CN113919242B - Particle migration damage hydrocarbon reservoir modeling method, damage degree spatial-temporal evolution 4D quantitative and intelligent diagnosis method and system - Google Patents
Particle migration damage hydrocarbon reservoir modeling method, damage degree spatial-temporal evolution 4D quantitative and intelligent diagnosis method and system Download PDFInfo
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Abstract
The invention discloses a modeling method for a particle migration damage hydrocarbon reservoir, a 4D quantitative and intelligent diagnosis method for damage degree spatial-temporal evolution and a system thereof, relates to the technical field of oil field exploration, and discloses a modeling method for a particle damage reservoir in a reservoir, a method for determining the damage degree of the reservoir and a system thereof. The modeling method comprises the following steps: determining a velocity of fluid in the reservoir; establishing a mass balance equation between the fluid and the sedimentary particulates on the rock in the reservoir based on the rate of change of mass of the migrating particulates; establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid; and determining a space-time evolution simulation equation of the particles in the reservoir damaging the reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the speed of the fluid, the mass balance equation and the connection condition equation. The method can quantitatively simulate the four-dimensional space-time evolution process of the reservoir damage characteristics caused by the particles in the reservoir, thereby carrying out reservoir damage quantitative prediction and damage rule space-time deduction on wells without reservoir damage.
Description
Technical Field
The invention relates to the technical field of oilfield exploration, in particular to a modeling method and a system for a particle-damaged reservoir in a reservoir and a method and a system for determining the damage degree of the reservoir.
Background
In each period of the exploration and development of the oil field, the original physical, chemical, thermodynamic and hydrodynamic equilibrium states of the reservoir are changed due to the influence of various internal and external factors, so that the internal permeability of the reservoir in a near well wall region and even a far well wall region of the reservoir is inevitably reduced, fluid flow is blocked, the reservoir is damaged, the yield of an oil well is reduced, and even the reservoir is killed. The reservoir damage is caused by various and complex reasons, particularly in the production process, the reservoir rock seepage storage space, the surface wettability, the hydrodynamic field, the temperature field, the rock type and the like are continuously changed, the damage mechanism is changed along with time, the damage period is long, the damage range is wide, and the damage is more complex and more superimposed. Once reservoir damage occurs, corresponding blockage removal measures must be taken to restore the fluid flow channels according to the reservoir damage condition so as to improve the oil well production and the water well injection capacity. Therefore, the reservoir damage to be deblocked is clearly determined by which factors are caused, how the damage factors occupy the proportion, and the space distribution rule and the time-varying rule of the reservoir damage are of great importance to the optimal design of the deblocking measures and directly influence the deblocking and yield increasing effects.
Currently, methods for diagnosing reservoir damage can be divided into mine field diagnostics and indoor evaluation. Wherein the mine site diagnostic method comprises a well testing method. While the well testing method can quantitatively give important parameters such as skin factor, plugging ratio, additional drawdown, etc., which characterize the extent of damage of the reservoir within the predetermined area of the well to be diagnosed, the skin factor characterized by it is correlated with other parameters. That is, the skin coefficient obtained by the well testing method does not only reflect the real reservoir damage characteristics, but also represents the comprehensive performance of each link and multiple factors (i.e. the skin coefficient is the sum of the real damage skin coefficient and a simulated skin coefficient composed of a well deviation skin coefficient, a reservoir shape skin coefficient, an open reservoir imperfect skin coefficient, a dawsie flow skin coefficient, a perforation skin coefficient and the like), and the real damage skin coefficient can be obtained only by performing skin coefficient decomposition. Wherein the indoor evaluation method comprises a core flow experiment method. The core flow experimental method is used for knowing the damage degree through the permeability change before and after core displacement, and is suitable for researching single-factor reservoir damage, but is difficult to reflect the reservoir damage rule on a larger scale. In addition, because the indoor core experiment conditions are more ideal, the core for evaluation is the original core, and the dynamic change of the reservoir property cannot be considered, the actual damage of the experiment result and the underground reservoir is larger.
Disclosure of Invention
The invention aims to provide a modeling method and a system for damaging a reservoir by particles in the reservoir and a method and a system for determining the degree of reservoir damage, which can quantitatively simulate the four-dimensional space-time evolution process of reservoir damage characteristics caused by the particles in the reservoir, thereby carrying out quantitative prediction of reservoir damage and space-time deduction of damage rules on wells without reservoir damage, having scientific guiding significance for preventing or avoiding reservoir damage, making development schemes of oil reservoirs and subsequent production increasing measures, and having great significance for optimally designing blockage removal measures for damaged wells, improving or recovering oil well yield and water injection capacity of water wells and improving numerical simulation precision of oil reservoirs.
In order to achieve the above object, a first aspect of the present invention provides a modeling method for a particle-damaged reservoir inside a reservoir, the modeling method comprising: determining a velocity of a fluid in a reservoir, wherein the reservoir is located within a preset region of a well to be diagnosed; establishing a mass balance equation between the fluid and sedimentary particulates on rock in the reservoir based on a convective parameter and a diffusive parameter of the fluid and a rate of mass change of migrating particulates, wherein there is a correlation between the rate of mass change of the migrating particulates and a velocity of the fluid; establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on the convection parameter and the diffusion parameter of the fluid; and determining a space-time evolution simulation equation of the reservoir internal particle damage reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the speed of the fluid, the mass balance equation and the connection condition equation, wherein the space-time evolution simulation equation is used for simulating a four-dimensional space-time evolution process of the reservoir damage characteristics caused by the particles.
Preferably, the correlation between the rate of change of mass of the migrating particles and the velocity of the fluid comprises: the rate of change of mass of the dislodged particles is greater than 0 where the velocity of the fluid is greater than a critical velocity.
Preferably, the critical speed is obtained by: establishing a moment balance equation of the deposited particles according to the stress condition of the deposited particles, wherein the stress condition of the deposited particles is related to the speed of the fluid; and determining the critical speed according to a moment balance equation of the deposited particles.
Preferably, the mass change rate of the migrating particles is obtained by: determining the intensity Q (r) of the release field of the deposited particles; determining a decay function Y (t) of the strength of the release field; and determining the rate of change of mass Q (r) of the moving particle from the intensity Q (r) of the release field and the decay function Y (t) of the intensity of the release field s ＝Q(r)Y(t)。
Preferably, said determining the velocity of fluid in the reservoir comprises: establishing a pressure conduction equation of the fluid into the reservoir; and determining the velocity of the fluid according to the pressure conduction equation and the Darcy formula.
