Method, device and apparatus for determining solid surface fluid transport properties

Abstract

The application discloses a method, device and equipment for determining fluid transport characteristics of a solid surface. The method comprises: obtaining first scanning image data of a target rock surface; determining a position distribution of the target rock surface based on the first scanning image data; obtaining second scanning image data of the target rock surface with mixed wettability and a variation range of a fluid wetting angle; determining a distribution of different wettability blocks of the target rock surface based on the second scanning image data; determining a solid-liquid interaction force range of each wettability block based on the variation range of the fluid wetting angle of each wettability block; and determining fluid transport characteristics of the target rock surface based on the position distribution, the distribution of different wettability blocks and the solid-liquid interaction force range of each wettability block. Through the method, the simulation of fluid transport of the target rock surface can be closer to the actual micro fluid transport, so that the accuracy and reliability of the fluid transport simulation are improved.

Description

Technical Field

[0001] This application relates to the field of shale gas exploration and development technology, and in particular to a method, apparatus and equipment for determining the fluid transport characteristics of a solid surface. Background Technology

[0002] Rock roughness and wettability are important parameters affecting the dynamic migration of crude oil within porous media in oil reservoirs. Traditional microscopic experiments, which study fluid migration on the surface of low-permeability porous media at the micro- and nano-scale, are challenging to design and operate, making it difficult to fully capture the flow details of fluids on complex solid surfaces. Numerical simulation, however, allows for flexible parameter settings and adjustments, enabling a comprehensive understanding of solid-liquid wetting mechanisms.

[0003] The Lattice Boltzmann method (LBM) is a mesoscopic flow simulation method that describes the motion of fluid particles using discrete Boltzmann equations. It overcomes the limitations of the continuity assumption, simplifies the handling of fluid flows under complex boundaries and structures, and has unique advantages in simulating fluid flow at solid-liquid interfaces. Commonly used LBM models include the color gradient model, pseudo-potential model, free energy model, and phase field model. Compared to the other three models, the pseudo-potential model can construct complex structures on solid surfaces. By adjusting the wetting angle, it controls the interaction potential between fluid particles, thereby affecting the interaction forces between particles at the solid-liquid interface, making it suitable for investigating solid-liquid contact line transport.

[0004] However, current simulations of complex rock surfaces within the LBM framework handle roughness and wettability in a rather simplistic way, failing to accurately simulate the roughness and wettability of actual rock surfaces. Furthermore, the simulation process only uses the steady-state wetting angle as a parameter to limit the range of the solid-liquid contact line. During transport, the real-time wetting angle may exceed the actual range due to changes in droplet morphology, leading to deviations in the construction of the entire transport process and making it impossible to accurately reproduce the actual microscopic experiment.

[0005] There is currently no effective solution to the problem of not being able to accurately and reliably simulate fluid transport on rock surfaces. Summary of the Invention

[0006] The purpose of the embodiments in this specification is to provide a method, apparatus, and device for determining the fluid transport characteristics of a solid surface, so as to solve the problem that it is impossible to accurately and reliably simulate the fluid transport on a rock surface.

[0007] To address the aforementioned technical problems, the first aspect of this specification provides a method for determining the fluid transport characteristics of a solid surface, comprising:

[0008] Acquire first scan image data of the target rock surface, wherein the first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface;

[0009] Based on the first scanned image data, the location distribution of the scanned points on the target rock surface is determined;

[0010] The second scan image data of the target rock surface with mixed wetting and the variation range of the fluid wetting angle of each wetting block of the target rock surface with mixed wetting are obtained. The second scan image data is image data of the wettability of multiple wetting blocks of the target rock surface obtained by scanning the wetting blocks of the target rock surface.

[0011] Based on the second scanned image data, the distribution of different wetting blocks on the surface of the target rock is determined;

[0012] Based on the variation range of the fluid wetting angle in each wetting block, the range of solid-liquid interaction force in each wetting block is determined.

[0013] Based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, the fluid transport characteristics of the target rock surface are determined.

[0014] In some embodiments of this specification, determining the positional distribution of scan points on the target rock surface based on the first scanned image data includes:

[0015] Determine the height of the position corresponding to each scanning point on the target rock surface in the first scanned image data;

[0016] Based on the determined height and scanning side length, the dimensionless height matrix corresponding to the scanning points on the target rock surface is determined;

[0017] Based on the dimensionless height matrix, the height distribution of the scanning points on the target rock surface is determined, and the height distribution is used as the position distribution.

[0018] In some embodiments of this specification, determining the height distribution of scanning points on the target rock surface based on the dimensionless height matrix includes:

[0019] Within the framework of lattice Boltzmann simulation: Based on the dimensionless height matrix and the simulated lattice number corresponding to the target rock surface, the height lattice matrix of the scanning points on the target rock surface is determined, wherein each element in the height lattice matrix is ​​used to characterize the lattice number corresponding to the stiffnessless height of the corresponding scanning point; based on each element in the height lattice matrix, a distribution histogram of the lattice number is determined, and the determined distribution histogram is used as the height distribution.

[0020] In some embodiments of this specification, the range of variation of the fluid wetting angle of each wetting block on the target rock surface in the mixed wetting process is determined by the following method:

[0021] The wetting angle of the target rock surface was measured using a rolling wetting angle measuring instrument;

[0022] Based on the wetting angle corresponding to the critical moment when the solid-liquid contact line on the wetted target rock surface changes, the advance angle and retreat angle of each wetting block are determined.

[0023] Based on the determined advance and retreat angles of each wetting block, the range of variation of the fluid wetting angle of each wetting block on the target rock surface is determined.

[0024] In some embodiments of this specification, determining the distribution of different wettability zones on the surface of the target rock based on the second scanned image data includes:

[0025] The second scanned image data is processed, and based on the image processing results, the solid surface image features in the second scanned image data are determined.

[0026] Based on the determined wetted area distinction rules corresponding to the solid surface image features, the wetted area categories and the locations of the wetted areas in the second scanned image data are determined.

[0027] Based on the determined wetted block categories, the locations of wetted blocks in each category, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

[0028] In some embodiments of this specification, before determining the distribution of different wettability blocks on the target rock surface based on the determined wettability block categories, the locations of wettability blocks in each category, and the correspondence between each location in the second scanned image data and the wettability blocks on the target rock surface, the following steps are included:

[0029] For two adjacent wetting blocks of different categories, the gradient range of the linear wetting angle gradient between the first wetting block and the second wetting block is determined based on the first wetting angle of the first wetting block and the second wetting angle of the second wetting block.

[0030] Based on the determined gradient range, the wettability at each location between the first wetting block and the second wetting block is determined as the region boundary wettability;

[0031] Accordingly, based on the determined wettability block categories, the locations of wettability blocks in each category, and the correspondence between each location in the second scanned image data and the wettability blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined, including:

[0032] Based on the determined wetted block categories, the locations of wetted blocks in each category, the wettability of the region boundary, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

[0033] In some embodiments of this specification, the solid-liquid interaction force range of each wetting block is determined based on the variation range of the fluid wetting angle of each wetting block, including:

[0034] Based on the mapping relationship between wetting angle and fluid density, the mapping relationship between fluid density and solid-liquid interaction potential, the mapping relationship between solid-liquid interaction force and solid-liquid interaction potential and velocity, and the variation range of fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined.

