CN113674100A - Oil reservoir injection-production optimization method and device, storage medium and electronic equipment - Google Patents

Oil reservoir injection-production optimization method and device, storage medium and electronic equipment Download PDF

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CN113674100A
CN113674100A CN202010408280.5A CN202010408280A CN113674100A CN 113674100 A CN113674100 A CN 113674100A CN 202010408280 A CN202010408280 A CN 202010408280A CN 113674100 A CN113674100 A CN 113674100A
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oil
viscosity
water phase
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CN113674100B (en
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杨森
孙建芳
龚蔚青
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China Petroleum and Chemical Corp
Sinopec Exploration and Production Research Institute
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China Petroleum and Chemical Corp
Sinopec Exploration and Production Research Institute
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    • G06Q50/02—Agriculture; Fishing; Mining
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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Abstract

The application relates to the technical field of numerical simulation application of an oil reservoir and improvement of oil reservoir recovery efficiency, in particular to an oil reservoir injection-production optimization method, device, storage medium and electronic equipment, and solves the problem that the oil reservoir production rate cannot be accurately evaluated under the influence of the characteristics of a temperature-sensitive composite profile control system in the prior art. According to the method, a relation model of the water phase viscosity, the concentration of a temperature-sensitive plugging agent component and the temperature change is used for representing the change rule of the viscosity after the temperature-sensitive plugging agent component exists in each grid block, a chemical relation model of a water-soluble viscosity reducer component in the water phase and an original component in the oil phase is used for representing a chemical viscosity reduction process, the oil phase relative permeability curve corrects the change rule of the permeability curve along with the change relation model of the improved capillary number, dynamic changes of reservoir physical properties and fluid rheological parameters calculated by each grid in each iteration are updated, and the oil reservoir injection and production are optimized according to the obtained second water phase relative permeability and the second oil phase relative permeability.

Description

Oil reservoir injection-production optimization method and device, storage medium and electronic equipment
Technical Field
The application relates to the technical field of numerical reservoir simulation application and optimization of reservoir injection and production, in particular to a reservoir injection and production optimization method and device, a storage medium and electronic equipment.
Background
At present, the numerical reservoir simulation technology is the most important means for evaluating the effect of a certain oil field development mode. However, currently, oil reservoir numerical simulation software developed at home and abroad generally only has mature chemical flooding numerical simulation methods for polymer flooding, surfactant flooding, ASP (active-oil-displacing) ternary combination flooding and the like, and the methods generally assume that the oil reservoir is in a constant temperature state (oil reservoir temperature) in a chemical flooding process or the influence of temperature change on the chemical flooding effect in a certain range can be ignored, and indoor experimental research shows that the oil displacement technology based on a temperature-sensitive composite profile control and flooding system can remarkably expand the spread and greatly improve the oil reservoir recovery ratio.
However, the rheological change of the displacement phase (plugging agent) caused by temperature, the rheological change of the displaced phase (crude oil) caused by the physical and chemical action of a chemical agent and the change of the oil displacement action when the displacement phase is a novel temperature-sensitive composite profile control and flooding system cannot be reasonably represented in the related technology, and great errors exist in the estimation of the oil displacement effect, the residual macroscopic distribution and the potential of the temperature-sensitive composite profile control and flooding system. The temperature-sensitive composite profile control system can change the accumulated oil production and the recovery ratio of the oil reservoir by changing the concentration and the viscosity of the temperature-sensitive profile control agent in the oil reservoir, and the injection-production optimization of the oil reservoir is not realized under the influence of the characteristics of the temperature-sensitive composite profile control system in the prior art.
Disclosure of Invention
In order to solve the problems, the application provides an oil reservoir injection-production optimization method, an oil reservoir injection-production optimization device, a storage medium and electronic equipment, and solves the technical problem that oil reservoir injection-production optimization is not realized under the influence of the characteristics of a temperature-sensitive composite profile control system in the related technology.
In a first aspect, the present application provides a reservoir injection-production optimization method, including:
step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the data field comprises a saturation data field, a pressure data field, a temperature data field, a viscosity data field and a relative permeability data field;
step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow;
step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change;
step S140: obtaining an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field and an aqueous phase second saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer component in the aqueous phase and the raw oil component in the oil phase;
step S150: acquiring a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of temperature-sensitive plugging agent components in the water phase in unit pore volume and the change of the water phase relative permeability;
step S160, obtaining a first oil phase relative permeability data field according to a variation relation model of the oil phase relative permeability data field along with the number of capillary tubes;
step S170: obtaining updated data fields according to the first saturation data field, the first temperature data field, the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field, the water phase second saturation data field, the first water phase relative permeability data field and the first oil phase relative permeability data field;
step S180: replacing the initial data field in the step S120 with the updated data field, and circularly executing the steps S120 to S170 within preset time to obtain a second water phase relative permeability and a second oil phase relative permeability;
step S190: and optimizing the injection and the production of the oil reservoir based on the relative permeability of the second water phase and the relative permeability of the second oil phase.
According to an embodiment of the present application, optionally, in the above method for optimizing injection and production of a reservoir, the establishing a reservoir production model based on the reservoir parameters includes establishing based on the following calculation formula:
Figure BDA0002492153760000021
wherein, FiRepresenting a convection term, AiRepresents the accumulation phase, BiAnd (3) representing a yield item, t represents time, and the value range of i is 3-4.
According to an embodiment of the present application, optionally, in the above reservoir injection-production optimization method, the step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the method comprises the following steps: and acquiring a data field of all components of each phase of each grid block in the oil reservoir exploitation model.
According to an embodiment of the present application, optionally, in the above reservoir injection-production optimization method, the step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow, wherein the method comprises the following steps:
respectively acquiring the flow of all components of each phase of each grid block in each direction according to the pressure data field, and respectively acquiring the accumulated flow of each phase of each grid block in all directions according to the flow;
respectively acquiring a first saturation data field, a first temperature data field and a first pressure data field of each phase of each grid block in all directions according to the accumulated flow and the state equation of each phase of each grid block in all directions;
wherein the accumulated flow rate includes accumulating the total mass of fluid passing through each phase in each grid block X, Y, Z and the mass of all components in each grid block at a time step.
