Experimental determination method for viscosity of shale oil in shale pore network model

Abstract

The invention relates to the technical field of unconventional oil and gas reservoir development, and discloses a shale oil viscosity experimental determination method in a shale pore network model, which comprises the following steps: making a shale pore network model, putting the model into a microscopic model holder, vacuumizing, and heating the holder to a formation temperature; confining pressure liquid is injected into the clamping device until the whole annular cavity is filled with the confining pressure liquid and is kept stable, and the pressure in the annular cavity is higher than the pressure in the model; the pressure of the outlet end of the clamp holder is adjusted to the formation condition, and the pressure difference is controlled to be unchanged in the adjusting process; carrying out wetting modification on the model, and simulating the wetting ability of shale; shale oil at the formation temperature is injected into the model, meanwhile, a model image is collected, and the inlet and outlet pressure, the shale oil liquid column length and the time when the liquid column passes through a flowing channel at different inlet flow speeds are recorded; and determining the viscosity of the nano-pore shale oil of the shale reservoir according to the acquired images and data. According to the method, the viscosity of the shale oil in the heterogeneous nano channel can be accurately determined.

Description

Technical Field

[0001] The invention relates to the technical field of unconventional oil and gas reservoir development, and in particular to a method for experimentally determining shale oil viscosity in a shale pore network model. Background Art

[0002] The transport mechanism of shale oil in nanopores is very complex. Viscosity is an important transport property of shale oil in nanoflow space, but its research and testing methods and changing laws have never been solved through flow experiments.

[0003] At present, the experimental test method for shale oil viscosity is mainly measured by a viscometer, and the viscosity of shale oil in the container is obtained by combining the rotor and the rotation speed. However, this test method has obvious limitations, because there is a micro-nano scale effect in the micro-nano flow space, the fluid is compressed in the confined space, and the initial flow viscosity resistance may increase. At the same time, the change of displacement pressure during the flow process and the complexity of the pore structure will also affect the flow ability of shale oil. Therefore, it will be different from the viscosity obtained in the conventional test method. At the same time, in terms of simulation, although molecular dynamics simulation can predict the viscosity of fluids at different pore sizes and pressures, it is limited by the model conditions of pure substances, and it is difficult to apply molecular dynamics models in pore models above 20nm. Therefore, it is necessary to study the test method for measuring the viscosity of shale oil in micro-nano flow space. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for experimentally determining the viscosity of shale oil in a shale pore network model. The viscosity of shale oil in a heterogeneous nanochannel is calculated by the pressure difference at both ends of the model, the height difference between layers, the flow velocity, tortuosity and fractal dimension, thereby solving the problem that it was previously impossible to test the viscosity of fluids in micro-nano spaces and their changes through flow experiments.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] A method for experimentally determining the viscosity of shale oil in a shale pore network model comprises the following steps:

[0007] A shale pore network model is prepared, the shale pore network model is placed in a microscopic model holder, vacuuming the holder, and the microscopic model holder is heated to formation temperature;

[0008] Injecting confining pressure liquid into the microscopic model holder until the confining pressure liquid fills the entire annular cavity and keeps the confining pressure stable, so that the pressure in the annular cavity is higher than the internal pressure of the nano-etching model;

[0009] The outlet pressure of the micro-model holder is adjusted to the formation conditions, and the pressure difference is kept constant during the adjustment process;

[0010] The wettability of the shale core was simulated by introducing a wettability modifier into the shale pore network model.

[0011] The shale oil is heated to the formation temperature and then injected into the shale pore network model. At the same time, the shale pore network model image is collected and the inlet and outlet pressures, the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel at different inlet flow rates are recorded.

[0012] The viscosity of nanoporous shale oil in the shale reservoir is determined based on the collected shale pore network model images, the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time it takes for the liquid column to pass through the flow channel.

[0013] In an optional manner, making a shale pore network model includes:

[0014] The shale cube model is scanned by nano-CT to obtain a two-dimensional cross-sectional image of the shale cube model;

[0015] Perform threshold segmentation on the two-dimensional cross-sectional image of the shale cube model to obtain a binary image of the shale cross-sectional image;

[0016] Draw the shale pore network pattern based on the shale cross-section binary image;

[0017] According to the shale pore network pattern, the shale pore network model was made by electron beam etching.

[0018] In an optional manner, the shale pore network model includes a flow channel composed of multiple grating structures, a first fan-shaped cavity and a second fan-shaped cavity respectively connected to the two ends of the flow channel, and a diversion channel connected to the other end of the second fan-shaped cavity, and the other end of the diversion channel is the model inlet and outlet.

