。并且常规实验室岩心样品分析方法分析尺度跨越大，造成微观与宏观分析脱节，导致结果对实际生产指导意义下降。
综上所述，如何能够实现在不破坏岩心样品的基础上高效、准确的进行岩心样品分析是目前需要解决的问题之一。
发明内容
本发明的目的在于提供一种能够实现在不破坏岩心样品的基础上高效、准确的进行岩心样品分析从而实现确定油气勘探所需的关键参数的方法与装置。
为了实现上述目的，本发明提供了如下四个方面的技术方案。
第一方面，本发明提供了一种岩心样品分析方法，其中，该方法包括：
获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小 岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
第二方面，本发明提供了一种岩心样品分析系统，其中，该系统包括：
大岩心数据获取模块：用于获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
小岩心数据获取模块：用于获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
小岩心参数确定模块：用于分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
大岩心参数确定模块：用于基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
第三方面，本发明提供了一种电子设备，包括处理器、存储器及存储在存储器上并可在处理器上运行的计算机程序，处理器执行程序时实现岩心样品分析方法的步骤。
第四方面，本发明提供了一种计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现岩心样品分析方法的步骤。
本发明提供的技术方案能够在勘探现场实地获取岩心的基础上，在不破坏地层标准米级大岩心的基础上，确定米级大岩心的有机质体积含量分布、孔隙度分布、无机矿物体积含量分布等参数，大幅提高油气储层评价描述的精度，为勘探开采提供参考依据。本发明提供的技术方案加速了现场取心后岩心的分析速度，提高了分析效率，并在不破坏岩心的基础上大幅提高分析精度。
附图说明
图1为密度曲线图。
图2为相对原子序数曲线图。
图3为本发明的无机矿物分析演示示意图。
图4为微米CT提取有机质的示意图(青色为有机质)。
图5为本发明实施例的数字岩心技术计算的微米CT岩心连通孔隙三维结构图和孔隙分布计算。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚完整的描述。显然，所描述的实施例是本发明的一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明的保护范围。
本发明一具体实施方式提供了一种岩心样品分析方法，其中，该方法包括：
步骤S1：获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
步骤S2：获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
步骤S3：分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
步骤S4：基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
在上述岩心样品分析方法中，认为岩心样品由有机质、孔隙和无机矿物组成，即对于某岩心样品而言，有机质体积含量、孔隙度和无机矿物体积含量的和为1。
一实施例中，小岩心样品为厘米级或者毫米级。
一实施例中，小岩心样品的XRF扫描图为通过微束X射线荧光分析扫描得到图。
一实施例中，小岩心样品的微米CT扫描图为通过微米X射线显微镜双能量扫描得到的图。
一实施例中，待分析米级大岩心的双能量螺旋CT扫描图为通过双能量螺旋CT加标样扫描得到的图。
一实施例中，步骤S3，分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量包括：
步骤S31：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机质分布、孔隙度分布和无机矿物分布；
步骤S32：基于各小岩心样品的有机质分布、孔隙度分布和无机矿物分布，分别确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
进一步地，步骤S31中，各小岩心样品的有机质分布、孔隙度分布和无机矿物分布通过下述方式进行确定：
步骤S311：基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质、孔隙和无机矿物；
步骤S312：基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定；
举例而言，步骤S312中，可以基于小岩心样品的表层特征区域内的有机质的微米CT扫描图灰度、孔隙的微米CT扫描图灰度和无机矿物的微米CT扫描图灰度，进行小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定；
举例而言，步骤S311中，基于小岩心样品的表层特征区域的微米CT扫描图初步确定小岩心样品的表层特征区域内的有机质、孔隙和无机矿物，然后利用小岩心样品的表层特征区域的XRF扫描图对初步确定的小岩心样品的表层特征区域内的有机质、孔隙和无机矿物进行组分认定，进而对小岩心样品的表层特征区域内的有机质、孔隙和无机矿物进行校正，从而准确确定小岩心样品的表层特征区域内的有机质、孔隙和无机矿物。
一实施例中，步骤S4，基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布包括：
步骤S41：基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的第一CT表征值和第二CT表征值；其中，第一CT表征值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，第二CT表征值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值；
步骤S42：基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结 合待分析米级大岩心中与各小岩心样品对应的各层的第一CT表征值和第二CT表征值，分别确定单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力；
步骤S43：基于待分析米级大岩心每层的第一CT表征值和第二CT表征值，结合单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力，确定待分析米级大岩心每层的有机质体积含量和/或孔隙度和/或无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布确定；
进一步地，步骤S42中，单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力分别满足：
CT x＝X 1·V 1+X 2·V 2+X 3·V 3
CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
式中，CT x为第一CT表征值；X 1为单位体积含量有机质对第一CT表征值的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对第一CT表征值的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对第一CT表征值的贡献能力；V 3为无机矿物体积含量；CT Y为第二CT表征值；Y 1为单位体积含量有机质对第二CT表征值的贡献能力；Y 2为单位体积含量孔隙对第二CT表征值的贡献能力；Y 3为单位体积含量无机矿物对第二CT表征值的贡献能力；
进一步地，所述第一CT表征值为能够表征相对原子序数，第二CT表征值能够表征平均密度；例如，所述第一所述第一CT表征值为灰度值，第二CT表征值为灰度值；例如，所述第一所述第一CT表征值为相对原子序数，第二CT表征值为平均密度。
一实施例中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机碳含量；
