CN113486565A - Method and device for simulating flow of active nanoparticles and water phase - Google Patents

Method and device for simulating flow of active nanoparticles and water phase Download PDF

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CN113486565A
CN113486565A CN202110705196.4A CN202110705196A CN113486565A CN 113486565 A CN113486565 A CN 113486565A CN 202110705196 A CN202110705196 A CN 202110705196A CN 113486565 A CN113486565 A CN 113486565A
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袁彬
李跃
戴彩丽
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China University of Petroleum East China
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Abstract

The invention discloses a method and a device for simulating two-phase flow of active nanoparticles and water. The method comprises the following steps: updating the parameters of the nano particles, and determining the electrostatic force among the particles by a Langewan dynamics method
Figure DDA0003131861320000011
And van der Waals forces
Figure DDA0003131861320000012
And receive the friction force of water
Figure DDA0003131861320000013
And random force
Figure DDA0003131861320000014
And electrostatic force of pore throat wall surface to particles
Figure DDA0003131861320000015
And van der Waals forces
Figure DDA0003131861320000016
Thereby updating the particle flow rate and position; if the particles are attached to the wall surface of the pore throat, executing a coupling step; if not, updating the water molecule particle swarm distribution function according to the boundary conditions of the rebound and the mirror reflection, and then executing the coupling step; water and particle coupling step according to
Figure DDA0003131861320000017
And
Figure DDA0003131861320000018
determining a force source term distribution function suffered by a water molecule particle swarm; updating the flow rate of water by a lattice boltzmann method; and returning to the particle parameter updating step until the set conditions. The method can comprehensively utilize a Langmuir dynamics method and a lattice Boltzmann method to couple macroscopic fluid and microscopic particles and simulate the two-phase flow of active nano particles and water.

Description

Method and device for simulating flow of active nanoparticles and water phase
Technical Field
The invention relates to the technical field of oil and gas exploitation, in particular to a method and a device for simulating flow of active nanoparticles and water.
Background
The hypotonic/ultra-hypotonic oil reservoir has the characteristics of poor water injection capacity, quick stratum pressure failure and the like, and the active nano particles have great advantages in the aspects of reducing water injection resistance, improving injection capacity and the like due to the characteristics of large specific surface area, surface activity and the like. However, the current micro mechanism for how the active nanoparticles reduce the flow resistance and improve the water injection capability is still unclear, so that the optimization of the active nanoparticles in the field design of the oil field depends too much on experience, and the realization of the development target of cost reduction and efficiency improvement of the oil field is not facilitated due to the lack of sufficient theoretical guidance.
The Lattice Boltzmann Method (LBM) has the advantages of simple algorithm, convenience for parallel operation, high calculation efficiency and the like, and has a good effect in simulating single-phase water and oil-water two-phase displacement and complex flow; the Langevin Dynamics (LD) method has high accuracy and computational efficiency in capturing brownian motion, inter-particle interaction, and the like of active nanoparticles.
Because the complex microscopic characteristics of the nanometer effect, the fluid-solid interface regulation and the like of the active nanometer particles lead to the complexity of the active nanometer particle/water two-phase flow simulation, how to comprehensively utilize the LBM and LD method to couple the macroscopic fluid and the microscopic particles to simulate the active nanometer particle/water two-phase flow under the condition of a low-permeability/ultra-low-permeability reservoir is a technical problem to be solved urgently at present.
Disclosure of Invention
In view of the above problems, the present invention has been made to provide an active nanoparticle and water two-phase flow simulation method and apparatus capable of simulating active nanoparticle and water two-phase flow by coupling macroscopic fluid and microscopic active nanoparticles by using a langevin dynamics method and a lattice boltzmann method in combination, which overcomes or at least partially solves the above problems.
In a first aspect, an embodiment of the present invention provides a method for simulating a flow of active nanoparticles in a water phase, including:
an active nanoparticle parameter updating step, comprising: determining the electrostatic force among the active nano-particles according to the radius, the current position, the flow rate of the active nano-particles and the flow rate of water at the active nano-particles by a Langmuir dynamics method
Figure BDA0003131861300000021
And van der Waals forces
Figure BDA0003131861300000022
And the friction force of the active nano-particles in the water phase
Figure BDA0003131861300000023
And random force
Figure BDA0003131861300000024
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure BDA0003131861300000025
And van der Waals forces
Figure BDA0003131861300000026
Wherein i is the serial number of the active nano-particles, p represents the active nano-particles, and wall represents the wall surface of the pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure BDA0003131861300000027
And
Figure BDA0003131861300000028
updating the flow rate and position of the active nanoparticles;
judging whether the active nano particles are attached to the wall surface of the pore throat or not according to the current positions of the active nano particles; if not, executing a step of coupling the aqueous phase fluid and the active nanoparticles; if the water phase fluid and the active nanoparticles are judged to be the same, updating the current water molecule particle swarm distribution function according to the boundary conditions of rebound and specular reflection, and then executing the step of coupling the water phase fluid and the active nanoparticles;
an aqueous phase fluid and active nanoparticle coupling step comprising: according to the current
Figure BDA0003131861300000029
And
Figure BDA00031318613000000210
determining a force source term distribution function suffered by a water molecule particle swarm;
the method comprises the following steps of: updating the flow velocity of water by a lattice boltzmann method according to the distribution function of the current water molecule particle swarm and the received force source term distribution function, and determining the flow velocity of water at the current active nano particle position by an interpolation method according to the flow velocity of water;
and returning to execute the active nanoparticle parameter updating step until the set conditions.