Preferably, the establishing a mass balance equation between the fluid and the sedimentary particulates on the rock in the reservoir comprises: establishing the mass balance equation represented by the following formula based on the convection parameter and the diffusion parameter of the fluid,
wherein ρ is the density of the fluid; φ is the porosity of the reservoir;
is the mass fraction of the microparticles; u is the darcy apparent velocity;
in order to diffuse the flow rate of the fluid,
where ρ is L Is a seal of said fluidThe degree of the magnetic field is measured,
in order to be the diffusion coefficient,
alpha is the vertical diffusivity of the light,
is the velocity of the fluid;
is the accumulated mass of the deposited particles per unit time; t is time; and qs is the rate of change of mass of the migrating particles.
Preferably, the establishing of the connection condition equation between the volume concentration of the deposition particles and the volume concentration of the fluid includes: establishing the connection condition equation represented by the following formula based on the convection parameter and the diffusion parameter of the fluid,
where ρ is p Density of the deposited microparticles;
is the volume concentration of the deposited particles;
wherein k is 0 Is the original fluid loss coefficient, G 1 (C d ) Is and C d A related power law exponential function; and F 1 (T) is an exponential function related to temperature.
Preferably, the relationship between the mass fraction of the migrating particles and the volume concentration of the migrating particles is
Wherein ρ p Is the density of the deposited particles; rho L Is the density of the fluid;
is the mass fraction of the migrating particles; and
is the volume concentration of the migrating particles.
Preferably, the determining the spatiotemporal evolution simulation equation of the particle damaging the reservoir comprises: determining a spatiotemporal evolution simulation equation for the particulates damaging the reservoir represented by the following equation from the relationship between the mass fraction of the migrating particulates and the volume concentration of the migrating particulates, the velocity of the fluid, and the mass balance equation:
and
wherein the content of the first and second substances,
is the volume concentration of the migrating particles;
is the velocity of the fluid; τ is tortuosity of the reservoir; rho p Is the density of the deposited particulates; rho L Is the density of the fluid;
an initial value of a fluid loss coefficient for the reservoir,
is the volume concentration of the deposited particles, C dmax For the deposition ofMaximum volume concentration of microparticles, m k Is a first verified value; alpha is the vertical diffusivity; phi is the porosity of the reservoir; and qs is the rate of change of mass of the migrating particles.
Through the technical scheme, the mass balance equation between the fluid and the sedimentary particles on the rock in the reservoir is creatively established according to the convection parameter and the diffusion parameter of the fluid and the mass change rate of the migration particles; establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid according to the convection parameter and the diffusion parameter of the fluid; and determining a space-time modeling simulation equation of the particles in the reservoir damaging the reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the velocity of the fluid, the mass balance equation and the connection condition equation. Therefore, the four-dimensional space-time evolution process of the reservoir damage characteristics caused by the particles in the reservoir can be quantitatively simulated through the determined space-time evolution simulation equation, so that the reservoir damage quantitative prediction and the damage rule space-time deduction are carried out on the well without the reservoir damage, the scientific guiding significance is provided for preventing or avoiding the reservoir damage, formulating the development scheme of the reservoir and subsequent yield increasing measures, and the great significance is provided for optimally designing the deblocking measures of the damaged well, improving or recovering the yield of the oil well and the water injection capability of the water well, and improving the numerical simulation precision of the reservoir.
In a second aspect the present invention provides a method of determining the extent of reservoir damage, the method comprising: determining the volume concentration of the sedimentary particles based on a space-time evolution simulation equation established by the modeling method for damaging the reservoir by the particles in the reservoir; and determining a characteristic parameter characterizing the extent of damage of the reservoir within a predetermined region of the well to be diagnosed, based on the volume concentration of the sedimentary particulates.
Preferably, the characteristic parameter is permeability of the reservoir and/or fluid loss coefficient of the reservoir, and accordingly, the determining the characteristic parameter characterizing the damage degree of the reservoir in the preset area of the well to be diagnosed comprises: based on the volume concentration of the deposited particles
And formula
Determining permeability of the reservoir
And/or based on the volume concentration of the deposited particles
And the formula
Determining a fluid loss coefficient for the reservoir
Wherein phi is 0 Is an initial value of porosity; c dmax Is the maximum volume concentration of the deposited particles; m is k And m K Respectively a first empirical value and a second empirical value;
an initial value for the permeability of the reservoir; and
an initial value of a fluid loss coefficient for the reservoir.
Preferably, the characteristic parameter is a skin coefficient of the reservoir, and accordingly, the determining the characteristic parameter characterizing the damage degree of the reservoir in the preset area of the well to be diagnosed comprises: based on the volume concentration of the deposited microparticles
And formula
Determining permeability of the reservoir
And permeability based on said reservoir
And formula
Determining skin coefficients of the reservoir
Wherein, the first and the second end of the pipe are connected with each other,
is an initial value of the permeability of the reservoir,
r w the radius of the wellbore for the well to be diagnosed, and r sw Is the radius of damage to the reservoir.
Through the technical scheme, the volume concentration of the sediment particles can be determined through the determined space-time evolution simulation equation, and characteristic parameters (such as permeability and/or skin coefficient of the reservoir) for representing the damage degree of the reservoir in the preset area of the well to be diagnosed can be determined according to the volume concentration of the sediment particles, so that the four-dimensional space-time evolution process of the reservoir damage characteristic caused by the particles in the reservoir can be quantitatively simulated, the reservoir damage quantitative prediction and damage rule space-time deduction are carried out on the well without the reservoir damage, a scientific guiding significance is provided for preventing or avoiding the reservoir damage, developing schemes of the reservoir and subsequent yield increasing measures, and a significant significance is provided for optimally designing blockage removal measures, improving or recovering the oil well yield and the water injection capacity of the water well and improving the numerical simulation precision of the reservoir.
Accordingly, the third aspect of the present invention also provides a modeling system for a particulate-damaged reservoir inside the reservoir, the modeling system comprising: a velocity determination device for determining the velocity of fluid in a reservoir, wherein the reservoir is located within a preset region of a well to be diagnosed; first establishing means for establishing a mass balance equation between the fluid and sedimentary particulates on rocks in the reservoir based on a convection parameter and a diffusion parameter of the fluid and a rate of change of mass of migrating particulates within the fluid, wherein the rate of change of mass of the migrating particulates has a correlation with a velocity of the fluid; second establishing means for establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on a convection parameter and a diffusion parameter of the fluid; and simulation equation determining means for determining a space-time evolution simulation equation of the reservoir internal particle damage reservoir according to the relationship between the mass fraction of the migration particle and the volume concentration of the migration particle, the velocity of the fluid, the mass balance equation and the connection condition equation, wherein the space-time evolution simulation equation is used for simulating a four-dimensional space-time evolution process of the reservoir damage characteristic caused by the particle.