进一步地，各小岩心样品的有机碳含量通过下述方式进行确定：
基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质；
基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取，进而结合小岩心样品的体积确定小岩心样品中有机质的体积；
利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度；
基于小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
利用有机质的体积、密度和碳元素质量含量，结合小岩心样品的质量，确定小岩心样品的有机碳含量TOC；
更进一步地，有机碳含量TOC通过下述公式确定得到：
TOC＝m C÷m 2
m O＝ρ O×V O
m C＝m O×W OC
式中，TOC为有机碳含量；m C为总有机碳质量；m O为有机质总质量；m 2为待分析岩心样品的质量；ρ O为有机质的密度；V O为有机质的体积；W OC为有机质的碳元素质量含量；
其中，利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度，利用常规方式进行即可；例如，利用小岩心样品的有机质的微米CT扫描图的平均灰度结合标样的微米CT扫描图的灰度，确定有机质的密度。
一实施例中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布；
进一步地，利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布包括：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
利用各小岩心样品的有机质的微米CT扫描图，确定有机质的密度；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
利用待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的平均密度；
利用有机质的密度和碳元素质量含量，结合待分析米级大岩心每层的平均密度和有机质体积含量，确定待分析米级大岩心每层的有机碳含量；
更进一步地，待分析米级大岩心每层的有机碳含量通过下述公式确定得到：
TOC i＝ρ O·V 1i·W OC÷ρ i
式中，TOC i为待分析米级大岩心第i层的有机碳含量；ρ O为有机质的密度；ρ O为有机质的密度；V 1i为待分析米级大岩心第i层的有机质体积含量；W OC为有机质的碳元素质量含量；ρ i为待分析米级大岩心第i层的平均密度；
其中，利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度，利用常规方式进行即可；例如，利用小岩心样品的有机质的微米CT扫描图的平均灰度结合标样的微米CT扫描图的灰度，确定有机质的密度；
其中，利用待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的平均密度，利用常规方式进行即可；例如，利用待分析米级大岩心每层的双能量螺旋CT扫描图中高能量CT扫描图的平均灰度结合标样的CT扫描图的灰度，确定待分析米级大岩心每层的平均密度。
一实施例中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质类型；
进一步地，有机质类型通过下述方式进行确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氧元素质量含量；
基于有机质的碳元素质量含量和氧元素质量含量，确定有机质的氧、碳原子数之比；
利用有机质的氧、碳原子数之比确定有机质类型；
其中，有机质的氧、碳原子数之比可以通过下述公式确定：
Figure PCTCN2022138665-appb-000001
式中，R OC为有机质的氧、碳原子数之比；W OO为有机质的氧元素质量含量；W OC为有机质的碳元素质量含量；
其中，通常情况下，有机质类型为I型干酪根时的氧、碳原子数之比＜有机质类型 为II型干酪根时的氧、碳原子数之比＜有机质类型为III型干酪根时的氧、碳原子数之比；
进一步地，有机质类型通过下述方式进行确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氢元素质量含量；
基于有机质的碳元素质量含量和氢元素质量含量，确定有机质的氢、碳原子数之比；
利用有机质的氢、碳原子数之比确定有机质类型；
其中，有机质的氢、碳原子数之比可以通过下述公式确定：
Figure PCTCN2022138665-appb-000002
式中，R OC为有机质的氢、碳原子数之比；W OH为有机质的氢元素质量含量；W OC为有机质的碳元素质量含量；
其中，通常情况下有机质类型为I型干酪根时的氢、碳原子数之比有机质类型为II型干酪根时的氢、碳原子数之比＞有机质类型为III型干酪根时的氢、碳原子数之比。
一实施例中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质成熟度；
进一步地，有机质成熟度通过下述方式进行确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的元素组成和各元素的含量；
基于有机质的元素组成和各元素的含量，确定有机质的平均原子序数；
基于有机质的平均原子序数，确定有机质的镜质体反射率；
进一步地，有机质的平均原子序数通过下述公式确定：
Figure PCTCN2022138665-appb-000003
式中，Z 0为有机质的平均原子序数；f i是有机质的第i个组成元素在有机质中贡献能力的电子数比例；Z i为有机质的第i个组成元素的原子序数；n i为有机质的第i个组成元素的原子个数；N为有机质的组成元素的总个数；A为系数，通常取值3.2；
进一步地，基于有机质的平均原子序数，确定有机质的镜质体反射率包括：
获取有机质的镜质体反射率与平均原子序数的关系式；举例而言，可以利用标样的镜质体反射率与平均原子序数进行拟合确定有机质的镜质体反射率与平均原子序数的关系式；
基于有机质的平均原子序数，利用有机质镜质体反射率与平均原子序数的关系式，确定有机质的镜质体反射率；
进一步地，该方法还包括：
根据有机质成熟度判断是否为烃源岩。
一实施例中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定无机矿物组成；
进一步地，无机矿物组成通过下述方式进行确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；
基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量；基于各类无机矿物的元素组成和各元素含量，确定各类无机矿物的矿物种类；
基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物的提取，进而确定各类无机矿物在无机矿物中的占比；
由此实现无机矿物组成确定(确定了无机矿物的矿物种类以及各类无机矿物的占比)。
一实施例中，该方法还包括：
基于各小岩心样品的微米CT扫描图，确定各小岩心样品的孔隙尺寸、孔隙分布特征和有效孔隙度(连通孔隙体积与岩心体积的比值)。
本发明实施例还提供了一种岩心样品分析系统的具体实施方式，该系统用于实现上述的岩心样品分析方法实施例。该系统包括：
大岩心数据获取模块21：用于获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
小岩心数据获取模块22：用于获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
小岩心参数确定模块23：用于分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
大岩心参数确定模块24：用于基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
一实施例中，小岩心样品为厘米级或者毫米级。
一实施例中，小岩心样品的XRF扫描图为通过微束X射线荧光分析扫描得到图。
一实施例中，小岩心样品的微米CT扫描图为通过微米X射线显微镜双能量扫描得到的图。
一实施例中，待分析米级大岩心的双能量螺旋CT扫描图为通过双能量螺旋CT加标样扫描得到的图。
一实施例中，小岩心参数确定模块23包括：