According to an embodiment of the present application, optionally, in the above reservoir injection-production optimization method, the step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change, wherein the first viscosity data field comprises:
obtaining a first viscosity field of the water phase in each grid block according to the component viscosity of the temperature-sensitive plugging agent and the component viscosity of the water phase after the temperature-sensitive plugging agent is added into each grid block on the basis of the following calculation formula:
Figure BDA0002492153760000031
wherein, muaqThe water phase mixing viscosity is shown in the specification,
Figure BDA0002492153760000032
wprepresents the molar concentration of the polymer,. mu.wDenotes the viscosity of the aqueous phase, M denotes the mass of fluid in the reservoir, μp(C, T) represents the viscosity of the temperature-sensitive plugging agent, ncThe number of components of the water phase is represented, S is a preset range, the value range of i is 3-4, and w isiRepresents the molar fraction of the j-phase i component, muiRepresents the viscosity of the i component of the water phase.
According to an embodiment of the present application, optionally, in the above reservoir injection-production optimization method, the step S140: obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer components in the water phase and the raw oil components in the oil phase, wherein the second oil phase viscosity data field, the second oil phase saturation data field, the second water phase viscosity data field and the second water phase saturation data field comprise:
and obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction formula of the viscosity reducer component in the water phase and the raw oil component in the oil phase in a chemical reaction process.
According to an embodiment of the present application, optionally, in the above reservoir injection-production optimization method, the step S150: obtaining a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of temperature-sensitive plugging agent components in the water phase in unit pore volume and the change of the water phase relative permeability, wherein the relation model comprises the following steps:
according to the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase of each grid in unit pore volume and the relative permeability of the water phase, acquiring a first water phase relative permeability data field in each grid block based on the following calculation formula:
Figure BDA0002492153760000041
wherein k iswIndicates the effective permeability of the aqueous phase after plugging, krwIs the water phase permeability, kabsDenotes the absolute permeability of the rock, RkwRepresenting a water phase permeability reduction factor.
In a second aspect, the present application provides a reservoir injection-production optimization apparatus, comprising:
a model building module configured to build a reservoir exploitation model based on reservoir parameters, and obtain an initial data field of each grid block in the reservoir exploitation model, wherein the data fields include a saturation data field, a pressure data field, a temperature data field, a viscosity data field, and a relative permeability data field;
a first data acquisition module configured to acquire an accumulated flow of each grid block in the reservoir exploitation model, and obtain a first saturation data field, a first temperature data field, and a first pressure data field in each grid block according to the accumulated flow;
a second data acquisition module configured to obtain a water phase first viscosity data field in each grid block according to a relational model of water phase viscosity and temperature-sensitive plugging agent component concentration and temperature change;
a third data acquisition module configured to obtain an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field, and an aqueous phase second saturation data field in each grid block according to a chemical reaction relationship model of viscosity reducer components in the aqueous phase and crude oil components in the oil phase;
a fourth data acquisition module configured to acquire a first water phase relative permeability data field in each grid block according to a relational model of changes in adsorption amount of temperature-sensitive plugging agent components in a water phase in a unit pore volume and relative permeability of the water phase;
a fifth data acquisition module configured to obtain a first oil-phase relative permeability data field according to a model of a variation of the oil-phase relative permeability data field with the number of capillaries;
a sixth data acquisition module configured to obtain updated data fields from the first saturation data field, first temperature data field, and first pressure data field, the aqueous phase first viscosity data field, the oil phase second viscosity data field, oil phase second saturation data field, aqueous phase second viscosity data field, and aqueous phase second saturation data field, first aqueous phase relative permeability data field, first oil phase relative permeability data field;
the control module is configured to replace the initial data field in the oil reservoir exploitation model according to the updated data field, and control the oil reservoir exploitation model to perform iterative computation within a preset time to obtain a second water-phase relative permeability and a second oil-phase relative permeability;
an optimization module configured to optimize reservoir injection and production based on the second water phase relative permeability and second oil phase relative permeability.
According to an embodiment of the present application, optionally, in the above oil reservoir injection and production optimization apparatus, the establishing an oil reservoir production model based on the oil reservoir parameters includes establishing based on the following calculation formula:
Figure BDA0002492153760000051
wherein, FiRepresenting a convection term, AiRepresents the accumulation phase, BiAnd (3) representing a yield item, t represents time, and the value range of i is 3-4.
According to an embodiment of the present application, optionally, in the above reservoir injection and production optimization apparatus, the step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the method comprises the following steps: and acquiring a data field of all components of each phase of each grid block in the oil reservoir exploitation model.
According to an embodiment of the present application, optionally, in the above reservoir injection and production optimization apparatus, the step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow, wherein the method comprises the following steps:
respectively acquiring the flow of all components of each phase of each grid block in each direction according to the pressure data field, and respectively acquiring the accumulated flow of each phase of each grid block in all directions according to the flow;
respectively acquiring a first saturation data field, a first temperature data field and a first pressure data field of each phase of each grid block in all directions according to the accumulated flow and the state equation of each phase of each grid block in all directions;
wherein the accumulated flow rate includes accumulating the total mass of fluid passing through each phase in each grid block X, Y, Z and the mass of all components in each grid block at a time step.
According to an embodiment of the present application, optionally, in the above reservoir injection and production optimization apparatus, the step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change, wherein the first viscosity data field comprises:
obtaining a first viscosity field of the water phase in each grid block according to the component viscosity of the temperature-sensitive plugging agent and the component viscosity of the water phase after the temperature-sensitive plugging agent is added into each grid block on the basis of the following calculation formula:
Figure BDA0002492153760000052
wherein, muaqThe water phase mixing viscosity is shown in the specification,
Figure BDA0002492153760000053
wprepresents the molar concentration of the polymer,. mu.wDenotes the viscosity of the aqueous phase, M denotes the mass of fluid in the reservoir, μp(C, T) represents the viscosity of the temperature-sensitive plugging agent, ncThe number of components of the water phase is represented, S is a preset range, the value range of i is 3-4, and w isiRepresents the mole fraction of the i component of the water phase, muiRepresents the viscosity of the i component of the water phase.
According to an embodiment of the present application, optionally, in the above reservoir injection and production optimization apparatus, the step S140: obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer components in the water phase and the raw oil components in the oil phase, wherein the second oil phase viscosity data field, the second oil phase saturation data field, the second water phase viscosity data field and the second water phase saturation data field comprise:
and obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction formula of the viscosity reducer component in the water phase and the raw oil component in the oil phase in a chemical reaction process.