Compared with the prior art, the modeling system of the reservoir internal particle damage reservoir and the modeling method of the reservoir internal particle damage reservoir have the same advantages, and are not repeated herein.
Accordingly, the fourth aspect of the present invention also provides a system for determining the extent of reservoir damage, the system comprising: the concentration determining device is used for determining the volume concentration of the sedimentary particles based on a space-time evolution simulation equation established by the modeling system for the particle damage reservoir in the reservoir; and characteristic parameter determination means for determining, on the basis of the volume concentration of the sedimentary particulates, a characteristic parameter characterizing the degree of damage of the reservoir within a preset region of the well to be diagnosed.
The system for determining the degree of reservoir damage has the same advantages as the method for determining the degree of reservoir damage has over the prior art, and is not described herein again.
Accordingly, the fifth aspect of the present invention also provides a machine readable storage medium having stored thereon instructions for causing a machine to perform the method of modeling a particulate damage reservoir within a reservoir and/or the method of determining a degree of reservoir damage.
Additional features and advantages of embodiments of the present invention will be described in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments 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 embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 is a flow chart of a method for modeling a particulate-damaged reservoir within a reservoir, according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the force applied to the surface of the rock pore upon particle initiation;
FIG. 3 is a flow chart of a method of determining a degree of reservoir impairment as provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of the evolution of the skin coefficients over time according to an embodiment of the present invention;
FIG. 5 is a schematic representation of the radius of the reservoir damaged by internal particulate migration within the reservoir at day 40 as characterized by the reservoir permeability damage provided by an embodiment of the present invention;
FIG. 6 is a block diagram of a modeling system for a particulate-damaged reservoir within a reservoir provided by an embodiment of the present invention; and
fig. 7 is a block diagram of a system for determining a level of reservoir damage provided by an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
The essence of plugging by particulates within the reservoir (i.e., solid phase particles having a particle size less than a predetermined size, such as 37 microns) is migration and deposition of particulates within the reservoir. Thus, the core of the various embodiments of the present invention is to establish a kinetic model of migration and deposition of particulates within the reservoir. In particular, based on the mass conservation and diffusion relationshipWait for the creation of a spatiotemporal evolution control phenomenological model of the concentration distribution of the particles inside the reservoir in the reservoir surrounding the well to be diagnosed (this model contains the concentration C of the migrating particles and the concentration C of the sedimentary particles d ) And then, by combining the relation between reservoir damage characteristic parameters such as deposition concentration, permeability and the like, the space-time field distribution of the reservoir damage characteristic parameters such as permeability and the like can be diagnosed.
It should be noted that, for simplicity of description, the variables of the physical quantities and chemical quantities evolving over time in the various embodiments of the present invention may be omitted
For example, in
Can be abbreviated as phi w (ii) a And
may be abbreviated as K.
Fig. 1 is a flow chart of a method for modeling a particle-damaged reservoir inside a reservoir according to an embodiment of the present invention. The modeling method may include steps S101-S104.
In step S101, the velocity of the fluid in the reservoir is determined.
Wherein the reservoir is located in a predetermined area of a well to be diagnosed (e.g. a water injection well, a production well).
For step S101, the determining the velocity of the fluid in the reservoir may include: establishing a pressure conduction equation for the fluid into the reservoir; and determining the velocity of the fluid according to the pressure conduction equation and the Darcy formula.
Specifically, the pressure is the power driving the solid-liquid mixture (i.e. the fluid containing the migrating particles) to continuously invade the surrounding reservoir from the wellbore of the injection well, whereby the pressure conduction equation of the fluid into the reservoir can be established as in equation (1):
the velocity of the fluid can then be determined according to equation (1) and darcy's equation (2),
wherein the content of the first and second substances,
is the pressure of the fluid; φ is the porosity of the reservoir; μ is the fluid viscosity; c. C t The fluid-rock comprehensive compression coefficient;
is the permeability of the reservoir; and τ is tortuosity of the reservoir.
Step S102, establishing a mass balance equation between the fluid and the sedimentary particulates on the rock in the reservoir based on the convection parameter and the diffusion parameter of the fluid and the mass change rate of the migration particulates in the fluid.
Wherein there is a correlation between the rate of change of mass of the migrating particles and the velocity of the fluid. The process of obtaining the mass change rate of the migrating particles will be described in detail below.
In establishing the particle migration damage model, the critical speed of the fluid when the migration of the deposited particles is started is considered firstly, and then how the migration particles change the solid-liquid flow deposition equation is considered.
According to the particle start model, radius r s The stress condition of the elastic solid particles on the rough inner surface of the rock pores is shown in figure 2. The deposited particles are subjected to forces and moments under the scouring of the fluid and the interaction with the rock surface, and the critical velocity is the fluid velocity corresponding to the moment when the forces and moments are just balanced. The critical speed may be obtained by: establishing a moment balance equation of the deposited particles according to the stress condition of the deposited particles, wherein the stress condition of the deposited particles is related to the speed of the fluid; and according toAnd determining the critical speed by a moment balance equation of the deposited particles.
In particular, the deposited particles are subjected to a dragging force F in the same direction as the flow velocity v d Gravity F g Electrostatic force F e Lifting force F l . Due to drag force F d And lifting force F l Is a function of the flow velocity v, so that the corresponding flow velocity is the critical velocity v when the moments are balanced cr . Establishing a moment balance equation of the deposited particles shown in the following formula (3) according to the stress condition of the deposited particles:
F d ·l d ＝(F e -F l +F g )·l n ， (3)
the drag force F generated by the flow field near the rough inner surface of the rock pore on the deposited particles attached on the surface d Can be obtained by an asymptotic solution of the Navier-Stokes equation, which is expressed as follows:
F d ＝ωπμr s v cr ， (4)
wherein μ is the viscosity of the fluid, r s Is the radius of the deposited particle, v cr Is a distance from the surface r s The flow velocity, ω, is the drag coefficient (e.g., ω =6 × 1.7, especially if ω is 6, the drag force at this time corresponds to the drag force experienced by the solid phase particles in the free borderless flow).