第一确定子模块231：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机质分布、孔隙度分布和无机矿物分布；
第二确定子模块232：用于基于各小岩心样品的有机质分布、孔隙度分布和无机矿物分布，分别确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
进一步地，第一确定子模块231包括：
表层特征区域提取单元2311：用于基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质、孔隙和无机矿物；
分布确定单元2312：用于基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定。
一实施例中，大岩心参数确定模块24包括：
CT表征值确定子模块241：用于基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的第一CT表征值和第二CT表征值；其中，第一CT表征值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，第二CT表征值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值；
贡献能力确定子模块242：用于基于各小岩心样品的有机质体积含量、孔隙度和无 机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的第一CT表征值和第二CT表征值，分别确定单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力；
大岩心参数确定子模块243：用于基于待分析米级大岩心每层的第一CT表征值和第二CT表征值，结合单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力，确定待分析米级大岩心每层的有机质体积含量和/或孔隙度和/或无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布确定。
进一步地，单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力分别满足：
CT x＝X 1·V 1+X 2·V 2+X 3·V 3
CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
式中，CT x为第一CT表征值；X 1为单位体积含量有机质对第一CT表征值的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对第一CT表征值的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对第一CT表征值的贡献能力；V 3为无机矿物体积含量；CT Y为第二CT表征值；Y 1为单位体积含量有机质对第二CT表征值的贡献能力；Y 2为单位体积含量孔隙对第二CT表征值的贡献能力；Y 3为单位体积含量无机矿物对第二CT表征值的贡献能力；
进一步地，所述第一CT表征值为能够表征相对原子序数，第二CT表征值能够表征平均密度；例如，所述第一所述第一CT表征值为灰度值，第二CT表征值为灰度值；例如，所述第一所述第一CT表征值为相对原子序数，第二CT表征值为平均密度。
一实施例中，该系统进一步包括：
小岩心有机碳含量确定模块25：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机碳含量；
进一步地，小岩心有机碳含量确定模块25具体用于通过下述方式确定各小岩心样品的有机碳含量：
基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质；
基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取，进而结合小岩心样品的体积确定小岩心样品中有机质的体积；
利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度；
基于小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
利用有机质的体积、密度和碳元素质量含量，结合小岩心样品的质量，确定小岩心样品的有机碳含量TOC；
更进一步地，有机碳含量TOC通过下述公式确定得到：
TOC＝m C÷m 2
m O＝ρ O×V O
m C＝m O×W OC
式中，TOC为有机碳含量；m C为总有机碳质量；m O为有机质总质量；m 2为待分析岩心样品的质量；ρ O为有机质的密度；V O为有机质的体积；W OC为有机质的碳元素质量含量。
一实施例中，该系统进一步包括：
有机碳含量分布确定模块26：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布；
进一步地，有机碳含量分布确定模块26用于通过下述方式进行待分析米级大岩心的有机质碳含量分布确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
利用各小岩心样品的有机质的微米CT扫描图，确定有机质的密度；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
利用待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的平均 密度；
利用有机质的密度和碳元素质量含量，结合待分析米级大岩心每层的平均密度和有机质体积含量，确定待分析米级大岩心每层的有机碳含量；
更进一步地，待分析米级大岩心每层的有机碳含量通过下述公式确定得到：
TOC i＝ρ O·V 1i·W OC÷ρ i
式中，TOC i为待分析米级大岩心第i层的有机碳含量；ρ O为有机质的密度；ρ O为有机质的密度；V 1i为待分析米级大岩心第i层的有机质体积含量；W OC为有机质的碳元素质量含量；ρ i为待分析米级大岩心第i层的平均密度。
一实施例中，该系统进一步包括：
有机质类型确定模块27：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质类型；
进一步地，有机质类型确定模块27用于通过下述方式进行有机质类型确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氧元素质量含量；
基于有机质的碳元素质量含量和氧元素质量含量，确定有机质的氧、碳原子数之比；
利用有机质的氧、碳原子数之比确定有机质类型；
其中，有机质的氧、碳原子数之比可以通过下述公式确定：
Figure PCTCN2022138665-appb-000004
式中，R OC为有机质的氧、碳原子数之比；W OO为有机质的氧元素质量含量；W OC为有机质的碳元素质量含量；
其中，通常情况下，有机质类型为I型干酪根时的氧、碳原子数之比＜有机质类型为II型干酪根时的氧、碳原子数之比＜有机质类型为III型干酪根时的氧、碳原子数之比；
进一步地，有机质类型确定模块27用于通过下述方式进行有机质类型确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氢元素质量含量；
基于有机质的碳元素质量含量和氢元素质量含量，确定有机质的氢、碳原子数之比；
利用有机质的氢、碳原子数之比确定有机质类型；
其中，有机质的氢、碳原子数之比可以通过下述公式确定：
Figure PCTCN2022138665-appb-000005
式中，R OC为有机质的氢、碳原子数之比；W OH为有机质的氢元素质量含量；W OC为有机质的碳元素质量含量；
其中，通常情况下有机质类型为I型干酪根时的氢、碳原子数之比有机质类型为II型干酪根时的氢、碳原子数之比＞有机质类型为III型干酪根时的氢、碳原子数之比。
一实施例中，该系统进一步包括：
有机质成熟度确定模块28：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质成熟度；
进一步地，有机质成熟度确定模块28用于通过下述方式进行有机质成熟度确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的元素组成和各元素的含量；
基于有机质的元素组成和各元素的含量，确定有机质的平均原子序数；
基于有机质的平均原子序数，确定有机质的镜质体反射率；
