CN113671596B - Bacterial damage hydrocarbon reservoir modeling method, damage degree spatial-temporal evolution 4D quantitative and intelligent diagnosis method and system - Google Patents

Bacterial damage hydrocarbon reservoir modeling method, damage degree spatial-temporal evolution 4D quantitative and intelligent diagnosis method and system Download PDF

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CN113671596B
CN113671596B CN202110991127.4A CN202110991127A CN113671596B CN 113671596 B CN113671596 B CN 113671596B CN 202110991127 A CN202110991127 A CN 202110991127A CN 113671596 B CN113671596 B CN 113671596B
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蒋官澄
朱鸿昊
李奕政
贺垠博
杨丽丽
董腾飞
彭春耀
骆小虎
罗绪武
梁兴
谭宾
冉启发
刘小波
程荣超
全晓虎
崔凯潇
蔡军
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Abstract

The invention relates to the technical field of oil field exploration, and discloses a modeling method for a bacterial damage reservoir, a method for determining the damage degree of the reservoir and a system thereof. The modeling method comprises the following steps: determining the growth rate of bacteria according to the temperature distribution field of a reservoir in a preset area of a well to be diagnosed; determining the total amount of bacteria on the rock surface of a reservoir according to the attachment amount of the bacteria on the rock surface of the reservoir, the growth rate and the decay rate of the bacteria; establishing an apparent concentration distribution equation of bacteria in the fluid; establishing an apparent concentration distribution equation of the nutrient; 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. The invention can quantitatively simulate the four-dimensional space-time evolution process of reservoir damage characteristics caused by bacteria, thereby carrying out reservoir damage quantitative prediction and damage rule space-time deduction on wells without reservoir damage.

