Method for preparing microfluidic chip, microscopic visualization experimental device and method

Abstract

The present application provides a method for preparing a microfluidic chip, a microscopic visualization experimental device and a method, which belong to the field of microfluidic chip technology. The preparation method includes: obtaining a scanned image through electron beam imaging technology; extracting features from the scanned image to generate corresponding feature vectors, judging the feature vectors using a preset mineral and pore identification vector space, and obtaining a transition classification feature vector; calculating the probability that the feature to be identified belongs to various features, and combining the preset identification rules to identify the category of the feature to be identified to form a three-dimensional reconstruction of the core identification; based on the feature distribution of the three-dimensional reconstruction and using fracture simulation technology, the feature distribution after fracturing is obtained; and preparing a microfluidic chip. The present application classifies the features and uses core reconstruction and fracture simulation technology to obtain the true characteristics of the fracture network distribution after fracturing; and also designs a microfluidic chip suitable for flow research based on the target permeability to effectively simulate its permeability flow characteristics.

Description

Technical Field

[0001] The present application belongs to the field of microfluidic chip technology, and in particular relates to a method for preparing a microfluidic chip, a control device, a readable storage medium, a microscopic visualization experimental device, and an experimental method. Background Art

[0002] Microfluidic chip technology is a technology for visualizing flow within porous media. Among related technologies, microfluidic chip technology can be used to simulate geological environments such as soil or shale. However, due to the complex morphology of fractures during fracturing, monitoring is difficult. Microfluidic chip technology for the construction of porous media is still in its early stages, and the chip models established are generally ideal, mainly used for simulating homogeneous structures. For example, using a homogeneous structure composed of staggered microcolumns or narrow rectangles to directly characterize pores and fractures is difficult to truly reflect the pore and fracture characteristics and heterogeneous characteristics of the geological body after fracturing. Summary of the Invention

[0003] The purpose of this application is to provide a method for preparing a microfluidic chip, a control device, a readable storage medium, a microscopic visualization experimental device and an experimental method, which are intended to truly reflect the pore and fracture characteristics and heterogeneous characteristics of a geological body after being fractured.

[0004] According to a first aspect of the present application, a method for preparing a microfluidic chip is provided, the method comprising: for a core sample to be tested of a preset shape, obtaining a scanned image of the core sample to be tested by electron beam imaging technology when continuously cutting the core sample using a gallium ion beam; performing feature extraction on the scanned image to generate a corresponding feature vector, and judging the feature vector using a preset mineral and pore identification vector space to obtain a transition classification feature vector; based on the obtained transition classification feature vector, calculating the probability that the feature to be identified belongs to various features, and identifying the category of the feature to be identified in combination with preset identification rules to form a three-dimensional reconstruction of the core identification; based on the feature distribution of the formed three-dimensional reconstruction and using fracture simulation technology, deriving the feature distribution after fracturing; and preparing a microfluidic chip based on the feature distribution after fracturing.

[0005] In an optional embodiment, the probability that the feature to be identified belongs to various features is calculated based on the obtained transition classification feature vector, including: dividing the various features into a first feature and a second feature, the first feature being pores and fractures, and the second feature being minerals; calculating the distance from the transition classification feature vector to the spatial feature center point of the mineral in a preset network, and calculating the distance from the transition classification feature vector to the spatial feature center point of the pores and fractures in the preset network to obtain the probability of pores and fractures; for multiple minerals in the second feature, calculating the distance from the transition classification feature vector to the spatial feature center point of each mineral in the preset network to obtain the probability of each mineral; and generating a probability distribution vector based on the obtained probability of each mineral.

[0006] In an optional embodiment, the combination of preset recognition rules to identify the category of the feature to be identified includes: dividing the feature to be identified into pore fractures and multiple minerals; when the probability of pore fractures exceeds a first threshold, identifying it as a pore fracture; when the probability of pore fractures is less than the first threshold, identifying it as a non-pore fracture; when the probability of any mineral exceeds a second threshold, identifying the corresponding mineral category; when the probabilities of all minerals are less than the second threshold, screening a set of mineral categories with probabilities greater than a third threshold, and combining the mechanical superordinate category to identify the mineral category. Wherein, the first threshold is greater than the second threshold, and the second threshold is greater than the third threshold.

[0007] In an optional embodiment, the combination of mechanical superordinate categories to identify mineral categories includes: if the minerals in the mineral category set belong to the same mechanical superordinate category, then they are identified as that category; if the minerals in the mineral category set belong to multiple mechanical superordinate categories, then they are identified as the highest category.