In a second aspect, embodiments of the present invention provide an active nanoparticle and water two-phase flow simulation device, including:
an active nanoparticle parameter updating module for determining the electrostatic force between the active nanoparticles according to the radius, current position, flow rate of the active nanoparticles and the flow rate of water at the active nanoparticles by Langewan dynamics method
Figure BDA00031318613000000211
And van der Waals forces
Figure BDA00031318613000000212
And the friction force of the active nano-particles in the water phase
Figure BDA00031318613000000213
And random force
Figure BDA0003131861300000031
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure BDA0003131861300000032
And van der Waals forces
Figure BDA0003131861300000033
Wherein i is the serial number of the active nano-particles, p represents the active nano-particles, and wall represents the wall surface of the pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure BDA0003131861300000034
And
Figure BDA0003131861300000035
updating the flow rate and position of the active nanoparticles;
the judging module is used for judging whether the active nano particles are attached to the wall surface of the pore throat according to the current positions of the active nano particles;
the water phase fluid and active nano particle coupling module is used for judging whether the water phase fluid and active nano particle are in a negative state according to the current state
Figure BDA0003131861300000036
And
Figure BDA0003131861300000037
determining a force source term distribution function suffered by a water molecule particle swarm;
the attached suspension characterization module of the active nano particles is used for updating the current water molecule particle swarm distribution function according to the boundary conditions of rebound and specular reflection if the judgment module judges that the particle swarm distribution function is positive;
the water phase fluid parameter updating module is used for updating the flow velocity of water according to the distribution function of the current water molecule particle swarm and the received force source item distribution function by a lattice boltzmann method, and determining the flow velocity of water at the current active nano particle position by utilizing an interpolation method according to the flow velocity of the water;
and the active nanoparticle parameter updating module returns to execute the active nanoparticle parameter updating step until the set conditions are met.
In a third aspect, embodiments of the present invention provide a computer readable storage medium having stored thereon computer instructions that, when executed by a processor, implement the above-described active nanoparticle and water two-phase flow simulation method.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
(1) according to the active nanoparticle and water two-phase flow simulation method provided by the embodiment of the invention, a Langevin Dynamics (LD) method is utilized to simulate the flow of the active nanoparticle, the interaction force (electrostatic force and Van der Waals force) among the active nanoparticles and the friction force and random force of the active nanoparticles in water phase fluid are described, and the electrostatic force and van der Waals force of the throat wall facing the active nanoparticles are determined, so that the flow speed and the position of the active nanoparticles are updated according to the Newton's second law and the stress condition of the active nanoparticles; and simulating the aqueous phase flow field by using a Lattice Boltzmann Method (LBM), updating the flow rate of water according to the distribution function of the current water molecule particle swarm and the received force source term distribution function, and realizing the coupling of the active nanoparticles and the aqueous phase flow field by introducing the force source term distribution function. Finally, the comprehensive utilization of the Langewan dynamics method and the lattice Boltzmann method to couple the macroscopic fluid and the microscopic active nano particles is realized, and the two-phase flow of the active nano particles and the water is simulated.
(2) Before the LBM is utilized to simulate the water phase flow field, whether the active nano particles are attached to the pore throat wall surface or not is judged according to the current positions of the active nano particles, if yes, the current water molecule particle swarm distribution function is updated according to the boundary conditions of rebound and mirror reflection, and the simulation result is closer to the real condition.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow diagram of a method for simulating two-phase flow of active nanoparticles and water in an embodiment of the invention;
FIG. 2 is a schematic diagram of dynamic attachment of active nanoparticles in a typical pore-throat configuration in an embodiment of the present disclosure;
FIG. 3 is a graphical representation of the dynamic attachment concentration of active nanoparticles versus time for a typical pore-throat configuration in accordance with an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of an active nanoparticle and water two-phase flow simulator in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to solve the problem that the LBM and LD methods cannot be comprehensively utilized to couple the macroscopic fluid and the microscopic particles to simulate the flow of the active nanoparticles and the water phase, the embodiment of the invention provides an active nanoparticle and water phase flow simulation method and device, which can comprehensively utilize the LBM and LD methods to couple the macroscopic fluid and the microscopic active nanoparticles to simulate the flow of the active nanoparticles and the water phase.
Examples
The embodiment of the invention provides a method for simulating the flow of active nanoparticles and water two phases, wherein the flow is shown in figure 1, and the method comprises the following steps:
step S11: and (3) updating the parameters of the active nanoparticles.
The method specifically comprises the following steps: determining the electrostatic force among the active nano-particles according to the radius, the current position, the flow rate of the active nano-particles and the flow rate of water at the active nano-particles by a Langmuir dynamics method
Figure BDA0003131861300000051
And van der Waals forces
Figure BDA0003131861300000052
And the friction force of the active nano-particles in the water phase
Figure BDA0003131861300000053
And random force
Figure BDA0003131861300000054
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure BDA0003131861300000055
And van der Waals forces
Figure BDA0003131861300000056
Wherein i is active sodiumThe serial number of the rice particles, p represents active nano particles, and wall represents the wall surface of a pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure BDA0003131861300000057
And
Figure BDA0003131861300000058
the flow rate and position of the active nanoparticles are updated.
The van der Waals forces between the active nanoparticles can be determined by equation (1)
Figure BDA0003131861300000059
Figure BDA00031318613000000510
In the formula (1), the first and second groups,
Figure BDA00031318613000000511
to set the minimum distance of the active nanoparticle i to the surface of the active nanoparticle j within a range,
Figure BDA00031318613000000512
the radius and the current position of the active nano particles i and j are determined; n is the number of active nano particles in a set range;
Figure BDA00031318613000000513
is the van der waals potential energy between the active nanoparticles i, j,
Figure BDA00031318613000000514
determined by equation (2):
Figure BDA00031318613000000515
in the formula (2), AccIs Hamaker constant, Acc＝4π2kBT，kBBoltzmann constant, T is the absolute temperature of the environment, which may be empirically set, to a constant value; r is the radius of the active nanoparticle.
