CN116858630B - Method and system for constructing real shale kerogen pore model - Google Patents
Method and system for constructing real shale kerogen pore model Download PDFInfo
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- 239000011148 porous material Substances 0.000 title claims abstract description 248
- 238000000034 method Methods 0.000 title claims abstract description 34
- 239000011435 rock Substances 0.000 claims abstract description 50
- 238000003708 edge detection Methods 0.000 claims abstract description 21
- 238000010586 diagram Methods 0.000 claims abstract description 18
- 238000002922 simulated annealing Methods 0.000 claims abstract description 17
- 238000000605 extraction Methods 0.000 claims abstract description 10
- 238000004088 simulation Methods 0.000 claims description 20
- 239000003079 shale oil Substances 0.000 claims description 14
- 239000007789 gas Substances 0.000 claims description 12
- 238000010276 construction Methods 0.000 claims description 10
- 238000000137 annealing Methods 0.000 claims description 9
- 230000004927 fusion Effects 0.000 claims description 8
- 238000013527 convolutional neural network Methods 0.000 claims description 7
- 150000001335 aliphatic alkanes Chemical class 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- 125000004430 oxygen atom Chemical group O* 0.000 claims description 4
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 238000011161 development Methods 0.000 abstract description 4
- 230000008569 process Effects 0.000 description 7
- 230000008859 change Effects 0.000 description 5
- 239000005416 organic matter Substances 0.000 description 5
- 238000000329 molecular dynamics simulation Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 238000012900 molecular simulation Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000011800 void material Substances 0.000 description 2
- 239000008186 active pharmaceutical agent Substances 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 125000004429 atom Chemical group 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
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- 230000005012 migration Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000001179 sorption measurement Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/42—Low-temperature sample treatment, e.g. cryofixation
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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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- 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
- G01N23/225—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 using electron or ion
- G01N23/2251—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 using electron or ion using incident electron beams, e.g. scanning electron microscopy [SEM]
Abstract
The invention discloses a method and a system for constructing a real shale kerogen pore model, which relate to the technical field of oil and gas field development, and comprise the following steps: scanning a real rock sample to be used by adopting an SEM scanning electron microscope to obtain a two-dimensional scanning image of the real rock sample to be used; adopting a preset RCF edge detection model to perform feature extraction on a two-dimensional scanning image of a real rock sample to be used so as to obtain a kerogen pore shape feature image; constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape feature diagram; the three-dimensional initial kerogen pore model comprises a pore radical and a plurality of kerogen molecules; and after performing simulated annealing on the three-dimensional initial kerogen pore model, removing the pore atomic groups in the three-dimensional initial kerogen pore model to obtain the kerogen pore model of the real rock sample to be used. The shale kerogen pore model is more practical and has higher precision.
Description
Technical Field
The invention relates to the technical field of oil and gas field development, in particular to a method and a system for constructing a real shale kerogen pore model.
Background
Along with the rapid increase of oil and gas demands, the oil and gas production guarantee pressure is continuously increased, and shale oil becomes an important supplementary resource of traditional oil and gas resources. In an actual stratum, shale oil pores can be divided into organic matter pores and inorganic matter pores according to different development positions of the shale oil pores, and compared with the inorganic matter pores, the organic matter pores play a more complex role in the generation and migration of oil gas. The kerogen pores are important components of the organic matter pores, and when the process of simulating the adsorption, diffusion and flow of shale oil gas in the kerogen pores is simulated, the change of the pore shape can cause larger deviation of the simulation result. Therefore, in order to accurately describe various phenomena of fluids in pores of different strata, interaction between the fluids and organic matter pores is observed, and a reasonable and real kerogen pore structure model is necessary to be constructed.
The current construction of the kerogen pore model has the following problems: 1) The structure of kerogen molecules is very complex, and before the kerogen pores are established, a model of the kerogen molecules is subjected to simulated annealing treatment, so that the density of the kerogen molecules is ensured to be consistent with that of a real stratum, and the kerogen pore model is constructed on the basis, so that the process is very complicated. 2) Because the model construction process of the molecular dynamics simulation of shale oil gas in the nano holes is complex, especially the pore structure except the parallel slits. Therefore, most shale oil organic matter nanopores are constructed based on parallel slits, the slit structure of kerogen pores obtained by the method has larger deviation from the true stratum pore structure, and the shale oil gas characteristic research of different pore forms is very lacking.