[0008] In an optional embodiment, the use of fracture simulation technology to obtain the characteristic distribution after fracturing includes: using the fracture phase field equation to construct a basic model for fracture simulation to obtain a three-dimensional mineral distribution; performing corresponding model loading according to preset requirements, recording the basic pore and mineral characteristic distribution at the starting time and the new pore and mineral characteristic distribution formed after loading is completed, and selecting a slice in one direction for processing, so as to design the structure of the microfluidic chip after processing.

[0009] In an optional embodiment, the microfluidic chip includes two pieces of glass, the pore throat characteristics of the mineral distribution are etched on one of the pieces of glass, and the other piece of glass is unetched glass. The two pieces of glass are bonded to obtain a sealed microfluidic chip.

[0010] According to a second aspect of the present application, a control device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above method.

[0011] According to a third aspect of the present application, a machine-readable storage medium is provided, on which instructions are stored, and the instructions enable a machine to execute the above method.

[0012] According to the fourth aspect of the present application, a microscopic visualization experimental device is provided, which includes a displacement pump, a crude oil intermediate container, a gas intermediate container, a microscope, a camera system, a pressure sensor, a back pressure unit, a confining pressure tracking pump, and a microfluidic chip prepared by the above method. The injection port of the microfluidic chip is connected to the outlet ends of the crude oil intermediate container and the gas intermediate container respectively through an injection pipeline, and a first control valve and the pressure sensor are provided on the injection pipeline. The inlet end of the crude oil intermediate container is connected to the displacement pump through a crude oil delivery pipeline, and a second control valve is provided on the crude oil delivery pipeline. The inlet end of the gas intermediate container is connected to the displacement pump through a gas delivery pipeline, and a third control valve is provided on the gas delivery pipeline. The microscope is arranged above the microfluidic chip, the microscope is connected to the camera system, the outlet of the microfluidic chip is connected to the back pressure unit through a production pipeline, a fourth control valve is provided on the production pipeline, and the confining pressure tracking pump is connected to the injection pipeline.

[0013] According to a fifth aspect of the present application, a microscopic visualization experimental method is provided, which uses the above-mentioned microscopic visualization experimental device to conduct experiments, and the microscopic visualization experimental method includes: installing a microfluidic chip in a high-pressure visual kettle, adding confining pressure liquid, and heating to a preset formation temperature; controlling the confining pressure by a confining pressure tracking pump to make it higher than the internal pressure of the microfluidic chip; placing a microscope above the microfluidic chip, and adjusting the focus position and magnification of the microscope; filling crude oil into a crude oil intermediate container connected to a displacement pump, and filling a preset gas into a gas intermediate container; closing the first control valve, vacuuming the microfluidic chip, opening the first control valve and the second control valve, and using the displacement pump to inject crude oil into the injection port of the microfluidic chip; closing the second control valve, keeping the first control valve open, opening the third control valve and the fourth control valve, and using the displacement pump to inject a preset gas into the microfluidic chip to discharge the crude oil, closing the fourth control valve, and injecting the preset gas; when the pressure in the microfluidic chip reaches a preset value, stopping the gas injection to simulate sealing.

[0014] Through the above technical solution, the method for preparing a microfluidic chip provided in the embodiments of the present application includes: obtaining a scanned image of a core sample of a predetermined shape using electron beam imaging technology while continuously cutting the core sample using a gallium ion beam; extracting features from the scanned image to generate corresponding feature vectors, and then judging the feature vectors using a preset mineral and pore and fracture identification vector space to obtain transition classification feature vectors; calculating the probability of the identified feature belonging to various features based on the obtained transition classification feature vectors, and identifying the category of the identified feature in combination with preset identification rules to form a three-dimensional reconstruction of the core identification; deriving a post-fracture feature distribution based on the feature distribution of the generated three-dimensional reconstruction and using fracture simulation technology; and preparing a microfluidic chip based on the post-fracture feature distribution. The embodiments of the present application utilize a preset network to identify different features (pores, fractures, and different minerals); classifying the features, and using core reconstruction and fracture simulation technology to derive the true characteristics of the post-fracture fracture network distribution. The embodiments of the present application also design a microfluidic chip suitable for flow research based on the target permeability to effectively simulate its permeability flow characteristics.

[0015] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present application. The purpose and other advantages of the present application can be achieved and obtained through the structures and processes indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. It is obvious that the drawings described below are certain embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 It is a flow chart of a method for preparing a microfluidic chip provided by an exemplary embodiment of the present application.

[0018] Figure 2 Schematic diagram of feature distribution of three-dimensional reconstruction provided by an exemplary embodiment of the present application.