Lifting force F of shear flow field to the deposited particles l Can be expressed as follows:
F l ＝χ[ρμ(r s v cr ) 3 ] 1/2 ， (5)
wherein ρ and μ are the density and viscosity of the fluid, respectively, and χ is the lift coefficient.
Gravity F of the deposited particles g Can be expressed as follows:
wherein g isAcceleration of gravity, ρ s Is the density of the deposited particles, and ρ is the density of the fluid.
In general, the electrostatic force F of the deposited particles e The magnitude of (d) is determined from the derivative of the electrostatic potential with respect to space:
where V (h) is the total electrostatic potential energy, it comprises three components: v LVA (London-Van der Waals potential), V DLR (electric double layer potential) and V BR (Bonn potential). That is, V (h) can be expressed as:
V＝V LVA +V DLR +V BR
V LVA and V DLR It can be derived from the well-known theory of DLVO:
V BR can be expressed as:
wherein, the first and the second end of the pipe are connected with each other,
h is the Hamaker constant, H is the distance separating the surface of the deposited particles from the surface of the medium (e.g., rock) ∈ 0 To deposit the dielectric constant of the particles, D e Electric double layer constant,/, for deposition of microparticles 01 、 ψ 02 Surface potential energy, σ, of sedimentary and rock skeleton particles, respectively LJ For atomic molecular interactions Lennard-Jones potential constant, κ is the length of the reverse Debye (i.e., its dimension is the length in degreesOne), the two parts are combined.
v cr And the flow velocity v of the fluid (true darcy velocity, v in the particle migration model) is related as follows:
in the formula, r c Is the average radius of the reservoir pore throat (i.e., the average radius of the pores). The joint type (4) and (8) can determine the relationship between the flow velocity v of the fluid and the surface particle dragging force of the fluid.
(Normal force F) n Of) arm of force l n About at normal force F n (F n ＝F e -F l +F g ) Radius of contact deformation surface of deposited micro-particles and substrate (such as rock) under action:
r s in order to initiate the radius of the particles (a portion of the deposited particles that begin to migrate under the scouring action of the fluid and merge into migrating particles in the fluid, where the portion of the particles become initiating particles), K is the composite young's modulus,
wherein E is 1 、E 2 Young's modulus, v, of the starting particles and matrix, respectively 1 、ν 2 Poisson's ratio for the starting particle and the matrix, respectively.
Once l is found n ，l d Can be determined by a simple geometric relationship:
the critical velocity v can be obtained by combining the above equations (3) to (10) cr It is represented as follows:
from the equation (11), the critical velocity v cr Related to the mechanical, physical, chemical properties of the deposited particles and the medium (e.g. rock). Only if the actual velocity of the fluid in the reservoir exceeds the critical velocity v cr The deposited particles are transported by the fluid to become the transported particles (or the source of the transported substance). 1. Typically, the closer the fluid flow rate is to the center of the well bore of the well being diagnosed, the particle migration zone should be a donut-shaped zone near the well bore.
According to the mass equation, let the mass change rate of the migrating particles (i.e., the amount of released particles) be q s Then q is s Has the following properties:
that is, only when the velocity of the fluid (which may also be referred to as the fluid flow rate) exceeds a critical velocity does the particles start and add to the fluid to participate in the migration, thereby increasing the mass of the fluid-solid mixture. Thus, for step S102, the establishing a mass balance equation between the fluid and the sedimentary particulates on the rock in the reservoir may comprise: establishing the mass balance equation represented by the following formula based on a convection parameter and a diffusion parameter of the fluid,
wherein ρ is the density of the fluid; φ is the porosity of the reservoir;
is the mass fraction (also referred to as mass concentration) of the deposited particles; u is the darcy apparent velocity;
in order to diffuse the flow rate of the fluid,
where ρ is L Is the density of the fluid in question,
in order to obtain the diffusion coefficient of the transported particles,
alpha is the vertical diffusivity of the light,
is the velocity of the fluid;
is the cumulative mass of the deposited particles per unit time; t is time; and q is s Is the rate of change of mass of the migrating particles.
Wherein the mass change rate q of the migration fine particles s The method comprises the following steps: determining the intensity Q (r) of the release field of the deposited particles; determining a decay function Y (t) of the strength of the release field; and determining the rate of change of mass Q (r) of the moving particle from the intensity Q (r) of the release field and the decay function Y (t) of the intensity of the release field s = Q (r) Y (t). In particular, the strength Q (r) of the release field may be a constant (Q) 0 ) The decay function Y (t) may be an exponential decay function (e.g., e) that varies with time -λt Where λ is the decay constant).
Step S103, establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on the convection parameter and the diffusion parameter of the fluid.
For step S103, the establishing of the connection condition equation between the volume concentration of the deposition particles and the volume concentration of the fluid may include: establishing the connection condition equation represented by the following formula (13) based on a convection parameter and a diffusion parameter of the fluid,
where ρ is p Is the density of the deposited particles;
is the volume concentration of the deposition particles;
wherein k is 0 In the form of the original fluid loss coefficient,
and F 1 (T) 
Due to F 1 The dependence of (T) on temperature is measured by exp (1/T), and in a common temperature range (e.g., 300K-400K), the change of the function is rather slow, actually approaching an isothermal process, so
Wherein
Is the volume concentration of the deposited particles, C dmax Is the maximum volume concentration of the deposited particles, and m k Is the first empirical value. All the parameters mentioned above can be either constant or spatially varying, i.e. non-homogeneous.
And S104, determining a space-time evolution simulation equation of the particles in the reservoir damaging the reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the velocity of the fluid, the mass balance equation and the connection condition equation.
Wherein the spatiotemporal evolution simulation equation is used to simulate a four-dimensional spatiotemporal evolution process of reservoir damage characteristics caused by particulates.
Wherein the relationship between the mass fraction of the migration fine particles and the volume concentration of the migration fine particles may be
Where ρ is p Is the density of the deposited particles; ρ is a unit of a gradient L Is the density of the fluid;
is the mass fraction of the migrating particles; and
is the volume concentration of the migrating particles. The spatiotemporal evolution simulation equation for the particulate damage reservoir may include: the simulation equation of spatiotemporal evolution of particle migration damaging the reservoir shown in equation (14), and the simulation equation of spatiotemporal evolution of particle deposition damaging the reservoir shown in equation (15).