The electrostatic force between the active nanoparticles can be determined by equation (3)
Figure BDA00031318613000000516
Figure BDA00031318613000000517
In formula (3), κ is the reciprocal of the debye length and is a constant; z is an interaction constant, and Z is determined by equation (4):
Z＝64πεoε(kBT/e)2tanh2(z0e/4kBT) (4)
in the formula (4), εoIs the dielectric constant in vacuum,. epsilon.is the relative dielectric constant of water, z0Is the electrolyte valence.
The frictional force to which the active nanoparticles are subjected in the aqueous phase can be determined by equation (5)
Figure BDA0003131861300000061
Figure BDA0003131861300000062
In the formula (5), ζ is a friction coefficient, which can be determined by stokes' law of resistance, and ζ is 6 pi μwR ψ, wherein μwThe kinetic viscosity of water is used, psi is an active nano-particle shape factor, and psi is more than 0 and less than or equal to 1;
Figure BDA0003131861300000063
is the current flow rate of the active nanoparticle i;
Figure BDA0003131861300000064
is the current flow rate of water at the active nanoparticle i.
According to the fact that the random force of the active nanoparticles in the water phase conforms to the Gaussian distribution, the random force of the active nanoparticles in the water phase can be determined through the formula (6)
Figure BDA0003131861300000065
Figure BDA0003131861300000066
The random force that the active nanoparticles are subjected to in the aqueous phase is due to heat dissipation, reflecting the thermal fluctuation effect of the fluid.
Electrostatic force between the active nanoparticles
Figure BDA0003131861300000067
And van der Waals forces
Figure BDA0003131861300000068
And the friction force of the active nano-particles in the water phase
Figure BDA0003131861300000069
And random force
Figure BDA00031318613000000610
The following Langmuim kinetic equations are satisfied:
Figure BDA00031318613000000611
in the formula (7), mpIs the weight of the active nanoparticles;
Figure BDA00031318613000000612
is the current flow rate of the active nanoparticle i; t is time.
Under the actual physical background, electrostatic force and van der waals force exist between the pore throat wall surface and the active nanoparticles, and when the active nanoparticles are very close to the wall surface (generally less than 0.3nm), the wall surface and the active nanoparticles can generate strong hydrogen bonding action, so that the active nanoparticles generate adhesion behavior on the wall surface.
The van der Waals force of the throat wall surface against the active nanoparticles can be determined by equation (8)
Figure BDA00031318613000000613
Figure BDA0003131861300000071
In the formula (8), the first and second groups,
Figure BDA0003131861300000072
is the minimum distance between the surface of the active nanoparticle i and the wall surface of the pore throat.
The electrostatic force of the throat wall facing the active nanoparticles can be determined by equation (9)
Figure BDA0003131861300000073
Figure BDA0003131861300000074
After determining the various forces to which the active nanoparticles are subjected, the current flow rate of the active nanoparticles i can be used
Figure BDA0003131861300000075
And
Figure BDA0003131861300000076
determining the flow velocity after the time step Δ t of the active nanoparticles according to equation (10)
Figure BDA0003131861300000077
Figure BDA0003131861300000078
Can be used forUsing the current position of the active nanoparticle i
Figure BDA0003131861300000079
And flow rate after a time step Δ t
Figure BDA00031318613000000710
Determining the position of the active nanoparticles after a time step Δ t according to equation (11)
Figure BDA00031318613000000711
Figure BDA00031318613000000712
In the formula (10), mpIs the weight of the active nanoparticles.
Therefore, the parameters of the active nanoparticles are updated, including the parameters of various applied forces, speeds, positions and the like.
In this embodiment, Δ t is used as a time step to simulate the states of the seepage fields of the active nanoparticles and the water from the moment when the active nanoparticles and the water are injected to the moments within a set time period, so that the current moment refers to the current moment of the simulation, a certain parameter of the current moment, sometimes represented by a t marked in a following bracket, and sometimes omitted t, for example, the current position of the active nanoparticle i
Figure BDA00031318613000000713
Sometimes also simplified as
Figure BDA00031318613000000714
Step S12: and judging whether the active nano particles are attached to the wall surface of the pore throat according to the current positions of the active nano particles.
The active nanoparticles are modeled as standard spherical particles, the current location of the active nanoparticles, and more specifically, the current location of the spherical center of the active nanoparticles.
And determining the shortest distance from the current position of the active nano-particles to the pore throat wall surface, wherein the difference value between the shortest distance and the particle radius is less than a set threshold value, and determining that the active nano-particles are attached to the pore throat wall surface.
The threshold may be set to 0.3nm, for example.
If the judgment in the step S12 is NO, executing a step S14; if the determination in step S12 is positive, step S13 is executed, and then step S14 is executed.
Step S13: and updating the current water molecule particle swarm distribution function according to the boundary conditions of the rebound and the specular reflection.
Due to the action force between the pore throat wall surface and the particles, part of the active nano particles can be attached to the pore throat wall surface. The active nano particles are attached to the wall surface to influence the wettability of the wall surface, and the surface properties of the wall surface become more hydrophobic after the active nano particles are attached to the wall surface due to the hydrophobic groups modified on the surface, so that the liquid-solid acting force between the wall surface and water is weakened, and the liquid has the sliding length. And (4) obtaining the sliding length under the corresponding wall surface condition through molecular dynamics simulation. At the active nanoparticle adsorption sites, the wall boundary conditions are modified to be the reflection-bounce combination boundaries according to equation (12).
Updating the current water molecule particle swarm distribution function through a formula (12) according to the boundary conditions of the rebound and the specular reflection:
Figure BDA0003131861300000081
in the formula (12), the first and second groups,
Figure BDA0003131861300000082
is a position
Figure BDA0003131861300000083
The distribution function of the water molecule particle swarm in the set direction d at the current time t, wherein d is the serial number of the set direction;
Figure BDA0003131861300000084
is a rebound boundary conditionTo position of
Figure BDA0003131861300000085
The distribution function of the water molecule particle swarm at the current moment t and in the set direction d,
Figure BDA0003131861300000086
position derived from boundary conditions of specular reflection
Figure BDA0003131861300000087
Setting a distribution function of the water molecule particle swarm at the current time t and in the set direction d; c is a combination coefficient of the two or more,
Figure BDA0003131861300000088
lsfor slip length, τ is the single relaxation time, c characterizes wettability, and more hydrophilic the smaller the c value, the more hydrophobic the c value.