[0019] Figure 3 It is a schematic diagram of the post-compression characteristic distribution of an exemplary embodiment of the present application.

[0020] Figure 4 It is a schematic diagram of the mineral and fracture distribution characteristics before compression of an exemplary embodiment of the present application.

[0021] Figure 5It is a schematic diagram of the mineral and fracture distribution characteristics after compression of an exemplary embodiment of the present application.

[0022] Figure 6 Schematic diagram of a triangular array cylinder of an exemplary embodiment of the present application.

[0023] Figure 7 It is a structural schematic diagram of a microscopic visualization experimental device provided by an exemplary embodiment of the present application.

[0024] Figure 8 It is a schematic diagram comparing the flow conditions of the microfluidic chip design of the exemplary embodiment of the present application with the flow conditions of the actual rock core.

[0025] Figure 9 It is a schematic diagram comparing the flow conditions of the microfluidic chip design of the exemplary embodiment of the present application with the flow conditions of the traditional microfluidic uniform design.

[0026] Among them, 1-displacement pump, 2-crude oil intermediate container, 3-gas intermediate container, 4-confining pressure tracking pump, 5-third control valve, 6-second control valve, 7-first control valve, 8-microfluidic chip, 9-fourth control valve, 10-microscope, 11-pressure sensor, 12-computing module, 13-back pressure unit, 14-camera system. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] Figure 1 1 is a flow chart of a method for preparing a microfluidic chip provided by an exemplary embodiment of the present application. The method may include the following steps:

[0029] Step S110: For a core sample to be tested with a preset shape, a scanning image of the core sample to be tested is obtained by electron beam imaging technology when the gallium ion beam is used for continuous cutting.

[0030] In the embodiments of the present application, a suitable core sample to be tested (e.g., a shale micro-mineral structure) can be selected and cut into a rectangular parallelepiped shape. Preferably, a gallium ion beam is used to continuously cut the core sample to be tested, while simultaneously imaging the sample under an electron beam to obtain a scanned image. For example, an 80mm*80mm*140mm sample is selected and continuously cut using a gallium ion beam while simultaneously imaging the sample under an electron beam to obtain a scanned image.

[0031] Step S120: extracting features from the scanned image to generate corresponding feature vectors, and using a preset mineral and pore identification vector space to judge the feature vectors to obtain transition classification feature vectors.

[0032] In this embodiment, shale microstructures can be classified into clay minerals, aggregate minerals, and organic matter based on their mechanical properties. Clay minerals include illite, kaolinite, and montmorillonite, while aggregate minerals include pyrite, quartz, albite, and potassium feldspar. A convolution operation within a deep learning neural network can be used to extract feature vectors from scanned images. Once these feature vectors are obtained, they can be evaluated using a pre-defined mineral and pore identification vector space to generate a transition classification feature vector.

[0033] The pre-set mineral and pore identification vector space can be considered a feature set, where each mineral has a corresponding feature range. For example, in three-dimensional space, if two cubes are stacked, each representing a different mineral, the (x, y, z) coordinates of a feature point may fall within them, meaning that the feature vector falls within the pre-set mineral and pore identification vector space.

[0034] Taking clay minerals as an example, after obtaining the corresponding feature vector, the feature vector is judged using the preset mineral and pore identification vector space to obtain the transition classification feature vector Among them, the transition classification feature vector , which is the position of the area to be identified in the high-dimensional space, Can represent a series of characteristics.

[0035] Step S130: Based on the obtained transition classification feature vector, the probability that the feature to be identified belongs to various features is calculated, and the category of the feature to be identified is identified in combination with the preset identification rules to form a three-dimensional reconstruction of the core identification.

[0036] In an embodiment of the present application, based on the obtained transition classification feature vector, the probability that the feature to be identified belongs to various features is calculated, which can include: dividing the various features into a first feature and a second feature, the first feature being pores and cracks, and the second feature being minerals; calculating the distance from the transition classification feature vector to the spatial feature center point of the mineral in a preset network, and calculating the distance from the transition classification feature vector to the spatial feature center point of the pores and cracks in the preset network to obtain the probability of pores and cracks; for multiple minerals in the second feature, calculating the distance from the transition classification feature vector to the spatial feature center point of each mineral in the preset network to obtain the probability of each mineral; and generating a probability distribution vector based on the obtained probability of each mineral.