进一步地，有机质的平均原子序数通过下述公式确定：
Figure PCTCN2022138665-appb-000006
式中，Z 0为有机质的平均原子序数；f i是有机质的第i个组成元素在有机质中贡献能力的电子数比例；Z i为有机质的第i个组成元素的原子序数；n i为有机质的第i个组成元素的原子个数；N为有机质的组成元素的总个数；A为系数，通常取值3.2；
进一步地，有机质成熟度确定模块28用于通过下述方式进行有机质的平均原子序数确定：
获取有机质的镜质体反射率与平均原子序数的关系式；举例而言，可以利用标样的镜质体反射率与平均原子序数进行拟合确定有机质的镜质体反射率与平均原子序数的关系式；
基于有机质的平均原子序数，利用有机质镜质体反射率与平均原子序数的关系式， 确定有机质的镜质体反射率；
进一步地，该系统进一步包括：
烃源岩确定模块29：用于根据有机质成熟度判断是否为烃源岩。
一实施例中，该系统进一步包括：
无机矿物组成确定模块30：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定无机矿物组成；
进一步地，无机矿物组成确定模块30用于通过下述方式进行无机矿物组成确定：
基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；
基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量；基于各类无机矿物的元素组成和各元素含量，确定各类无机矿物的矿物种类；
基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物的提取，进而确定各类无机矿物在无机矿物中的占比；
由此实现无机矿物组成确定(确定了无机矿物的矿物种类以及各类无机矿物的占比)。
一实施例中，该系统进一步包括：
孔隙参数确定模块31：用于各小岩心样品的微米CT扫描图，确定各小岩心样品的孔隙尺寸、孔隙分布特征和有效孔隙度(连通孔隙体积与岩心体积的比值)。
本发明的实施例还提供能够实现上述实施例中的岩心样品分析方法中全部步骤的一种电子设备的具体实施方式，电子设备具体包括如下内容：
处理器、存储器、通信接口和总线；
其中，处理器、存储器、通信接口通过总线完成相互间的通信；通信接口用于实现服务器端设备以及客户端设备等相关设备之间的信息传输；处理器用于调用存储器中的计算机程序，处理器执行计算机程序时实现上述实施例中的岩心样品分析方法中的全部步骤，例如，处理器执行计算机程序时实现下述步骤：
步骤S1：获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
步骤S2：获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米 CT扫描图；
步骤S3：分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
步骤S4：基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
本发明的实施例还提供能够实现上述实施例中的岩心样品分析方法中全部步骤的一种计算机可读存储介质，计算机可读存储介质上存储有计算机程序，该计算机程序被处理器执行时实现上述实施例中的岩心样品分析方法的全部步骤，例如，处理器执行计算机程序时实现下述步骤：
步骤S1：获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
步骤S2：获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
步骤S3：分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量(即有机质体积与小岩心样品的体积比)、孔隙度(即孔隙与小岩心样品的体积比)和无机矿物体积含量(即无机矿物体积与小岩心样品的体积比)；
步骤S4：基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
实施例1
本实施例提供了一种岩心样品分析方法，该方法用于对生油岩米级岩心进行分析，具体包括：
A、将生油岩待分析米级大岩心进行双能量螺旋CT加标样扫描，得到待分析米级大岩心每层的双能量螺旋CT扫描图；并基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的相对原子序数和平均密度；其中，相对原子序数为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，平均密度为对应于双能量 螺旋CT扫描图中的高能量CT扫描图的CT表征值(如图1、图2所示)。
由于岩性、有机质含量、孔隙特征和裂缝特征的影响，待分析米级大岩心不同层的平均密度和相对原子序数会产生明显高低变化，基于待分析米级大岩心每层的平均密度和相对原子序数，确定待分析米级大岩心中的典型岩段，自典型岩段中确定多个小岩心样品(厘米级或者毫米级)。
B、获取各小岩心样品的质量、体积、和密度。
C、分别对各小岩心样品表层通过微束X射线荧光分析(Micro-XRF)进行特征区域扫描，得到各小岩心样品的表层特征区域的XRF扫描图；分别对各小岩心样品通过微米X射线显微镜(Micro-CT)进行双能量扫描，得到各小岩心样品的微米CT扫描图。
D、基于各小岩心样品的表层特征区域的XRF扫描图，确定各小岩心样品的表层特征区域的元素组成和各元素质量分数(包括碳W C、硫W S、氮W N、氧W O等有机质主要元素和铁W Fe、铜W Cu、镁W Mg、锌W Zn、钼W Mu、镍W Ni、汞W Hg等微量元素)。
E、分别基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质(如图4所示)、孔隙和无机矿物；基于各小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现各小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定；
基于各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取结果，结合各小岩心样品的体积确定各小岩心样品中有机质的体积、孔隙的体积和无机矿物的体积，从而确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
利用各小岩心样品的有机质的微米CT扫描图的平均灰度，确定各小岩心样品的有机质密度(根据扫描标样进行)、质量和相对原子序数(根据扫描标样进行)，进而通过加权平均的方式确定有机质平均密度和平均相对原子序数作为待分析米级大岩心的有机质密度和有机质对原子序数；
分别基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定各小岩心样品的有机质的碳元素、氧元素、硫元素、氮元素的质量含量，进而通过加权平均的方式确定有机质的平均碳元素质量含量、平均氧元素质量含量、平均硫元素质量含量、平均氮元素的质量含量作为待分析米级大岩心的有机质的碳元素、氧元素、硫元素、氮元素的质量含量。
F、基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的 第一CT灰度值和第二CT灰度值；其中，第一CT灰度值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT灰度值，第二CT灰度值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT灰度值；
基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的第一CT灰度值和第二CT灰度值，分别确定单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力；其中，单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力分别满足：
CT x＝X 1·V 1+X 2·V 2+X 3·V 3
CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