[0035] In some embodiments of this specification, the fluid transport characteristics of the target rock surface are determined based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, including:

[0036] Within the framework of lattice Boltzmann simulation: based on the location distribution and the distribution of different wettability blocks on the target rock surface, the solid-liquid interaction force interval of each lattice scanning point in the solid surface model corresponding to the target rock surface is constructed, and the interparticle interaction force between the solid-liquid interfaces of each lattice in the solid surface model is dynamically constrained to obtain transport simulation data.

[0037] The fluid transport simulation characteristics of the solid surface model are determined by analyzing the transport simulation data.

[0038] Based on the determined fluid transport simulation characteristics, the fluid transport characteristics of the target rock surface are determined.

[0039] The second aspect of this specification provides an apparatus for determining the fluid transport characteristics of a solid surface, comprising:

[0040] The first acquisition module is used to acquire first scan image data of the target rock surface. The first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface.

[0041] The location determination module is used to determine the location distribution of the scanning points on the target rock surface based on the first scanned image data;

[0042] The second acquisition module is used to acquire the second scan image data of the mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block of the mixed-wetting target rock surface. The second scan image data is image data of the wettability of multiple wetting blocks of the mixed-wetting target rock surface obtained by scanning the wetting blocks of the mixed-wetting target rock surface.

[0043] A wetting determination module is used to determine the distribution of different wettability blocks on the surface of the target rock based on the second scanned image data;

[0044] The interval determination module is used to determine the solid-liquid interaction force interval of each wetting block based on the variation interval of the fluid wetting angle of each wetting block.

[0045] The transport determination module is used to determine the fluid transport characteristics of the target rock surface based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block.

[0046] A third aspect of this specification provides an electronic device, comprising: a memory and a processor, the processor and the memory being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to implement the steps of the method described in the first aspect.

[0047] A fourth aspect of this specification provides a computer-readable storage medium storing computer program instructions that, when executed, implement the steps of the method described in the first aspect.

[0048] The method for determining the fluid transport characteristics of a solid surface provided in this specification involves: acquiring first scanned image data of a target rock surface, which is image data obtained by scanning the morphology of the target rock surface and including the positions of multiple scan points on the target rock surface; determining the positional distribution of the scan points on the target rock surface based on the first scanned image data; acquiring second scanned image data of a mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block on the mixed-wetting target rock surface, which is image data obtained by scanning the wetting blocks on the mixed-wetting target rock surface and including the wettability of multiple wetting blocks on the mixed-wetting target rock surface; determining the distribution of different wettability blocks on the target rock surface based on the second scanned image data; determining the solid-liquid interaction force range of each wetting block based on the variation range of the fluid wetting angle of each wetting block; and determining the fluid transport characteristics of the target rock surface based on the positional distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wetting block. By determining the location distribution of scanning points on the target rock surface, the surface roughness can be restored. By determining the wettability distribution of each wetted block on the target rock surface, the wettability of the target rock surface can be restored. By determining the solid-liquid interaction force range through the variation range of the fluid wetting angle, the droplet morphology changes during the droplet migration process on the target rock surface can be restricted. Furthermore, based on the rough and wetted target rock surface combined with the solid-liquid interaction force range, the simulation of fluid migration on the target rock surface can be made to more closely resemble the actual microscopic fluid migration situation, thereby improving the accuracy and reliability of fluid migration simulation. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0050] Figure 1 The diagram shown is a schematic representation of a method for determining the fluid transport characteristics of a solid surface provided in an embodiment of this specification.

[0051] Figure 2 The diagram shown is a schematic representation of the construction process of the solid surface model provided in the embodiments of this specification.

[0052] Figure 3 The image shown is a schematic diagram of an atomic force microscope height scan image provided in an embodiment of this specification;

[0053] Figure 4 The diagram shown is a schematic representation of the simulation results of a mixed-wetting solid surface provided in the embodiments of this specification.

[0054] Figure 5 The image shown is a schematic diagram of an atomic force microscope height scan image provided in an embodiment of this specification;

[0055] Figure 6 The image shown is a schematic diagram of the simulation results of a rough solid surface provided in the embodiments of this specification;

[0056] Figure 7 The diagram shown is a schematic representation of the oil droplet transport simulation process of the solid surface model provided in the embodiments of this specification.

[0057] Figure 8 The diagram shown is a schematic representation of the oil droplet transport simulation process of the solid surface model provided in the embodiments of this specification.

[0058] Figure 9 The diagram shown is a schematic of a device for determining the fluid transport characteristics of a solid surface provided in an embodiment of this specification.

[0059] Figure 10 The diagram shown is a schematic of an electronic device provided in an embodiment of this specification. Detailed Implementation

[0060] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0061] As mentioned above, current numerical simulations of complex rock surfaces handle roughness and wettability in a rather simplistic way, failing to accurately simulate the roughness and wettability of actual rock surfaces. Furthermore, the simulation does not restrict changes in droplet morphology, resulting in deviations in the construction of the entire transport process and an inability to accurately reproduce actual microscopic experiments.

[0062] To address the aforementioned problems, embodiments of this specification provide a method for determining the fluid transport characteristics of a solid surface. This method involves acquiring first scanned image data of a target rock surface, which is image data obtained by scanning the morphology of the target rock surface and including the positions of multiple scan points on the target rock surface; determining the positional distribution of the scan points on the target rock surface based on the first scanned image data; acquiring second scanned image data of a mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block on the mixed-wetting target rock surface, which is image data obtained by scanning the wetting blocks on the mixed-wetting target rock surface and including the wettability of multiple wetting blocks on the mixed-wetting target rock surface; determining the distribution of different wettability blocks on the target rock surface based on the second scanned image data; determining the solid-liquid interaction force range of each wetting block based on the variation range of the fluid wetting angle of each wetting block; and determining the fluid transport characteristics of the target rock surface based on the positional distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wetting block.

[0063] The method for determining the fluid transport characteristics of a solid surface provided in this specification can restore the surface roughness of a target rock by determining the positional distribution of scanning points on the target rock surface, restore the surface wettability by determining the wettability distribution of each wetted block on the target rock surface, and limit the droplet morphology changes during droplet transport on the target rock surface by determining the solid-liquid interaction force range through the variation range of the fluid wetting angle. Furthermore, based on the rough and wetted target rock surface combined with the solid-liquid interaction force range, the simulation of fluid transport on the target rock surface can be made closer to the actual microscopic fluid transport situation, thereby improving the accuracy and reliability of the fluid transport simulation.