[0037] The preset network can be a trained convolutional neural network, which includes a high-dimensional space feature vector space. For example, various features are first divided into pores and cracks and minerals. Pores and cracks and minerals can have projection centers of different features (i.e., feature centers). For example, two spaces, pores and cracks and minerals, are preset in the high-dimensional space. The two spaces have feature centers respectively. The feature center point of the pore and crack space is, for example, , the characteristic center point of the mineral space is, for example, , the transition classification feature vector can be calculated by the following formula The distance to the center point of the mineral's high-dimensional spatial feature:

[0038]

[0039] The distance from the transition classification feature vector to the center point of the pore fracture high-dimensional space feature can be calculated by the following formula:

[0040]

[0041] The probability of pore cracks can be calculated using the following formula:

[0042]

[0043] Furthermore, N feature subspaces (corresponding to multiple minerals) can be preset within the high-dimensional mineral feature space. For example, the multiple minerals include illite, kaolinite, montmorillonite, pyrite, quartz, albite, potassium feldspar, and organic matter. The corresponding feature space center point position is, for example: , … The following formula can be used to calculate the distance between the feature of the point to be identified and the center point of the corresponding feature of different minerals based on the transition classification feature vector:

[0044]

[0045]

[0046] in, is the distance from the transition classification feature vector to the feature center point of each mineral subspace, is the probability of the mineral, is the high-dimensional space capacity corresponding to the mineral subspace, is the total high-dimensional space capacity of the mineral space, from which the probability distribution vector can be obtained. Among them, the probability of the mineral is calculated based on the normalized probability distribution vector, and the sum of the probabilities of all minerals is 1.

[0047] In an embodiment of the present application, in combination with preset recognition rules, identifying the category of the feature to be identified may include: classifying the feature to be identified as pore fractures and multiple minerals; when the probability of pore fractures exceeds a first threshold, identifying it as a pore fracture; when the probability of pore fractures is less than the first threshold, identifying it as a non-pore fracture; when the probability of any mineral exceeds a second threshold, identifying the corresponding mineral category; when the probabilities of all minerals are less than the second threshold, screening the set of mineral categories with probabilities greater than a third threshold, and combining the mechanical superordinate category to identify the mineral category. Wherein, the first threshold is greater than the second threshold, and the second threshold is greater than the third threshold.

[0048] For example, the probability that the feature to be identified belongs to various features (i.e., pores and cracks and different minerals) is calculated to obtain a probability distribution vector; the probability that it belongs to pores and cracks is calculated, and if the probability is greater than a first threshold (e.g., 0.8), its probability is output to determine that the feature to be identified is a pore and crack; if its probability is less than the first threshold, it is not a pore and crack; the probability of being a mineral is calculated, and according to the probability distribution vector, when the probability of any mineral category in the probability distribution vector is greater than a second threshold (e.g., 0.5), the probability of the mineral category is output; when the probabilities of all mineral categories are less than the second threshold, multiple mineral categories with probabilities greater than a third threshold (e.g., 0.06) are obtained.

[0049] In an embodiment of the present application, the identification of mineral categories is performed in combination with mechanical superordinate categories, which may include: if the minerals in the mineral category set belong to the same mechanical superordinate category, then they are identified as that category; if the minerals in the mineral category set belong to multiple mechanical superordinate categories, then they are identified as the highest category.

[0050] Continuing with the above example, when multiple mineral categories belong to the same mechanical superordinate category, the mechanical superordinate category of the group of minerals is output. If multiple minerals belong to multiple mechanical superordinate categories, the mechanical superordinate category of the mineral with the highest probability of occurrence is output. Mechanical superordinate categories can include aggregate minerals, clay minerals, and organic matter, and are marked with labels.

[0051] For example, the probability that the feature to be identified belongs to pore fracture is calculated (for example, 0.2), that is, its probability is less than the first threshold (for example, 0.8), then it is determined that the feature to be identified is not a pore fracture. For example, the output probability distribution vector is an 8-dimensional normalized vector: [illite 10%, kaolinite 50%, montmorillonite 2%, pyrite 10%, quartz 5%, albite 12%, potassium feldspar 10%, organic matter 1%]; according to the probability distribution vector, in the probability distribution vector, the probability of the kaolinite category is greater than the second threshold (for example, 0.5), and the mineral category is output; if the mineral mechanics superordinate category is clay mineral, it is determined to be a clay mineral and marked with a label. If Figure 2As shown, a three-dimensional reconstruction of the core identification is formed, where black, light gray, and dark gray represent aggregate minerals, clay minerals, and organic matter, respectively.