In step S13, the current water molecule particle group distribution function is updated.
Step S14: and coupling the aqueous phase fluid with the active nanoparticles.
The two-phase coupling of the water phase fluid and the active nano particles can be realized by determining the force source term distribution function suffered by the water molecule particle swarm.
The method specifically comprises the following steps: according to the friction force currently suffered by the active nano-particles in the water phase
Figure BDA0003131861300000091
And random force
Figure BDA0003131861300000092
And determining a force source term distribution function suffered by the water molecule particle swarm.
Further, according to the time step, the grid step, the weight coefficient and the current
Figure BDA0003131861300000093
And
Figure BDA0003131861300000094
to keep movingConservation of quantity, and determining the pulse density of the active nano particles corresponding to the water molecule particle swarm by using the formula (13)
Figure BDA0003131861300000095
Figure BDA0003131861300000096
In the formula (13), the first and second groups,
Figure BDA0003131861300000097
the current position of the water molecule particle swarm is taken as the current position of the water molecule particle swarm;
Figure BDA0003131861300000098
is the current position of the active nanoparticle i;
Figure BDA0003131861300000099
is a weight coefficient;
Figure BDA00031318613000000910
is the fluid force to which the active nanoparticles i are subjected in the aqueous phase,
Figure BDA00031318613000000911
Δ t is the time step; Δ r is the trellis step.
And adding the force source term distribution function into the evolution equation of the water phase to complete the two-phase coupling of the water phase fluid and the active nano particles. Specifically, according to the weight coefficient and the pulse density of the active nanoparticles corresponding to the water molecule particle swarm, determining a force source term distribution function suffered by the water molecule particle swarm by using a formula (14);
Figure BDA00031318613000000912
in the formula (14), the reaction mixture,
Figure BDA00031318613000000913
for the water molecule particle group in the setting directionDistribution function of force source term, omega, to ddIs a weight coefficient in the d direction, is composed of
Figure BDA00031318613000000914
Interpolation is carried out to obtain; csIn order to be the pseudo-sound velocity,
Figure BDA00031318613000000915
Figure BDA00031318613000000916
is the unit direction vector of the d direction velocity component of the water molecule particle swarm.
Step S15: and updating the parameters of the water phase fluid.
As a class of mesoscopic methods, the Lattice Boltzmann Method (LBM) is a bridge that links macroscopic and microscopic, and obtains distribution functions by simulating migration and collision of particle groups, and further obtains macroscopic fluid properties such as pressure, temperature, flow rate, and the like.
Step S15 may specifically include: and updating the flow velocity of the water according to the distribution function of the current water molecule particle swarm and the received force source term distribution function by a lattice boltzmann method, and determining the flow velocity of the water at the current active nano particle position by an interpolation method according to the flow velocity of the water.
According to the distribution function of the current water molecule particle swarm
Figure BDA00031318613000000917
The current water density is determined by equation (15):
Figure BDA0003131861300000101
in the formula (15), the first and second groups,
Figure BDA0003131861300000102
is a position
Figure BDA0003131861300000103
The water molecule particle swarm at the current time t,A distribution function of a speed discrete direction d, wherein d is a serial number of a set speed discrete direction, and Q is the total direction number of speed discrete;
Figure BDA0003131861300000104
is a position
Figure BDA0003131861300000105
The current water density of (c).
As described above
Figure BDA0003131861300000106
If the current distribution function is the current distribution function of the water molecule particle swarm, the step S12 judges the current position
Figure BDA0003131861300000107
The active nano-particles are attached to the wall surface of the pore throat
Figure BDA0003131861300000108
Is updated through step S14.
The lattice boltzmann equation can be restored to the navier stokes equation, and an expression (15) of the equilibrium state distribution function can be obtained. According to the current density of water
Figure BDA0003131861300000109
Determining the equilibrium distribution function of the current water molecule particle swarm through the formula (16)
Figure BDA00031318613000001010
Figure BDA00031318613000001011
In the formula (16), the first and second groups,
Figure BDA00031318613000001012
is a position
Figure BDA00031318613000001013
OfThe current equilibrium state distribution function of the water molecule particle swarm in the speed dispersion direction d, the initial moment
Figure BDA00031318613000001014
ωdA weight coefficient being a speed dispersion direction d; csIn order to be the pseudo-sound velocity,
Figure BDA00031318613000001015
Δ t is the time step; Δ r is the lattice step;
Figure BDA00031318613000001016
is the injection flow rate of water;
Figure BDA00031318613000001017
is the unit direction vector of the d direction velocity component of the water molecule particle swarm.
The active nano particles have great advantages in solving the problems of low water injection capacity, high flow resistance and the like of a low-permeability/ultra-low-permeability reservoir, but at present, the micro mechanism of how the active nano particles reduce the flow resistance and improve the water injection capacity is still unclear, so that the parameters of the field design and optimization of the injection flow rate, the injection concentration, the particle size and the like of the active nano particles of an oil field excessively depend on experience, and sufficient theoretical guidance is lacked. The embodiment of the invention provides an active nano particle and water two-phase flow simulation method, wherein the injection flow rate of water is utilized
Figure BDA00031318613000001018
The number N (representing the injection concentration) of the active nanoparticles, the radius R of the active nanoparticles and other initialization parameters can be set by using a simulation result obtained by changing any one parameter, and a theoretical basis is provided for the parameter.