[0019] In an optional manner, the wettability modification of the shale pore network model by introducing a wettability modifier comprises:

[0020] The temperature of the shale pore network model is controlled at the formation temperature, and xylene solution, petroleum ether, ethanol, distilled water and 20% hydrochloric acid solution are introduced into the shale pore network model in a ratio of 1:2:2:10:5 to 1:8:8:2:1 for two hours, and then 1% hexamethyldisilazane methanol solution is introduced into the shale pore network model for two hours to control the contact angle between the shale pore network model and the oil to be 90° to 30°.

[0021] In an optional manner, heating the shale oil to the formation temperature and then injecting it into the shale pore network model includes:

[0022] Shale oil is dyed red by oil soluble red.

[0023] In an optional manner, the viscosity of nanoporous shale oil in a shale reservoir is determined based on the collected shale pore network model image, and the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time it takes to pass through the flow channel, including the following steps:

[0024] calibrating a selected liquid column from the acquired shale pore network model image, and selecting a first reference point and a second reference point of the liquid column;

[0025] Calculating the height difference between layers of the liquid column according to the first reference point and the second reference point of the liquid column;

[0026] The velocity difference of the liquid column is calculated based on the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel;

[0027] The viscosity of nanoporous shale oil in shale reservoirs is calculated based on the height difference between liquid column layers, the liquid column velocity difference, the tortuosity of the flow channel and the fractal dimension of the shale pore network model.

[0028] In an optional manner, the first reference point is the upper boundary of the liquid film, and the second reference point is the center point of the flow channel.

[0029] In an optional manner, the tortuosity of the flow channel is specifically:

[0030]

[0031] Where τ0 is the tortuosity of the flow channel, l t is the flow channel length, and l is the shale oil column length.

[0032] In an optional manner, the fractal dimension of the shale pore network model is specifically:

[0033]

[0034] Among them, D T is the fractal dimension of the shale pore network model, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

[0035] In an optional manner, the calculation formula for the viscosity of nanoporous shale oil in shale reservoir is:

[0036]

[0037] Among them, μ b is the viscosity of nanoporous shale oil in shale reservoir, t is the time for the liquid column to pass through the flow channel, Δp is, l tis the length of the flow channel, l is the length of the shale oil column, r is the height of the center point of the flow channel, h is the thickness of the upper boundary of the liquid film, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

[0038] The present invention has the following beneficial effects:

[0039] The present invention determines the viscosity of shale oil in heterogeneous nanochannels through the pressure difference at both ends of the model, the height difference between layers, the flow velocity, tortuosity and fractal dimension, which solves the problem that traditional experimental methods cannot test the viscosity of fluids and their changes in micro-nano spaces through flow experiments, thereby achieving the purpose of accurately simulating the transport mechanism of shale oil in nanopore throats. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a process for experimentally determining the viscosity of shale oil in a shale pore network model;

[0041] Figure 2 Schematic diagram of the quartz model of microscopic shale pore network;

[0042] Figure 3 It is a schematic diagram of the structure of the shale reservoir nanopore shale oil viscosity experimental device;

[0043] Figure 4 Schematic diagram of the viscosity-pressure gradient curve of the shale pore network. DETAILED DESCRIPTION

[0044] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0045] like Figure 1 As shown, an embodiment of the present invention provides a method for experimentally determining the viscosity of shale oil in a shale pore network model, comprising the following steps S1 to S6:

[0046] S1. Making a shale pore network model, placing the shale pore network model in a microscopic model holder, evacuating the vacuum, and heating the microscopic model holder to the formation temperature;