[0064] The method provided in this application can be executed by an electronic device, which is an electronic device with data computing, processing, and storage capabilities. This electronic device can be a terminal such as a personal computer (PC), tablet computer, smartphone, wearable device, or intelligent robot; or it can be a server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0065] The method for determining the fluid transport characteristics of a solid surface, as provided in the embodiments of this specification, will be described below with reference to the accompanying drawings. It is understood that the embodiments in this specification use the simulation of fluid transport on a solid surface under the LBM framework as an example to illustrate the above-mentioned method for determining the fluid transport characteristics of a solid surface. Other embodiments may also employ other frameworks, and this specification does not limit this approach.

[0066] Figure 1 The diagram illustrates a method for determining the fluid transport characteristics of a solid surface according to an embodiment of this specification. While this specification provides method operation steps or apparatus structures as shown in the following embodiments or figures, more or fewer operation steps or module units may be included in the method or apparatus based on conventional or non-inventive effort. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure shown in the embodiments or figures of this specification. When the method or module structure is applied in actual devices, servers, or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or figures (e.g., in a parallel processor or multi-threaded processing environment, or even in a distributed processing or server cluster implementation environment). Figure 1 As shown, the method may include:

[0067] S101: Acquire first scan image data of the target rock surface, wherein the first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface.

[0068] It can be understood that the first scan image data is obtained by scanning the surface of the target rock using atomic force microscopy (AFM). The scan points on the target rock surface can be understood as the locations of the target rock surface scanned by AFM. The number of scan points is related to the resolution and scanning speed of the AFM.

[0069] S102: Based on the first scanned image data, determine the positional distribution of the scanned points on the target rock surface.

[0070] It can be understood that the positional distribution of the scanning points can be the positional distribution of the scanning points on the target rock surface in three-dimensional space, that is, the determined positional distribution is in terms of three-dimensional space; the positional distribution of the scanning points can also be the height distribution of the scanning points on the target rock surface, that is, the height of a certain position on the target rock surface can be used as the baseline height, and then the height of the scanning points on the target rock surface can be determined based on the baseline height, and the positional distribution of the scanning points on the target rock surface can be obtained based on the determined height of the scanning points.

[0071] It is understandable that the location distribution can be used to characterize the roughness of the target rock surface. The roughness of the rock surface is positively correlated with the effective solid-liquid contact area. Determining the roughness of the target rock surface based on the scanning results of atomic force microscopy can provide a real and reliable basis for subsequent numerical simulation of fluid transport on the target rock surface.

[0072] In some embodiments of this specification, determining the positional distribution of scan points on the target rock surface based on the first scanned image data may include:

[0073] Determine the height of the position corresponding to each scanning point on the target rock surface in the first scanned image data;

[0074] Based on the determined height and scanning side length, the dimensionless height matrix corresponding to the scanning points on the target rock surface is determined;

[0075] Based on the dimensionless height matrix, the height distribution of the scanning points on the target rock surface is determined, and the height distribution is used as the position distribution.

[0076] It is understood that in this embodiment, atomic force microscopy is used to quantify the height variation of each scanning point on the target rock surface, and the roughness of the target rock surface is determined by the height distribution of the scanning points on the target rock surface. This can realize the restoration of the rough solid surface in the numerical modeling process and provide a basis for the construction of the rough solid surface model.

[0077] In some embodiments of this specification, after obtaining the height of the position corresponding to each scanning point on the target rock surface in the first scan image data, a corresponding height distribution histogram can be obtained based on the obtained height data to characterize the proportion of each height value in the height of the scanning point on the target rock surface, so as to obtain the height fluctuation pattern of the target rock surface.

[0078] In some embodiments of this specification, the first scanned image data can be sampled at a preset sampling frequency to reduce the position data corresponding to the scan points. For example, the height of the position corresponding to each scan point in the first scanned image data can be reduced at intervals. This can avoid the problem of excessive computation of the simulated surface of the target rock due to too many scan points, and at the same time ensure that the overall undulation pattern of the constructed rough solid surface is consistent with the surface of the target rock.

[0079] In some embodiments of this specification, determining the height distribution of scan points on the target rock surface based on the dimensionless height matrix may include:

[0080] Within the framework of lattice Boltzmann simulation: Based on the dimensionless height matrix and the simulated lattice number corresponding to the target rock surface, the height lattice matrix of the scanning points on the target rock surface is determined, wherein each element in the height lattice matrix is ​​used to characterize the lattice number corresponding to the stiffnessless height of the corresponding scanning point; based on each element in the height lattice matrix, a distribution histogram of the lattice number is determined, and the determined distribution histogram is used as the height distribution.

[0081] It can be understood that in the LBM framework, the solid surface model corresponding to the target rock surface can be a continuous surface composed of simulated lattices. The pseudo-potential model of the target rock surface in the LBM framework can be constructed through the distribution histogram of the number of lattices determined above, which provides a basis for the subsequent simulation of fluid transport on the model surface.

[0082] It is understood that in the above embodiments, the roughness of the target rock surface slice is determined by simulating the height distribution of the target rock surface. In other embodiments, the roughness of the target rock surface in three dimensions can be constructed by performing a three-dimensional scan on the surface of the three-dimensional target rock and determining the position distribution of the target rock surface in three-dimensional space, thereby realizing the simulation of the surface fluid transport of the complete target rock.

[0083] S103: Acquire second scan image data of the mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block of the mixed-wetting target rock surface.

[0084] The second scanned image data is image data of the wettability of multiple wetted blocks on the surface of the target rock, obtained by scanning the wetted blocks of the target rock surface with mixed wettability.

[0085] It is understandable that hydrophilic and oleophilic wetting modification experiments can be conducted on the target rock surface to obtain target rock surfaces with different wettability. Then, atomic force microscopy can be used to scan the wetted areas of the wetted target rock surface, obtaining image data including the wettability of each wetted area. That is, based on the second scan image data, the location data of the wetted areas on the wetted target rock surface can be obtained. Further, the wettability of different wetted areas can be divided, such as the division into hydrophilic and oleophilic regions, to obtain the wettability distribution of the target rock surface.

[0086] It is understandable that by varying the wetting angle of each wetting block, the dynamic wetting angle range of each wetting block can be obtained. This constrains the deformation of the liquid during fluid transport on the target rock surface, avoiding a significant difference between the simulated oil droplet deformation range and the actual value due to the fluid exceeding the wetting angle variation range during fluid transport. This would affect the realistic and reliable simulation of fluid transport on the target rock surface. Through the above method, the steady-state morphology of the fluid transport simulation on the target rock surface can be restored, effectively restoring the microscopic fluid transport situation on the target rock surface.

[0087] In some embodiments of this specification, the range of variation of the fluid wetting angle of each wetting block on the target rock surface can be determined in the following manner:

[0088] The wetting angle of the target rock surface was measured using a rolling wetting angle measuring instrument;

[0089] Based on the wetting angle corresponding to the critical moment when the solid-liquid contact line on the wetted target rock surface changes, the advance angle and retreat angle of each wetting block are determined.