According to an embodiment of the present application, optionally, in the above reservoir injection and production optimization apparatus, the step S150: obtaining a first water phase relative permeability data field of the water phase in each grid block according to a relation model of the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase in unit pore volume and the change of the water phase relative permeability, wherein the data field comprises:
according to the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase of each grid in unit pore volume and the relative permeability of the water phase, acquiring a first water phase relative permeability data field in each grid block based on the following calculation formula:
Figure BDA0002492153760000061
wherein k iswIndicates the effective permeability of the aqueous phase after plugging, krwIs the water phase permeability, kabsDenotes the absolute permeability of the rock, RkwRepresenting a water phase permeability reduction factor.
In a third aspect, the present application provides a storage medium storing a computer program executable by one or more processors for implementing the method for reservoir injection and production optimization as described above.
In a fourth aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, the memory and the processor are communicatively connected to each other, and the computer program is executed by the processor to perform the above-mentioned reservoir injection and production optimization method.
Compared with the prior art, the oil reservoir injection-production optimization method, the storage medium and the electronic equipment have the beneficial effects that:
the method is characterized in that a relation model of the change of the viscosity of each grid block after the temperature-sensitive plugging agent component exists through a water phase viscosity and temperature-sensitive plugging agent component concentration and temperature change represents the change rule of the viscosity of each grid block, a chemical relation model of the water-soluble viscosity reducer component in the water phase and the original component in the oil phase represents a chemical viscosity reduction process, a change relation model of the oil phase relative permeability curve along with the change of the number of the improved capillary tubes modifies the change rule of the permeability curve, a data field in each grid is updated in an iterative calculation process of an oil reservoir exploitation model, an injection and extraction scheme is optimized under the influence of the characteristics of a sensitive composite profile control system, the precision of numerical simulation prediction results of the chemical viscosity reduction and oil displacement effects of the water-soluble oil reservoir viscosity reducer is improved, the stability and reliability of oil reservoir exploitation model simulation results are ensured, and the oil field development technology is reasonably optimized, the potential of oil reservoir recovery is accurately evaluated, and the potential of the oil reservoir is improved, Effective formulation of oilfield development schemes provides powerful support.
Drawings
The present application will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings:
FIG. 1 is a schematic flow chart of a reservoir injection-production optimization method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of the relationship between the component concentration and the temperature change of the temperature-sensitive viscoelastic polymer plugging agent provided in the embodiment of the present application;
FIG. 3 is a schematic diagram illustrating a relationship between a change in adsorption capacity per unit pore volume of a component of a temperature-sensitive viscoelastic polymeric plugging agent and a change in relative permeability of an aqueous phase according to an embodiment of the present application;
FIG. 4 is a schematic representation of the improved relationship between capillary count and relative permeability endpoint values provided in the examples of the present application;
FIG. 5 is a graph comparing recovery without considering the characteristics of a temperature-sensitive complex flooding system and with considering the characteristics of the temperature-sensitive complex flooding system provided in the examples of the present application;
fig. 6 is a connection block diagram of a reservoir injection-production optimization device according to an embodiment of the present disclosure.
In the drawings, like parts are designated with like reference numerals, and the drawings are not drawn to scale.
Detailed Description
The following detailed description will be provided with reference to the accompanying drawings and embodiments, so that how to apply the technical means to solve the technical problems and achieve the corresponding technical effects can be fully understood and implemented. The embodiments and various features in the embodiments of the present application can be combined with each other without conflict, and the formed technical solutions are all within the scope of protection of the present application.
The method characterizes the change rule of the viscosity of each grid block after the temperature-sensitive plugging agent component exists through a relation model of the viscosity of a water phase, the concentration of the temperature-sensitive plugging agent component and the temperature change, characterizes the chemical viscosity reduction process through a chemical relation model of the water-soluble viscosity reducer component in the water phase and the original component in an oil phase, corrects the change rule of a permeability curve of an oil phase relative permeability curve along with the change relation model of the improved capillary number, updates the dynamic changes of reservoir physical properties and fluid rheological parameters of each grid in each iterative calculation, can realize the rapid, continuous and accurate simulation calculation based on the characteristics of a temperature-sensitive composite profile control system, and ensures the stability and reliability of a simulation result of an oil reservoir exploitation model.
Example one
Fig. 1 is a schematic flow chart of a reservoir injection-production optimization method provided in an embodiment of the present application, and as shown in fig. 1, the method includes:
step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the data field comprises a saturation data field, a pressure data field, a temperature data field, a viscosity data field and a relative permeability data field;
step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow;
step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change;
step S140: obtaining an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field and an aqueous phase second saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer component in the aqueous phase and the raw oil component in the oil phase;
step S150: acquiring a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase in unit pore volume and the change of the water phase relative permeability;
step S160, obtaining a first oil phase relative permeability data field according to a variation relation model of the oil phase relative permeability data field along with the number of capillary tubes;
step S170: obtaining updated data fields according to the first saturation data field, the first temperature data field, the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field, the water phase second saturation data field, the first water phase relative permeability data field and the first oil phase relative permeability data field;
specifically, the updated data field is obtained by a finite difference method according to the first saturation data field, the first temperature data field and the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field and the water phase second saturation data field, the first water phase relative permeability data field and the first oil phase relative permeability data field.
Obtaining the updated data field by the finite difference method is a technical means well known to those skilled in the art, and is not described in detail herein.
Step S180: replacing the initial data field in the step S120 with the updated data field, and circularly executing the steps S120 to S170 within preset time to obtain a second water phase relative permeability and a second oil phase relative permeability;
in this embodiment, the preset time is 10 years.
Step S190: and optimizing the injection and the production of the oil reservoir based on the relative permeability of the second water phase and the relative permeability of the second oil phase.
The sequence of steps S130 to S150 is adjustable.
Further, establishing the reservoir exploitation model based on the reservoir parameters includes establishing based on the following calculation formula:
Figure BDA0002492153760000091
wherein i is a component number, i is 1, 2.
FiIs a convection term;
Aiis an accumulated term;
Biis a yield item.
Specifically, the method comprises the following steps:
convection term
Figure BDA0002492153760000092
Wherein, YijIs the phase concentration, representing the concentration of the i component in the j phase;
ρjrepresents the concentration of j phases, the number of phases j being 1, 2.
VjRepresents the Darcy velocity in m3/d。
Specifically, the calculation formula of darcy speed is as follows:
Figure BDA0002492153760000093
wherein p isjRepresents the pressure of the j phase, and the phase number j is 1, 2.