Disclosure of Invention
The invention aims to provide a method and a system for constructing a real shale kerogen pore model so as to obtain the shale kerogen pore model which is more fit with reality and has higher precision.
In order to achieve the above object, the present invention provides the following solutions:
a method for constructing a real shale kerogen pore model comprises the following steps:
scanning a real rock sample to be used by adopting an SEM scanning electron microscope to obtain a two-dimensional scanning image of the real rock sample to be used;
performing feature extraction on the two-dimensional scanned image of the real rock sample to be used by adopting a preset RCF edge detection model to obtain a kerogen pore shape feature image;
constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape feature map; the three-dimensional initial kerogen pore model comprises a pore radical and a plurality of kerogen molecules;
and after performing simulated annealing on the three-dimensional initial kerogen pore model, removing the pore atomic groups in the three-dimensional initial kerogen pore model to obtain the kerogen pore model of the real rock sample to be used.
Optionally, the preset RCF edge detection model includes a trunk convolutional neural network, a deep supervision network and a feature fusion network which are sequentially connected;
the backbone convolutional neural network is used for carrying out edge detection on the two-dimensional scanned image of the real rock sample to be used so as to obtain a multi-dimensional pore characteristic image;
the deep supervision network is used for performing supervision learning on each dimension pore characteristic diagram output by the main convolution neural network so as to obtain a corresponding pore edge image;
and the feature fusion network is used for fusing a plurality of pore edge images output by the deep supervision network to obtain a kerogen pore shape feature map of the real rock sample to be used.
Optionally, constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape feature map, specifically including:
constructing a pore atomic group; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram;
inserting the pore atomic groups into a simulation box, and then inserting the prepared plurality of kerogen molecules into the simulation box, so that the plurality of kerogen molecules are uniformly distributed around the pore atomic groups, and a three-dimensional initial kerogen pore model is obtained.
Optionally, performing simulated annealing on the three-dimensional initial kerogen pore model, specifically including:
relaxation treatment is carried out on the three-dimensional initial kerogen pore model by adopting a regular ensemble, so that the three-dimensional initial kerogen pore model in an equilibrium state is obtained;
applying a preset acting force to the three-dimensional initial kerogen pore model in an equilibrium state in the horizontal direction, and then annealing by adopting an isothermal and isobaric ensemble;
and stopping annealing treatment when the densities of the plurality of kerogen molecules in the three-dimensional initial kerogen pore model are equal to the preset plurality of kerogen molecule densities.
Optionally, the method further comprises:
alkane mixtures with different proportions and different components are embedded into the kerogen pore model of the real rock sample to be used, so as to simulate the occurrence state and flow characteristics of shale oil gas in the kerogen pores.
Optionally, the cross-sectional size shape of the pore radical includes circular and triangular; the pore radical is composed of a plurality of oxygen atoms.
In order to achieve the above purpose, the present invention also provides the following technical solutions:
a system for building a true shale kerogen pore model, comprising:
the rock sample scanning module is used for scanning the real rock sample to be used by adopting an SEM scanning electron microscope so as to obtain a two-dimensional scanning image of the real rock sample to be used;
the pore shape extraction module is used for carrying out feature extraction on the two-dimensional scanned image of the real rock sample to be used by adopting a preset RCF edge detection model so as to obtain a kerogen pore shape feature image;
the initial pore model construction module is used for constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape characteristic diagram; the three-dimensional initial kerogen pore model comprises a pore radical and a plurality of kerogen molecules;
and the pore model optimization determining module is used for removing the pore atomic groups in the three-dimensional initial kerogen pore model after performing simulated annealing on the three-dimensional initial kerogen pore model so as to obtain the kerogen pore model of the real rock sample to be used.
