Disclosure of Invention
The invention aims to provide a modeling method and a system for a bacterial damage 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 bacteria, so that the quantitative prediction of reservoir damage and the space-time deduction of damage rules are carried out on wells without reservoir damage, the scientific guiding significance is provided for preventing or avoiding reservoir damage, making a development scheme of an oil reservoir and subsequent yield increasing measures, and the great significance is provided for optimally designing plugging removal measures for damaged wells, improving or recovering the yield of oil wells and the water injection capacity of water wells, and improving the numerical simulation precision of the oil reservoir.
In order to achieve the above object, a first aspect of the present invention provides a modeling method of a bacterial-damaged reservoir, the modeling method including: determining the growth rate of the bacteria according to the temperature distribution field of the reservoir in the preset area of the well to be diagnosed and the actual concentration of nutrients in the fluid in the reservoir; determining a total amount of bacteria on the rock surface in the reservoir from an amount of attachment of the bacteria on the rock surface, a growth rate and a decay rate of the bacteria associated with both an apparent concentration of the bacteria and the total amount of bacteria on the rock surface in the fluid; establishing an apparent concentration distribution equation of the bacteria in the fluid according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria and the attachment quantity of the bacteria on the rock surface in the reservoir; establishing an apparent concentration distribution equation of the nutrients according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the nutrients, the total amount of the bacteria on the rock surface and the apparent concentration of the bacteria; and determining a space-time evolution simulation equation of the reservoir damaged by the bacteria according to the apparent concentration distribution equation of the nutrients and the apparent concentration distribution equation of the bacteria in the fluid, 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 bacteria.
Preferably, said determining the growth rate of said bacteria comprises: determining the maximum growth rate of the bacteria according to the temperature distribution field of the reservoir and a maximum growth rate formula of the bacteria; and determining the growth rate of the bacteria based on the maximum growth rate of the bacteria and the actual concentration of the nutrient in the fluid.
Preferably, said determining the maximum growth rate of said bacteria comprises: according to the temperature distribution field of the reservoir
And determining the maximum growth rate of said bacteria by the following formula
Wherein, b
1、c
1Respectively a first experience parameter and a second experience parameter; t is
max、T
minThe maximum temperature and the minimum temperature for bacterial growth respectively; and said determining the growth rate of said bacteria comprises: according to the maximum growth rate of said bacteria
Actual concentration C of nutrients in the fluid
nuMono half growth coefficient k
SAnd determining the growth rate g of said bacterium
actual,
Preferably, said determining the total amount of said bacteria on said rock surface comprises: according to the attachment quantity C of the bacteria on the rock surface in the reservoir
depositionGrowth rate g of said bacterium
actualAnd rate of decay k
decayAnd determining the total amount V of said bacteria on said rock surface
bacteriatran,
Preferably, the establishing an apparent concentration distribution equation for the nutrient comprises: according to the Darcy apparent velocity u of the fluid and the diffusion coefficient D of the nutrient
nusumThe total amount V of said bacteria on said rock surface
bacteriatranAnd the apparent concentration C of the bacteria
bacteriatranEstablishing an apparent concentration distribution equation of the nutrient represented by the following formula,
wherein, g
actualIs the growth rate of the bacteria; y is the productivity coefficient of the bacterium; and C
nutranIs the apparent concentration profile of the nutrient.
Preferably, the establishing an apparent concentration distribution equation of bacteria in the fluid comprises:according to Darcy apparent velocity u of the fluid and diffusion coefficient D of the bacteria
sumGrowth rate g of said bacterium
actualAnd rate of decay k
decayAnd the amount of attachment C of said bacteria to the rock surface in said reservoir
depositionEstablishing an equation of apparent concentration distribution of bacteria in the fluid expressed by the following formula,
wherein, C
nutranIs the apparent concentration distribution of bacteria in the fluid.