[0090] Based on the determined advance and retreat angles of each wetting block, the range of variation of the fluid wetting angle of each wetting block on the target rock surface is determined.

[0091] Specifically, the advancing angle and retreating angle can be measured using a rolling wetting angle measuring instrument. During the measurement process, the increase or decrease of the droplet volume on the target rock surface is involved. The contact angle at the critical moment when the droplet volume changes at the solid-liquid contact line on the target rock surface can be used as the advancing angle and retreating angle. For example, the contact angle at the critical moment when the droplet volume increases is the advancing angle, and the contact angle at the critical moment when the droplet volume decreases is the retreating angle.

[0092] In some embodiments of this specification, when using a rolling wetting angle measuring instrument to measure the advance and retreat angles, if the droplet viscosity on the target rock surface is too high to provide accurate advance and retreat angles, the parameter ranges for the advance and retreat angles can be set during the construction of a pseudo-potential model of the target rock surface. The parameter ranges can be adjusted according to the actual migration process of the droplets on the mixed wetting surface, so that the migration process and steady-state morphology of the oil droplets on the solid surface in the model can be restored to the microscopic experiment, and the dynamic wetting angle parameters can be determined.

[0093] S104: Based on the second scanned image data, determine the distribution of different wettability blocks on the surface of the target rock.

[0094] It is understandable that, based on the image data corresponding to each wetting block in the second scan image data, the wettability corresponding to each wetting block can be further distinguished. The wettability can be hydrophilic, oleophilic, etc. Combining the determined wettability of each wetting block and the location of each wetting block, the distribution of different wettability blocks on the target rock surface can be obtained. It is understandable that, within the LBM framework, the aforementioned wetting blocks can be understood as the lattice obtained after modeling the rough target rock surface, and the determined distribution of different wettability blocks can be the wettability distribution of the lattice of the modeled solid surface.

[0095] In some embodiments of this specification, determining the distribution of different wettability zones on the target rock surface based on the second scanned image data may include:

[0096] The second scanned image data is processed, and based on the image processing results, solid-liquid image features in the second scanned image data are determined.

[0097] Based on the determined solid-liquid image features corresponding to the wetting block differentiation rules, the wetting block category and the location of each category of wetting block in the second scanned image data are determined.

[0098] Based on the determined wetted block categories, the locations of wetted blocks in each category, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

[0099] It is understandable that the target rock surface may exhibit mixed wetting. Different wetting block distinction rules are needed to differentiate between different types of wetting blocks based on their varying distributions. The corresponding solid surface image features in the second scan image data differ depending on the distribution of these wetting blocks. Therefore, the appropriate wetting block distinction rules can be determined by extracting these features, thus classifying each wetting block in the second scan image data. These different distributions could include, for example, hydrophilic regions with oleophilic oil stains; oleophilic regions with hydrophilic water stains; or a uniform texture in the second scan image data where hydrophilic regions exhibit differences in physical characteristics such as hardness and viscoelastic modulus.

[0100] In some embodiments of this specification, the rules for distinguishing wetted areas may include the following three:

[0101] Firstly, when oleophilic (hydrophilic) oil spots are attached to a continuous hydrophilic (oleophilic) surface, the proportion of oleophilic (hydrophilic) blocks on the continuous hydrophilic (oleophilic) surface can be calculated using the second scan image data. Specifically, the baseline height can be selected based on the second scan image data, that is, the continuous hydrophilic (oleophilic) surface is used as the baseline, and then the particle size analysis function in the offline analysis function of atomic force microscopy is used to quantify the specific location of the blocks with heights higher than the baseline in the scan image, which are the attached oleophilic (hydrophilic) spots.

[0102] Secondly, when the surface texture of the mixed wetted area is uniform and the height difference between the hydrophilic and oleophilic areas cannot be distinguished, but there are differences in hardness and viscoelastic modulus, the phase map of the wetted target rock surface can be obtained by using the tapping mode of the atomic force microscope. Then, the positions of the hydrophilic and oleophilic areas in the second scan image data can be calculated based on the phase map.

[0103] Third, when neither of the above two methods can distinguish between hydrophilic and oleophilic regions, the hydrophilicity of different regions can be determined by Young's modulus diagram. Specifically, the interaction forces between the hydrophilic and oleophilic surfaces and the probe are different. By performing a force curve surface scan on the wetted target rock surface, a Young's modulus diagram can be fitted, and then the positions of the hydrophilic and oleophilic regions in the second scan image data can be distinguished based on the Young's modulus diagram.

[0104] In some embodiments of this specification, before determining the distribution of different wettability blocks on the target rock surface based on the determined wettability block categories, the locations of wettability blocks in each category, and the correspondence between the locations in the second scanned image data and the wettability blocks on the target rock surface, the following may be included:

[0105] For two adjacent wetting blocks of different categories, the gradient range of the linear wetting angle gradient between the first wetting block and the second wetting block is determined based on the first wetting angle of the first wetting block and the second wetting angle of the second wetting block.

[0106] Based on the determined gradient range, the wettability at each location between the first wetting block and the second wetting block is determined as the region boundary wettability;

[0107] Accordingly, based on the determined wettability block categories, the locations of wettability blocks in each category, and the correspondence between each location in the second scanned image data and the wettability blocks on the target rock surface, determining the distribution of different wettability blocks on the target rock surface may include:

[0108] Based on the determined wetted block categories, the locations of wetted blocks in each category, the wettability of the region boundary, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

[0109] It is understandable that the boundary width of the wetted blocks in the second scanned image data can be determined by scanning the wetted target rock surface using a confocal microscope. That is, for the wetted target rock surface, the percentage of the actual boundary width between wetted blocks relative to the total area is calculated using a confocal microscope scan. Furthermore, when modeling the wetted surface within the LBM framework, wetted boundaries can be set between each wetted block in the pseudo-potential model corresponding to the target rock surface based on boundary parameters. A linear wetted angle gradient can be set at the boundary, with the gradient range being the wetted angle from the first wetted block to the second wetted block. Through these settings, the progressive changes in wettability of different types of wetted blocks in fluid transport simulation can be realized, constructing a pseudo-potential model that better reflects the wettability of the target rock surface, thus improving the accuracy and reliability of fluid transport simulation.

[0110] S105: Based on the variation range of the fluid wetting angle of each wetting block, determine the solid-liquid interaction force range of each wetting block.

[0111] It is understandable that during the lattice Boltzmann simulation, as the fluid wetting angle changes at different locations, the fluid deformation, i.e., the density of fluid particles, will change. Consequently, the solid-liquid interaction potential and the interparticle interaction force at the solid-liquid interface will also change. When the change in the fluid wetting angle reaches a critical value, such as the advancing or retreating angle, the fluid on the solid surface will undergo morphological changes such as splitting. By determining the variation range of the fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block can be determined. Then, based on the determined solid-liquid interaction force range, the fluid transport during the simulation process can be constrained, making the wettability of the constructed solid surface model closer to the real situation of the target rock surface and restoring the fluid transport process of the microscopic solid surface.