K represents the absolute permeability of the rock and has the unit mD;
Krjthe relative permeability of the j phase is shown as decimal;
λjthe unit of the flow correction coefficient of the j phase is mPa & s;
Yijthe phase concentration represents the concentration of the i component in the j phase.
In particular, the method comprises the following steps of,
yield term Bi＝Qi+Ri (4)
Wherein Q isiRepresents the injection/output of the i component;
Riindicating an increase or decrease in mass of the i component due to a chemical reaction or the like.
Further, step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the method comprises the following steps: and acquiring a data field of all components of each phase of each grid block in the oil reservoir exploitation model.
Wherein each phase comprises an aqueous phase, an oil phase, and, in the presence of a gas reservoir, a gas phase; the total components include all components included in the reservoir, such as a water component, an oil component, a polymer component (emulsion component) after adding a temperature sensitive plugging agent, and the like.
Further, step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow, wherein the method comprises the following steps:
respectively acquiring the flow of all components of each phase of each grid block in each direction according to the pressure data field, and respectively acquiring the accumulated flow of each phase of each grid block in all directions according to the flow;
respectively acquiring a first saturation data field, a first temperature data field and a first pressure data field of each phase of each grid block in all directions according to the accumulated flow and the state equation of each phase of each grid block in all directions;
wherein the accumulated flow rate includes accumulating the total mass of fluid passing through each phase in each grid block X, Y, Z and the mass of all components in each grid block at a time step.
Wherein the equation of state refers to an equation describing the relationship between fluid density and temperature and pressure.
The state equations include: ρ ═ ρ0[1+CL(P-P0)] (5)
Where ρ represents the current density;
ρ0represents the initial density;
CLrepresents the elastic compression coefficient;
p current pressure;
P0indicating the initial pressure.
Further, step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change, wherein the first viscosity data field comprises:
obtaining a first viscosity field of the water phase in each grid block according to the component viscosity of the temperature-sensitive plugging agent and the component viscosity of the water phase after the temperature-sensitive plugging agent is added into each grid block on the basis of the following calculation formula:
Figure BDA0002492153760000101
wherein, muaqRepresents the water phase mixing viscosity;
μp(C, T) represents the viscosity of the temperature-sensitive plugging agent;
μirepresents the viscosity of the water phase component i;
wprepresents the molar concentration of the polymer;
wirepresenting the mole fraction of the i components in the water phase;
ncrepresents the number of components of the aqueous phase;
s is a preset range;
the value range of i is 3-4.
In particular, the method comprises the following steps of,
Figure BDA0002492153760000102
Figure BDA0002492153760000111
wherein, muaqRepresents the water phase mixing viscosity;
μp(C, T) represents the viscosity of the temperature-sensitive plugging agent;
μirepresents the viscosity of the water phase component i;
wprepresents the molar component concentration of the polymer;
wirepresenting the mole fraction of the i components in the water phase;
m represents the mass of fluid in the reservoir, μwRepresents the viscosity of the aqueous phase;
the value range of i is 3-4.
Wherein the temperature-sensitive profile control agent comprises a temperature-sensitive high-molecular profile control agent.
Further, step S140: obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer components in the water phase and the raw oil components in the oil phase, wherein the second oil phase viscosity data field, the second oil phase saturation data field, the second water phase viscosity data field and the second water phase saturation data field comprise:
and obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction formula of the viscosity reducer component in the water phase and the raw oil component in the oil phase in a chemical reaction process.
Wherein, the chemical reaction formula in the chemical reaction process of the viscosity reducer component in the water phase and the original component in the oil phase comprises:
Figure BDA0002492153760000112
wherein oil is crude oil, A is the proportion of the crude oil in the chemical reaction formula, reducer is a viscosity reducer, B is the proportion of the viscosity reducer in the chemical reaction formula, Emulsion is Emulsion, and C is the proportion of the Emulsion in the chemical reaction formula.
Further, the step S150: obtaining a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of the temperature-sensitive plugging agent component in the water phase in unit pore volume and the change of the water phase relative permeability, wherein the relation model comprises the following steps:
according to the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase of each grid in unit pore volume and the relative permeability of the water phase, acquiring a first water phase relative permeability data field of the water phase in each grid block based on the following calculation formula:
Figure BDA0002492153760000113
wherein k iswRepresents the effective permeability of the aqueous phase after plugging, mD;
krwthe water phase permeability is shown;
kabsrepresents the absolute permeability of the rock;
Rkwrepresenting a water phase permeability reduction factor.
Wherein the content of the first and second substances,
Figure BDA0002492153760000121
wherein R iskwRepresents a water phase permeability reduction factor;
RRFwrepresents the residual resistance factor of the water phase;
Adcellexpressing the adsorption quantity, mol, of the plugging agent in the unit volume grid;
ADMAXT represents the maximum adsorption of the plugging agent in the grid per unit volume, mol.
The relative permeability is used as an important oil deposit physical property parameter, and the accuracy of the value has important practical significance for reliably predicting the oil deposit behavior.
Further, step S190: optimizing injection and production of the oil reservoir based on the second water phase relative permeability and the second oil phase relative permeability, comprising: and obtaining the recovery ratio and the accumulated oil yield of the oil field under different concentrations and dosages of the temperature-sensitive plugging agent according to the relative permeability of the second water phase and the relative permeability of the second oil phase, and comparing the recovery ratio and the accumulated oil yield under different conditions, thereby determining the optimal oil reservoir injection-production scheme to realize the oil reservoir injection-production optimization.
The yield and the water flooding dynamic analysis of each small layer of the oil field can be estimated according to the relative permeability, and the fitting degree of the estimation result and the physical experiment result reaches more than 90%.
Specifically, in the preset time, the oil reservoir exploitation model obtains new water phase relative permeability and oil phase relative permeability in each iterative calculation process, different water phase relative permeability and oil phase relative permeability can reflect different concentrations and different dosages of the temperature-sensitive plugging agent, and the accumulated oil production and the recovery ratio of the oil reservoir are different under different concentrations and different dosages of the temperature-sensitive plugging agent. When the accumulated oil production of the oil reservoir is low and/or the recovery ratio is low, the accumulated oil production and/or the recovery ratio of the oil reservoir can be changed by adjusting the concentration and the dosage of the temperature-sensitive plugging agent to obtain an oil reservoir injection-production scheme, so that the oil reservoir injection-production optimization is realized.