For step S104, the determining the spatiotemporal evolution modeling equation of the particle-damaged reservoir may include: determining a spatiotemporal evolution simulation equation of the particle migration damage reservoir represented by the following formula (14) according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the velocity of the fluid and the mass balance equation represented by the formula (12):
and determining a space-time evolution simulation equation of the particle deposition damage reservoir shown by the formula (15) according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the speed of the fluid and the connection condition equation shown by the formula (13):
wherein the content of the first and second substances,
is the volume concentration of the migrating particles;
is the velocity of the fluid; τ is tortuosity of the reservoir; ρ is a unit of a gradient p Is the density of the deposited particles; rho L Is the density of the fluid;
an initial value of a fluid loss coefficient for the reservoir;
is the volume concentration of the deposited particles; c dmax Is the maximum volume concentration of the deposited particles; m is k Is a first empirical value; α is the vertical diffusivity; φ is the porosity of the reservoir; and qs is the rate of change of mass of the migrating particles. Wherein
Wherein N is R 、N P e、N A 、N DL 、N E1 、N E2 、N G 、N Lo 、N vdW ，、ζ p(g) The number of respective radii, the number of pick-offs, the number of attractors, the number of double layers, the number of first potential forces, the number of second potential forces, the number of gravities, the number of london forces, the number of van der waals forces, and the potential of migrating particles and matrix particles (i.e., particles deposited on the rock) (the relevant expressions for each parameter are detailed in table 1);
TABLE 1 dimensionless parameter Table containing solid phase deposition driving factors and expressions thereof
Note: d ∞ Is the free diffusivity of the migrating particles. H is Hamaker number. D p 、D g The diameter of the migrating particles and the diameter of the matrix particles, respectively. μ is the fluid viscosity. k is a radical of B Boltzmann constant. ζ represents a unit p 、 ζ g The potentials of the migrating microparticles and the matrix particles, respectively.
In conclusion, the invention creatively establishes a mass balance equation between the fluid and the sedimentary particulates on the rocks in the reservoir according to the convection parameter and the diffusion parameter of the fluid in the reservoir and the mass change rate of the migration particulates; establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid according to the convection parameter and the diffusion parameter of the fluid; and determining a space-time modeling simulation equation of the particles in the reservoir damaging the reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the speed of the fluid, the mass balance equation and the connection condition equation. Therefore, the four-dimensional space-time evolution process of the reservoir damage characteristics caused by particles in the reservoir can be quantitatively simulated through the determined space-time evolution simulation equation, so that reservoir damage quantitative prediction and damage rule space-time deduction are carried out on wells without reservoir damage, scientific guiding significance is provided for preventing or avoiding reservoir damage, formulating development schemes of oil reservoirs and subsequent yield increasing measures, and great significance is provided for optimally designing blockage removing measures for damaged wells, improving or recovering oil well yield and water well water injection capacity and improving numerical simulation precision of oil reservoirs.
Fig. 3 is a flow chart of a method for determining reservoir damage according to an embodiment of the present invention. As shown in fig. 3, the method of determining a reservoir impairment degree may comprise steps S301-S302.
Step S301, determining the volume concentration of the sedimentary particles based on a space-time evolution simulation equation established by the modeling method for the particle damage reservoir in the reservoir.
For the spatiotemporal evolution modeling equation for particle migration damage reservoir shown in equation (14) above, in the one-dimensional case, this type of equation can be organized into the following general form:
wherein, a a ,b b ,c c Either constant (e.g., diffusion coefficient) or a function (e.g., velocity of the fluid); f may be pressure, species concentration, stress, etc. Backward difference is used for time, and central difference is used for space. The above equation can have the following difference equation:
wherein i =1,2,3 i ，
n＝1,2,3...，t＝nΔt，N i The number of discrete spatial points.
Solving interval x belongs to (0, x) max )(x max Is the size of a preset area of the water injection well), deltax and deltat are space and time step lengths. At the same time, consider the initial condition f i n |n＝0＝f i 0 ，i＝1，2，3…，N i And boundary conditions (f) i n | i＝1 ＝f 0 N =1,2,3. (at the borehole wall) and
) (a virtual grid i +1 is constructed, at the boundary of the preset range or several meters from the well wall).
First, for i =2,3 i -1 arranging said differential format as:
wherein, A1 i ，A2 i ，A3 i Respectively, are as follows,
at the same time, a can be determined according to equation (14) i 、b i And c i 。
And will determine a i 、b i And c i The iterative relationship (18) is obtained by substituting the formula (19), and the iterative relationship (18) is not shown because its representation is complicated. Then, the value of the field f is obtained by performing an iterative calculation using the initial condition and the boundary condition.
Next, a difference solving process for explaining the boundary conditions will be explained.
The iterative relationship (18) described above applies to non-boundary meshes. For i =1 (at the borehole wall), since a point-centered grid is used, which is a Dirichlet (Dirichlet) boundary condition, the following relationship is directly obtained:
f 1 n ＝f 0 (constant), i =1 (20)
For i = N (several meters from the borehole wall at the boundary of the predetermined range), which is a noriman or second class (Neumann) boundary condition, add a virtual grid i = N i +1, from
To know that
This is substituted into equation (18) to find:
the space-time variation condition of the field function f can be solved according to the process. Due to the fact thatThe numerical model is established for a reservoir layer near a shaft of a well (water injection well) to be diagnosed, and a cylindrical coordinate system is required to be adopted when the distribution of a certain physical quantity f around the well is solved. Thus, formula
Need to be changed into
This form is not conducive to equidistant differentiation, and coordinate transformation can be introduced: r = r w e x′ Wherein r is w Is the wellbore radius, and x' is a dimensionless spatial coordinate. By substituting this transformation into a general equation, one can obtain an equation for x':
if it will be
And
as new equation coefficients, the above equation and
in contrast, it is essentially the same. Thus, equidistant differences in the x' coordinates can be made and the iterative format described above can be followed. After the value of f is calculated, the space coordinate is mapped back to r from x', and then f (r, t) can be obtained.
The volume concentration of the migration particles is calculated by the method
Then, the volume concentration of the deposited particles can be calculated according to the formula (15)
Thereby passing through the above-mentioned microThe space-time evolution simulation equation established by the particle damage reservoir modeling method comprehensively considers the influence of various physical and chemical factors on reservoir damage during the migration of the particles in the reservoir, so that the volume concentration of the deposited particles obtained by the solution in the step S301 is very accurate.
Step S302, determining characteristic parameters representing the damage degree of the reservoir in the preset area of the well to be diagnosed based on the volume concentration of the sedimentary particulates.
Wherein the characteristic parameter may be a permeability of the reservoir and/or a fluid loss coefficient of the reservoir.
In an embodiment, the characteristic parameter may be a permeability of the reservoir.