[0112] In some embodiments of this specification, determining the solid-liquid interaction force range of each wetting block based on the variation range of the fluid wetting angle of each wetting block may include:

[0113] Based on the mapping relationship between wetting angle and fluid density, the mapping relationship between fluid density and solid-liquid interaction potential, the mapping relationship between solid-liquid interaction force and solid-liquid interaction potential and velocity, and the variation range of fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined.

[0114] In some embodiments of this specification, the simulation of fluid transport on a solid surface can be realized within an LBM framework. Therefore, within this LBM framework, the mapping relationship between the wetting angle and the fluid density can be expressed by the following formula:

[0115] ρ(x,y,z)=ρ(x,y+2,z)+tan(2π-θ in Formula (1) for Xi;

[0116] Where ρ(x,y,z) represents the fluid density of the current lattice at position coordinates (x,y,z) on the solid surface model corresponding to the target rock surface, and ρ(x,y+2,z) represents the fluid density of the current lattice two lattice points above the y-axis. θ in Xi can represent the wetting angle of the current lattice during the fluid transport simulation, and Xi can represent the density gradient of the fluid in the current lattice. Furthermore, the region of variation of the fluid wetting angle of the current lattice can be set by limiting the advancing and receding angles of the wetting angle, specifically through θ. in ∈[θ rec ,θ adv Constraints are applied to θ. rec θ can represent the current lattice advance angle. adv It can represent the receding angle of the current lattice.

[0117] It is understandable that the wetting angle θ is important in fluid transport simulation. in The wetting angle can change with the morphology of the droplets on the solid surface. However, when the droplet morphology undergoes unsteady changes, such as splitting, it is necessary to constrain the wetting angle based on the range of its variation. Specifically, in the fluid transport simulation process, if θ in >θ adv Then θ in Corrected to θ adv If θ in <θ rec Then θ in Corrected to θ rec This allows for the limitation of fluid density during the simulation process.

[0118] In some embodiments of this specification, under the LBM framework, the mapping relationship between fluid density and solid-liquid interaction potential, and the mapping relationship between solid-liquid interaction force and solid-liquid interaction potential and velocity, can be expressed by the following formulas:

[0119]

[0120]

[0121] Where o represents the current lattice position, specifically (x, y, z), ψ(o,t) represents the solid-liquid interaction potential at time t, p represents the fluid pressure, which can be determined based on the Carnahan-Starling equation of state, ρ(o,t) represents the fluid density at time t, G represents the solid-liquid interaction constant, F(o,t) represents the solid-liquid interaction force at time t, and w α It can represent the weighting coefficient, e α This can represent the velocity direction vector, where α is the particle's transport direction. Based on the aforementioned constraints on fluid density, constraints on the solid-liquid interaction potential and solid-liquid interaction force can be achieved.

[0122] S106: Based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, determine the fluid transport characteristics of the target rock surface.

[0123] It is understandable that after determining the location distribution and the distribution of different wettability blocks on the target rock surface, a rough wettability surface model of the target rock surface can be constructed. Based on the solid-liquid interaction force range of each wettability block, the solid-liquid interaction force in the simulation process can be dynamically constrained. Based on the constraint conditions and the constructed rough wettability surface model, the fluid transport on the solid surface can be simulated. Then, based on the simulation results, the fluid transport characteristics of the target rock surface can be analyzed.

[0124] In some embodiments of this specification, determining the fluid transport characteristics of the target rock surface based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block may include:

[0125] Within the framework of lattice Boltzmann simulation: based on the location distribution and the distribution of different wettability blocks on the target rock surface, the height and wettability at each location in the solid surface model corresponding to the target rock surface are constructed; the fluid transport process of the solid surface model is simulated, and during the simulation, based on the solid-liquid interaction force range of each lattice, the interparticle interaction force between the solid and liquid interfaces of each lattice in the solid surface model is dynamically constrained to obtain transport simulation data;

[0126] The fluid transport simulation characteristics of the solid surface model are determined by analyzing the transport simulation data.

[0127] Based on the determined fluid transport simulation characteristics, the fluid transport characteristics of the target rock surface are determined.

[0128] It is understandable that the solid-liquid interaction force range of each wetting block can be used as a transport constraint condition in the transport simulation process. At each simulation time point in the simulation process, the interparticle interaction force between the solid and liquid interfaces of the wetting block can be constrained based on the solid-liquid interaction force range corresponding to the wetting block, so as to realize the dynamic constraint of fluid morphology in the simulation process, avoid unsteady changes such as excessive deformation of oil droplets in the transport simulation process, and improve the realism and reliability of fluid transport simulation on the target rock surface.

[0129] In the embodiments of this specification, the above-described method is used to quantify the fluctuations in the height of each scanning point on the target rock surface using atomic force microscopy (AFM), and to establish a dimensionless matrix of the height of each scanning point. This ensures that the construction of the solid surface roughness during the fluid transport simulation accurately reflects the microscopic experiment. AFM is also used to quantify the distribution and proportion of different types of wetting blocks on the wetted target rock surface, ensuring that the division of wetting blocks on the solid surface accurately reflects the microscopic experiment during the fluid transport simulation. By setting the advance angle and retreat angle as the range of variation of the wetting angle in the fluid transport simulation, the density distribution range of fluid particles at the solid-liquid interface at each time point during the simulation is limited. This completes the setting of the interaction forces between solid-liquid interface particles at each location in the solid surface model, ultimately completing the construction of the solid surface wettability during the simulation. This ensures the matching degree between the simulation of droplet transport on the target rock surface and the actual experiment.

[0130] Figure 2 The diagram illustrates the construction process of a solid surface model provided in an embodiment of this specification. It is understood that this embodiment uses the construction process of a pseudo-potential model of a target rock surface under the LBM framework as an example for explanation. In other embodiments, other simulation environments and models can be used for model construction, and this specification does not impose any limitations on this.

[0131] like Figure 2 The above method includes the following steps:

[0132] S201: Based on the height distribution of each scanning point in the atomic force microscope scan image, a rough surface is constructed within the pseudo-potential LBM framework.

[0133] Specifically, atomic force microscopy can be used to scan the surface of the target rock, and the surface roughness of the solid can be restored in the pseudo-potential LBM framework using the following method: the actual height of each scanning point within the scanned area of ​​the target rock surface is obtained through the height scan map of the target rock surface (i.e., the first scan image data mentioned above), and the ratio of the height of each scanning point to the scanned side length is used as a dimensionless parameter matrix, thereby realizing the simulation of the rough surface.