式中，CT x为第一CT灰度值；X 1为单位体积含量有机质对第一CT灰度值的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对第一CT灰度值的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对第一CT灰度值的贡献能力；V 3为无机矿物体积含量；CT Y为第二CT灰度值；Y 1为单位体积含量有机质对第二CT灰度值的贡献能力；Y 2为单位体积含量孔隙对第二CT灰度值的贡献能力；Y 3为单位体积含量无机矿物对第二CT灰度值的贡献能力；
基于待分析米级大岩心每层的第一CT灰度值和第二CT灰度值，结合单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力，确定待分析米级大岩心每层的有机质体积含量、孔隙度和无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布、孔隙度分布和无机矿物体积含量分布确定。
G、分别针对各小岩心样品，利用有机质的体积、密度和碳元素质量含量，结合岩心样品的质量，通过下述公式确定各小岩心样品的有机碳含量TOC；
TOC＝m C÷m 2
m O＝ρ O×V O
m C＝m O×W OC
式中，TOC为有机碳含量；m C为总有机碳质量；m O为有机质总质量；m 2为待分析岩心样品的质量；ρ O为有机质的密度；V O为有机质的体积；W OC为有机质的碳元素质量含量。
H、利用待分析米级大岩心的有机质的密度和碳元素质量含量，结合待分析米级大岩心每层的平均密度和有机质体积含量，通过下述公式确定待分析米级大岩心每层的有机碳含量：
TOC i＝ρ O·V 1i·W OC÷ρ i
式中，TOC i为待分析米级大岩心第i层的有机碳含量；ρ O为有机质的密度；ρ O为有机质的密度；V 1i为待分析米级大岩心第i层的有机质体积含量；W OC为有机质的碳元素质量含量；ρ i为待分析米级大岩心第i层的平均密度。
I、基于待分析米级大岩心的有机质的碳元素质量含量和氧元素质量含量，确定有机质的氧、碳原子数之比；利用有机质的氧、碳原子数之比确定有机质类型；其中，有机质的氧、碳原子数之比可以通过下述公式确定：
Figure PCTCN2022138665-appb-000007
式中，R OC为有机质的氧、碳原子数之比；W OO为有机质的氧元素质量含量；W OC为有机质的碳元素质量含量。
J、基于待分析米级大岩心的有机质的元素组成和各元素的含量，确定有机质的平均原子序数；获取有机质的镜质体反射率与平均原子序数的关系式；基于有机质的平均原子序数，利用有机质镜质体反射率与平均原子序数的关系式，确定有机质的镜质体反射率；其中，有机质的平均原子序数通过下述公式确定：
Figure PCTCN2022138665-appb-000008
式中，Z 0为有机质的平均原子序数；f i是有机质的第i个组成元素在有机质中贡献能力的电子数比例；Z i为有机质的第i个组成元素的原子序数；n i为有机质相的第i个组成元素的原子个数；N为有机质的组成元素的总个数；A为系数，取值3.2；
根据有机质成熟度判断是否为烃源岩。
K、基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量(包括铁、铜、镁、锌、钼、镍、汞等微量元素含量)；基于各类无机矿物的元素组成和各元素含量， 确定各类无机矿物的矿物种类；基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物相的提取，进而确定各类无机矿物相在无机矿物中的占比；由此实现无机矿物组成确定(确定了无机矿物的矿物种类以及各类无机矿物的占比)。
L、针对各小岩心样品，基于表层特征区域的微米CT扫描图和XRF扫描图确定表层特征区域内的的各类无机矿物，基于表层特征区域内各类矿物的微米CT扫描图特征进行微米CT扫描图中各类矿物的提取，实现无机矿物分布确定(如图3所示)。
实施例2
本实施例提供了一种岩心样品分析方法，该方法用于对储层米级岩心进行分析，具体包括：
A、将储层待分析米级大岩心进行双能量螺旋CT加标样扫描，得到待分析米级大岩心每层的双能量螺旋CT扫描图；并基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的相对原子序数和平均密度；其中，相对原子序数为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，平均密度为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值。
基于待分析米级大岩心每层的平均密度和相对原子序数，确定待分析米级大岩心中的典型岩段，自典型岩段中确定多个小岩心样品(厘米级或者毫米级)。
B、获取各小岩心样品的质量、体积、和密度。
C、分别对各小岩心样品表层通过微束X射线荧光分析(Micro-XRF)进行特征区域扫描，得到各小岩心样品的表层特征区域的XRF扫描图；分别对各小岩心样品通过微米X射线显微镜(Micro-CT)进行双能量扫描，得到各小岩心样品的微米CT扫描图。
D、基于各小岩心样品的表层特征区域的XRF扫描图，确定各小岩心样品的表层特征区域的元素组成和各元素质量分数(包括碳W C、硫W S、氮W N、氧W O等有机质主要元素和铁W Fe、铜W Cu、镁W Mg、锌W Zn、钼W Mu、镍W Ni、汞W Hg等微量元素)。
E、分别基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质、孔隙和无机矿物；基于各小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现各小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定；
基于各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取结果，结合各小岩心样品的体积确定各小岩心样品中有机质的体积、孔隙的体积和无机矿物的 体积，从而确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
利用各小岩心样品的有机质的微米CT扫描图的平均灰度，确定各小岩心样品的有机质密度(根据扫描标样进行)、质量和相对原子序数(根据扫描标样进行)，进而通过加权平均的方式确定有机质平均密度和平均相对原子序数作为待分析米级大岩心的有机质密度和有机质对原子序数；
分别基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定各小岩心样品的有机质的碳元素、氧元素、硫元素、氮元素的质量含量，进而通过加权平均的方式确定有机质的平均碳元素质量含量、平均氧元素质量含量、平均硫元素质量含量、平均氮元素的质量含量作为待分析米级大岩心的有机质的碳元素、氧元素、硫元素、氮元素的质量含量。
F、基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的相对原子序数和平均密度，分别确定单位体积含量有机质对相对原子序数的贡献能力、单位体积含量孔隙对相对原子序数的贡献能力、单位体积含量无机矿物对相对原子序数的贡献能力、单位体积含量有机质对平均密度的贡献能力、单位体积含量孔隙对平均密度的贡献能力和单位体积含量无机矿物对平均密度的贡献能力；其中，单位体积含量有机质对相对原子序数的贡献能力、单位体积含量孔隙对相对原子序数的贡献能力、单位体积含量无机矿物对相对原子序数的贡献能力、单位体积含量有机质对平均密度的贡献能力、单位体积含量孔隙对平均密度的贡献能力和单位体积含量无机矿物对平均密度的贡献能力分别满足：
CT x＝X 1·V 1+X 2·V 2+X 3·V 3
CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
式中，CT x为相对原子序数；X 1为单位体积含量有机质对相对原子序数的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对相对原子序数的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对相对原子序数的贡献能力；V 3为无机矿物体积含量；CT Y为平均密度；Y 1为单位体积含量有机质对平均密度的贡献能力；Y 2为单位体积含量孔隙对平均密度的贡献能力；Y 3为单位体积含量无机矿物对平均密度的贡献能力；