For step S302, the determining characteristic parameters characterizing the degree of impairment of the reservoir within the preset region of the well to be diagnosed may include: based on the volume concentration of the deposited particles
And equation (23) determining the permeability of the reservoir
In an embodiment, the characteristic parameter may be a permeability of the reservoir.
For step S302, the determining characteristic parameters characterizing the damage degree of the reservoir in the preset region of the well to be diagnosed may include: based on the volume concentration of the deposited particles
And equation (24) determining the fluid loss coefficient of the reservoir
Wherein phi is 0 Is an initial value of porosity; c dmax Is the maximum volume concentration of the deposited particles; m is a unit of k And m K Respectively a first empirical value and a second empirical value;
an initial value for the permeability of the reservoir; and
an initial value of a fluid loss coefficient for the reservoir.
Wherein the characteristic parameter may be an epidermal coefficient of the reservoir.
For step S302, the determining characteristic parameters characterizing the degree of impairment of the reservoir within the preset region of the well to be diagnosed may include: based on the volume concentration of the deposited particles
And formula
Determining permeability of the reservoir
And permeability based on the reservoir
And equation (25) determining the skin factor of the reservoir
Wherein the content of the first and second substances,
an initial value for the permeability of the reservoir; and
r w the radius of the wellbore for the well to be diagnosed, and r sw Is the radius of damage to the reservoir.
The characteristic parameter (e.g. permeability of the reservoir) obtained by this step S302
Coefficient of epidermis
) Is the result of a 4D quantitative simulation of spatio-temporal evolution (as shown in figure 4). More specifically, FIG. 5 shows the rate of damage by reservoir permeability (based on the permeability of the reservoir)
And formula
Determining the permeability impairment rate I (r) of the reservoir i T) in which
Is composed of
Maximum of) the radius at which the migration of particulates within the reservoir damaged the reservoir at day 40 (radius as indicated by the arrow), and the associated personnel can visually confirm the extent to which the reservoir was damaged through this figure 5. Therefore, quantitative prediction of reservoir damage and time-space deduction of damage rules can be carried out according to the evolution characteristics of permeability or skin coefficient, and the method has scientific guiding significance for preventing or avoiding reservoir damage, making a development scheme of an oil reservoir and then increasing production measures.
In conclusion, the volume concentration of the sedimentary particulates can be determined through the determined spatiotemporal evolution simulation equation, and then characteristic parameters (such as permeability and/or skin coefficient of the reservoir) representing the damage degree of the reservoir in the preset region of the well to be diagnosed can be determined according to the volume concentration of the sedimentary particulates, so that the four-dimensional spatiotemporal evolution process of the reservoir damage characteristic caused by the particulates in the reservoir can be quantitatively simulated, the reservoir damage is quantitatively predicted and the damage rule is temporally deduced for the well without reservoir damage, the scientific guidance significance is provided for preventing or avoiding the reservoir damage, formulating the development scheme and the subsequent yield increasing measures, and the significance is provided for optimally designing the blockage removing measures, improving or recovering the oil well yield and the water well water injection capacity and improving the numerical reservoir simulation precision.
Fig. 6 is a structural diagram of a modeling system for a particle damaged reservoir inside a reservoir according to an embodiment of the invention. As shown in fig. 6, the modeling system may include: a velocity determination means 10 for determining the velocity of a fluid in a reservoir, wherein the reservoir is located within a predetermined area of a well to be diagnosed; first establishing means 20 for establishing a mass balance course between the fluid and sedimentary particulates on rocks in the reservoir based on a convection parameter and a diffusion parameter of the fluid and a mass change rate of migrating particulates within the fluid, wherein the mass change rate of the migrating particulates has a correlation with a velocity of the fluid; second establishing means 30 for establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on a convection parameter and a diffusion parameter of the fluid; and simulation equation determining means 40 for determining a space-time evolution simulation equation of the reservoir internal particle damage reservoir according to the relationship between the mass fraction of the migration particles and the volume concentration of the migration particles, the velocity of the fluid, the mass balance equation and the connection condition equation, wherein the space-time evolution simulation equation is used for simulating a four-dimensional space-time evolution process of the reservoir damage characteristics caused by the particles.
Optionally, the correlation between the mass change rate of the migrating particles and the velocity of the fluid comprises: in the case where the velocity of the fluid is greater than the critical velocity, the rate of change of mass of the dislodged particles is greater than 0.
Optionally, the modeling system further includes: third establishing means (not shown) for establishing a moment equilibrium equation of the deposited particles according to the stress of the deposited particles, wherein the stress of the deposited particles is related to the velocity of the fluid; and a critical velocity determining means (not shown) for determining the critical velocity based on a moment balance equation of the deposited particles.
Optionally, the modeling system further includes: intensity determination means for determining the intensity Q (r) of the release field of the deposited particles; -attenuation function determining means for determining an attenuation function Y (t) of the strength of the release field; and mass change rate determining means for determining a mass change rate Q (r) of the migrating particles based on the intensity Q (r) of the release field and a decay function Y (t) of the intensity of the release field s ＝Q(r)Y(t)。
Optionally, the speed determination apparatus 10 includes: a pressure conduction equation building block (not shown) for pressure conduction equations of the fluid into the reservoir; and a velocity determination module (not shown) for determining a velocity of the fluid based on the pressure conduction equation and the darcy equation.
Compared with the prior art, the modeling system of the reservoir internal particle damage reservoir and the modeling method of the reservoir internal particle damage reservoir have the same advantages, and are not repeated herein.
Fig. 7 is a block diagram of a system for determining a level of reservoir damage provided by an embodiment of the present invention. As shown in fig. 7, the system may include: the concentration determining device 50 is used for determining the volume concentration of the sedimentary particles based on a space-time evolution simulation equation established by the modeling system of the reservoir damaged by the particles in the reservoir; and a characteristic parameter determination means 60 for determining a characteristic parameter characterizing the degree of damage of the reservoir within a predetermined area of the well to be diagnosed, based on the volume concentration of the sedimentary particulates.
Optionally, the characteristic parameter is permeability of the reservoirPermeability and/or fluid loss coefficient of the reservoir, the characteristic parameter determination means 60 accordingly comprising: a permeability calculation module (not shown) for calculating a permeability based on the volume concentration of the deposited particulates
And the formula
Determining the permeability of the reservoir
And/or a fluid loss coefficient calculation module (not shown) for calculating a fluid loss coefficient based on the volume concentration of the deposited particles
And the formula
Determining a fluid loss coefficient for the reservoir
Wherein phi is 0 Is an initial value of porosity; c dmax Is the maximum volume concentration of the deposited particles; m is k And m K Respectively a first empirical value and a second empirical value;
an initial value for the permeability of the reservoir; and
an initial value of a fluid loss coefficient for the reservoir.