Preferably, the modeling method further comprises: and determining the temperature distribution field of the reservoir according to the Darcy apparent velocity of the fluid, the thermal conductivity and thermal diffusivity of the fluid and the energy conservation theorem.
Through the technical scheme, the growth rate of the bacteria is creatively determined according to the temperature distribution field of the reservoir and the actual concentration of the nutrients in the fluid; determining the total amount of the bacteria on the rock surface in the reservoir according to the attachment amount of the bacteria on the rock surface, the growth rate and the decay rate of the bacteria; establishing an apparent concentration distribution equation of the bacteria in the fluid according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria and the attachment quantity of the bacteria on the rock surface in the reservoir; establishing an apparent concentration distribution equation of the nutrients according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the nutrients, the total amount of the bacteria on the rock surface and the apparent concentration of the bacteria; and determining a space-time evolution simulation equation of the bacteria damaging the reservoir according to the apparent concentration distribution equation of the nutrient and the apparent concentration distribution equation of the bacteria in the fluid. Therefore, the four-dimensional space-time evolution process of the reservoir damage characteristics caused by bacteria 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 a development scheme of an oil reservoir 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.
In a second aspect the present invention provides a method of determining the extent of reservoir damage, the method comprising: determining the attachment amount of the bacteria on the rock surface based on a space-time evolution simulation equation established according to the modeling method of the bacteria damaged reservoir; and determining a characteristic parameter characterizing the extent of damage of the reservoir within a preset region of the well to be diagnosed, based on the amount of adhesion of said bacteria on the rock surface.
Preferably, the characteristic parameter is the permeability 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 amount of attachment C of the bacteria on the rock surface in the reservoir
depositionDetermining the permeability of the reservoir from the density of the bacteria, rho, and the formula
Determining permeability of the reservoir
Wherein phi is
0Is an initial value of the porosity of the reservoir; and
is an initial value of the permeability of 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 apparent concentration of nutrients in the fluid
To the actual concentration
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
wthe radius of the wellbore for the well to be diagnosed, and r
swIs the radius of damage to the reservoir.
By the technical scheme, the apparent concentration of the nutrient in the fluid can be determined through the determined space-time evolution simulation equation, and then the actual concentration of the nutrient in the fluid is determined based on the apparent concentration and the actual concentration, characteristic parameters (such as permeability and/or epidermal coefficient of the reservoir) characterizing the extent of damage of the reservoir within a preset region of the well to be diagnosed can be determined, whereby the four-dimensional spatiotemporal evolution process of the reservoir damage characteristics caused by bacteria can be quantitatively simulated, thereby carrying out quantitative prediction of reservoir damage and time-space 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 increasing production measures afterwards, and has great significance for optimizing design plugging removal measures of damaged wells, improving or recovering oil well yield and water well water injection capacity and improving numerical simulation precision of oil reservoirs.
Accordingly, the third aspect of the present invention also provides a modeling system for a bacterial-damage reservoir, the modeling system comprising: a growth rate determining means for determining the growth rate of the bacteria according to the temperature distribution field of the reservoir within a preset region of the well to be diagnosed and the actual concentration of nutrients in the fluid in the reservoir; total amount determination means for determining the total amount of bacteria on the rock surface in the reservoir from the amount of attachment of the bacteria to the rock surface, the rate of growth and the rate of decay of the bacteria associated with both the apparent concentration of bacteria in the fluid and the total amount of bacteria on the rock surface; first establishing means for establishing an apparent concentration distribution equation of bacteria in the fluid based on the darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria, and the attachment amount of the bacteria on the rock surface in the reservoir; second establishing means for establishing an apparent concentration distribution equation of the nutrient according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the nutrient, the total amount of the bacteria on the rock surface, and the apparent concentration of the bacteria; and simulation equation determining means for determining a space-time evolution simulation equation of the reservoir damaged by the bacteria according to the apparent concentration distribution equation of the nutrients and the apparent concentration distribution equation of the bacteria in the fluid, 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 bacteria.