Can be based on the distribution function of the current water molecule particle swarm
Figure BDA00031318613000001019
Distribution function of force source term
Figure BDA00031318613000001020
And equilibrium state distribution function
Figure BDA00031318613000001021
The flow simulation of the water phase is carried out by using a classical single relaxation collision format, and the water molecule particle swarm distribution function at the next moment is determined by a formula (17)
Figure BDA0003131861300000111
Figure BDA0003131861300000112
In formula (17), τ is the single relaxation time.
If the aqueous phase is pure, none of the above formula (17)
Figure BDA0003131861300000113
Therefore, the two-phase coupling of the water phase and the active nano-particles is realized through the force source term distribution function.
According to water molecule particle swarm distribution function
Figure BDA0003131861300000114
And equation (15) determining the density of water
Figure BDA0003131861300000115
The flow rate of water at the next time is determined by the formula (18)
Figure BDA0003131861300000116
Figure BDA0003131861300000117
In one embodiment, it may also be based on the density of the water
Figure BDA0003131861300000118
The water pressure at the next moment is determined by equation (19)
Figure BDA0003131861300000119
Figure BDA00031318613000001110
The steps can realize the simulation of the pressure field and the speed field of the water in the seepage process.
Step S16: and judging whether the set conditions are reached.
Whether the simulation termination condition is met or not can be judged according to whether the current time t meets the requirement of the set duration or not.
If yes, executing step S17 to finish the simulation; if not, the process returns to step S11.
Step S17: and finishing the simulation.
According to the active nanoparticle and water two-phase flow simulation method provided by the embodiment of the invention, a Langevin Dynamics (LD) method is utilized to simulate the flow of the active nanoparticle, the interaction force (electrostatic force and Van der Waals force) among the active nanoparticles and the friction force and random force of the active nanoparticles in water phase fluid are described, and the electrostatic force and van der Waals force of the throat wall facing the active nanoparticles are determined, so that the flow speed and the position of the active nanoparticles are updated according to the Newton's second law and the stress condition of the active nanoparticles; and simulating the aqueous phase flow field by using a Lattice Boltzmann Method (LBM), updating the flow rate of water according to the distribution function of the current water molecule particle swarm and the received force source term distribution function, and realizing the coupling of the active nanoparticles and the aqueous phase flow field by introducing the force source term distribution function. Finally, the comprehensive utilization of the Langewan dynamics method and the lattice Boltzmann method to couple the macroscopic fluid and the microscopic active nano particles is realized, and the two-phase flow of the active nano particles and the water is simulated.
Before the LBM is utilized to simulate the water phase flow field, whether the active nano particles are attached to the pore throat wall surface or not is judged according to the current positions of the active nano particles, if yes, the current water molecule particle swarm distribution function is updated according to the boundary conditions of rebound and mirror reflection, and the simulation result is closer to the real condition.
In one embodiment, after determining that the set condition is reached, determining the limit attachment concentration and/or the time of the dynamic equilibrium attachment process of the active nanoparticles according to the determination time and the determination result of whether the active nanoparticles are attached to the pore throat wall surface may be further included.
Referring to fig. 2, at the time when t is 0, the active nanoparticles are not injected yet, and the number of active nanoparticles in the pore throat is zero; t is t1At any moment, with the injection of active nano particles, sporadic particles are attached to the wall surface of the pore throat; t ═ τcrAt the moment, with the continuous injection of the active nano particles, the quantity of the active nano particles attached to the pore throat wall surface reaches the maximum, and then the dynamic equilibrium attachment process time of the active nano particles is determined to be taucr；t＝t2At this time, as the injection of the active nanoparticles is continued, the number of active nanoparticles attached to the throat wall surface is not changed.
The limiting attachment concentration C of active nanoparticles can be determined using FIG. 3crAnd dynamic equilibrium attachment process time τcrWith the continuous injection of the active nanoparticles, the maximum density of the particles is reached to the limit attachment concentration C of the active nanoparticlescrTime τ at which maximum density will begin to be reachedcrThe dynamic equilibrium attachment process time for the active nanoparticles was determined.
The multivariate prediction chart of the radius, the injection flow rate and the injection concentration of the active nano particles, the limit adhesion concentration of the active nano particles and the dynamic balance adhesion process time can be obtained under the condition of different wettability of the wall surface.
The wettability of the hydrophobic active nano-particles is changed due to the attachment of the hydrophobic active nano-particles to the pore throat wall surface, and the water injection pressure is an opposite influence factor due to the reduction of the rock pore throat radius due to the attachment of the active nano-particles to the pore throat wall surface.
The active nanoparticle and water two-phase flow simulation method provided by the embodiment of the invention is based on LBM (lattice Boltzmann method) -LD (Lankiwan dynamics method) to carry out active nanoparticle and water two-phase flow microscopic simulation. Step S11, calculating the random force, the friction force, the van der Waals force and the electrostatic force of the active nano-particles through the Langmuim equation, and updating the stress, the speed and the displacement parameters of the active nano-particles in real time by considering the van der Waals force and the electrostatic force between the active nano-particles and the wall surface; step S15, simulating the change of the pressure field and the velocity field of the water phase fluid through a lattice Boltzmann evolution equation; step S13, a fluid-solid coupling method for the movement of the water phase flow field and the active nano particles is established by utilizing a force source term distribution function, and the oscillation influence generated when solving the solid coupling of the active nano particles and the water two-phase flow is weakened; and step S14, quantifying and representing the microscopic behavior of the active nanoparticles in water phase suspension and in rock wall attachment, finely depicting the influence of the active nanoparticles attached to the wall on the wettability of the wall, introducing the slippage length, and representing the influence rule of the wettability change of the active nanoparticles after adsorption on the pore flow field and the pressure field. The method quantificationally represents the unbalanced process of the interference of the nanoparticles on the velocity field and the pressure field of the water-phase fluid, simulates the dynamic attachment behavior of the active nanoparticles, represents key parameters such as the time and the ultimate attachment concentration of the dynamic attachment process of the nanoparticles, represents the influence rule of the wettability change of the nanoparticles after attachment on the pore flow field and the pressure field, and provides a key theoretical basis for popularizing and applying the active nanoparticles to improve the water injection process of the low-permeability/ultra-low permeability reservoir.