Optionally, the initial pore model building module specifically includes:
the atomic group constructing submodule is used for constructing pore atomic groups; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram;
and the pore model construction submodule is used for inserting the pore atomic groups into a simulation box, inserting the prepared plurality of kerogen molecules into the simulation box, and uniformly distributing the plurality of kerogen molecules around the pore atomic groups to obtain a three-dimensional initial kerogen pore model.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a method and a system for constructing a real shale kerogen pore model, wherein an SEM scanning electron microscope is adopted to scan a real rock sample to obtain a two-dimensional scanning image, and a preset RCF edge detection model is adopted to extract features of the two-dimensional scanning image so as to obtain a kerogen pore shape feature image, so that the obtained pore shape feature is attached to an actual rock sample structure, and the method has higher precision. Constructing a three-dimensional initial kerogen pore model based on the feature map, wherein the model comprises pore atomic groups and a plurality of kerogen molecules; and (3) performing simulated annealing on the three-dimensional initial kerogen pore model, and removing pore atomic groups in the model to obtain the kerogen pore model of the real rock sample. The invention utilizes the RCF edge detection model to extract the pore shape, on the basis, atomic groups with the same shape as the kerogen pore shape are constructed, the real kerogen pore structure is obtained through a molecular simulation method, a new thought is provided for researching the occurrence state, the flowing form and the like of the developed shale oil, and the constructed kerogen pore model is attached to a real rock sample, so that the accuracy is higher.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a method of constructing a true shale kerogen pore model of the present invention;
FIG. 2 is a schematic diagram of the structure of a preset RCF edge detection model according to the present invention;
FIG. 3 is a diagram of the pore shape characteristics of kerogen in accordance with the present invention;
FIG. 4 is a schematic representation of two types of differently shaped pore radicals in a three-dimensional initial kerogen pore model of the present invention;
FIG. 5 is a schematic representation of the structure of a three-dimensional initial kerogen pore model of the present invention;
FIG. 6 is a schematic representation of the density change of the three-dimensional initial kerogen void model of the present invention during construction;
FIG. 7 is a schematic flow diagram of a system for constructing a true shale kerogen void model of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention will be further described in detail with reference to the drawings and detailed description below in order to make the objects, features and advantages of the invention more comprehensible.
As shown in fig. 1, the invention provides a method for constructing a true shale kerogen pore model, which comprises the following steps:
and 100, scanning a real rock sample to be used by adopting an SEM scanning electron microscope (Scanning ElectronMicroscope) to obtain a two-dimensional scanning image of the real rock sample to be used.
And 200, carrying out feature extraction on the two-dimensional scanned image of the to-be-used real rock sample by adopting a preset RCF edge detection model so as to obtain a kerogen pore shape feature image.
As shown in fig. 2, the preset RCF edge detection model includes a main convolutional neural network, a deep-supervision (deep-supervision) network, and a feature fusion network, which are sequentially connected; the backbone convolutional neural network is used for carrying out edge detection on the two-dimensional scanned image of the real rock sample to be used so as to obtain a multi-dimensional pore characteristic image; the deep supervision network is used for performing supervision learning on each dimension pore characteristic diagram output by the main convolution neural network so as to obtain a corresponding pore edge image; and the feature fusion network is used for fusing a plurality of pore edge images output by the deep supervision network to obtain a kerogen pore shape feature map of the real rock sample to be used.
Further, the backbone convolutional neural network comprises five convolutional modules (corresponding to five stage one in fig. 2) which are connected in sequence, and the deep supervised network comprises five supervised learning modules (corresponding to five DS in fig. 2).
The input end of the first convolution module is used for inputting the two-dimensional scanning image of the real rock sample to be used, the first output end of the first convolution module is connected with the input end of the second convolution module, and the second output end of the first convolution module is connected with the input end of the first supervised learning module; and the convolution module is used for carrying out edge detection on the two-dimensional scanned image of the real rock sample to be used so as to obtain a pore characteristic image with corresponding dimension.