The embodiment provides a reservoir injection-production optimization method, which comprises the following steps: establishing an oil reservoir exploitation model based on oil reservoir parameters, representing a change rule of viscosity after the temperature-sensitive plugging agent component exists in each grid block through a relation model of water phase viscosity, temperature-sensitive plugging agent component concentration and temperature change, representing a chemical viscosity reduction process through a chemical relation model of water-soluble viscosity reducer components in the water phase and original components in the oil phase, modifying a change rule of an oil phase relative permeability curve along with the change relation model of the number of improved capillary tubes, and updating a data field in each grid in an iterative calculation process of the oil reservoir exploitation model to obtain the oil reservoir exploitation model based on the characteristics of a sensitive composite profile control system; for the water-soluble viscosity reducer and the oil displacement effect, the simulation prediction result of the oil reservoir exploitation model meets the requirement of industrial application precision; and the simulation result of the oil reservoir exploitation simulation model reasonably evaluates the synergistic effect of the temperature-sensitive composite profile control and flooding system, ensures the goodness and reliability of oil reservoir injection and production, and provides powerful support for reasonably optimizing oil field development technical policies, accurately evaluating the oil reservoir to improve the recovery efficiency potential and effectively making oil field development schemes.
Example two
In an oil reservoir, a temperature-sensitive composite profile control and flooding system is designed and constructed according to the heterogeneous characteristics of the oil reservoir and the distribution rule of residual oil, is a novel composite oil displacement system, is formed by combining a temperature-sensitive viscoelastic high-molecular profile control and plugging agent and a water-soluble viscosity reducer in a slug mode according to a certain proportion, and has the functions of medium-deep profile control and emulsification viscosity reduction oil displacement. A large amount of indoor experimental research data show that the oil displacement technology based on the temperature-sensitive composite profile control and flooding system can remarkably expand the spread and greatly improve the oil reservoir recovery ratio.
The temperature-sensitive viscoelastic macromolecule profile control agent is a multipolymer with temperature-sensitive property prepared by a free radical aqueous solution polymerization method on the basis of selecting proper comonomer. The main characteristic of the temperature-sensitive viscous high-molecular plugging agent is that the viscosity of the plugging agent is set at a certain temperature or a certain temperature interval to generate huge change aiming at the geological conditions and the development characteristics of a target oil reservoir, and if the temperature rises above a certain critical value and gradually rises in a certain interval, the viscosity of a solution system of the plugging agent is suddenly increased. The characteristics of the temperature-sensitive viscoelastic polymer plugging agent in a porous medium are that when a temperature-sensitive viscoelastic polymer plugging agent solution just enters a reservoir stratum, the temperature is low, the viscosity is low, the flowing capability is strong, and the temperature-sensitive viscoelastic polymer plugging agent solution enters a high-water-content and high-permeability pore medium of the reservoir stratum along with injected water; in the process of moving to the deep part of a reservoir, the temperature of the solution is gradually increased under the action of stratum heating, when the temperature reaches critical temperature, the viscosity of the solution is suddenly increased, and a high-water-content and high-permeability channeling channel is blocked, so that the subsequently injected fluid is turned to flow; thereby realizing the pressure bearing and the shear reduction of the near well zone and the blockage regulation and spread of the far well zone.
Therefore, when considering the influence of the temperature-sensitive composite profile control system on the oil reservoir simulation result, the change of the data field of each component of each grid block in the oil reservoir exploitation model under the influence of the temperature-sensitive composite profile control system needs to be considered in the working process of the oil reservoir exploitation model.
In the embodiment, a relation model of the water phase viscosity, the concentration of the temperature-sensitive plugging agent component and the temperature change is used for representing the change rule of the viscosity of each grid block after the temperature-sensitive viscoelastic plugging agent component exists.
For example, fig. 2 is a schematic diagram of a relationship between component concentration and temperature change of the temperature-sensitive viscoelastic polymer plugging agent provided in this embodiment, as shown in fig. 2, in a temperature state of 40 ℃, when the concentration of the temperature-sensitive viscous polymer plugging agent is 1500ppm, the viscosity of the aqueous phase is greater than that of the aqueous phase having a concentration of 3000ppm, and when the temperature rises above a certain critical value and gradually rises within a certain interval, the viscosity of the solution system of the temperature-sensitive viscoelastic polymer plugging agent suddenly increases, and the viscosity of the fluid after the fluid is injected is affected.
Fig. 3 is a schematic diagram of a change relationship between the adsorption amount per unit pore volume of the components of the temperature-sensitive viscoelastic polymer plugging agent and the relative permeability of the aqueous phase provided in the embodiment of the present application, as shown in fig. 3, the adsorption amount per unit pore volume of the components of the temperature-sensitive viscoelastic polymer plugging agent is proportional to the relative permeability of the aqueous phase, and in the process of continuously increasing the adsorption amount per unit pore volume of the components of the temperature-sensitive viscoelastic polymer plugging agent, the relative permeability of the aqueous phase is also increased, and the relative permeability of the aqueous phase in the fluid is also affected after the temperature-sensitive viscoelastic polymer plugging agent is injected with a fluid.
The temperature-sensitive plugging agent and the water-soluble viscosity reducer are matched with each other to generate a synergistic effect, under the same condition, the oil displacement efficiency of the temperature-sensitive composite profile control and flooding system is higher than that of a single agent and exceeds the sum of the oil displacement efficiency of the single agent, and the synergistic effect is also one of the main characteristics of the temperature-sensitive composite profile control and flooding system.
The synergistic property of chemical complex Flooding systems such as general SP (Surfactant-Polymer Flooding, Polymer surface binary Flooding) and ASP (Alkali-Surfactant-Polymer Flooding) is described by a phase permeability curve difference calculation method based on a capillary number model.
However, in recent years, researchers at home and abroad find that when the properties of crude oil and an oil displacement system are changed, because the traditional capillary tube number model is not suitable for describing the relationship between the seepage phase endpoint value and the temperature-sensitive composite profile control and flooding system parameters under the condition, the synergistic interaction between chemical agents is ignored, so that the traditional capillary tube number model does not necessarily have good correlation with the recovery ratio.
Fig. 4 is a schematic diagram of a relationship between the number of modified capillaries and the phase permeability end point value provided in this embodiment, as shown in fig. 4, under the same number of modified capillaries 1E-07, the phase permeability end point value corresponding to the residual oil saturation value is greater than the phase permeability end point value corresponding to the water phase permeability under the residual oil saturation value, and at this time, the phase permeability end point value needs to be corrected.