Compared with the prior art, the modeling system of the bacterial damage reservoir has the same advantages as the modeling method of the bacterial damage reservoir, and the detailed description is omitted.
Accordingly, the fourth aspect of the present invention also provides a system for determining the extent of reservoir damage, the system comprising: concentration determination means for determining the amount of attachment of said bacteria to said rock surface based on a spatiotemporal evolution simulation equation established from said modeling system of said bacterial damage reservoir; and characteristic parameter determination means for determining a characteristic parameter characterizing the extent of damage of the reservoir within a preset region of the well to be diagnosed, based on the amount of adhesion of said bacteria on the rock surface.
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 bacterial damage reservoir and/or the method of determining a degree of reservoir damage.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
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 the present invention, are given by way of illustration and explanation only, not limitation.
The metabolism of bacteria is controlled by the catalytic action of various enzymes in their cells, and the activity of enzymes is extremely sensitive to temperature, e.g., too high or too low a temperature inactivates the enzymes in the cells. In the water injection process, a temperature change interval is formed between the inside of the well and the reservoir, the bacterial metabolism rate is seriously influenced, bacteria are attached to the surface of rock to form a biological membrane, and therefore the porosity of the reservoir is reduced. Thus, the core of the various embodiments of the present invention is to establish a changing relationship between the apparent concentration distribution equation of the nutrients in the fluid inside the reservoir and the temperature and a changing relationship between the apparent concentration distribution equation of the bacteria in the fluid and the temperature. Specifically, a spatiotemporal evolution control phenomenological model of the concentration distribution of nutrients and bacteria in the fluid in the reservoir around the well to be diagnosed is established based on the energy conservation, the mass conservation, the diffusion relation and the like, and the spatiotemporal field distribution of the reservoir damage characteristic parameters such as the permeability and the like can be diagnosed by combining the relation between the reservoir damage characteristic parameters such as the concentration distribution and the permeability.
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
Can be abbreviated as r
0(ii) a And
may be abbreviated as T.
Fig. 1 is a flow chart of a modeling method for a bacterial damage reservoir according to an embodiment of the present invention. The modeling method may include steps S101-S105.
Before performing step S101, the modeling method further includes: determining a darcy superficial velocity of a fluid in a reservoir within a preset region of a well to be diagnosed.
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 a darcy apparent velocity of the fluid according to the pressure conduction equation and a darcy formula.
In particular, the pressure is the power driving the solid-liquid mixture (i.e. the fluid containing the bacteria and nutrients) from the wellbore of the water injection well into the reservoir surrounding the well to be diagnosed (e.g. the water injection well), whereby the pressure conduction equation of the fluid into the reservoir can be established as in equation (1):
the Darcy apparent velocity of the fluid can be determined according to the formula (1) and the Darcy formula (2),
wherein the content of the first and second substances,
is the pressure of the fluid; phi is a
0Is an initial value of the porosity of the reservoir; μ is the fluid viscosity; c. C
tFor fluid-rock combined compression factor and
is the permeability of the reservoir.
Before performing step S101, the modeling method further includes: and determining the temperature distribution field of the reservoir according to the Darcy apparent velocity of the fluid, the thermal conductivity and thermal diffusivity of the fluid and the energy conservation theorem.
During waterflooding, energy is transferred between reservoir rock and fluid in the form of temperature changes due to the temperature difference between the injected water temperature and the reservoir temperature. In this case, the apparent velocity of the fluid in the reservoir within a predetermined zone of the well to be diagnosed may be determined according to the Darcy's apparent velocity
Thermal conductivity D of the fluid
conAnd thermal diffusivity of D
disEstablishing a mathematical model of temperature distribution of a reservoir stratum with a size of a mine field according to the law of conservation of energy to obtainTo reservoir temperature distribution control equation expression:
wherein the content of the first and second substances,
is the reservoir temperature profile; the thermal diffusivity may be expressed in terms of thermal conductivity.