[0052] In the embodiments of this application, Figure 2 As shown, after performing 3D reconstruction to obtain pores, clay minerals, aggregate minerals (e.g., pyrite), and organic matter, nanoindentation experiments are then used to characterize the basic mechanical properties of different mineral types, or to directly obtain the basic properties of different mineral compositions based on records. As in the example above, different components (different features) are labeled (i.e., tagged) to obtain the characteristic distribution after 3D reconstruction.

[0053] Step S140: Based on the formed three-dimensional reconstructed characteristic distribution and using fracture simulation technology, the characteristic distribution after fracturing is obtained.

[0054] In an embodiment of the present application, step S140 may include using the fracture phase field equation to construct a basic model for fracture simulation to obtain a three-dimensional mineral distribution; performing corresponding model loading according to preset requirements, recording the basic pore and mineral characteristic distribution at the starting time and the new pore and mineral characteristic distribution formed after the loading is completed, and selecting a slice in one direction for processing, so as to design the structure of the microfluidic chip after processing.

[0055] In the embodiment of the present application, in order to obtain the true fracture development characteristics of the post-compression reservoir as much as possible, the embodiment of the present application preferably assigns values ​​to its mechanical parameters, preferably using a fracture phase field simulation method. The fracture phase field equation can be solved by the following formula:

[0056]

[0057] in, is the Cauchy tensor, is the displacement tensor, Indicates physical strength, is the phase field diffusion width, To avoid small singularities, The largest strain energy in history, is the phase field variable, is the critical energy release rate.

[0058] by [ ] is an example of the mechanical assignment rule. Corresponding to the mechanical parameters of aggregate minerals, clay minerals and organic matter. For example, [ ] correspond to the fracture energies of aggregate minerals, clay minerals, and organic matter, respectively. After setting up the basic model, a three-dimensional mineral distribution is obtained and loaded accordingly. The basic pore and mineral distribution at the start and the new pore and mineral distribution formed after loading are recorded. A slice in one direction is selected for processing, and the microfluidic chip structure is designed after processing.

[0059] In the embodiment of the present application, displacement loading simulation can be set, for example, the loading rate is 0.1 [m / s], to simulate matrix dilatancy, or load boundary conditions directly corresponding to the on-site monitoring results can be used for simulation. After loading, the crack development and fracture conditions of the core can be obtained, such as Figure 3 After the matrix dilatancy simulation is performed, slices are selected to extract their corresponding features. Figure 4 and Figure 5 The mineral and fracture distribution characteristics before and after fracturing show great differences. The fractures and pores are redistributed, and the simulation after fracturing is accurately realized.

[0060] Step S150: preparing a microfluidic chip based on the characteristic distribution after fracturing.

[0061] The preferred microfluidic chip in the embodiment of the present application may include two pieces of glass, the pore throat characteristics of the mineral distribution are etched on one of the pieces of glass, and the other piece of glass is unetched glass. The two pieces of glass are bonded to obtain a sealed microfluidic chip.

[0062] The present embodiment preferably adopts a triangular array cylindrical design microfluidic chip structure, and the target permeability is known. and cylinder diameter (It can be selected according to the design accuracy of the microfluidic chip), and the design porosity of the organic mineral can be calculated according to the following formula: :

[0063] (7)

[0064]

[0065]

[0066] in, It is an intermediate variable of organic minerals. It is the second intermediate variable of organic minerals.

[0067] For clay minerals, the following formula can be used to solve :

[0068] (10)

[0069]

[0070]

[0071] in, is an intermediate variable of clay minerals. It is the second intermediate variable of clay minerals.

[0072] In getting and After that, the distance between adjacent cylinders can be calculated according to the following formula:

[0073]

[0074] in, is pi, To design the porosity for the corresponding mineral, is the distance between adjacent cylinders.

[0075] For example, if Figure 6 As shown, a triangular array cylindrical design is used, and the target permeability For example, , the design diameter is e.g. The porosity of organic minerals can be calculated according to formula (7)-formula (9). ,For example, For clay minerals, equations (10) to (12) can be used to solve ,For example, . In getting and After that, the distance between adjacent cylinders can be obtained according to formula (13), for example, and .

[0076] In the embodiment of the present application, a broken basic chip is obtained after design, and the design method is as follows Figure 6 As shown, according to the obtained correspond Figure 5 The structure is designed and then processed to produce a microfluidic chip. The microfluidic chip can be composed of two pieces of glass, one of which has the pore throat characteristics of the mineral distribution etched on it, and the other piece of glass is smooth and unetched. The two pieces of glass are bonded together to form a sealed microscopic visualization chip.