Optionally, the characteristic parameter is a skin coefficient of the reservoir, and accordingly, the characteristic parameter determining device 60 includes: a permeability calculation module (not shown) for calculating a permeability based on a volume concentration of the deposited particles
And formula
Determining permeability of the reservoir
And a skin coefficient calculation module (not shown) for calculating a permeability of the reservoir based on the measured permeability
And formula
Determining skin coefficients of the reservoir
Wherein the content of the first and second substances,
is an initial value of the permeability of the reservoir, an
The system for determining the damage degree of the reservoir has the same advantages as the method for determining the damage degree of the reservoir has relative to the prior art, and the details are not repeated.
Accordingly, an embodiment of the present invention also provides a machine-readable storage medium having stored thereon instructions for causing a machine to perform the method for modeling a particulate damage reservoir within a reservoir and/or the method for determining a degree of reservoir damage.
The machine-readable storage medium includes, but is not limited to, phase Change Random Access Memory (PRAM, also known as RCM/PCRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash Memory (Flash Memory) or other Memory technology, compact disc read only Memory (CD-ROM), digital Versatile Disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, and the like, which can store program codes.
The steps S101 to S104 and the steps S301 to S302 can be executed by a computer, and the processing of various physicochemical quantities involved in the steps S101 to S104 realizes the simulation of the spatiotemporal evolution field of the particle deposition damage reservoir, and the processing of various physicochemical quantities involved in the steps S301 to S302 realizes the prediction of the spatiotemporal evolution of the particle deposition damage reservoir.
The preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, however, the present invention is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present invention within the technical idea of the present invention, and these simple modifications all fall within the protection scope of the present invention.
It should be noted that the various features described in the foregoing embodiments may be combined in any suitable manner without contradiction. The invention is not described in detail in order to avoid unnecessary repetition.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as the disclosure of the present invention as long as it does not depart from the spirit of the present invention.
Claims (14)
1. A method of modeling a particulate-damaged reservoir within a reservoir, the method comprising:
determining a velocity of a fluid in a reservoir, wherein the reservoir is located within a preset region of a well to be diagnosed;
establishing a mass balance equation between the fluid and sedimentary particulates on rock in the reservoir based on a convective parameter and a diffusive parameter of the fluid and a rate of change of mass of migrating particulates within the fluid, wherein the rate of change of mass of migrating particulates has a correlation with a velocity of the fluid;
establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on the convection parameter and the diffusion parameter of the fluid; and
determining a space-time evolution simulation equation of the reservoir internal particle damage reservoir according to the relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the speed of the fluid, the mass balance equation and the connection condition equation, wherein the space-time evolution simulation equation is used for simulating a four-dimensional space-time evolution process of the reservoir damage characteristics caused by the particles,
wherein the determining the spatiotemporal evolution modeling equation of the particle-damaged reservoir comprises:
determining a spatiotemporal evolution simulation equation of the particulates damaging the reservoir represented by the following equation from the relationship between the mass fraction of the migrating particulates and the volume concentration of the migrating particulates, the velocity of the fluid, and the mass balance equation:
wherein the content of the first and second substances,
is the volume concentration of the migrating particles;
is the velocity of the fluid; τ is tortuosity of the reservoir; rho p Is the density of the deposited particles; ρ is a unit of a gradient L Is the density of the fluid;
is the fluid loss coefficient of the reservoir in question,
an initial value of a fluid loss coefficient for the reservoir,
is the volume concentration of the deposited particles, C dmax Is the maximum volume concentration of the deposited particles, m k Is a first verified value; α is the vertical diffusivity; φ is the porosity of the reservoir; q. q of s Is the rate of change of mass of the migrating particles; and t is time.
2. A method of modeling a particulate-damaged reservoir within a reservoir as defined in claim 1, wherein the correlation between the rate of change of mass of migrating particulates and the velocity of the fluid comprises: in the case where the velocity of the fluid is greater than the critical velocity, the rate of change of mass of the dislodged particles is greater than 0.
3. The method of modeling a particulate-damaged reservoir within a reservoir as defined in claim 2, wherein the critical velocity is obtained by:
establishing a moment balance equation of the deposited particles according to the stress condition of the deposited particles, wherein the stress condition of the deposited particles is related to the speed of the fluid; and
and determining the critical speed according to a moment balance equation of the deposited particles.
4. The method of modeling a particulate-damaged reservoir within a reservoir of claim 2, wherein the mass rate of change of the migrating particulates is obtained by:
determining the intensity Q (r) of the release field of the deposited particles;
determining a decay function Y (t) of the strength of the release field; and
determining the rate of change of mass Q (r) of the migrating particles from the intensity Q (r) of the release field and the decay function Y (t) of the intensity of the release field s ＝Q(r)Y(t)。
5. The method of claim 1, wherein determining the velocity of the fluid in the reservoir comprises:
establishing a pressure conduction equation for the fluid into the reservoir; and
and determining the speed of the fluid according to the pressure conduction equation and the Darcy formula.
6. The method of modeling a particle-damaged reservoir within a reservoir of claim 1, wherein said establishing a mass balance equation between the fluid and sedimentary particles on rock in the reservoir comprises:
establishing the mass balance equation represented by the following formula based on a convection parameter and a diffusion parameter of the fluid,
wherein φ is the porosity of the reservoir;
is the mass fraction of the migrating particles; u is the darcy apparent velocity;
in order to diffuse the flow rate of the fluid,
where ρ is L Is the density of the fluid in question,
in order to be the diffusion coefficient,
alpha is the vertical diffusion rate of the light,
is the velocity of the fluid;
is the cumulative mass of the deposited particles per unit time; t is time; and q is s Is the rate of change of mass of the migrating particles.
7. A method of modeling a particle-damaged reservoir within a reservoir as defined in claim 1, wherein establishing a connection condition equation between the volume concentration of sedimentary particles and the volume concentration of fluid comprises:
establishing the connection condition equation represented by the following formula based on the convection parameter and the diffusion parameter of the fluid,
where ρ is p Density of the deposited particles;
is the volume concentration of the deposited particles;
wherein k is 0 Is the original fluid loss coefficient, G 1 (C d ) Is and C d A related power law exponential function; f 1 (T) is at an angle ofA degree-dependent exponential function;
in order to diffuse the flow rate of the fluid,
where ρ is L Is the density of the fluid in question,
in order to be the diffusion coefficient,
alpha is the vertical diffusivity of the light,
is the velocity of the fluid; u is the darcy apparent velocity; and t is time.