Based on the same inventive concept, the embodiment of the present invention further provides an active nanoparticle and water two-phase flow simulation device, the structure of which is shown in fig. 4, and the device includes:
an active nanoparticle parameter updating module 41 for determining the electrostatic force between the active nanoparticles according to the radius, current position, flow rate of the active nanoparticles and the flow rate of water at the active nanoparticles by the Langewan dynamics method
Figure BDA0003131861300000131
And van der Waals forces
Figure BDA0003131861300000132
And the friction force of the active nano-particles in the water phase
Figure BDA0003131861300000133
And random force
Figure BDA0003131861300000134
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure BDA0003131861300000135
And van der Waals forces
Figure BDA0003131861300000136
Wherein i is the serial number of the active nano-particles, p represents the active nano-particles, and wall represents the wall surface of the pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure BDA0003131861300000137
And
Figure BDA0003131861300000138
updating the flow rate and position of the active nanoparticles;
the judging module 42 is used for judging whether the active nanoparticles are attached to the pore throat wall surface according to the current positions of the active nanoparticles;
a module 43 for coupling the aqueous phase fluid and the active nanoparticles, configured to determine whether the determination module 42 determines that the aqueous phase fluid and the active nanoparticles are not present
Figure BDA0003131861300000141
And
Figure BDA0003131861300000142
determining a force source term distribution function suffered by a water molecule particle swarm;
the attached suspension characterization module 44 of the active nanoparticles is used for updating the current water molecule particle swarm distribution function according to the boundary conditions of the rebound and the specular reflection if the judgment module 42 judges that the particle swarm distribution function is positive;
the water phase fluid parameter updating module 45 is used for updating the flow velocity of water according to the distribution function of the current water molecule particle swarm and the received force source item distribution function by a lattice boltzmann method, and determining the flow velocity of water at the current active nano particle position by utilizing an interpolation method according to the flow velocity of the water;
the active nanoparticle parameter update module 41 returns to execute the active nanoparticle parameter update step until the set condition.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Based on the same inventive concept, embodiments of the present invention also provide a computer readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the above-described active nanoparticle and water two-phase flow simulation method.
It should be understood that the specific order or hierarchy of steps in the processes disclosed is an example of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not intended to be limited to the specific order or hierarchy presented.
In the foregoing detailed description, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, invention lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.
What has been described above includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent that the term "includes" is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term "comprising" as "comprising" is interpreted when employed as a transitional word in a claim. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or".

Claims (10)

1. An active nanoparticle and water two-phase flow simulation method, comprising:
an active nanoparticle parameter updating step, comprising: determining the electrostatic force among the active nano-particles according to the radius, the current position, the flow rate of the active nano-particles and the flow rate of water at the active nano-particles by a Langmuir dynamics method
Figure FDA0003131861290000011
And van der Waals forces
Figure FDA0003131861290000012
And the friction force of the active nano-particles in the water phase
Figure FDA0003131861290000013
And random force
Figure FDA0003131861290000014
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure FDA0003131861290000015
And van der Waals forces
Figure FDA0003131861290000016
Wherein i is the serial number of the active nano-particles, p represents the active nano-particles, and wall represents the wall surface of the pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure FDA0003131861290000017
And
Figure FDA0003131861290000018
updating the flow rate and position of the active nanoparticles;
judging whether the active nano particles are attached to the wall surface of the pore throat or not according to the current positions of the active nano particles; if not, executing a step of coupling the aqueous phase fluid and the active nanoparticles; if the water phase fluid and the active nanoparticles are judged to be the same, updating the current water molecule particle swarm distribution function according to the boundary conditions of rebound and specular reflection, and then executing the step of coupling the water phase fluid and the active nanoparticles;
an aqueous phase fluid and active nanoparticle coupling step comprising: according to the current
Figure FDA00031318612900000114
And
Figure FDA00031318612900000115
determining a force source term distribution function suffered by a water molecule particle swarm;
the method comprises the following steps of: updating the flow velocity of water by a lattice boltzmann method according to the distribution function of the current water molecule particle swarm and the received force source term distribution function, and determining the flow velocity of water at the current active nano particle position by an interpolation method according to the flow velocity of water;
and returning to execute the active nanoparticle parameter updating step until the set conditions.