The water-soluble viscosity reducer molecule consists of a host hydrophobic structure and an object hydrophilic structure, the main viscosity reduction and oil displacement mechanism of the water-soluble viscosity reducer molecule is that cyclodextrin on the viscosity reducer host and a benzyl hydrophobic group on the object are self-assembled after a heavy oil component substance is connected to the viscosity reducer host in a stable covalent bond mode through the chemical reaction of the host hydrophobic structure and a function carried by the heavy oil component; under the traction action of the object hydrophilic polymer chain, large pi bonds formed by aromatic polycyclic conjugation among the heavy oil macromolecular aggregates are destroyed to form smaller heavy oil molecular aggregates.
The diameter of the emulsified oil drops after dispersion is far smaller than the diameter of the pore throat which mainly contributes to permeability, and meanwhile, the liquid phase formed after thick oil emulsification has smaller apparent viscosity, so that the flow capacity of the thick oil is improved, and the oil displacement efficiency is improved.
Therefore, when considering the influence of the temperature-sensitive composite profile control system on the oil reservoir injection-production scheme, the change of the data field of each component of each grid block in the oil reservoir simulation model under the influence of the temperature-sensitive composite profile control system needs to be considered in the working process of the oil reservoir exploitation model.
For example, an oil reservoir exploitation model is established according to preset oil reservoir parameters, wherein 29 grids are arranged in the X direction, 31 grids are arranged in the Y direction, 5 grids are arranged in the Z direction, the step length of a plane grid of the oil reservoir exploitation model is 10m, and the step length of a longitudinal grid is not 0.7 m; the porosity of the oil reservoir exploitation model is 0.32, the plane permeability is 1300mD, the longitudinal permeability is 0.5 time of the plane permeability, the initial oil saturation is 0.65, when 1 injection and 2 extraction are set, the injection speed is 0.1PV/a, and the injection-extraction ratio is 1.1:1, the oil reservoir can be produced for 12 years according to the oil reservoir exploitation model result.
Fig. 5 is a graph comparing recovery ratio without considering the characteristics of the temperature-sensitive compound flooding system and with considering the characteristics of the temperature-sensitive compound flooding system, which is provided in the examples of the present application. As shown in fig. 5, the simulation results show that:
when the characteristics of the temperature-sensitive composite profile control and flooding system are not considered, the temperature-sensitive viscoelastic macromolecule profile control and plugging agent only has the viscosity which changes with the concentration like a common polymer, and the mobility control effect of the temperature-sensitive viscoelastic macromolecule profile control and plugging agent cannot be exerted because the viscosity of a water phase is further increased when the temperature of the temperature-sensitive viscoelastic macromolecule profile control and plugging agent is increased from the ground temperature to the oil reservoir temperature without calculation of an oil reservoir exploitation model; the water-soluble viscosity reducer injected subsequently is similar to surfactant flooding and cannot reflect the effect of improving the flow capacity of the displaced phase (crude oil) due to chemical viscosity reduction; meanwhile, because the traditional capillary model is not suitable for describing the relationship between the phase permeation endpoint value and the temperature-sensitive composite profile control system parameter under the condition, the synergistic effect between the chemical agents is ignored.
Therefore, when the characteristics of the temperature-sensitive composite profile control and flooding system are not considered, the water content of the simulation prediction calculation result is high, and the enhanced recovery ratio amplitude is low.
When the characteristics of the temperature-sensitive composite profile control and flooding system are considered, the viscosity of the components of the temperature-sensitive viscoelastic macromolecule profile control and plugging agent is rapidly and greatly increased along with the rise of the temperature, the flow resistance of a water phase in the simulation process is increased, a high-permeability channel is plugged, and the spread is enlarged; the water-soluble viscosity reducer is characterized in that after the crude oil is subjected to an emulsification reaction, the apparent viscosity of the generated emulsified oil component is greatly reduced, the oil phase flowing capability is improved, the saturation of residual oil in partial pores in a swept area is reduced, and the oil washing efficiency is improved; finally, due to the synergistic effect of the chemical agents, the recovery ratio of the analog computation temperature-sensitive composite profile control and flooding system is increased by more than one chemical agent, and the single flooding of more than two chemical agents is the sum of the recovery ratio and the amplification.
Simulation results show that the characteristics of the temperature-sensitive composite profile control and flooding system have very obvious influence on oil displacement efficiency, effectiveness rules and development effects, and the characteristics must be fully paid attention to the actual oil reservoir numerical simulation research so as to accurately evaluate the oil field development potential, deepen the oil displacement rules of the temperature-sensitive composite profile control and flooding system, obtain a better oil reservoir injection and production scheme and guide the optimal deployment of the oil field development scheme.
In this embodiment, when considering the characteristics of the temperature-sensitive composite profile control and flooding system, the specific embodiment process of the method steps may refer to embodiment one, and this embodiment is not repeated herein.
EXAMPLE III
Fig. 6 is a connection block diagram of a reservoir injection and production optimization apparatus 200 according to an embodiment of the present disclosure, where the apparatus 200 shown in fig. 6 includes:
a model building module 201, wherein the model building module 201 is configured to build a reservoir exploitation model based on reservoir parameters, and obtain an initial data field of each grid block in the reservoir exploitation model, wherein the data fields include a saturation data field, a pressure data field, a temperature data field, a viscosity data field, and a relative permeability data field;
a first data acquisition module 202, wherein the first data acquisition module 202 is configured to acquire an accumulated flow of each grid block in the reservoir exploitation model, and obtain a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow;
a second data obtaining module 203, wherein the second data obtaining module 203 is configured to obtain a water phase first viscosity data field in each grid block according to a relation model of water phase viscosity and temperature change and temperature-sensitive plugging agent component concentration;
a third data acquisition module 204, wherein the third data acquisition module 204 is configured to obtain an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field, and an aqueous phase second saturation data field in each grid block according to a chemical reaction relationship model of viscosity reducer components in the aqueous phase and crude oil components in the oil phase;
a fourth data obtaining module 205, where the fourth data obtaining module 205 is configured to obtain a first water phase relative permeability data field in each grid block according to a relational model of adsorption amount per unit pore volume of a temperature-sensitive plugging modifier component in the water phase and change in relative permeability of the water phase;
a fifth data acquisition module 206, said fifth data acquisition module 206 configured to obtain a first oil phase relative permeability data field according to a model of a variation of the oil phase relative permeability data field with number of capillaries;
a sixth data acquisition module 207, the sixth data acquisition module 207 configured to obtain updated data fields from the first saturation data field, the first temperature data field, and the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field, and the water phase second saturation data field, the first water phase relative permeability data field, the first oil phase relative permeability data field;
a control module 208, wherein the control module 208 is configured to control the reservoir exploitation model to perform iterative computation within a preset time according to the updated data field replacing the initial data field in the reservoir exploitation model, and obtain a second water-phase relative permeability and a second oil-phase relative permeability;
an optimization module 209, the optimization module 209 configured to optimize reservoir injection and production based on the second water phase relative permeability and the second oil phase relative permeability.