[0047] In an optional embodiment of the present invention, the shale reservoir nanopore shale oil viscosity experimental device used in this embodiment is as follows: Figure 3As shown, it includes a data and image acquisition system 1, an air compressor 2, a constant pressure and constant speed micro-flow pump 3, a first valve 4, a high-temperature medium-sized intermediate container 5, a confining pressure tracking pump 6, a second valve 7, a third valve 8, a high-temperature small intermediate container 9, a high-precision pressure sensor 10, a fourth valve 11, a high-range pressure sensor 12, a high-speed camera and a microscope 13, a micro-model holder 14, a light source 15, a medium-range pressure sensor 16, a fifth valve 17, a back pressure control unit 18, a back pressure valve 19, a micro-lift tube 20, and a high-precision balance 21; the air compressor 2 is respectively connected to the constant pressure and constant speed micro-flow pump 3 and the confining pressure tracking pump 6, the constant pressure and constant speed micro-flow pump 3 is connected to one end of the high-temperature medium-sized intermediate container 5 through the first valve 4, the inlet end of the micro-model holder 14 is provided with two longitudinally arranged second valves 7 and third valves 8, the second valves 7 are respectively connected to the other end of the high-temperature medium-sized intermediate container 5, and the second valves 7 are also connected to the high-precision pressure control unit 18, the back pressure valve 19, the micro-lift tube 20, and the high-precision balance 21. The micromodel holder 14 is connected to a force sensor 10, the third valve 8 is connected to a high-temperature small intermediate container 9 filled with a wetting modifier, the confining pressure tracking pump 6 is connected to the micromodel holder 14 through the fourth valve 11, and the fourth valve 11 is also connected to the high-range pressure sensor 12, the outlet end of the micromodel holder 14 is connected to the back pressure valve 19 through the fifth valve 17, and the fifth valve 17 is also connected to the mid-range pressure sensor 16, the back pressure valve 19 is connected to a microliter tube 20 placed on a high-precision balance 21, and the back pressure valve 19 is also connected to the back pressure control unit 18, a high-speed camera and a microscope 13 are fixed above the micromodel holder 14, the microscope magnification body and the focal length are adjusted to make the internal flow channel of the nano-etching model clearly visible, a light source 15 is arranged below the micromodel holder 14, and the data and image acquisition system 1 is respectively connected to the high-range pressure sensor 12, the high-speed camera and the microscope 13, the mid-range pressure sensor 16 and the fifth valve 17.

[0048] In an optional embodiment of the present invention, step S1 of preparing a shale pore network model includes:

[0049] The shale cube model is scanned by nano-CT to obtain a two-dimensional cross-sectional image of the shale cube model;

[0050] Perform threshold segmentation on the two-dimensional cross-sectional image of the shale cube model to obtain a binary image of the shale cross-sectional image;

[0051] Draw the shale pore network pattern based on the shale cross-section binary image;

[0052] According to the shale pore network pattern, the shale pore network model was made by electron beam etching.

[0053] The shale pore network model produced in this embodiment includes a flow channel composed of multiple grating structures, a first fan-shaped cavity and a second fan-shaped cavity connected to the two ends of the flow channel respectively, and a diversion channel connected to the other end of the second fan-shaped cavity, and the other end of the diversion channel is the model inlet and outlet.

[0054] For example, this embodiment uses nano CT to scan a 1 mm 3 The shale cube model obtained nearly 3000 two-dimensional cross-section images and selected the most representative one, such as Figure 2 As shown on the left, after threshold segmentation using Avizo software, a black-and-white binary image is obtained, which is then placed in the CAD drawing software to draw the shale pore network pattern according to the bedding and texture orientation. Based on the drawn pore network pattern, the electron beam etching method is used to make a microscopic shale pore network quartz model ( Figure 2 Right). The size of the microscopic shale pore network quartz model is 75mmx75mmx3.5mm, the internal flow channel length is 1mm, the tube diameter varies from 500nm to 2μm, the internal flow channel is connected to the fan-shaped cavity with a width of 3mm and a height of 1mm, the fan-shaped cavity is connected to the diversion channel with a length of 47mm and a diameter of 1mm, and the model inlet and outlet are connected to the diversion channel. The prepared model is placed in a special microscopic model holder 14 of high temperature and high pressure to evacuate, and the box is heated to the formation temperature (80℃) and kept at a constant temperature for 2h.

[0055] S2, injecting confining pressure liquid into the microscopic model holder until the confining pressure liquid fills the entire annular cavity and keeps the confining pressure stable, so that the pressure in the annular cavity is higher than the internal pressure of the nano-etching model;

[0056] In an optional embodiment of the present invention, step S2 uses the confining pressure tracking pump 6 to inject colorless and transparent pure water from the bottom of the micro model holder 14 at a constant speed of 15 ml / min until the pure water fills the entire cavity, and switches the constant speed mode to the constant pressure mode, keeping the confining pressure stable at 2 MPa, so that the pressure in the annular cavity is higher than the internal pressure of the nano-etching model.

[0057] S3, adjusting the outlet pressure of the micro-model holder to the formation condition, and controlling the pressure difference to remain unchanged during the adjustment process;

[0058] In an optional embodiment of the present invention, step S3 loads shale oil with a viscosity of 3.86 mPa·s into a high-temperature medium-sized intermediate container 5, and heats the high-temperature medium-sized intermediate container 5 to a formation temperature of 80°C. The outlet of the micro-model holder 14 adjusts the pressure to 30 MPa under the formation condition through the back pressure control unit 18, and the confining pressure tracking 6 is set to the tracking mode, maintaining a 2 MPa pressure difference and slowly increasing the back pressure until the pressure stabilizes.