2. The method of claim 1, wherein the method further comprises the step of applying a voltage to the substrateDetermining electrostatic forces between the active nanoparticles according to the radius of the active nanoparticles, the current position, the flow rate, and the flow rate of water at the active nanoparticles by the Langmuim kinetic method
Figure FDA0003131861290000019
And van der Waals forces
Figure FDA00031318612900000110
And the friction force of the active nano-particles in the water phase
Figure FDA00031318612900000111
And random force
Figure FDA00031318612900000112
The method specifically comprises the following steps:
determination of Van der Waals forces between active nanoparticles by equation (1)
Figure FDA00031318612900000113
Figure FDA0003131861290000021
In the formula (1), the first and second groups,
Figure FDA0003131861290000022
to set the minimum distance of the active nanoparticle i to the surface of the active nanoparticle j within a range,
Figure FDA0003131861290000023
the radius and the current position of the active nano particles i and j are determined; n is the number of active nanoparticles in the set range;
Figure FDA0003131861290000024
is the van der waals potential energy between the active nanoparticles i, j,
Figure FDA0003131861290000025
determined by equation (2):
Figure FDA0003131861290000026
in the formula (2), AccIs Hamaker constant, Acc＝4π2kBT，kBBoltzmann constant, T is the absolute temperature of the environment; r is the radius of the active nanoparticle;
determination of the Electrostatic forces between active nanoparticles by equation (3)
Figure FDA0003131861290000027
Figure FDA0003131861290000028
In formula (3), κ is the reciprocal of the debye length; z is an interaction constant, and Z is determined by equation (4):
Z＝64πεoε(kBT/e)2tanh2(z0e/4kBT) (4)
in the formula (4), εoIs the dielectric constant in vacuum,. epsilon.is the relative dielectric constant of water, z0Is the electrolyte valence;
the friction force of the active nanoparticles in the aqueous phase is determined by equation (5)
Figure FDA0003131861290000029
Figure FDA00031318612900000210
In the formula (5), ζ is a friction coefficient, and ζ is 6 pi μwR ψ, wherein μwIs dynamic viscosity of waterPsi is active nano-particle shape factor, phi is more than 0 and less than or equal to 1;
Figure FDA00031318612900000211
is the current flow rate of the active nanoparticle i;
Figure FDA00031318612900000212
is the current flow rate of water at the active nanoparticle i;
determining the random force of the active nano-particles in the water phase through a formula (6) according to the fact that the random force of the active nano-particles in the water phase conforms to the Gaussian distribution
Figure FDA00031318612900000213
Figure FDA0003131861290000031
3. The method of claim 2, wherein the determining the electrostatic force of the throat wall against the active nanoparticles is based on the radius and current position of the active nanoparticles
Figure FDA0003131861290000032
And van der Waals forces
Figure FDA0003131861290000033
The method specifically comprises the following steps:
determination of Van der Waals force of pore throat wall surface to active nanoparticles by equation (7)
Figure FDA0003131861290000034
Figure FDA0003131861290000035
In the formula (7), the first and second groups,
Figure FDA0003131861290000036
the minimum distance between the surface of the active nano-particle i and the wall surface of the pore throat;
by the formula (8), the electrostatic force of the throat wall facing the active nanoparticles is determined
Figure FDA0003131861290000037
Figure FDA0003131861290000038
4. The method of claim 1, wherein the current location, flow rate, or rate of flow of the active nanoparticle is utilized,
Figure FDA0003131861290000039
And
Figure FDA00031318612900000310
updating the flow rate and the position of the active nanoparticles specifically comprises:
using the current flow rate of the active nanoparticle i
Figure FDA00031318612900000311
And
Figure FDA00031318612900000312
determining the flow velocity after the time step Δ t of the active nanoparticles according to equation (9)
Figure FDA00031318612900000313
Figure FDA00031318612900000314
Using active nanoparticles of iFront position
Figure FDA00031318612900000315
And flow rate after a time step Δ t
Figure FDA00031318612900000316
Determining the position of the active nanoparticles after a time step Δ t according to equation (10)
Figure FDA00031318612900000317
Figure FDA00031318612900000318
In formula (9), mpIs the weight of the active nanoparticles.
5. The method of claim 1, wherein said updating the current water molecule particle swarm distribution function according to the bounces and specular reflection boundary conditions comprises:
updating the current water molecule particle swarm distribution function according to the boundary conditions of the rebound and the specular reflection by the formula (11):
Figure FDA0003131861290000041
in the formula (11), the reaction mixture,
Figure FDA0003131861290000042
is a position
Figure FDA0003131861290000043
The distribution function of the water molecule particle swarm in the set direction d at the current time t, wherein d is the serial number of the set direction;
Figure FDA0003131861290000044
is a rebound edgeBoundary condition derived position
Figure FDA0003131861290000045
The distribution function of the water molecule particle swarm at the current moment t and in the set direction d,
Figure FDA0003131861290000046
position derived from boundary conditions of specular reflection
Figure FDA0003131861290000047
Setting a distribution function of the water molecule particle swarm at the current time t and in the set direction d; c is a combination coefficient of the two or more,
Figure FDA0003131861290000048
lsfor the slip length, τ is the single relaxation time.
6. The method of claim 1, wherein the determining is based on a current
Figure FDA0003131861290000049
And
Figure FDA00031318612900000410
determining a force source term distribution function suffered by a water molecule particle swarm, specifically comprising:
according to the time step, the grid step, the weight coefficient and the current
Figure FDA00031318612900000411
And
Figure FDA00031318612900000412
determining the pulse density of the active nanoparticles corresponding to the water molecule particle group by using the formula (13)
Figure FDA00031318612900000413
Figure FDA00031318612900000414
In the formula (12), the first and second groups,
Figure FDA00031318612900000415
the current position of the water molecule particle swarm is taken as the current position of the water molecule particle swarm;
Figure FDA00031318612900000416
is the current position of the active nanoparticle i;
Figure FDA00031318612900000417
is a weight coefficient;
Figure FDA00031318612900000418
is the fluid force to which the active nanoparticles i are subjected in the aqueous phase,
Figure FDA00031318612900000419
Δ t is the time step; Δ r is the lattice step;
determining a force source term distribution function suffered by the water molecule particle swarm by utilizing a formula (13) according to the weight coefficient and the pulse density of the active nano particles corresponding to the water molecule particle swarm;
Figure FDA00031318612900000420
in the formula (13), the first and second groups,
Figure FDA00031318612900000421
is a force source term distribution function, omega, of the water molecule particle swarm in a set direction ddIs a weight coefficient in the d direction, is composed of
Figure FDA00031318612900000422
Interpolation is carried out to obtain; csIn order to be the pseudo-sound velocity,
Figure FDA00031318612900000423
Figure FDA00031318612900000424
is the unit direction vector of the d direction velocity component of the water molecule particle swarm.