The first output end of the second convolution module is connected with the input end of the third convolution module, and the second output end of the second convolution module is connected with the input end of the second supervised learning module; the output ends of the third convolution module and the fourth convolution module are connected with each other to obtain the same principle; the output end of the fifth convolution module is connected with the input end of the fifth supervised learning module. And the supervised learning module is used for performing supervised learning on each stage so that each stage outputs an edge detection image. The output ends of the five supervised learning modules are connected with a feature fusion network, and the five edge detection images are fused by the fusion module and a final edge detection image, namely a kerogen pore shape feature diagram, is output, as shown in fig. 3.
Step 300, constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape feature map; the three-dimensional initial kerogen pore model includes a pore radical and a plurality of kerogen molecules.
The kerogen pore characteristics contained in the rock samples in different areas are different, so that pore structures with different shapes are extracted according to different scanning images, and the constructed model is more attached to the shape structure of the local rock sample. As can be seen from fig. 3, the cross-sectional shape of the pore radical may comprise any shape including circular, triangular, quadrilateral, etc., including in particular a number of circles and partial triangles. In one embodiment, kerogen pore modeling is performed using two typical pores, one each, i.e., circular, triangular.
Step 300 specifically includes:
(1) Constructing a pore atomic group; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram, namely, the detected kerogen geometric configuration is utilized to construct the radical, so that the shape of the radical is consistent with the size and shape of the extracted kerogen pore, and the pore space is not changed along with the change of pressure and temperature in the simulation process in the step 400, and only the function of filling the pore space is achieved.
The cross-sectional size shape of the pore radical includes circular and triangular; the corresponding cylindrical atomic group consists of 4500 oxygen atoms (any atoms can be used), the triangular atomic group consists of 3000 oxygen atoms, and the atomic group is placed in the containerAs shown in fig. 4.
(2) Inserting the pore atomic groups into a simulation box, and then inserting the prepared plurality of kerogen molecules into the simulation box, so that the plurality of kerogen molecules are uniformly distributed around the pore atomic groups, and a three-dimensional initial kerogen pore model is obtained. Specifically, 75 II-B kerogen molecules were randomly generated in a simulated box and uniformly dispersed around the radicals, the initial configuration of the kerogen pores was completed, as shown in FIG. 5. The initial density of kerogen backbone was 0.043g cm -3 . Further, the pore radical is inserted into the middle portion of the simulated box.
Step 400, after performing simulated annealing on the three-dimensional initial kerogen pore model, removing the pore atomic groups in the three-dimensional initial kerogen pore model to obtain the kerogen pore model of the real rock sample to be used. In one embodiment, the simulated annealing of step 400 is performed in molecular simulation software LAMMPS, during which the kerogen molecular density is continuously changing, gradually approaching reality. The simulated annealing method is to simulate by adopting two different healds (mainly using regular heald NVT and isothermal isobaric heald NPT), and the temperature and pressure are continuously adjusted to gradually approach the balance of the system.
In step 400, performing simulated annealing on the three-dimensional initial kerogen pore model, which specifically includes:
(1) And adopting a regular ensemble to carry out relaxation treatment on the three-dimensional initial kerogen pore model so as to obtain the three-dimensional initial kerogen pore model in an equilibrium state. Specifically, the system was modeled with a canonical ensemble (NVT) at 800K for 200ps to reach an equilibrium state, i.e., to achieve a gradual increase in the average density of the plurality of kerogen molecules to remain consistent with formation levels.
(2) And applying a preset acting force to the three-dimensional initial kerogen pore model in an equilibrium state in the horizontal direction, and then carrying out annealing treatment by adopting an isothermal and isobaric ensemble (NPT). Specifically, a preset 30MPa acting force is applied to the model in the horizontal direction, isothermal and isobaric ensemble is adopted to perform simulated annealing calculation, so that the temperature of the model is gradually reduced from 800K to 353K, and the specific cooling process and the simulation time are shown in fig. 6.