[0059] S4, using a wettability modifier to pass into the shale pore network model for wettability modification to simulate the wettability of a real shale core;

[0060] In an optional embodiment of the present invention, step S4 of introducing a wettability modifier into the shale pore network model for wettability modification includes:

[0061] The temperature of the shale pore network model is controlled at the formation temperature, and xylene solution, petroleum ether, ethanol, distilled water and 20% hydrochloric acid solution are introduced into the shale pore network model in a ratio of 1:2:2:10:5 to 1:8:8:2:1 for two hours, and then 1% hexamethyldisilazane methanol solution is introduced into the shale pore network model for two hours, and the contact angle between the shale pore network model and the oil is controlled to be 90° to 30°, and the wettability of the real shale core is simulated in this way. In this embodiment, the wettability modifier is introduced into the interior of the model to achieve wettability modification, which solves the problem that the wettability modification purpose can only be achieved by soaking in different wettability modifiers for multiple times.

[0062] In this embodiment, shale oil can be dyed red by using oil-soluble red, so that the flow of shale oil can be observed through an image acquisition system.

[0063] S5, heating the shale oil to the formation temperature and injecting it into the shale pore network model, while collecting images of the shale pore network model and recording the inlet and outlet pressures, the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel at different inlet flow rates;

[0064] In an optional embodiment of the present invention, step S5 drives the piston in the high-temperature small intermediate container 9 through the constant pressure and constant speed micro-flow pump 3 to inject light shale oil with a viscosity of 3.86 mPa·s into the nano-etching model. In this process, the image brightness and clarity are increased by adjusting the exposure time, regional white balance, sharpness and noise reduction of the high-speed camera and microscope 13 and the data and image acquisition system 1, and the inlet and outlet pressures, shale oil liquid column length and the time it takes for the liquid column to pass through the flow channel at different inlet flow rates are recorded.

[0065] S6. Determine the nanoporous shale oil viscosity of the shale reservoir based on the collected shale pore network model image, the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time it takes for the liquid column to pass through the flow channel.

[0066] In an optional embodiment of the present invention, step S6 determines the viscosity of nanoporous shale oil in the shale reservoir according to the collected shale pore network model image, and the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time of passing through the flow channel, including the following steps:

[0067] calibrating a selected liquid column from the acquired shale pore network model image, and selecting a first reference point and a second reference point of the liquid column;

[0068] Calculating the height difference between layers of the liquid column according to the first reference point and the second reference point of the liquid column;

[0069] The velocity difference of the liquid column is calculated based on the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel;

[0070] The viscosity of nanoporous shale oil in shale reservoirs is calculated based on the height difference between liquid column layers, the liquid column velocity difference, the tortuosity of the flow channel and the fractal dimension of the shale pore network model.

[0071] Exemplarily, in this embodiment, two reference points of the liquid column are selected through the image acquisition system, which are recorded as the first reference point and the second reference point. The first reference point is the upper boundary of the adsorption layer thickness, with a thickness of h, and the second reference point is the center area of ​​the tube, with a height of r. The height difference between the liquid column layers is obtained by selecting two representative reference points inside the flow channel. The height difference between the two points is (rh); the flow velocity v is obtained by calibrating the length l of the flow channel in the acquisition system screen and the time t of the liquid column flowing through the flow channel. Since the fluid flow velocity in the adsorption layer area is 0, the flow velocity difference between the two reference points is v.

[0072] This embodiment adopts a non-homogeneous network model, and thus introduces tortuosity and fractal dimension.

[0073] The tortuosity of the flow channel is specifically:

[0074]

[0075] Where τ0 is the tortuosity of the flow channel, l t is the flow channel length, and l is the shale oil column length.

[0076] The fractal dimension of the shale pore network model is:

[0077]

[0078] Among them, D T is the fractal dimension of the shale pore network model, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

[0079] The calculation formula for the viscosity of nanoporous shale oil in shale reservoirs is:

[0080]

[0081] Wherein, μb is the viscosity of nanopore shale oil in shale reservoir, t is the time for the liquid column to pass through the flow channel, Δp is, l tis the length of the flow channel, l is the length of the shale oil column, r is the height of the center point of the flow channel, h is the thickness of the upper boundary of the liquid film, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

[0082] The method of the present invention was used to carry out the shale oil adsorption boundary layer thickness experiment under high temperature and high pressure (30MPa, 80℃) conditions. The results are shown in Table 1. Figure 4 All data in Table 1 are obtained by high-precision pressure sensors, image acquisition systems and the above expressions. It can be seen that with the increase of effective pore size, the viscosity of shale oil gradually decreases and tends to stabilize to the value measured by the rotational viscometer under normal pressure.