[0134] Furthermore, the obtained dimensionless height matrix can be multiplied by the number of lattice points representing the edge length of the simulated surface under the pseudo-potential LBM framework to obtain the number of lattice points representing the height of each scan point on the target rock surface. Based on the established histogram of the distribution of the number of dimensionless height lattice points, the height of each scan point on the solid surface is constructed in the pseudo-potential LBM to ensure that the proportion of each height in the total simulation range is consistent with the actual scan results. To avoid excessive computational load on the simulated surface due to an excessive number of scan points, the scan points can be reduced at intervals to ensure that the overall undulation pattern of the constructed solid surface matches the actual undulation pattern of the target rock surface.

[0135] S202: Based on the distribution of different wetting blocks on the solid surface as shown in the atomic force microscopy scanning images, the hydrophilic and oleophilic regions of the solid surface are divided within the pseudopotential LBM framework.

[0136] It is understood that the distribution locations of different wetting blocks on the solid surface in step S202 can be obtained by scanning the wetting target rock surface using an atomic force microscope. The atomic force microscope scan image can be the second scan image data mentioned above.

[0137] Specifically, if the target rock surface exhibits mixed wetting, atomic force microscopy can be used to scan the surface and effectively distinguish between hydrophilic and oleophilic regions using the following three methods:

[0138] 1) When oleophilic (hydrophilic) oil stains adhere to a continuous hydrophilic (oleophilic) surface, the proportion of oleophilic (hydrophilic) blocks on the continuous hydrophilic (oleophilic) surface can be calculated using a height scan map. The specific method is as follows: Select a baseline height based on the height scan map, i.e., use the continuous hydrophilic (oleophilic) surface as the baseline. Then, use the particle size analysis function in the offline analysis function of atomic force microscopy to quantify the specific location of blocks with heights higher than the baseline in the scan map; these are the adhered oleophilic (hydrophilic) patches.

[0139] 2) When the mixed wetting surface has a uniform texture and it is impossible to distinguish the height difference between the hydrophilic and oleophilic regions, but there are differences in hardness and viscoelastic modulus, a phase map is obtained by using the tapping mode of an atomic force microscope, and the positions of the hydrophilic and oleophilic regions in the map are calculated.

[0140] 3) When the above methods cannot distinguish between hydrophilic and oleophilic regions, the hydrophilicity of different regions is determined by Young's modulus diagram. The principle is that the interaction forces between the hydrophilic and oleophilic surfaces and the probe are different. By performing a force curve surface scan on the mixed wetting surface and fitting it into Young's modulus diagram, the positions of the hydrophilic and oleophilic regions in the diagram can be distinguished.

[0141] Furthermore, after obtaining the distribution patterns of hydrophilic and oleophilic zones on the target rock surface in step S202, the solid surface can be divided into different blocks within the pseudo-potential LBM framework, constructed using the following two methods:

[0142] 1) If the oleophilic (hydrophilic) blocks are randomly distributed on the surface of the target rock, the ratio of the block area to the total scan area is taken as a parameter. During the construction of the pseudo-potential LBM model, the position and size of the oleophilic (hydrophilic) blocks are randomly selected on the solid surface to ensure that the total ratio is the same as the atomic force microscopy scanning result.

[0143] 2) If the oleophilic (hydrophilic) blocks are distributed in an orderly manner on the surface of the target rock, a coordinate system is established on the atomic force microscope scan image. Based on the actual wetting situation at each coordinate point, the wetting blocks are constructed on the solid surface in the pseudo-potential LBM model.

[0144] Understandably, the two construction methods mentioned above can also be set based on actual application needs. For example, for application scenarios that do not require determining the specific wetting angle of the target rock surface, the above method 1) can be used, and for application scenarios that require accurately determining the specific wetting angle of the target rock surface, the above method 2) can be used.

[0145] S203: In the D3Q19 model of the pseudo-potential LBM framework, by setting the range of dynamic wetting angle variation at each point on the solid surface in the model, the interaction force between particles at the solid-liquid interface in the model is simulated, and the wettability of each point on the rough solid surface is constructed.

[0146] Specifically, the D3Q19 model is used in the pseudo-potential LBM to simulate multiphase flow. The advance and retreat angles of each point on the solid surface are set to limit the range of fluid wetting angle variation on the solid surface during the simulation, thereby controlling the density at different coordinate points of the solid-liquid interface. The fluid density can be controlled based on the formula (1) mentioned above. Furthermore, if there is mixed wetting on the target rock surface, the θ of different wetting blocks should be adjusted. rec θ adv Assign values ​​to each.

[0147] Specifically, by controlling the range of wetting angle during the simulation, the range of density variation at each coordinate point of the solid-liquid interface can be limited, thereby limiting the range of solid-liquid interaction potential variation during the simulation, thus completing the setting of the interaction force between particles at the solid-liquid interface in different blocks, and finally completing the construction of the wettability of the rough solid surface. The range of solid-liquid interaction potential variation can be set based on the formula (2) above, and the interaction force between solid-liquid interface particles can be set based on the formula (3) above.

[0148] S204: Based on the microscopic experiments of oil droplet migration on the wetted target rock surface, adjust and verify the wettability parameters of the solid surface under the pseudo-potential LBM framework, and complete the construction of the oil droplet migration model on the mixed-wetting rough solid surface under the pseudo-potential LBM framework.

[0149] It is understandable that due to the high viscosity of the droplets, accurate values ​​for the advance and retreat angles may not be available. In such cases, the parameter ranges for the advance and retreat angles can be set within the pseudo-potential model. These parameters can then be adjusted based on the actual transport process of the droplets on the mixed-wetting surface. This allows the model to accurately reproduce the transport process and steady-state morphology of the oil droplets on the mixed-wetting surface from microscopic experiments, ultimately determining the dynamic wetting angle parameters.

[0150] The following section, with reference to the accompanying figures, describes the construction process of a mixed wetting surface considering randomly distributed oily patches on a continuously wetted surface.

[0151] Figure 3 The image shown is a schematic diagram of an atomic force microscope height scan image provided in an embodiment of this specification. Figure 4 The diagram shown is a schematic representation of the simulation results of a mixed-wetting solid surface provided in the embodiments of this specification. Specifically, in this embodiment, the simulation of a mixed-wetting surface with randomly distributed oily patches on a continuously wetted surface is considered. The tested mixed-wetting surface is a smooth hydrophilic quartz surface with highly viscous oil stains. The surface is imaged using an atomic force microscope in tapping mode to obtain a height scan image. (Refer to...) Figure 3 As shown. Furthermore, using the smooth quartz surface as the baseline height, particle size analysis was performed on the oil spots attached within the scanning area to obtain the total area proportion of oleophilic blocks (oil spots) within the scanning area, as well as the individual area proportion of each block. Since oleophilic blocks on the actual surface are randomly distributed, the area proportion of oil spots was used as a parameter in the process of dividing the solid surface wetting blocks within the pseudo-potential LBM framework. Using the random number function in C language, the position and size of oleophilic blocks were randomly generated on the solid surface to ensure that the area proportion of a single oil spot and the total area proportion of oleophilic blocks both conform to the atomic force microscopy scanning results. Finally, the division of different wettability regions on the simulated mixed-wetting solid surface was achieved, resulting in... Figure 4 The simulation results are shown.