7. The method according to claim 1, wherein the updating the flow rate of the water according to the distribution function of the current water molecule particle swarm and the received force source term distribution function specifically comprises:
according to the distribution function of the current water molecule particle swarm
Figure FDA00031318612900000425
The current water density is determined by equation (14):
Figure FDA0003131861290000051
in the formula (14), the reaction mixture,
Figure FDA0003131861290000052
is a position
Figure FDA0003131861290000053
The distribution function of the water molecule particle swarm at the current time t and in the speed dispersion direction d, wherein d is a serial number in the set speed dispersion direction, and Q is the total direction number of speed dispersion;
Figure FDA0003131861290000054
is a position
Figure FDA0003131861290000055
The current water density of (d);
according to the current density of water
Figure FDA0003131861290000056
Determining the equilibrium state distribution function of the current water molecule particle swarm through the formula (15)
Figure FDA0003131861290000057
Figure FDA0003131861290000058
In the formula (15), the first and second groups,
Figure FDA0003131861290000059
is a position
Figure FDA00031318612900000510
The equilibrium state distribution function of the current water molecule particle swarm in the speed discrete direction d; omegadA weight coefficient being a speed dispersion direction d; csIn order to be the pseudo-sound velocity,
Figure FDA00031318612900000511
Δ t is the time step; Δ r is the lattice step;
Figure FDA00031318612900000512
is the injection flow rate of water;
Figure FDA00031318612900000513
a unit direction vector of a d-direction velocity component of the water molecule particle swarm;
according to the distribution function of the current water molecule particle swarm
Figure FDA00031318612900000514
Distribution function of force source term
Figure FDA00031318612900000515
And equilibrium state distribution function
Figure FDA00031318612900000516
Determining the water molecule particle swarm distribution function at the next moment through the formula (16)
Figure FDA00031318612900000517
Figure FDA00031318612900000518
In equation (16), τ is the single relaxation time;
according to water molecule particle swarm distribution function
Figure FDA00031318612900000519
And equation (14) determining the density of water
Figure FDA00031318612900000520
The flow rate of water at the next time is determined by equation (17)
Figure FDA00031318612900000521
Figure FDA00031318612900000522
8. The method of claim 7, wherein updating the flow rate of the water according to a force source term distribution function to which the current population of water particles is subjected, further comprises:
according to the density of water
Figure FDA0003131861290000061
The water pressure at the next moment is determined by equation (18)
Figure FDA0003131861290000062
Figure FDA0003131861290000063
9. The method according to any one of claims 1 to 8, further comprising, after reaching the set condition:
and determining the limit attachment concentration and/or the dynamic equilibrium attachment process time of the active nanoparticles according to the judgment time and the judgment result of whether the active nanoparticles are attached to the wall surface of the pore throat.
10. An active nanoparticle and water two-phase flow simulation device, comprising:
an active nanoparticle parameter updating module for determining the electrostatic force between the active nanoparticles according to the radius, current position, flow rate of the active nanoparticles and the flow rate of water at the active nanoparticles by Langewan dynamics method
Figure FDA0003131861290000064
And van der Waals forces
Figure FDA0003131861290000065
And the friction force of the active nano-particles in the water phase
Figure FDA0003131861290000066
And random force
Figure FDA0003131861290000067
Determining the electrostatic force of the pore throat wall surface to the active nano-particles according to the radius and the current position of the active nano-particles
Figure FDA0003131861290000068
And van der Waals forces
Figure FDA0003131861290000069
Wherein i is the serial number of the active nano-particles, p represents the active nano-particles, and wall represents the wall surface of the pore throat; according to Newton's second law, the current position, flow rate, and the like of the active nanoparticles are used,
Figure FDA00031318612900000610
And
Figure FDA00031318612900000611
updating the flow rate and position of the active nanoparticles;
the judging module is used for judging whether the active nano particles are attached to the wall surface of the pore throat according to the current positions of the active nano particles;
the water phase fluid and active nano particle coupling module is used for judging whether the water phase fluid and active nano particle are in a negative state according to the current state
Figure FDA00031318612900000612
And
Figure FDA00031318612900000613
determining a force source term distribution function suffered by a water molecule particle swarm;
the attached suspension characterization module of the active nano particles is used for updating the current water molecule particle swarm distribution function according to the boundary conditions of rebound and specular reflection if the judgment module judges that the particle swarm distribution function is positive;
the water phase fluid parameter updating module is used for updating the flow velocity of water according to the distribution function of the current water molecule particle swarm and the received force source item distribution function by a lattice boltzmann method, and determining the flow velocity of water at the current active nano particle position by utilizing an interpolation method according to the flow velocity of the water;
and the active nanoparticle parameter updating module returns to execute the active nanoparticle parameter updating step until the set conditions are met.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116306186A (en) * 2023-03-03 2023-06-23 中国石油大学(华东) Active nanoparticle oil/water interface adsorption-diffusion behavior simulation method and device
CN117973272A (en) * 2024-04-02 2024-05-03 中国石油大学(华东) Prediction method for changing wettability of heterogeneous porous medium by nano fluid

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108509724A (en) * 2018-04-03 2018-09-07 嘉兴学院 A kind of method of multi-scale Simulation nano particle heterogeneous fluid characteristic

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108509724A (en) * 2018-04-03 2018-09-07 嘉兴学院 A kind of method of multi-scale Simulation nano particle heterogeneous fluid characteristic

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
周国峰等: "基于时驱硬球算法与格子玻尔兹曼方法的颗粒流体系统直接数值模拟", 《科学通报》 *
孙东科等: "格子玻尔兹曼方法模拟弯流道中粒子的惯性迁移行为", 《物理学报》 *
王思娴等: "水基纳米流体流动与换热数值模拟", 《能源工程》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116306186A (en) * 2023-03-03 2023-06-23 中国石油大学(华东) Active nanoparticle oil/water interface adsorption-diffusion behavior simulation method and device
CN116306186B (en) * 2023-03-03 2023-10-03 中国石油大学(华东) Active nanoparticle oil/water interface adsorption-diffusion behavior simulation method and device
CN117973272A (en) * 2024-04-02 2024-05-03 中国石油大学(华东) Prediction method for changing wettability of heterogeneous porous medium by nano fluid
CN117973272B (en) * 2024-04-02 2024-05-31 中国石油大学(华东) Prediction method for changing wettability of heterogeneous porous medium by nano fluid

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