[0077] Accordingly, the method for preparing a microfluidic chip provided in an embodiment of the present application includes: obtaining a scanned image of a core sample of a predetermined shape using electron beam imaging technology while continuously cutting the core sample using a gallium ion beam; extracting features from the scanned image to generate corresponding feature vectors, and then judging the feature vectors using a predetermined mineral and pore / fracture identification vector space to obtain transition classification feature vectors; calculating the probability of the identified feature belonging to various features based on the obtained transition classification feature vectors, and identifying the category of the identified feature based on predetermined identification rules to form a three-dimensional reconstruction of the core identification; deriving a post-fracture feature distribution based on the feature distribution of the generated three-dimensional reconstruction and using fracture simulation techniques; and preparing a microfluidic chip based on the post-fracture feature distribution. This embodiment of the present application utilizes a predetermined network to identify different features (pores, fractures, and different minerals); classifying the features, and using core reconstruction and fracture simulation techniques to derive the true characteristics of the post-fracture fracture network distribution. This embodiment of the present application also designs a microfluidic chip suitable for flow research based on the target permeability to effectively simulate its permeability flow characteristics.

[0078] An embodiment of the present application also provides a control device, characterized in that the control device may include: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the above method.

[0079] An embodiment of the present application also provides a machine-readable storage medium, on which instructions are stored, and the instructions enable a machine to execute the above method.

[0080] It should be noted that the above-mentioned control device and machine-readable storage medium can implement the method for preparing a microfluidic chip provided in the above-mentioned embodiment. The specific implementation method can be found in the description of the method for preparing a microfluidic chip in the above-mentioned embodiment, which will not be repeated here.

[0081] like Figure 7As shown, the present invention also provides a microscopic visualization experimental device, which may include a displacement pump 1, a crude oil intermediate container 2, a gas intermediate container 3, a microscope 10, a camera system 14, a pressure sensor 11, a back pressure unit 13, a confining pressure tracking pump 4, and a microfluidic chip 8 prepared using the above method. The injection port of the microfluidic chip 8 is connected to the outlets of the crude oil intermediate container 2 and the gas intermediate container 3 respectively via injection pipelines. The injection pipelines are provided with a first control valve 7 and a pressure sensor 11. The inlet of the crude oil intermediate container 2 is connected to the displacement pump 1 via a crude oil delivery pipeline, which is provided with a second control valve 6. The inlet of the gas intermediate container 3 is connected to the displacement pump 1 via a gas delivery pipeline, which is provided with a third control valve 5. The microscope 10 is disposed above the microfluidic chip 8 and connected to the camera system 14. The outlet of the microfluidic chip 8 is connected to the back pressure unit 13 via a production pipeline, which is provided with a fourth control valve 9. The confining pressure tracking pump 4 is connected to the injection pipeline.

[0082] For example, the microscopic visualization experimental device can be used to simulate CO2 throughput, using the microfluidic chip 8 prepared by the above method, and the experimental device also includes a computing module 12. Figure 7 As shown, the injection port of the microfluidic chip 8 is connected to the outlets of the crude oil intermediate container 2 and the CO2 gas intermediate container 3, respectively, via injection pipelines. A first control valve 7 and a pressure sensor 11 are installed on the injection pipelines. The inlet of the crude oil intermediate container 2 is connected to the displacement pump 1 via a crude oil delivery pipeline, on which a second control valve 6 is installed. The inlet of the CO2 gas intermediate container 3 is connected to the displacement pump 3 via a CO2 gas delivery pipeline, on which a third control valve 5 is installed. A microscope 10 is installed above the microscopic visualization chip 8 and is connected to a camera system 14, which in turn is connected to a computing module 12. The production port of the microfluidic chip 8 is connected to a backpressure unit 13 via a production pipeline, on which a fourth control valve 9 is installed. The injection pipeline is also connected to a confining pressure tracking pump 4.

[0083] The embodiment of the present application further provides a microscopic visualization experimental method, which utilizes the above-mentioned microscopic visualization experimental device to conduct experiments. The microscopic visualization experimental method may include steps S11 to S16.

[0084] Step S11: Install the microfluidic chip in a high-pressure visual autoclave, add confining pressure fluid, and heat to a preset formation temperature.

[0085] In step S12, the surrounding pressure is controlled by a surrounding pressure tracking pump to be higher than the internal pressure of the microfluidic chip.

[0086] Step S13: Place a microscope above the microfluidic chip and adjust the focus position and magnification of the microscope.

[0087] Step S14: Fill crude oil into the crude oil intermediate container connected to the displacement pump, and fill a preset gas into the gas intermediate container.

[0088] Step S15 , closing the first control valve, evacuating the microfluidic chip, opening the first control valve and the second control valve, and injecting crude oil into the injection port of the microfluidic chip using a displacement pump.