[0152] The following section, in conjunction with the accompanying diagrams, further describes the process of constructing a rough surface using the solid surface model construction method described earlier.

[0153] Figure 5 The image shown is a schematic diagram of an atomic force microscope height scan image provided in an embodiment of this specification. Figure 6 The image shown is a schematic diagram of the simulation results of a rough solid surface provided in the embodiments of this specification. Figure 7 The diagram shown is a schematic representation of the oil droplet transport simulation process using a solid surface model provided in the embodiments of this specification. Figure 8 The diagram illustrates a simulation of oil droplet transport on a solid surface model provided in this embodiment. Specifically, in this embodiment, the simulation of oil droplet transport on a rough surface, considering the limitations of the advance and retreat angles, can be achieved by scanning the rough solid surface with an atomic force microscope to obtain a height scan image. (Refer to...) Figure 5 As shown, the ratio of the height of each point to the width of the scan boundary can then be calculated. A histogram of the dimensionless height distribution of the rough surface will be constructed based on this ratio. According to the proportion of each dimensionless height, the height of each point on the solid surface will be constructed in the pseudo-potential LBM to ensure that the proportion of each height in the total simulation range is consistent with the actual scan results. The rough solid surface described above will be constructed in the D3Q19 model, referring to... Figure 6 As shown. Within the framework of the pseudo-potential LBM, a steady-state contact angle is set to limit the fluid equilibrium state, while the dynamic wetting angle range of the oil droplet during transport is limited to between its advance and retreat angles. By applying an external force to the oil droplet, causing it to move in the same direction on the mixing and wetting surface, the following can be obtained: Figure 7 and Figure 8 The two simulation results are shown.

[0154] like Figure 7 As shown, for Figure 7 An external force is applied to the oil droplet in 'a', causing the oil droplet to move along... Figure 7 Moving in the direction of motion of 'a', at a back angle of 7°, we obtain... Figure 7 In the image of b, the oil droplet is in a steady state and has not split. Figure 8 As shown, for Figure 8 An external force is applied to the oil droplet in 'a', causing the oil droplet to move along... Figure 8 Moving along the direction of motion in 'a', at a back angle of 5°, we obtain... Figure 8 In the image of b, the oil droplet is in a non-steady state and splits. Figure 8 The splitting state of the oil droplets in b and Figure 8 The results of the microscopic experiments in c are consistent. Figure 8 The splitting position of the oil droplet in step c can be seen from the arrow in the figure. That is, when the steady-state contact angle and advance angle are kept the same in both simulations, changing the size of the retreat angle reveals a critical value for the retreat angle. When the value is greater than the critical value, the transported oil droplet does not split, which is inconsistent with the actual results. When the value is less than or equal to the critical value, the oil droplet splits, better simulating the actual situation. Therefore, setting the advance angle and retreat angle as the range of variation of the wetting angle within the pseudo-potential LBM framework can effectively ensure the matching degree between the simulation of droplet transport on mixed wetting surfaces and the actual experiment.

[0155] Based on the method for determining the fluid transport characteristics of a solid surface described above, one or more embodiments of this specification also provide an apparatus for determining the fluid transport characteristics of a solid surface. The apparatus may include devices (including distributed systems), software (applications), modules, plug-ins, servers, clients, etc., using the methods described in the embodiments of this specification, combined with necessary implementation hardware. Based on the same innovative concept, the apparatuses in one or more embodiments provided in this specification are as described in the following embodiments. Since the implementation schemes and methods for solving the problem by the apparatus are similar, the implementation of the specific apparatus in the embodiments of this specification can refer to the implementation of the foregoing method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0156] Figure 9 The diagram shown is a schematic representation of a device for determining the fluid transport characteristics of a solid surface provided in an embodiment of this specification. Figure 9 As shown, the apparatus 900 for determining the fluid transport characteristics of the solid surface may include:

[0157] The first acquisition module 901 is used to acquire first scan image data of the target rock surface. The first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface.

[0158] The location determination module 902 is used to determine the location distribution of the scanning points on the target rock surface based on the first scanned image data.

[0159] The second acquisition module 903 is used to acquire second scan image data of the mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block of the mixed-wetting target rock surface. The second scan image data is image data of the wettability of multiple wetting blocks of the mixed-wetting target rock surface obtained by scanning the wetting blocks of the mixed-wetting target rock surface.

[0160] The wetting determination module 904 is used to determine the distribution of different wettability blocks on the surface of the target rock based on the second scanned image data.

[0161] The interval determination module 905 is used to determine the solid-liquid interaction force interval of each wetting block based on the variation interval of the fluid wetting angle of each wetting block.

[0162] The transport determination module 906 is used to determine the fluid transport characteristics of the target rock surface based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block.

[0163] The descriptions and functions of the above modules can be understood by referring to the section on methods for determining fluid transport characteristics on solid surfaces, and will not be repeated here.

[0164] This application also provides an electronic device, such as... Figure 10 As shown, the electronic device may include a processor 1001 and a memory 1002, wherein the processor 1001 and the memory 1002 may be connected via a bus or other means. Figure 10 Taking the example of a connection between China and Israel via a bus.

[0165] Processor 1001 may be a central processing unit (CPU). Processor 1001 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0166] Memory 1002, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for determining the fluid transport characteristics of a solid surface in this embodiment of the invention (e.g., Figure 9 The first acquisition module 901, position determination module 902, second acquisition module 903, wetting determination module 904, interval determination module 905, and migration determination module 906 are shown in the diagram. The processor 1001 executes various functional applications and data processing by running non-transitory software programs, instructions, and modules stored in the memory 1002, thereby realizing the method for determining the fluid migration characteristics of a solid surface in the above method embodiments.

[0167] The memory 1002 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 1001, etc. Furthermore, the memory 1002 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1002 may optionally include memory remotely located relative to the processor 1001, and these remote memories may be connected to the processor 1001 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0168] The one or more modules are stored in the memory 1002, and when executed by the processor 1001, they perform the following: Figure 1 The method for determining the fluid transport characteristics of a solid surface in the illustrated embodiment.

[0169] The specific details of the aforementioned electronic device can be understood by referring to the relevant descriptions and effects in the above method embodiments, and will not be repeated here.

[0170] This specification also provides a computer storage medium storing computer program instructions, which, when executed, implement the steps of the method for determining the fluid transport characteristics of the solid surface described above.

[0171] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0172] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, please refer to each other. The focus of each embodiment is to describe the differences from other embodiments.

[0173] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions.

[0174] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0175] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute certain parts of the methods of various embodiments of this application.

[0176] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0177] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0178] Although this application has been described through embodiments, those skilled in the art will know that this application has many modifications and variations without departing from the spirit of this application, and it is intended that the appended claims cover such modifications and variations without departing from the spirit of this application.