Step S101, determining the growth rate of the bacteria according to the temperature distribution field of the reservoir and the actual concentration of the nutrients in the fluid.
For step S101, the determining the growth rate of the bacteria (including bacteria attached to the rock surface and bacteria in the fluid) may include the following steps S201-S202, as shown in fig. 2.
Step S201, determining the maximum growth rate of the bacteria according to the temperature distribution field of the reservoir and a maximum growth rate formula of the bacteria.
At present, a square root model containing parameters such as activation energy, frequency factor and the like is generally adopted to describe the maximum growth rate of bacteria, but the field applicability of the model is poor (mainly shown as inaccurate prediction results). However, the inventors have conducted extensive studies to find that the temperature of the reservoir is a major factor affecting the maximum growth rate of bacteria and the distribution of bacteria in the reservoir. Therefore, under the condition that the water injection source and the bacterial nutrient source are sufficient, the embodiment adopts the maximum growth rate formula of the bacteria with the temperature as the main variable (including the bacteria attached to the rock surface and the bacteria in the fluid) to simulate the spatial distribution condition of the maximum growth rate of the bacteria in the reservoir.
For step S201, the determining the maximum growth rate of the bacteria comprises: according to the temperature distribution field of the reservoir
And determining the maximum growth rate of the bacteria by the following formula (4)
Wherein, b1、c1Respectively a first bacterial growth experience parameter and a second bacterial growth experience parameter; t ismax、TminThe maximum temperature and the minimum temperature for bacterial growth respectively;
step S202, determining the growth rate of the bacteria according to the maximum growth rate of the bacteria and the actual concentration of the nutrients in the fluid.
Considering that the bacteria grow as an irreversible first order reaction or that the bacteria metabolize to consume nutrients, for step S202, the determining the growth rate of the bacteria comprises: according to the maximum growth rate of said bacteria
Actual concentration C of nutrients in the fluid
nuMono half growth coefficient k
SAnd the following formula (5), determining the growth rate g of the bacterium
actual,
Step S102, determining the total amount of bacteria on the rock surface in the reservoir according to the attachment amount of the bacteria on the rock surface, the growth rate and the decay rate of the bacteria, which are associated with both the apparent concentration of the bacteria in the fluid and the total amount of the bacteria on the rock surface.
Specifically, the main factors influencing the attachment amount of bacteria on the rock surface are the adsorption and desorption rates of the bacteria, and the bacteria attached to the rock surface of the reservoir form a biofilm, so that the plugging rate k can be determined according toclogging(it is a constant, and the unit can be 1/day), the deblocking rate kdeclogging(which is a constant and may be in 1/day), the apparent concentration C of bacteria in the fluidbacteriatranThe total amount V of said bacteria on said rock surfacebacteriatranAnd the following formula (6), determining the attachment quantity C of the bacteria on the rock surface in the reservoirdeposition,
Cdeposition=kcloggingCbacteriatran-kdecloggingVbacteriatran。 (6)
Bacteria attached to the rock surface can form biofilms, thereby reducing the porosity of the reservoir. In this embodiment, the amount of bacteria on the rock surface is mainly determined by two factors, i.e., the growth of bacteria, net increase of decay and attachment amount.
For step S102, the determining the total amount of bacteria on the rock surface may comprise: according to the attachment quantity C of the bacteria on the rock surface in the reservoirdepositionGrowth rate g of said bacteriumactualAnd rate of decay kdecayAnd determining the total amount V of said bacteria on said rock surfacebacteriatran,
The left side of the above (7) describes the change of the total amount of bacteria on the rock surface with time, and the right side is the value of the total growth of metabolic decay and bacterial deposition on the rock surface.
Step S103, establishing an apparent concentration distribution equation of the bacteria in the fluid according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria and the attachment amount of the bacteria on the rock surface in the reservoir.