[0083] Table 1. Experimental test data table

[0084]

[0085]

[0086] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0087] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0088] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0089] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0090] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for experimentally determining the viscosity of shale oil in a shale pore network model, characterized in that: The following steps are involved: A shale pore network model is prepared, the shale pore network model is placed in a microscopic model holder, vacuuming the holder, and the microscopic model holder is heated to formation temperature; Injecting confining pressure liquid into the microscopic model holder until the confining pressure liquid fills the entire annular cavity and keeps the confining pressure stable, so that the pressure in the annular cavity is higher than the internal pressure of the nano-etching model; The outlet pressure of the micro-model holder is adjusted to the formation conditions, and the pressure difference is kept constant during the adjustment process; The wettability of the shale core was simulated by introducing a wettability modifier into the shale pore network model. The shale oil is heated to the formation temperature and then injected into the shale pore network model. At the same time, the shale pore network model image is collected and the inlet and outlet pressures, the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel at different inlet flow rates are recorded. The viscosity of nanoporous shale oil in the shale reservoir is determined based on the collected shale pore network model images, the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time it takes for the liquid column to pass through the flow channel.

2. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 1, characterized in that: Shale pore network modeling includes: The shale cube model is scanned by nano-CT to obtain a two-dimensional cross-sectional image of the shale cube model; Perform threshold segmentation on the two-dimensional cross-sectional image of the shale cube model to obtain a binary image of the shale cross-sectional image; Draw the shale pore network pattern based on the shale cross-section binary image; According to the shale pore network pattern, the shale pore network model was made by electron beam etching.

3. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 1, characterized in that: The shale pore network model includes a flow channel composed of multiple grating structures, a first fan-shaped cavity and a second fan-shaped cavity connected to the two ends of the flow channel respectively, and a diversion channel connected to the other end of the second fan-shaped cavity, and the other end of the diversion channel is the model inlet and outlet.

4. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 1, characterized in that: The wettability modification by introducing a wettability modifier into the shale pore network model includes: The temperature of the shale pore network model is controlled at the formation temperature, and xylene solution, petroleum ether, ethanol, distilled water and 20% hydrochloric acid solution are introduced into the shale pore network model in a ratio of 1:2:2:10:5 to 1:8:8:2:1 for two hours, and then 1% hexamethyldisilazane methanol solution is introduced into the shale pore network model for two hours to control the contact angle between the shale pore network model and the oil to be 90° to 30°.

5. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 1, characterized in that: The shale oil is heated to the formation temperature and then injected into the shale pore network model including: Shale oil is dyed red by oil soluble red.

6. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 1, characterized in that: The viscosity of nanoporous shale oil in a shale reservoir is determined based on the collected shale pore network model image, and the recorded inlet and outlet pressures at different inlet flow rates, the length of the shale oil liquid column, and the time it takes to pass through the flow channel, including the following steps: calibrating a selected liquid column from the acquired shale pore network model image, and selecting a first reference point and a second reference point of the liquid column; Calculating the height difference between layers of the liquid column according to the first reference point and the second reference point of the liquid column; The velocity difference of the liquid column is calculated based on the length of the shale oil liquid column and the time it takes for the liquid column to pass through the flow channel; The viscosity of nanoporous shale oil in shale reservoirs is calculated based on the height difference between liquid column layers, the liquid column velocity difference, the tortuosity of the flow channel and the fractal dimension of the shale pore network model.

7. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 6, characterized in that: The first reference point is the upper boundary of the liquid film, and the second reference point is the center point of the flow channel.

8. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 6, characterized in that: The tortuosity of the flow channel is specifically: Where τ0 is the tortuosity of the flow channel, l t is the flow channel length, and l is the shale oil column length.

9. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 6, characterized in that: The fractal dimension of the shale pore network model is: Among them, D T is the fractal dimension of the shale pore network model, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

10. The method for experimentally determining the viscosity of shale oil in a shale pore network model according to claim 6, characterized in that: The calculation formula for the viscosity of nanoporous shale oil in shale reservoirs is: Among them, μ b is the viscosity of nanoporous shale oil in shale reservoir, t is the time for the liquid column to pass through the flow channel, Δp is, l t is the length of the flow channel, l is the length of the shale oil column, r is the height of the center point of the flow channel, h is the thickness of the upper boundary of the liquid film, λ max is the maximum pore radius, λ is the average pore radius of shale, and λ min is the minimum pore radius, is the porosity of shale.

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