Description

Bacterial damage hydrocarbon reservoir modeling method, damage degree spatial-temporal evolution 4D quantitative and intelligent diagnosis method and system
Technical Field
The invention relates to the technical field of oil field exploration, in particular to a modeling method and a system for a bacterial damage reservoir and a method and a system for determining the degree of reservoir damage.
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 yield and the water well injection capacity. Therefore, the factors causing the reservoir damage of the well to be unplugged, the proportion of each damage factor, the spatial distribution rule of the reservoir damage and the time-varying rule are important for the optimal design of the unplugging measures, and the unplugging and yield increasing effects are directly influenced.
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 a skin factor, a plugging ratio, an additional drawdown, etc., which characterize the degree of damage of a reservoir within a preset region of a 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 pseudo-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 characterized in that the damage degree is known through the permeability change before and after core displacement, and although the method is more suitable for researching single-factor reservoir damage, the reservoir damage rule on a larger scale is difficult to reflect. In addition, because the indoor core experiment conditions are more ideal, the core for evaluation is the original state core, and the dynamic change of the reservoir characteristics 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 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
Figure BDA0003232446660000031
And determining the maximum growth rate of said bacteria by the following formula
Figure BDA0003232446660000032
Figure BDA0003232446660000033
Wherein, b1、c1Respectively a first experience parameter and a second experience parameter; t ismax、TminThe 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
Figure BDA0003232446660000034
Actual concentration C of nutrients in the fluidnuMono half growth coefficient kSAnd determining the growth rate g of said bacteriumactual，
Figure BDA0003232446660000035
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 reservoirdepositionGrowth rate g of said bacteriumactualAnd rate of decay kdecayAnd determining the total amount V of said bacteria on said rock surfacebacteriatran，
Figure BDA0003232446660000036
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 nutrientnusumThe total amount V of said bacteria on said rock surfacebacteriatranAnd the apparent concentration C of the bacteriabacteriatranEstablishing an apparent concentration distribution equation of the nutrient represented by the following formula,
Figure BDA0003232446660000041
wherein, gactualIs the growth rate of the bacteria; y is the productivity coefficient of the bacterium; and CnutranIs the apparent concentration profile of the nutrient.
Preferably, said establishing an apparent concentration distribution equation of bacteria in said fluid comprises: 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 equation of apparent concentration distribution of bacteria in the fluid expressed by the following formula,
Figure BDA0003232446660000042
wherein, CnutranIs 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 damaged reservoir according to the apparent concentration distribution equation of the nutrients 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 reservoirdepositionDetermining the permeability of the reservoir from the density of the bacteria, rho, and the formula
Figure BDA0003232446660000051
Determining permeability of the reservoir
Figure BDA0003232446660000052
Wherein phi is0Is an initial value of the porosity of the reservoir; and
Figure BDA0003232446660000053
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
Figure BDA0003232446660000054
To the actual concentration
Figure BDA0003232446660000055
And formula
Figure BDA0003232446660000056
Determining permeability of the reservoir
Figure BDA0003232446660000057
And permeability based on the reservoir
Figure BDA0003232446660000058
And formula
Figure BDA0003232446660000059
Determining skin coefficients of the reservoir
Figure BDA00032324466600000510
Wherein the content of the first and second substances,
Figure BDA00032324466600000511
is an initial value of the permeability of the reservoir,
Figure BDA00032324466600000512
rwthe radius of the wellbore for the well to be diagnosed, and rswIs 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 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 then increasing production measures, 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-damaged 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.
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 bacterial-damaged reservoir provided by an embodiment of the present invention;
FIG. 2 is a flow chart for determining the growth rate of the bacteria according to one embodiment of the present invention;
FIG. 3 is a flow chart of a method of determining a reservoir impairment level provided by an embodiment of the present invention;
FIG. 4 is a block diagram of a modeling system for a bacterial damage reservoir provided by an embodiment of the present invention; and
fig. 5 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 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
Figure BDA0003232446660000081
For example
Figure BDA0003232446660000082
Can be abbreviated as r0(ii) a And
Figure BDA0003232446660000083
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):
Figure BDA0003232446660000091
the Darcy apparent velocity of the fluid can be determined according to the formula (1) and the Darcy formula (2),
Figure BDA0003232446660000092
wherein the content of the first and second substances,
Figure BDA0003232446660000093
is the pressure of the fluid; phi is a0Is an initial value of the porosity of the reservoir; μ is the fluid viscosity; c. CtIs the fluid-rock combined compression coefficientAnd
Figure BDA0003232446660000094
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
Figure BDA0003232446660000095
Thermal conductivity D of the fluidconAnd thermal diffusivity of DdisAnd establishing a mathematical model of reservoir temperature distribution of the size of the mine field by using an energy conservation theorem to obtain an expression of a reservoir temperature distribution control equation:
Figure BDA0003232446660000096
wherein the content of the first and second substances,
Figure BDA0003232446660000097
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
Figure BDA0003232446660000101
And determining the maximum growth rate of the bacteria by the following formula (4)
Figure BDA0003232446660000102
Figure BDA0003232446660000103
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
Figure BDA0003232446660000104
Actual concentration C of nutrients in the fluidnuMono half growth coefficient kSAnd the following formula (5), determining the growth rate g of the bacteriumactual，
Figure BDA0003232446660000105
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，
Figure BDA0003232446660000111
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),
Figure BDA0003232446660000121
wherein, CnutranIs the apparent concentration distribution of bacteria in the fluid. The one-dimensional form of the above formula (8) can be written as
Figure BDA0003232446660000122
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
Figure BDA0003232446660000123
Diffusion coefficient D of the nutrientnusumThe total amount V of said bacteria on said rock surfacebacteriatranAnd the apparent concentration C of the bacteriabacteriatranEstablishing an apparent concentration distribution equation of the nutrient represented by the following formula (9),
Figure BDA0003232446660000131
wherein, gactualIs the growth rate of the bacteria; y is the productivity coefficient of the bacterium; and CnutranIs the apparent concentration profile of the nutrient. The one-dimensional form of the above formula (9) can be written as
Figure BDA0003232446660000132
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:
Figure BDA0003232446660000141
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 have the following difference equation:
Figure BDA0003232446660000142
wherein i ═ 1,2,3i，
Figure BDA0003232446660000143
n＝1,2,3...，t＝nΔt，NiIs the number of discrete spatial points.
Solving interval of x ∈ (0, x)max)(xmaxIs 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, consider the initial condition fi n|n＝0＝fi 0，i＝1，2，3...，NiAnd boundary conditions (f)i n|i＝1＝f0N-1, 2,3. (at the borehole wall) and
Figure BDA0003232446660000144
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:
Figure BDA0003232446660000151
wherein, A1i，A2i，A3iRespectively, are as follows,
Figure BDA0003232446660000152
meanwhile, a can be determined according to the formulas (8) to (9)i、biAnd ci。
And will determine ai、biAnd ciSubstituting equation (13) results in the iterative relationship (12), which is not listed here because the iterative relationship (12) is complex. 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 addedi+1, from
Figure BDA0003232446660000153
1,2,3
Figure BDA0003232446660000154
This is substituted into formula (12) to find:
Figure BDA0003232446660000161
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, the formula
Figure BDA0003232446660000162
Need to be changed into
Figure BDA0003232446660000163
This form is not conducive to equidistant differentiation, and coordinate transformation can be introduced: r ═ rwex′Wherein r iswIs the wellbore radius, and x' is a dimensionless spatial coordinate. Substituting this transformation into a general equation, one can obtain an equation for x':
Figure BDA0003232446660000164
if it will be
Figure BDA0003232446660000165
And
Figure BDA0003232446660000166
as new equation coefficients, the above equations and
Figure BDA0003232446660000167
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.
In the calculation by the above methodObtaining the amount of the bacteria adhered to the surface CdepositionTherefore, 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 a characteristic parameter characterizing the degree of damage of the reservoir in a preset area of the well to be diagnosed, based on the amount of adhesion of said 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 reservoirdepositionWith the density of the bacteria, p following formula (17), determining the permeability of the reservoir
Figure BDA0003232446660000168
Figure BDA0003232446660000171
Wherein phi is0Is an initial value of the porosity of the reservoir; and
Figure BDA0003232446660000172
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
Figure BDA0003232446660000173
To the actual concentration
Figure BDA0003232446660000174
And formula
Figure BDA0003232446660000175
Determining permeability of the reservoir
Figure BDA0003232446660000176
And permeability based on the reservoir
Figure BDA0003232446660000177
And the following formula (18), determining the skin factor of the reservoir
Figure BDA0003232446660000178
Figure BDA0003232446660000179
Wherein the content of the first and second substances,
Figure BDA00032324466600001710
is an initial value of the permeability of the reservoir,
Figure BDA00032324466600001711
rwthe radius of the wellbore for the well to be diagnosed, and rswIs the radius of damage to the reservoir.
The characteristic parameter (e.g. permeability of the reservoir) obtained by this step S302
Figure BDA00032324466600001712
Coefficient of epidermis
Figure BDA00032324466600001713
Is the result of a 4D quantitative simulation of the spatio-temporal evolution (not shown). Therefore, quantitative prediction of reservoir damage and space-time deduction of damage rules can be carried out according to evolution characteristics of permeability or skin coefficients, and scientific guiding significance is provided for preventing or avoiding reservoir damage, formulating a development scheme of an oil reservoir and carrying out subsequent production increasing 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 technologies, 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.