In this embodiment, the diffusion of bacteria due to concentration gradient, the convection migration of bacteria due to water injection, and the growth and decay of bacteria are mainly considered, and the first four factors cause the change of the concentration of bacteria (including the reduction of the concentration due to the attachment of bacteria to the reservoir rock to form a biofilm). Because the macroscopic action effect of the irregular movement of the vibration of the bacterial flagella in the reservoir is not obvious, the irregular movement effect generated by the vibration of the flagella is combined into a convection term in the model; while the bacterial brownian motion is covered by bacterial diffusion. In addition, since the bacteria chemotaxis has a small influence on the bacteria distribution law in the reservoir, the influence is covered by the convection effect, and the convection effect and the convection item are combined into one item.
For step S103, the establishing an apparent concentration distribution equation of bacteria in the fluid may include: according to Darcy apparent velocity u of the fluid and diffusion coefficient D of the bacteriasumGrowth rate g of said bacteriumactualAnd rate of decay kdecayAnd the amount of attachment C of said bacteria to the rock surface in said reservoirdepositionEstablishing an apparent concentration distribution equation of bacteria in the fluid represented by the following formula (8),
wherein, C
nutranIs the apparent concentration distribution of bacteria in the fluid. The one-dimensional form of the above formula (8) can be written as
And step S104, establishing an apparent concentration distribution equation of the nutrients according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the nutrients, the total amount of the bacteria on the rock surface and the apparent concentration of the bacteria.
In this embodiment, the diffusion of nutrients due to the concentration gradient and the convection transport of nutrients due to the injection of water are mainly considered, and the two factors cause the variation of the concentration of nutrients.
For step S104, the establishing an apparent concentration distribution equation for the nutrient may include: according to Darcy's apparent velocity of the fluid
Diffusion coefficient D of the nutrient
nusumThe total amount V of said bacteria on said rock surface
bacteriatranAnd the apparent concentration C of the bacteria
bacteriatranEstablishing an apparent concentration distribution equation of the nutrient represented by the following formula (9),
wherein, g
actualIs the growth rate of the bacteria; y is the productivity coefficient of the bacterium; and C
nutranIs the apparent concentration profile of the nutrient. The one-dimensional form of the above formula (9) can be written as
And S105, determining a space-time evolution simulation equation of the bacteria damage reservoir according to the apparent concentration distribution equation of the nutrients and the apparent concentration distribution equation of the bacteria in the fluid.
Wherein the spatiotemporal evolution simulation equation is used to simulate a four-dimensional spatiotemporal evolution process of reservoir damage characteristics caused by bacteria.
Specifically, from the apparent concentration distribution equation of the nutrient represented by the above formula (9) and the apparent concentration distribution equation of the bacteria in the fluid represented by the above formula (8), in combination with other formulas (1) to (7), a space-time evolution simulation equation of the bacteria-damaged reservoir can be obtained. That is, the simulation equation of the spatiotemporal evolution of the bacteria-damaged reservoir corresponds to the equation set consisting of equations (1) to (9).
In summary, the present invention inventively determines the growth rate of the bacteria based on the temperature profile of the reservoir and the actual concentration of nutrients in the fluid; determining the total amount of the bacteria on the rock surface in the reservoir according to the attachment amount of the bacteria on the rock surface, the growth rate and the decay rate of the bacteria; establishing an apparent concentration distribution equation of the bacteria in the fluid according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria and the attachment quantity of the bacteria on the rock surface in the reservoir; establishing an apparent concentration distribution equation of the nutrients according to the Darcy apparent velocity of the fluid, the diffusion coefficient of the nutrients, the total amount of the bacteria on the rock surface and the apparent concentration of the bacteria; and determining a space-time evolution simulation equation of the bacteria damaging the reservoir according to the apparent concentration distribution equation of the nutrient and the apparent concentration distribution equation of the bacteria in the fluid. Therefore, the four-dimensional space-time evolution process of the reservoir damage characteristics caused by bacteria 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 a development scheme of an oil reservoir 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 a reservoir damage level according to an embodiment of the present invention. As shown in fig. 3, the method comprises steps S301-S302.