基于待分析米级大岩心每层的相对原子序数和平均密度，结合单位体积含量有机质对相对原子序数的贡献能力、单位体积含量孔隙对相对原子序数的贡献能力、单位体积含量无机矿物对相对原子序数的贡献能力、单位体积含量有机质对平均密度的贡献能力、单位体积含量孔隙对平均密度的贡献能力和单位体积含量无机矿物对平均密度的贡 献能力，确定待分析米级大岩心每层的有机质体积含量和/或孔隙度和/或无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布确定。
G、基于各小岩心样品的微米CT扫描图，确定各小岩心样品的孔隙尺寸、孔隙分布特征(某一岩心样品的分布情况如图5所示)和有效孔隙度(连通孔隙体积与岩心体积的比值)。
F、基于待分析米级大岩心的有机质的元素组成和各元素的含量，确定有机质的平均原子序数；获取有机质的镜质体反射率与平均原子序数的关系式；基于有机质的平均原子序数，利用有机质镜质体反射率与平均原子序数的关系式，确定有机质的镜质体反射率；其中，有机质的平均原子序数通过下述公式确定：
Figure PCTCN2022138665-appb-000009
式中，Z 0为有机质的平均原子序数；f i是有机质的第i个组成元素在有机质中贡献能力的电子数比例；Z i为有机质的第i个组成元素的原子序数；n i为有机质相的第i个组成元素的原子个数；N为有机质的组成元素的总个数；A为系数，取值3.2。
G、针对各待分析岩心样品，基于表层特征区域的微米CT扫描图和XRF扫描图，确定表层特征区域内的岩石相；基于表层特征区域内的岩石相的XRF扫描图，确定岩石相的元素组成和各元素含量(包括铁、铜、镁、锌、钼、镍、汞等微量元素含量)；基于岩石相的元素组成和各元素含量，确定矿物组成；基于表层特征区域内各类矿物的CT扫描图特征，进行CT扫描图中各类矿物的提取，实现矿物分布确定。
H、基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量(包括铁、铜、镁、锌、钼、镍、汞等微量元素含量)；基于各类无机矿物的元素组成和各元素含量，确定各类无机矿物的矿物种类；基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物相的提取，进而确定各类无机矿物相在无机矿物中的占比；由此实现无机矿物组成确定(确定了无机矿物的矿物种类以及各类无机矿物的占比)。
I、针对各小岩心样品，基于表层特征区域的微米CT扫描图和XRF扫描图确定表层特征区域内的的各类无机矿物，基于表层特征区域内各类矿物的微米CT扫描图特征进行微米CT扫描图中各类矿物的提取，实现无机矿物分布确定(如图3所示)。
J、获取各小岩心样品的核磁共振图；基于各小岩心样品的核磁共振图，对各小岩心样品进行水的观测，确定各小岩心样品中水的分布；结合各小岩心样品的微米CT扫描图和XRF扫描图，确定各小岩心样品中孔隙束缚水和含油特征。
实施例3
本实施例提供了一种岩心样品分析方法，该方法用于对盖层米级岩心进行分析，具体包括：
A、将盖层待分析米级大岩心进行双能量螺旋CT加标样扫描，得到待分析米级大岩心每层的双能量螺旋CT扫描图；并基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的相对原子序数和平均密度；其中，相对原子序数为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，平均密度为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值。
基于待分析米级大岩心每层的平均密度和相对原子序数，确定待分析米级大岩心中的典型岩段，自典型岩段中确定多个小岩心样品(厘米级或者毫米级)。
B、获取各小岩心样品的质量、体积、和密度。
C、分别对各小岩心样品表层通过微束X射线荧光分析(Micro-XRF)进行特征区域扫描，得到各小岩心样品的表层特征区域的XRF扫描图；分别对各小岩心样品通过微米X射线显微镜(Micro-CT)进行双能量扫描，得到各小岩心样品的微米CT扫描图。
D、基于各小岩心样品的表层特征区域的XRF扫描图，确定各小岩心样品的表层特征区域的元素组成和各元素质量分数(包括碳W C、硫W S、氮W N、氧W O等有机质主要元素和铁W Fe、铜W Cu、镁W Mg、锌W Zn、钼W Mu、镍W Ni、汞W Hg等微量元素)。
E、分别基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质、孔隙和无机矿物；基于各小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现各小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定；
基于各小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取结果，结合各小岩心样品的体积确定各小岩心样品中有机质的体积、孔隙的体积和无机矿物的体积，从而确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
利用各小岩心样品的有机质的微米CT扫描图的平均灰度，确定各小岩心样品的有机质密度(根据扫描标样进行)、质量和相对原子序数(根据扫描标样进行)，进而通过加权平均的方式确定有机质平均密度和平均相对原子序数作为待分析米级大岩心的有 机质密度和有机质对原子序数；
分别基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定各小岩心样品的有机质的碳元素、氧元素、硫元素、氮元素的质量含量，进而通过加权平均的方式确定有机质的平均碳元素质量含量、平均氧元素质量含量、平均硫元素质量含量、平均氮元素的质量含量作为待分析米级大岩心的有机质的碳元素、氧元素、硫元素、氮元素的质量含量。
F、基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的第一CT灰度值和第二CT灰度值；其中，第一CT灰度值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT灰度值，第二CT灰度值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT灰度值；
基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的第一CT灰度值和第二CT灰度值，分别确定单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力；其中，单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力分别满足：
CT x＝X 1·V 1+X 2·V 2+X 3·V 3
CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
式中，CT x为第一CT灰度值；X 1为单位体积含量有机质对第一CT灰度值的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对第一CT灰度值的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对第一CT灰度值的贡献能力；V 3为无机矿物体积含量；CT Y为第二CT灰度值；Y 1为单位体积含量有机质对第二CT灰度值的贡献能力；Y 2为单位体积含量孔隙对第二CT灰度值的贡献能力；Y 3为单位体积含量无机矿物对第二CT灰度值的贡献能力；
基于待分析米级大岩心每层的第一CT灰度值和第二CT灰度值，结合单位体积含量有机质对第一CT灰度值的贡献能力、单位体积含量孔隙对第一CT灰度值的贡献能力、单位体积含量无机矿物对第一CT灰度值的贡献能力、单位体积含量有机质对第二 CT灰度值的贡献能力、单位体积含量孔隙对第二CT灰度值的贡献能力和单位体积含量无机矿物对第二CT灰度值的贡献能力，确定待分析米级大岩心每层的有机质体积含量、孔隙度和无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布、孔隙度分布和无机矿物体积含量分布确定。
F、基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量(包括铁、铜、镁、锌、钼、镍、汞等微量元素含量)；基于各类无机矿物的元素组成和各元素含量，确定各类无机矿物的矿物种类；基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物相的提取，进而确定各类无机矿物相在无机矿物中的占比；由此实现无机矿物组成确定(确定了无机矿物的矿物种类以及各类无机矿物的占比)。