[0089] Step S16: close the second control valve, keep the first control valve open, open the third control valve and the fourth control valve, use the displacement pump to inject the preset gas into the microfluidic chip to discharge the crude oil, close the fourth control valve, and inject the preset gas.

[0090] Step S17: When the pressure in the microfluidic chip reaches a preset value, gas injection is stopped to simulate sealing.

[0091] Please refer to Figure 7 For example, the microfluidic chip is installed in a high-pressure visualization autoclave, a confining pressure fluid is added, and the fluid is heated to a preset formation temperature. A confining pressure tracking pump controls the confining pressure to a level higher than the pressure inside the microvisualization chip. A microscope is placed above the microvisualization chip, and the focus and magnification are adjusted until a clear image of the micro- and nanoscale channels is displayed on a computer. The crude oil intermediate container connected to the displacement pump is filled with crude oil, and the CO2 intermediate container is filled with CO2 gas. Close the first control valve 7, and evacuate the microvisualization chip to ensure that no air is present inside the chip. Open the second and first control valves 6 and 7, and use the displacement pump to inject crude oil into the injection port of the microfluidic chip, ensuring that the chip is saturated with crude oil. Close the second control valve 6, open the third, first, and fourth control valves 5 and 7, and use the displacement pump to inject CO2 into the microfluidic chip to expel the crude oil. Then, close the fourth control valve 9 and inject CO2. When the pressure inside the chip reaches the preset value, gas injection is stopped, simulating sealing. Throughout the process, microscopes and cameras are used to capture fluid behavior and upload it to a computer for analysis.

[0092] In order to verify the validity of the results and the necessity of the invention, the present application also provides a two-phase flow simulation. According to the above method, the corresponding microfluidic chip is prepared and soaked with oil. Supercritical CO2 is injected from the left side at a rate of 0.1m / s to obtain a flow state. Then, the porous medium seepage simulation is directly performed according to the real mineral and crack distribution without microfluidic experimental simulation. The results are as follows Figure 8 As shown in the figure, (a) shows the flow of the microfluidic chip provided by the embodiment of the present application, and (b) shows the real simulation situation considering the distribution of minerals and cracks. Figure 8 In the figure, the overall flow morphology characteristics of (a) and (b) are similar, and and Blocked by low permeability minerals, it is different from the actual flow state. and All of them are subject to similar obstructions, which indicates that they are similar not only in overall flow morphology but also in mineral details. Figure 9 A flow comparison of two different microfluidic chips was conducted. It can be seen that compared with Figure 9 The conventional microfluidic experiment uniform design shown in (a) is provided in the embodiment of the present application. Figure 9 The microfluidic chip design shown in (b) can capture more flow characteristics and flow details.

[0093] Based on this, the present embodiment utilizes a pre-set network to identify different features (pores, fractures, and different minerals), classifies these features, and utilizes core reconstruction and fracture simulation techniques to derive the true characteristics of the fracture network distribution after fracturing. The present embodiment also designs a microfluidic chip suitable for flow research based on the target permeability, effectively simulating its permeability flow characteristics. Based on this, the present embodiment provides a microscopic visualization experimental device and method, addressing the limitations of existing technologies in describing the distribution characteristics of pores, fractures, and minerals in reservoirs after fracturing.

[0094] It is understood that the circuit structures, names, and parameters described in the above embodiments are merely examples. Those skilled in the art may also readily conceive of combinations and adjustments to the structural features of the above embodiments as needed, and should not limit the concept of this application to the specific details of the above examples.