Step S301, determining the attachment amount of the bacteria on the rock surface based on a space-time evolution simulation equation established by the modeling method of the bacteria damage reservoir.
For the equations of the spatiotemporal evolution simulation of the bacterial-damaged reservoir shown in equations (8) - (9) above, in the one-dimensional case, such equations can be organized into the following general form:
wherein, aa,bb,ccEither 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 may haveThe following differential format:
wherein i ═ 1,2,3
i,
n=1,2,3...,t=nΔt,N
iIs the number of discrete spatial points.
Solving interval of x ∈ (0, x)
max)(x
maxIs the size of a preset area of the water injection well), and deltax and deltat are space and time step lengths. At the same time, the initial condition f is considered
i n|
n=0=f
i 0,i=1,2,3...,N
iAnd boundary conditions (f)
i n|
i=1=f
0N-1, 2,3. (at the borehole wall) and
n 1,2, 3.) (a virtual grid i +1 is constructed, at the boundary of the preset range or a few meters from the borehole wall).
First, for i ═ 2,3i-1 arranging said differential format as:
wherein, A1i,A2i,A3iRespectively, are as follows,
meanwhile, a can be determined according to the formulas (8) to (9)i、biAnd ci。
And will determine ai、biAnd ciSubstituting equation (13) can obtain the concrete expression of the iterative relation (12), because the concrete expression of the iterative relation (12) is complexTherefore, it is not listed here. 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 (12) described above applies to non-boundary meshes. For i ═ 1 (at the borehole wall), since a point-centered grid is used, and it is a Dirichlet (Dirichlet) boundary condition, the following relationship is directly obtained:
f1 n=f0(constant), i ═ 1 (14)
For i-N (several meters from the borehole wall at the boundary of the preset range), which is a boundary condition of niemann or the second kind (Neumann), a virtual grid i-N is added
i+1, from
1,2,3
This is substituted into formula (12) to find:
the space-time variation condition of the field function f can be solved according to the process. Because the numerical model is established for the reservoir near the shaft of the well (water injection well) to be diagnosed, a cylindrical coordinate system is needed 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
we
x′Wherein r is
wIs the wellbore radius, and x' is a dimensionless spatial coordinate. By substituting this transformation into a general equationTo obtain the equation for x':
if it will be
And
as new equation coefficients, the above equations 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 amount of the bacteria attached C was calculated by the above methoddepositionTherefore, the spatiotemporal evolution simulation equation established by the modeling method for the bacterial damage reservoir comprehensively considers the influence of various physicochemical factors on the reservoir damage when the bacteria and the nutrients move in the fluid, and the attachment (i.e. deposition) quantity of the bacteria obtained by the solving of 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 attachment amount of the bacteria on the rock surface.
Wherein the characteristic parameter is the 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 includes: based on the amount of attachment C of the bacteria on the rock surface in the reservoir
depositionDetermining the permeability of the reservoir from the density of the bacteria, rho (17) below
Wherein phi is
0Is an initial value of the porosity of the reservoir; and
is an initial value of the permeability of the reservoir.
Wherein the characteristic parameter is the skin coefficient 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 includes: based on the apparent concentration of nutrients in the fluid
To the actual concentration
And formula
Determining permeability of the reservoir
And permeability based on the reservoir
And the following formula (18), determining the skin factor of the reservoir
Wherein the content of the first and second substances,
is the reservoirIs measured in the direction of the initial value of the permeability,
r
wthe radius of the wellbore for the well to be diagnosed, and r
swIs 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 the spatio-temporal evolution (not shown). 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, formulating a development scheme of an oil reservoir and then increasing production measures.