(3) And stopping annealing treatment when the densities of the plurality of kerogen molecules in the three-dimensional initial kerogen pore model are equal to the preset plurality of kerogen molecule densities. During annealing, the change of temperature and pressure can lead to the change of the size of the box, the volume of the simulation box is gradually reduced and tends to be stable, and the size of the simulation box is contracted to beThe average density of kerogen gradually increased and stabilized to 1.09 g.cm -3 The method is basically consistent with the stratum condition, namely the average density of the kerogen skeleton tends to be constant at the moment, and the annealing treatment is stopped.
And after the simulated annealing is finished, extracting pore atomic groups in the box, wherein the rest part of the three-dimensional initial kerogen pore model is the final configuration of the kerogen pores, and the structure comprises pores with two different shapes, namely circular and triangular.
In a specific embodiment, the method further comprises: and taking the alkane mixture with different proportions and different components as oil gas molecules, embedding the alkane mixture into a kerogen pore model of the real rock sample to be used to obtain a real pore structure of the reservoir so as to simulate the occurrence state and the flow characteristic of shale oil gas in kerogen pores. And analyzing occurrence characteristics and flow rules of each component in pores with different shapes according to simulation results, and providing theoretical basis for shale oil development.
As shown in fig. 7, the embodiment of the present invention further provides a system for constructing a true shale kerogen pore model, which includes:
and the rock sample scanning module 101 is used for scanning the real rock sample to be used by adopting an SEM scanning electron microscope so as to obtain a two-dimensional scanning image of the real rock sample to be used.
And the pore shape extraction module 201 is used for carrying out feature extraction on the two-dimensional scanned image of the to-be-used real rock sample by adopting a preset RCF edge detection model so as to obtain a kerogen pore shape feature image.
An initial pore model construction module 301, configured to construct a three-dimensional initial kerogen pore model based on the kerogen pore shape feature map; the three-dimensional initial kerogen pore model includes a pore radical and a plurality of kerogen molecules.
And the pore model optimization determining module 401 is configured to remove the pore atomic groups in the three-dimensional initial kerogen pore model after performing simulated annealing on the three-dimensional initial kerogen pore model, so as to obtain a kerogen pore model of the real rock sample to be used.
The initial pore model building module specifically comprises: the atomic group constructing submodule is used for constructing pore atomic groups; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram; and the pore model construction submodule is used for inserting the pore atomic groups into a simulation box, inserting the prepared plurality of kerogen molecules into the simulation box, and uniformly distributing the plurality of kerogen molecules around the pore atomic groups to obtain a three-dimensional initial kerogen pore model.
In conclusion, the invention scans the real rock sample by using an experimental method of an SEM scanning electron microscope to obtain a two-dimensional scanning image of the real rock sample; extracting the edges of the SEM scanning image by using an RCF edge detection model to obtain the geometrical shape of a real shale kerogen pore; constructing an initial structure of kerogen pores, placing atomic groups with the same shape as the kerogen pores in the middle of a box, and inserting a certain number of kerogen molecules around the atomic groups; performing simulated annealing calculation on the model by using a molecular simulation method to ensure that the average density of kerogen is gradually increased and kept consistent with the stratum level, and balancing the model at the moment; after the annealing process is finished, deleting the atomic groups in the middle of the box to generate a final configuration of kerogen pores; alkane mixtures with different proportions and components are inserted into kerogen pores to simulate the actual occurrence state and flow rule of shale oil. The alkane mixture is embedded into kerogen pores, and various simulation researches are carried out on the underground real pore structure.