[0095] Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for preparing a microfluidic chip, characterized in that: The method comprises: For a rock core sample of a preset shape to be tested, a scanning image of the rock core sample to be tested is obtained by electron beam imaging technology when continuously cutting the rock core sample using a gallium ion beam; Extracting features from the scanned image to generate corresponding feature vectors, and using a preset mineral and pore identification vector space to judge the feature vectors to obtain transition classification feature vectors; Based on the obtained transition classification feature vector, the probability that the feature to be identified belongs to various features is calculated, and the category of the feature to be identified is identified in combination with the preset recognition rules to form a three-dimensional reconstruction of the core identification; Based on the generated three-dimensional reconstructed characteristic distribution, and using fracture simulation technology, deriving the characteristic distribution after fracturing; and preparing a microfluidic chip based on the characteristic distribution after the fracturing; The method of calculating the probability that the feature to be identified belongs to various features based on the obtained transition classification feature vector includes: The various features are divided into a first feature and a second feature, wherein the first feature is pores and cracks, and the second feature is minerals; Calculating the distance between the transition classification feature vector and the center point of the spatial feature of the mineral in the preset network, and calculating the distance between the transition classification feature vector and the center point of the spatial feature of the pore fracture in the preset network, to obtain the probability of the pore fracture; For the multiple minerals in the second feature, calculating the distance between the transition classification feature vector and the spatial feature center point of each mineral in the preset network to obtain the probability of each mineral; and Based on the obtained probability of each mineral, a probability distribution vector is generated; The step of identifying the category of the feature to be identified by combining the preset identification rules includes: Classifying the features to be identified into pores, fractures and multiple minerals; When the probability of pore cracks exceeds a first threshold, it is identified as a pore crack; When the probability of a pore fracture is less than the first threshold, it is identified as a non-pore fracture; When the probability of any mineral exceeds a second threshold, identifying the corresponding mineral category; When the probability of all minerals is less than the second threshold, the mineral category set with a probability greater than the third threshold is screened, and the mineral category is identified in combination with the mechanical superordinate category. The first threshold is greater than the second threshold, and the second threshold is greater than the third threshold. The identification of mineral categories by combining mechanical superordinate categories includes: If the minerals in the mineral class set belong to the same mechanical superordinate class, they are identified as that class; If the minerals in the mineral class set belong to multiple mechanically superordinate classes, the highest class is identified. Among them, the preset network is a trained convolutional neural network.

2. The method according to claim 1, characterized in that The fracture simulation technology is used to obtain the characteristic distribution after fracturing, including: Using the fracture phase field equation, a basic model for fracture simulation is constructed to obtain the three-dimensional mineral distribution; The corresponding model is loaded according to the preset requirements, and the basic pore and mineral characteristic distribution at the starting time and the new pore and mineral characteristic distribution formed after the loading is completed are recorded. A slice in one direction is selected for processing, so that the structure of the microfluidic chip can be designed after processing.

3. The method according to claim 2, characterized in that The microfluidic chip comprises two pieces of glass, the pore throat features of mineral distribution are etched on one of the pieces of glass, and the other piece of glass is unetched glass. The two pieces of glass are bonded to obtain a sealed microfluidic chip.

4. A control device, characterized in that: The control device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the method according to any one of claims 1 to 3.

5. A machine-readable storage medium, characterized in that The machine-readable storage medium stores instructions, which enable the machine to execute the method according to any one of claims 1 to 3.

6. A microscopic visualization experimental device, characterized in that: The microscopic visualization experimental device comprises a displacement pump, a crude oil intermediate container, a gas intermediate container, a microscope, a camera system, a pressure sensor, a back pressure unit, a confining pressure tracking pump, and a microfluidic chip prepared by the method according to any one of claims 1 to 3. The injection port of the microfluidic chip is connected to the outlet ends of the crude oil intermediate container and the gas intermediate container respectively through an injection pipeline, and a first control valve and the pressure sensor are provided on the injection pipeline. The inlet end of the crude oil intermediate container is connected to the displacement pump through a crude oil delivery pipeline, and a second control valve is provided on the crude oil delivery pipeline. The inlet end of the gas intermediate container is connected to the displacement pump through a gas delivery pipeline, and a third control valve is provided on the gas delivery pipeline. The microscope is arranged above the microfluidic chip, and the microscope is connected to the camera system. The outlet of the microfluidic chip is connected to the back pressure unit through an extraction pipeline. A fourth control valve is provided on the extraction pipeline, and the confining pressure tracking pump is connected to the injection pipeline.

7. A microscopic visualization experimental method, characterized in that: The microscopic visualization experimental method is performed using the microscopic visualization experimental device according to claim 6, and the microscopic visualization experimental method includes: The microfluidic chip is installed in a high-pressure visual autoclave, confining pressure fluid is added, and heated to the preset formation temperature; The confining pressure is controlled by a confining pressure tracking pump to be higher than the internal pressure of the microfluidic chip; Place the microscope above the microfluidic chip and adjust the focus position and magnification of the microscope; Filling the crude oil intermediate container connected to the displacement pump with crude oil, and filling the gas intermediate container with preset gas; Close the first control valve, evacuate the microfluidic chip, open the first control valve and the second control valve, and inject crude oil into the injection port of the microfluidic chip using a displacement pump; Close the second control valve, keep the first control valve open, open the third and fourth control valves, use the displacement pump to inject a preset gas into the microfluidic chip to expel the crude oil, then close the fourth control valve and inject the preset gas; When the pressure inside the microfluidic chip reaches the preset value, gas injection is stopped to simulate sealing.

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