In conclusion, the apparent concentration of the nutrient in the fluid can be determined through the determined space-time evolution simulation equation, and then based on the apparent concentration and the actual concentration of the nutrient in the fluid, characteristic parameters (such as permeability and/or epidermal coefficient of the reservoir) characterizing the extent of damage of the reservoir within a preset region of the well to be diagnosed can be determined, whereby the four-dimensional spatiotemporal evolution process of the reservoir damage characteristics caused by bacteria can be quantitatively simulated, thereby carrying out quantitative prediction of reservoir damage and time-space 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 increasing production measures afterwards, and has great significance for optimizing design plugging removal measures of damaged wells, improving or recovering oil well yield and water well water injection capacity and improving numerical simulation precision of oil reservoirs.
Fig. 4 is a block diagram of a modeling system for a bacterial damage reservoir according to an embodiment of the present invention. As shown in fig. 4, the modeling system includes: a growth rate determining means 10 for determining the growth rate of said bacteria according to the temperature distribution field of the reservoir within a preset area of the well to be diagnosed and the actual concentration of nutrients in the fluid in said reservoir; total amount determination means 20 for determining the total amount of bacteria on the rock surface in the reservoir from the amount of attachment of the bacteria to the rock surface, the rate of growth and the rate of decay of the bacteria associated with both the apparent concentration of bacteria in the fluid and the total amount of bacteria on the rock surface; first establishing means 30 for establishing an apparent concentration distribution equation of bacteria in the fluid based on the darcy apparent velocity of the fluid, the diffusion coefficient of the bacteria, the growth rate and the decay rate of the bacteria, and the attachment amount of the bacteria on the rock surface in the reservoir; second establishing means 40 for establishing an apparent concentration distribution equation of the nutrient based on the darcy apparent velocity of the fluid, the diffusion coefficient of the nutrient, the total amount of the bacteria on the rock surface, and the apparent concentration of the bacteria; and simulation equation determination means 50 for determining a simulation equation of spatiotemporal evolution of the bacterial damage reservoir based on the apparent concentration distribution equation of the nutrient and the apparent concentration distribution equation of the bacteria in the fluid, wherein the simulation equation of spatiotemporal evolution is used for simulating a four-dimensional process of spatiotemporal evolution of the reservoir damage characteristics caused by the bacteria.
Preferably, the growth rate determining apparatus 10 includes: the maximum growth rate determining module is used for determining the maximum growth rate of the bacteria according to the temperature distribution field of the reservoir and a bacteria maximum growth rate formula; and a growth rate determination module for determining the growth rate of the bacteria based on the maximum growth rate of the bacteria and the actual concentration of the nutrients in the fluid.
Preferably, the modeling system further comprises: the temperature determining device is used for determining the temperature distribution field of the reservoir according to the Darcy apparent velocity of the fluid in the reservoir, the thermal conductivity and thermal diffusivity of the fluid and the energy conservation theorem;
compared with the prior art, the modeling system of the bacterial damage reservoir has the same advantages as the modeling method of the bacterial damage reservoir, and the detailed description is omitted.
Fig. 5 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. 5, the system includes: concentration determination means 60 for determining the amount of attachment of said bacteria to said rock surface based on a spatiotemporal evolution simulation equation established from said modeling system of said bacteria-damaged reservoir; and characteristic parameter determination means 70 for determining a characteristic parameter characterizing the extent of damage of the reservoir within a preset zone of the well to be diagnosed, based on the amount of adhesion of said bacteria on the rock surface.
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, 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 bacterial damage 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 various media capable of storing program code.
The steps S101 to S105, the steps S201 to S202 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 S105 realizes simulation of a spatial-temporal evolution field of the reservoir damaged by bacteria, the processing of various physicochemical quantities involved in the steps S201 to S202 realizes simulation of a growth rate of bacteria, and the processing of various physicochemical quantities involved in the steps S301 to S302 realizes prediction of spatial-temporal evolution of the reservoir damaged by bacteria.
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 can be made to the technical solution of the present invention within the technical idea of the present invention, and these simple modifications are within the protective scope of the present invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. 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.