Claims (13)

1. A method of modeling a bacterial-damage reservoir, the method comprising:
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
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.
2. The modeling method of claim 1, wherein the determining the growth rate of the 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.
3. According to claim 2The modeling method of (a), wherein the determining the maximum growth rate of the bacteria comprises: according to the temperature distribution field of the reservoir
Figure FDA0003595899240000011
And determining the maximum growth rate of said bacteria by the following formula
Figure FDA0003595899240000021
Figure FDA0003595899240000022
Wherein, b1、c1Respectively a first experience parameter and a second experience parameter; t ismax、TminThe 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
Figure FDA0003595899240000023
Actual concentration C of nutrients in the fluidnuMono half growth coefficient kSAnd the following formula, determining the growth rate g of the bacteriaactual，
Figure FDA0003595899240000024
4. The modeling method of claim 1, wherein the determining the total amount of bacteria on the rock surface comprises:
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，
Figure FDA0003595899240000025
5. The modeling method of claim 1, wherein the establishing an apparent concentration distribution equation for bacteria in the fluid comprises:
according to Darcy apparent velocity u of the fluid and diffusion coefficient D of the bacteriasumGrowth rate g of the bacteriumactualAnd rate of decay kdecayAnd the amount of attachment C of said bacteria to the rock surface in said reservoirdepositionEstablishing an equation of apparent concentration distribution of bacteria in the fluid expressed by the following formula,
Figure FDA0003595899240000031
wherein, CnutranIs the apparent concentration distribution of bacteria in the fluid.
6. The modeling method of claim 1, wherein 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 nutrientnusumThe total amount V of said bacteria on said rock surfacebacteriatranAnd the apparent concentration C of the bacteriabacteriatranEstablishing an apparent concentration distribution equation of the nutrient represented by the following formula,
Figure FDA0003595899240000032
wherein, gactualIs the growth rate of the bacteria; y is the productivity coefficient of the bacterium; and CnutranIs a table of said nutrientsConcentration distribution is observed.
7. The modeling method of claim 1, further comprising:
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.
8. A method of determining a level of reservoir damage, the method comprising:
determining the attachment amount of the bacteria on the rock surface based on a spatiotemporal evolution simulation equation established according to the modeling method of a bacteria damaged reservoir of any one of claims 1-7; 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.
9. A method of determining a degree of reservoir damage as defined in claim 8, wherein the characteristic parameter is a permeability 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 amount of attachment C of the bacteria on the rock surface in the reservoirdepositionDetermining the permeability of the reservoir from the density of the bacteria, rho, and the formula
Figure FDA0003595899240000041
Figure FDA0003595899240000042
Wherein phi0Is an initial value of the porosity of the reservoir; and
Figure FDA0003595899240000043
is an initial value of the permeability of the reservoir.
10. A method of determining a degree of reservoir damage as defined in claim 8, 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 apparent concentration of nutrients in the fluid
Figure FDA0003595899240000044
And actual concentration
Figure FDA0003595899240000045
And formula
Figure FDA0003595899240000046
Determining permeability of the reservoir
Figure FDA0003595899240000047
And
permeability based on the reservoir
Figure FDA0003595899240000048
And determining the skin factor of the reservoir
Figure FDA0003595899240000049
Figure FDA00035958992400000410
Wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003595899240000051
is an initial value of the permeability of the reservoir,
Figure FDA0003595899240000052
rwthe radius of the wellbore for the well to be diagnosed, and rswIs the radius of damage to the reservoir.
11. 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
and the simulation equation determining device is used for determining a space-time evolution simulation equation of the bacteria damage reservoir according to the apparent concentration distribution equation of the nutrient 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.
12. A system for determining a level 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 by a modeling system of a bacteria-damaged reservoir as defined in claim 11; 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 on the basis of the attachment amount of the bacteria on the rock surface.
13. A machine readable storage medium having stored thereon instructions for causing a machine to perform the method of modelling a bacterial-damage reservoir of any preceding claim 1 to 7 and/or the method of determining the extent of reservoir damage of any preceding claim 8 to 10.
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