Claims

1. A method for determining the fluid transport characteristics of a solid surface, characterized in that, include: Acquire first scan image data of the target rock surface, wherein the first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface; Based on the first scanned image data, the location distribution of the scanned points on the target rock surface is determined; The second scan image data of the target rock surface with mixed wetting and the variation range of the fluid wetting angle of each wetting block of the target rock surface with mixed wetting are obtained. The second scan image data is image data of the wettability of multiple wetting blocks of the target rock surface with mixed wetting obtained by scanning the wetting blocks of the target rock surface with mixed wetting. Based on the second scanned image data, the distribution of different wettability blocks on the surface of the target rock is determined; Based on the variation range of the fluid wetting angle in each wetting block, the range of solid-liquid interaction force in each wetting block is determined. Based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, the fluid transport characteristics of the target rock surface are determined. Based on the variation range of the fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined, including: Based on the mapping relationship between wetting angle and fluid density, the mapping relationship between fluid density and solid-liquid interaction potential, the mapping relationship between solid-liquid interaction force and solid-liquid interaction potential and velocity, and the variation range of fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined. Based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, the fluid transport characteristics of the target rock surface are determined, including: Within the framework of lattice Boltzmann simulation, based on the location distribution and the distribution of different wettability blocks on the target rock surface, the height and wettability at each location in the solid surface model corresponding to the target rock surface are constructed; the fluid transport process of the solid surface model is simulated, and during the simulation, based on the solid-liquid interaction force range of each lattice, the interparticle interaction force between the solid and liquid interfaces of each lattice in the solid surface model is dynamically constrained to obtain transport simulation data; The fluid transport simulation characteristics of the solid surface model are determined by analyzing the transport simulation data. Based on the determined fluid transport simulation characteristics, the fluid transport characteristics of the target rock surface are determined.

2. The method according to claim 1, characterized in that, Based on the first scanned image data, determining the positional distribution of scanned points on the target rock surface includes: Determine the height of the position corresponding to each scanning point on the target rock surface in the first scanned image data; Based on the determined height and scanning side length, the dimensionless height matrix corresponding to the scanning points on the target rock surface is determined; Based on the dimensionless height matrix, the height distribution of the scanning points on the target rock surface is determined, and the height distribution is used as the position distribution.

3. The method according to claim 2, characterized in that, Based on the dimensionless height matrix, the height distribution of the scanning points on the target rock surface is determined, including: Within the framework of lattice Boltzmann simulation, based on the dimensionless height matrix and the simulated lattice number corresponding to the target rock surface, the height lattice matrix of the scanning points on the target rock surface is determined, wherein each element in the height lattice matrix is ​​used to characterize the lattice number corresponding to the dimensionless height of the scanning point; based on each element in the height lattice matrix, a distribution histogram of the lattice number is determined, and the determined distribution histogram is used as the height distribution.

4. The method according to claim 1, characterized in that, The variation range of the fluid wetting angle in each wetting block of the target rock surface with mixed wetting was determined by the following method: The wetting angle of the target rock surface was measured using a rolling wetting angle measuring instrument; Based on the wetting angle corresponding to the critical moment when the solid-liquid contact line on the wetted target rock surface changes, the advance angle and retreat angle of each wetting block are determined. Based on the determined advance and retreat angles of each wetting block, the range of variation of the fluid wetting angle of each wetting block on the target rock surface is determined.

5. The method according to claim 1, characterized in that, Based on the second scanned image data, the distribution of different wettability zones on the surface of the target rock is determined, including: The second scanned image data is processed, and based on the image processing results, the solid surface image features in the second scanned image data are determined. Based on the determined wetted area distinction rules corresponding to the solid surface image features, the wetted area categories and the locations of the wetted areas in the second scanned image data are determined. Based on the determined wetted block categories, the locations of wetted blocks in each category, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

6. The method according to claim 5, characterized in that, Before determining the distribution of different wettability blocks on the target rock surface based on the determined wettability block categories, the locations of wettability blocks in each category, and the correspondence between each location in the second scanned image data and the wettability blocks on the target rock surface, the following steps are included: For two adjacent wetting blocks of different categories, the gradient range of the linear wetting angle gradient between the first wetting block and the second wetting block is determined based on the first wetting angle of the first wetting block and the second wetting angle of the second wetting block. Based on the determined gradient range, the wettability at each location between the first wetting block and the second wetting block is determined as the region boundary wettability; Based on the determined wettability block categories, the locations of wettability blocks within each category, and the correspondence between each location in the second scanned image data and the wettability blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined, including: Based on the determined wetted block categories, the locations of wetted blocks in each category, the wettability of the region boundary, and the correspondence between each location in the second scanned image data and the wetted blocks on the target rock surface, the distribution of different wettability blocks on the target rock surface is determined.

7. A device for determining the fluid transport characteristics of a solid surface, characterized in that, include: The first acquisition module is used to acquire first scan image data of the target rock surface. The first scan image data is image data including the positions of multiple scan points on the target rock surface obtained by scanning the morphology of the target rock surface. The location determination module is used to determine the location distribution of the scanning points on the target rock surface based on the first scanned image data; The second acquisition module is used to acquire the second scan image data of the mixed-wetting target rock surface and the variation range of the fluid wetting angle of each wetting block of the mixed-wetting target rock surface. The second scan image data is image data of the wettability of multiple wetting blocks of the mixed-wetting target rock surface obtained by scanning the wetting blocks of the mixed-wetting target rock surface. A wetting determination module is used to determine the distribution of different wettability blocks on the surface of the target rock based on the second scanned image data; The interval determination module is used to determine the solid-liquid interaction force interval of each wetting block based on the variation interval of the fluid wetting angle of each wetting block. The transport determination module is used to determine the fluid transport characteristics of the target rock surface based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block. Based on the variation range of the fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined, including: Based on the mapping relationship between wetting angle and fluid density, the mapping relationship between fluid density and solid-liquid interaction potential, the mapping relationship between solid-liquid interaction force and solid-liquid interaction potential and velocity, and the variation range of fluid wetting angle in each wetting block, the solid-liquid interaction force range of each wetting block is determined. Based on the location distribution, the distribution of different wettability blocks on the target rock surface, and the solid-liquid interaction force range of each wettability block, the fluid transport characteristics of the target rock surface are determined, including: Within the framework of lattice Boltzmann simulation, based on the location distribution and the distribution of different wettability blocks on the target rock surface, the height and wettability at each location in the solid surface model corresponding to the target rock surface are constructed; the fluid transport process of the solid surface model is simulated, and during the simulation, based on the solid-liquid interaction force range of each lattice, the interparticle interaction force between the solid and liquid interfaces of each lattice in the solid surface model is dynamically constrained to obtain transport simulation data; The fluid transport simulation characteristics of the solid surface model are determined by analyzing the transport simulation data. Based on the determined fluid transport simulation characteristics, the fluid transport characteristics of the target rock surface are determined.

8. An electronic device, characterized in that, include: A memory and a processor, the processor and the memory being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 6.

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