G、针对各小岩心样品，基于表层特征区域的微米CT扫描图和XRF扫描图确定表层特征区域内的的各类无机矿物，基于表层特征区域内各类矿物的微米CT扫描图特征进行微米CT扫描图中各类矿物的提取，实现无机矿物分布确定。
H、确定各小岩心样品的渗透率。
I、针对各小岩心样品，利用高浓度KI溶液进行驱替，将样品干燥后KI结晶会残留在普通成像无法观察到的连通孔喉中，再进行微米CT扫描从而观察到渗流路径。
以上所述仅为本发明的较佳实施例，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (19)

  1. 一种岩心样品分析方法，其中，该方法包括：
    获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
    获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
    分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
    基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
  2. 根据权利要求1所述的方法，其中，分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量包括：
    利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机质分布、孔隙度分布和无机矿物分布；
    基于各小岩心样品的有机质分布、孔隙度分布和无机矿物分布，分别确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量。
  3. 根据权利要求2所述的方法，其中，各小岩心样品的有机质分布、孔隙度分布和无机矿物分布通过下述方式进行确定：
    基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质、孔隙和无机矿物；
    基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征、孔隙的微米CT扫描图特征和无机矿物的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取、孔隙提取和无机矿物提取，实现小岩心样品的有机质分布、孔隙度分布和无机矿物分布确定。
  4. 根据权利要求1所述的方法，其中，基于待分析米级大岩心双能量螺旋CT扫描图，结合各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布包括：
    基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的第一 CT表征值和第二CT表征值；其中，第一CT表征值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，第二CT表征值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值；
    基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的第一CT表征值和第二CT表征值，分别确定单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力；
    基于待分析米级大岩心每层的第一CT表征值和第二CT表征值，结合单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力，确定待分析米级大岩心每层的有机质体积含量和/或孔隙度和/或无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布确定。
  5. 根据权利要求4所述的方法，其中，单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力分别满足：
    CT x＝X 1·V 1+X 2·V 2+X 3·V 3
    CT Y＝Y 1·V 1+Y 2·V 2+Y 3·V 3
    式中，CT x为第一CT表征值；X 1为单位体积含量有机质对第一CT表征值的贡献能力；V 1为有机质体积含量；X 2为单位体积含量孔隙对第一CT表征值的贡献能力；V 2为孔隙度；X 3为单位体积含量无机矿物对第一CT表征值的贡献能力；V 3为无机矿物体积含量；CT Y为第二CT表征值；Y 1为单位体积含量有机质对第二CT表征值的贡献能力；Y 2为单位体积含量孔隙对第二CT表征值的贡献能力；Y 3为单位体积含量无机矿物对第二CT表征值的贡献能力。
  6. 根据权利要求1所述的方法，其中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机碳含量；
    其中，各小岩心样品的有机碳含量通过下述方式进行确定：
    基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质；
    基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取，进而结合小岩心样品的体积确定小岩心样品中有机质的体积；
    利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度；
    基于小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
    利用有机质的体积、密度和碳元素质量含量，结合小岩心样品的质量，确定小岩心样品的有机碳含量TOC；
    其中，有机碳含量TOC通过下述公式确定得到：
    TOC＝m C÷m 2
    m O＝ρ O×V O
    m C＝m O×W OC
    式中，TOC为有机碳含量；m C为总有机碳质量；m O为有机质总质量；m 2为待分析岩心样品的质量；ρ O为有机质的密度；V O为有机质的体积；W OC为有机质的碳元素质量含量。
  7. 根据权利要求1所述的方法，其中，方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布；
    其中，利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布包括：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
    利用各小岩心样品的有机质的微米CT扫描图，确定有机质的密度；
    基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
    利用待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的平均 密度；
    利用有机质的密度和碳元素质量含量，结合待分析米级大岩心每层的平均密度和有机质体积含量，确定待分析米级大岩心每层的有机碳含量；
    其中，待分析米级大岩心每层的有机碳含量通过下述公式确定得到：
    TOC i＝ρ O·V 1i·W OC÷ρ i
    式中，TOC i为待分析米级大岩心第i层的有机碳含量；ρ O为有机质的密度；ρ O为有机质的密度；V 1i为待分析米级大岩心第i层的有机质体积含量；W OC为有机质的碳元素质量含量；ρ i为待分析米级大岩心第i层的平均密度。
  8. 根据权利要求1所述的方法，其中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质类型。
  9. 根据权利要求8所述的方法，其中，有机质类型通过下述方式进行确定：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
    基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氧元素质量含量；
    基于有机质的碳元素质量含量和氧元素质量含量，确定有机质的氧、碳原子数之比；
    利用有机质的氧、碳原子数之比确定有机质类型；
    其中，有机质类型为I型干酪根时的氧、碳原子数之比＜有机质类型为II型干酪根时的氧、碳原子数之比＜有机质类型为III型干酪根时的氧、碳原子数之比。