Further, the model building module 201 builds a reservoir exploitation model based on the reservoir parameters and the calculation formula (1).
Further, the model building module 201 builds an oil reservoir exploitation model based on the oil reservoir parameters, and obtains an initial data field of each grid block in the oil reservoir exploitation model, including: and acquiring a data field of all components of each phase of each grid block in the oil reservoir exploitation model.
Further, the acquiring a cumulative flow of each grid block in the reservoir exploitation model by the first data acquiring module 202, and acquiring a first saturation data field, a first temperature data field, and a first pressure data field in each grid block according to the cumulative flow includes:
respectively acquiring the flow of all components of each phase of each grid block in each direction according to the pressure data field, and respectively acquiring the accumulated flow of each phase of each grid block in all directions according to the flow;
respectively acquiring a first saturation data field, a first temperature data field and a first pressure data field of each phase of each grid block in all directions according to the accumulated flow and the state equation of each phase of each grid block in all directions;
wherein the accumulated flow rate includes accumulating the total mass of fluid passing through each phase in each grid block X, Y, Z and the mass of all components in each grid block at a time step.
Further, the second data obtaining module 203 obtains the first viscosity data field of the water phase in each grid block according to the relation model between the viscosity of the water phase and the concentration and temperature change of the temperature-sensitive plugging agent component, and the method includes:
and (3) obtaining a first viscosity field of the water phase in each grid block based on a calculation formula (6) according to the component viscosity of the temperature-sensitive plugging agent and the component viscosity of the water phase after the temperature-sensitive plugging agent is added into each grid block.
Further, the third data obtaining module 204 obtains, according to the chemical reaction relationship model between the viscosity reducer component in the water phase and the raw oil component in the oil phase, a second viscosity data field of the oil phase, a second saturation data field of the oil phase, a second viscosity data field of the water phase, and a second saturation data field of the water phase in each grid block, including:
and obtaining a chemical reaction formula of the viscosity reducer component in the water phase and the original oil component in the oil phase in the chemical reaction process, wherein a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field are arranged in each grid block.
Further, the fourth data obtaining module 205 obtains the first water phase relative permeability data field of the water phase in each grid block according to the relation model of the adsorption amount of the temperature-sensitive plugging agent component in the unit pore volume and the change of the water phase relative permeability, including:
and (3) acquiring a first water phase relative permeability data field in each grid block based on a calculation formula (9) according to the adsorption quantity of the temperature-sensitive plugging agent component in the water phase of each grid in unit pore volume and the water phase relative permeability.
The specific embodiment process of the above method steps can be referred to in the first embodiment and the second embodiment, and the detailed description of the embodiment is not repeated herein.
Example four
The present embodiment further provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., on which a computer program is stored, where the computer program, when executed by a processor, may implement the method steps of the first embodiment and the second embodiment, and no repeated description is provided herein.
EXAMPLE five
An electronic device provided in an embodiment of the present application may include: the device comprises a processor, a memory and a communication connection between the processor and the memory.
The memory stores a computer program, and when the program is executed by the processor, the program may perform all or part of the steps of the reservoir injection-production optimization method according to the first embodiment.
Specifically, the Processor may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is configured to execute the reservoir injection and production optimization method in the first embodiment.
Specifically, the Memory may be implemented by any type of volatile or nonvolatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk.
In summary, the present application provides a method, an apparatus, a storage medium, and an electronic device for optimizing injection and production of an oil reservoir, where the method includes: step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the data field comprises a saturation data field, a pressure data field, a temperature data field, a viscosity data field and a relative permeability data field; step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow; step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change; step S140: obtaining an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field and an aqueous phase second saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer component in the aqueous phase and the raw oil component in the oil phase; step S150: acquiring a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of temperature-sensitive plugging agent components in the water phase in unit pore volume and the change of the water phase relative permeability; step S160, obtaining a first oil phase relative permeability data field according to a variation relation model of the oil phase relative permeability data field along with the number of capillary tubes; step S170: obtaining updated data fields according to the first saturation data field, the first temperature data field, the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field, the water phase second saturation data field, the first water phase relative permeability data field and the first oil phase relative permeability data field; step S180: replacing the initial data field in the step S120 with the updated data field, and circularly executing the steps S120 to S170 within preset time to obtain a second water phase relative permeability and a second oil phase relative permeability; step S190: and optimizing the injection and the production of the oil reservoir based on the relative permeability of the second water phase and the relative permeability of the second oil phase.
The method comprises the steps of establishing an oil reservoir exploitation model based on oil reservoir parameters, representing the change rule of viscosity after the temperature-sensitive plugging agent component exists in each grid block through a relation model of water phase viscosity, temperature-sensitive plugging agent component concentration and temperature change, representing a chemical viscosity reduction process through a chemical relation model of water-soluble viscosity reducer components in the water phase and original components in the oil phase, correcting the change rule of a permeability curve along with the change relation model of the improved capillary number of an oil phase relative permeability curve, updating a data field in each grid in the iterative calculation process of the oil reservoir exploitation model, improving the accuracy of oil reservoir injection exploitation under the influence of the characteristics of a sensitive composite injection-displacement system, improving the accuracy of numerical simulation prediction results of chemical viscosity reduction and oil displacement effects of the water-soluble viscosity reducer, ensuring the accuracy and reliability of oil reservoir injection exploitation, and reasonably optimizing oil field development technical policies, The method can accurately evaluate the oil reservoir to improve the recovery efficiency potential and effectively make an oil field development scheme to provide powerful support.
In the embodiments provided in the present application, it should be understood that the disclosed method can be implemented in other ways. The above-described method embodiments are merely illustrative.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although the embodiments disclosed in the present application are described above, the above descriptions are only for the convenience of understanding the present application, and are not intended to limit the present application. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the disclosure as defined by the appended claims.