8. The method of modeling a particulate-damaged reservoir within a reservoir of claim 1, wherein the relationship between the mass fraction of migrating particulates and the volume concentration of the migrating particulates is
Where ρ is p Is the density of the deposited particles; ρ is a unit of a gradient L Is the density of the fluid;
is the mass fraction of the migrating particles;
is the volume concentration of the migrating particles; and t is time.
9. A method of determining the extent of reservoir damage, the method comprising:
determining the volume concentration of the sedimentary particulates based on a spatiotemporal evolution simulation equation established by the modeling method for the particle damage reservoir inside the reservoir according to any one of claims 1 to 8; and
determining a characteristic parameter characterizing the extent of damage of the reservoir within a predetermined region of the well to be diagnosed, based on the volume concentration of the sedimentary particulates.
10. A method of determining a degree of reservoir damage according to claim 9, wherein the characteristic parameter is the permeability of the reservoir and/or the fluid loss factor of the reservoir,
accordingly, the determining of the characteristic parameter characterizing the extent of damage of the reservoir within the preset zone of the well to be diagnosed comprises:
based on the volume concentration of the deposited particles
And the formula
Determining permeability of the reservoir
And/or
Based on the volume concentration of the deposited particles
And formula
Determining a fluid loss coefficient for the reservoir
Wherein phi 0 Is an initial value of porosity; c dmax Is the maximum volume concentration of the deposited particles; m is k And m K Respectively a first experience value and a second experience valueA value;
an initial value for the permeability of the reservoir;
is an initial value of a fluid loss coefficient for the reservoir; and t is time.
11. The method of determining a degree of reservoir damage of claim 9, wherein the characteristic parameter is a skin coefficient of the reservoir,
accordingly, the determining of the characteristic parameter characterizing the extent of damage of the reservoir within the preset zone of the well to be diagnosed comprises:
based on the volume concentration of the deposited particles
And formula
Determining permeability of the reservoir
And
permeability based on the reservoir
And formula
Determining skin coefficients of the reservoir
Wherein the content of the first and second substances,
is an initial value of the permeability of the reservoir,
r w is the wellbore radius of the well to be diagnosed, r sw Is the damage radius of the reservoir; phi is a unit of 0 Is an initial value of porosity; m is K Is a second empirical value; and t is time.
12. A modeling system for a particulate-damaged reservoir within a reservoir, the modeling system comprising:
a velocity determination device for determining the velocity of a fluid in a reservoir, wherein the reservoir is located within a preset region of a well to be diagnosed;
first establishing means for establishing a mass balance equation between the fluid and sedimentary particulates on rocks in the reservoir based on a convective parameter and a diffusive parameter of the fluid and a rate of change of mass of migrating particulates within the fluid, wherein the rate of change of mass of migrating particulates has a correlation with a velocity of the fluid;
second establishing means for establishing a connection condition equation between the volume concentration of the deposited particles and the volume concentration of the fluid based on a convection parameter and a diffusion parameter of the fluid; and
simulation equation determining means for determining a spatiotemporal evolution simulation equation of the particles inside the reservoir damaging the reservoir according to a relation between the mass fraction of the migration particles and the volume concentration of the migration particles, the velocity of the fluid, the mass balance equation and the connection condition equation, wherein the spatiotemporal evolution simulation equation is used for simulating a four-dimensional spatiotemporal evolution process of reservoir damage characteristics caused by the particles,
wherein the determining the spatiotemporal evolution modeling equation of the particle-damaged reservoir comprises:
determining a spatiotemporal evolution simulation equation of the particulates damaging the reservoir represented by the following equation from the relationship between the mass fraction of the migrating particulates and the volume concentration of the migrating particulates, the velocity of the fluid, and the mass balance equation:
wherein, the first and the second end of the pipe are connected with each other,
is the volume concentration of the migrating particles;
is the velocity of the fluid; τ is tortuosity of the reservoir; rho p Is the density of the deposited particles; rho L Is the density of the fluid;
is the fluid loss coefficient of the reservoir in question,
an initial value of a fluid loss coefficient for the reservoir,
is the volume concentration of the deposited particles, C dmax Is the maximum volume concentration of the deposited particles, m k Is a first verified value; alpha is the vertical diffusivity; φ is the porosity of the reservoir; q. q.s s Is the rate of change of mass of the migrating particles; and t is time.
13. A system for determining the extent of reservoir damage, the system comprising:
concentration determination means for determining the volume concentration of the sedimentary particulates based on the spatiotemporal evolution simulation equation established by the modeling system for particulate damage reservoirs within a reservoir as defined in claim 12; and
and the characteristic parameter determining device is used for determining a characteristic parameter for representing the damage degree of the reservoir in the preset area of the well to be diagnosed based on the volume concentration of the sedimentary particles.
14. A machine readable storage medium having stored thereon instructions for causing a machine to perform the method of modeling a reservoir for particulate damage within a reservoir as defined in any one of claims 1 to 8 above and/or the method of determining a degree of reservoir damage as defined in any one of claims 9 to 11 above.
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Inventor after: Jiang Guancheng Inventor after: Liang Xing Inventor after: Tan Bin Inventor after: Ran Qihua Inventor after: Liu Xiaobo Inventor after: Cheng Rongchao Inventor after: Quan Xiaohu Inventor after: Cui Kaixiao Inventor after: Cai Jun Inventor after: Zhu Honghao Inventor after: Li Yizheng Inventor after: He Kenbo Inventor after: Yang Lili Inventor after: Dong Tengfei Inventor after: Peng Chunyao Inventor after: Luo Xiaohu Inventor after: Luo Xuwu Inventor before: Jiang Guancheng Inventor before: Liang Xing Inventor before: Tan Bin Inventor before: Ran Qifa Inventor before: Liu Xiaobo Inventor before: Cheng Rongchao Inventor before: Quan Xiaohu Inventor before: Cui Kaixiao Inventor before: Cai Jun Inventor before: Zhu Honghao Inventor before: Li Yizheng Inventor before: He Kenbo Inventor before: Yang Lili Inventor before: Dong Tengfei Inventor before: Peng Chunyao Inventor before: Luo Xiaohu Inventor before: Luo Xuwu |
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