The invention combines a molecular dynamics simulation method, so that the geometry of the kerogen pores is not only remained in a single slit, a more real and reliable kerogen pore model is provided for the molecular dynamics simulation of shale oil, the problem of the kerogen pore characteristics under the real stratum condition is solved when the molecular dynamics simulation is constructed, the kerogen molecular pore structure can be more similar to the actual condition in the simulation process, and the accuracy is higher.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (6)
1. The method for constructing the real shale kerogen pore model is characterized by comprising the following steps of:
scanning a real rock sample to be used by adopting an SEM scanning electron microscope to obtain a two-dimensional scanning image of the real rock sample to be used;
performing feature extraction on the two-dimensional scanned image of the real rock sample to be used by adopting a preset RCF edge detection model to obtain a kerogen pore shape feature image;
constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape feature map; the three-dimensional initial kerogen pore model comprises a pore radical and a plurality of kerogen molecules; based on the kerogen pore shape feature diagram, constructing a three-dimensional initial kerogen pore model, which specifically comprises the following steps: constructing a pore atomic group; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram; inserting the pore atomic groups into a simulation box, and then inserting the prepared plurality of kerogen molecules into the simulation box, so that the plurality of kerogen molecules are uniformly distributed around the pore atomic groups to obtain a three-dimensional initial kerogen pore model;
and after performing simulated annealing on the three-dimensional initial kerogen pore model, removing the pore atomic groups in the three-dimensional initial kerogen pore model to obtain the kerogen pore model of the real rock sample to be used.
2. The method for constructing a true shale kerogen pore model according to claim 1, wherein the preset RCF edge detection model comprises a trunk convolutional neural network, a deep supervision network and a feature fusion network which are connected in sequence;
the backbone convolutional neural network is used for carrying out edge detection on the two-dimensional scanned image of the real rock sample to be used so as to obtain a multi-dimensional pore characteristic image;
the deep supervision network is used for performing supervision learning on each dimension pore characteristic diagram output by the main convolution neural network so as to obtain a corresponding pore edge image;
and the feature fusion network is used for fusing a plurality of pore edge images output by the deep supervision network to obtain a kerogen pore shape feature map of the real rock sample to be used.
3. The method for constructing a true shale kerogen pore model of claim 1, wherein the simulated annealing of the three-dimensional initial kerogen pore model specifically comprises:
relaxation treatment is carried out on the three-dimensional initial kerogen pore model by adopting a regular ensemble, so that the three-dimensional initial kerogen pore model in an equilibrium state is obtained;
applying a preset acting force to the three-dimensional initial kerogen pore model in an equilibrium state in the horizontal direction, and then annealing by adopting an isothermal and isobaric ensemble;
and stopping annealing treatment when the densities of the plurality of kerogen molecules in the three-dimensional initial kerogen pore model are equal to the preset plurality of kerogen molecule densities.
4. The method of constructing a true shale kerogen pore model of claim 1, wherein the method further comprises:
alkane mixtures with different proportions and different components are embedded into the kerogen pore model of the real rock sample to be used, so as to simulate the occurrence state and flow characteristics of shale oil gas in the kerogen pores.
5. The method of constructing a true shale kerogen pore model of claim 1 wherein the pore radical cross-sectional size shapes include circles and triangles; the pore radical is composed of a plurality of oxygen atoms.
6. A system for constructing a true shale kerogen pore model, the system comprising:
the rock sample scanning module is used for scanning the real rock sample to be used by adopting an SEM scanning electron microscope so as to obtain a two-dimensional scanning image of the real rock sample to be used;
the pore shape extraction module is used for carrying out feature extraction on the two-dimensional scanned image of the real rock sample to be used by adopting a preset RCF edge detection model so as to obtain a kerogen pore shape feature image;
the initial pore model construction module is used for constructing a three-dimensional initial kerogen pore model based on the kerogen pore shape characteristic diagram; the three-dimensional initial kerogen pore model comprises a pore radical and a plurality of kerogen molecules; the initial pore model construction module specifically comprises:
the atomic group constructing submodule is used for constructing pore atomic groups; the cross-sectional size shape of the pore radical is consistent with the pore shape in the kerogen pore shape feature diagram;
the pore model construction submodule is used for inserting the pore atomic groups into a simulation box, inserting the prepared plurality of kerogen molecules into the simulation box, and uniformly distributing the plurality of kerogen molecules around the pore atomic groups to obtain a three-dimensional initial kerogen pore model;
and the pore model optimization determining module is used for removing the pore atomic groups in the three-dimensional initial kerogen pore model after performing simulated annealing on the three-dimensional initial kerogen pore model so as to obtain the kerogen pore model of the real rock sample to be used.
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