  10. 根据权利要求8所述的方法，其中，有机质类型通过下述方式进行确定：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
    基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量和氢元素质量含量；
    基于有机质的碳元素质量含量和氢元素质量含量，确定有机质的氢、碳原子数之比；
    利用有机质的氢、碳原子数之比确定有机质类型；
    其中，有机质类型为I型干酪根时的氢、碳原子数之比有机质类型为II型干酪根时的氢、碳原子数之比＞有机质类型为III型干酪根时的氢、碳原子数之比。
  11. 根据权利要求1所述的方法，其中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定有机质成熟度；
    其中，有机质成熟度通过下述方式进行确定：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
    基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的元素组成和各元素的含量；
    基于有机质的元素组成和各元素的含量，确定有机质的平均原子序数；
    基于有机质的平均原子序数，确定有机质的镜质体反射率。
  12. 根据权利要求11所述的方法，其中，基于有机质的平均原子序数，确定有机质的镜质体反射率包括：
    获取有机质的镜质体反射率与平均原子序数的关系式；
    基于有机质的平均原子序数，利用有机质镜质体反射率与平均原子序数的关系式，确定有机质的镜质体反射率。
  13. 根据权利要求1所述的方法，其中，该方法进一步包括：利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定无机矿物组成；
    其中，无机矿物组成通过下述方式进行确定：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的各类无机矿物；
    基于各小岩心样品的表层特征区域内的各类无机矿物的XRF扫描图，确定各类无机矿物的元素组成和各元素含量；基于各类无机矿物的元素组成和各元素含量，确定各类无机矿物的矿物种类；
    基于各小岩心样品的表层特征区域内的各类无机矿物的微米CT扫描图特征，进行各小岩心样品的微米CT扫描图中各类无机矿物的提取，进而确定各类无机矿物在无机矿物中的占比。
  14. 一种岩心样品分析系统，其中，该系统包括：
    大岩心数据获取模块：用于获取待分析米级大岩心的双能量螺旋CT扫描图；自待分析米级大岩心中确定至少三个小岩心样品；其中，双能量螺旋CT扫描图包括低能量CT扫描图和高能量CT扫描图；
    小岩心数据获取模块：用于获取各小岩心样品的表层特征区域的XRF扫描图和各小岩心样品的微米CT扫描图；
    小岩心参数确定模块：用于分别利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，确定各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量；
    大岩心参数确定模块：用于基于待分析米级大岩心双能量螺旋CT扫描图，结合各 小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，确定待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布。
  15. 根据权利要求14所述的系统，其中，大岩心参数确定模块包括：
    CT表征值确定子模块：用于基于待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的第一CT表征值和第二CT表征值；其中，第一CT表征值为对应于双能量螺旋CT扫描图中的低能量CT扫描图的CT表征值，第二CT表征值为对应于双能量螺旋CT扫描图中的高能量CT扫描图的CT表征值；
    贡献能力确定子模块：用于基于各小岩心样品的有机质体积含量、孔隙度和无机矿物体积含量，结合待分析米级大岩心中与各小岩心样品对应的各层的第一CT表征值和第二CT表征值，分别确定单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力；
    大岩心参数确定子模块：用于基于待分析米级大岩心每层的第一CT表征值和第二CT表征值，结合单位体积含量有机质对第一CT表征值的贡献能力、单位体积含量孔隙对第一CT表征值的贡献能力、单位体积含量无机矿物对第一CT表征值的贡献能力、单位体积含量有机质对第二CT表征值的贡献能力、单位体积含量孔隙对第二CT表征值的贡献能力和单位体积含量无机矿物对第二CT表征值的贡献能力，确定待分析米级大岩心每层的有机质体积含量和/或孔隙度和/或无机矿物体积含量，从而实现待分析米级大岩心的有机质体积含量分布和/或孔隙度分布和/或无机矿物体积含量分布确定。
  16. 根据权利要求14所述的系统，其中，该系统进一步包括：
    小岩心有机碳含量确定模块：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，分别确定各小岩心样品的有机碳含量；
    其中，小岩心有机碳含量确定模块具体用于通过下述方式确定各小岩心样品的有机碳含量：
    基于小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定小岩心样品的表层特征区域内的有机质；
    基于小岩心样品的表层特征区域内的有机质的微米CT扫描图特征，进行小岩心样品的微米CT扫描图中有机质提取，进而结合小岩心样品的体积确定小岩心样品中有机质的体积；
    利用小岩心样品的有机质的微米CT扫描图，判断有机质的密度；
    基于小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
    利用有机质的体积、密度和碳元素质量含量，结合小岩心样品的质量，确定小岩心样品的有机碳含量TOC；
    其中，有机碳含量TOC通过下述公式确定得到：
    TOC＝m C÷m 2
    m O＝ρ O×V O
    m C＝m O×W OC
    式中，TOC为有机碳含量；m C为总有机碳质量；m O为有机质总质量；m 2为待分析岩心样品的质量；ρ O为有机质的密度；V O为有机质的体积；W OC为有机质的碳元素质量含量。
  17. 根据权利要求14所述的系统，其中，该系统进一步包括：
    有机碳含量分布确定模块：用于利用各小岩心样品的微米CT扫描图和表层特征区域的XRF扫描图，结合待分析米级大岩心双能量螺旋CT扫描图和待分析米级大岩心的有机质体积含量分布，确定待分析米级大岩心的有机质碳含量分布；
    其中，有机碳含量分布确定模块用于通过下述方式进行待分析米级大岩心的有机质碳含量分布确定：
    基于各小岩心样品的表层特征区域的微米CT扫描图和XRF扫描图，确定各小岩心样品的表层特征区域内的有机质；
    利用各小岩心样品的有机质的微米CT扫描图，确定有机质的密度；
    基于各小岩心样品的表层特征区域内的有机质的XRF扫描图，确定有机质的碳元素质量含量；
    利用待分析米级大岩心双能量螺旋CT扫描图，确定待分析米级大岩心每层的平均密度；
    利用有机质的密度和碳元素质量含量，结合待分析米级大岩心每层的平均密度和有机质体积含量，确定待分析米级大岩心每层的有机碳含量；
    其中，待分析米级大岩心每层的有机碳含量通过下述公式确定得到：
    TOC i＝ρ O·V 1i·W OC÷ρ i
    式中，TOC i为待分析米级大岩心第i层的有机碳含量；ρ O为有机质的密度；ρ O为有机质的密度；V 1i为待分析米级大岩心第i层的有机质体积含量；W OC为有机质的碳元素质量含量；ρ i为待分析米级大岩心第i层的平均密度。
  18. 一种电子设备，包括处理器、存储器及存储在存储器上并可在处理器上运行的计算机程序，处理器执行程序时实现权利要求1-13任一项所述的岩心样品分析方法的步骤。
  19. 一种计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现权利要求1-13任一项所述的岩心样品分析方法的步骤。
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