Claims (10)

1. A reservoir injection-production optimization method, comprising:
step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the data field comprises a saturation data field, a pressure data field, a temperature data field, a viscosity data field and a relative permeability data field;
step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow;
step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change;
step S140: obtaining an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field and an aqueous phase second saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer component in the aqueous phase and the raw oil component in the oil phase;
step S150: acquiring a first water phase relative permeability data field in each grid block according to a relation model of the adsorption capacity of temperature-sensitive plugging agent components in the water phase in unit pore volume and the change of the water phase relative permeability;
step S160: obtaining a first oil phase relative permeability data field according to a change relation model of the oil phase relative permeability data field along with the number of capillary tubes;
step S170: obtaining updated data fields according to the first saturation data field, the first temperature data field, the first pressure data field, the water phase first viscosity data field, the oil phase second saturation data field, the water phase second viscosity data field, the water phase second saturation data field, the first water phase relative permeability data field and the first oil phase relative permeability data field;
step S180: replacing the initial data field in the step S120 with the updated data field, and circularly executing the steps S120 to S170 within preset time to obtain a second water phase relative permeability and a second oil phase relative permeability;
step S190: and optimizing the injection and the production of the oil reservoir based on the relative permeability of the second water phase and the relative permeability of the second oil phase.
2. The method of claim 1, wherein the modeling reservoir production based on reservoir parameters comprises:
the method is established based on the following calculation formula:
Figure FDA0002492153750000021
wherein, FiRepresenting a convection term, AiRepresents the accumulation phase, BiAnd (3) representing a yield item, t represents time, and the value range of i is 3-4.
3. The method according to claim 1, wherein the step S110: establishing an oil reservoir exploitation model based on oil reservoir parameters, and acquiring an initial data field of each grid block in the oil reservoir exploitation model, wherein the method comprises the following steps: and acquiring a data field of all components of each phase of each grid block in the oil reservoir exploitation model.
4. The method according to claim 1, wherein the step S120: acquiring the accumulated flow of each grid block in the oil reservoir exploitation model, and acquiring a first saturation data field, a first temperature data field and a first pressure data field in each grid block according to the accumulated flow, wherein the method comprises the following steps:
respectively acquiring the flow of all components of each phase of each grid block in each direction according to the pressure data field, and respectively acquiring the accumulated flow of each phase of each grid block in all directions according to the flow;
respectively acquiring a first saturation data field, a first temperature data field and a first pressure data field of each phase of each grid block in all directions according to the accumulated flow and the state equation of each phase of each grid block in all directions;
wherein the accumulated flow rate includes accumulating the total mass of fluid passing through each phase in each grid block X, Y, Z and the mass of all components in each grid block at a time step.
5. The method according to claim 1, wherein the step S130: obtaining a first viscosity data field of the water phase in each grid block according to a relation model of the water phase viscosity, the component concentration of the temperature-sensitive plugging agent and the temperature change, wherein the first viscosity data field comprises:
obtaining a first viscosity field of the water phase in each grid block according to the component viscosity of the temperature-sensitive plugging agent and the component viscosity of the water phase after the temperature-sensitive plugging agent is added into each grid block on the basis of the following calculation formula:
Figure FDA0002492153750000022
wherein, muaqThe water phase mixing viscosity is shown in the specification,
Figure FDA0002492153750000023
wprepresents the molar concentration of the polymer,. mu.wDenotes the viscosity of the aqueous phase, M denotes the mass of fluid in the reservoir, μp(C, T) represents the viscosity of the temperature-sensitive plugging agent, ncThe number of components of the water phase is represented, S is a preset range, the value range of i is 3-4, and w isiRepresents the mole fraction of the i component of the water phase, muiRepresents the viscosity of the i component of the water phase.
6. The method according to claim 1, wherein the step S140: obtaining a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field in each grid block according to a chemical reaction relation model of the viscosity reducer components in the water phase and the raw oil components in the oil phase, wherein the second oil phase viscosity data field, the second oil phase saturation data field, the second water phase viscosity data field and the second water phase saturation data field comprise:
and obtaining a chemical reaction formula of the viscosity reducer component in the water phase and the original oil component in the oil phase in the chemical reaction process, wherein a second oil phase viscosity data field, a second oil phase saturation data field, a second water phase viscosity data field and a second water phase saturation data field are arranged in each grid block.
7. The method according to claim 1, wherein the step S150: obtaining a first water phase relative permeability data field of the water phase in each grid block according to a relation model of the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase in unit pore volume and the change of the water phase relative permeability, wherein the data field comprises:
according to the adsorption capacity of the temperature-sensitive plugging adjusting agent component in the water phase of each grid in unit pore volume and the relative permeability of the water phase, acquiring a first water phase relative permeability data field in each grid block based on the following calculation formula:
Figure FDA0002492153750000031
wherein k iswIndicates the effective permeability of the aqueous phase after plugging, krwIs the water phase permeability, kabsDenotes the absolute permeability of the rock, RkwRepresenting a water phase permeability reduction factor.
8. An oil reservoir injection-production optimization device, comprising:
a model building module configured to build a reservoir mining model based on reservoir parameters, obtaining an initial data field for each grid block in the reservoir mining model, wherein the data fields include a saturation data field, a pressure data field, a temperature data field, a viscosity data field, and a relative permeability data field;
a first data acquisition module configured to acquire an accumulated flow of each grid block in the reservoir exploitation model, and obtain a first saturation data field, a first temperature data field, and a first pressure data field in each grid block according to the accumulated flow;
a second data acquisition module configured to obtain a water phase first viscosity data field in each grid block according to a relational model of water phase viscosity and temperature-sensitive plugging agent component concentration and temperature change;
a third data acquisition module configured to obtain an oil phase second viscosity data field, an oil phase second saturation data field, an aqueous phase second viscosity data field, and an aqueous phase second saturation data field in each grid block according to a chemical reaction relationship model of viscosity reducer components in the aqueous phase and crude oil components in the oil phase;
a fourth data acquisition module configured to acquire a first water phase relative permeability data field in each grid block according to a relational model of changes in adsorption amount of temperature-sensitive plugging agent components in a water phase in a unit pore volume and relative permeability of the water phase;
a fifth data acquisition module configured to obtain a first oil-phase relative permeability data field according to a model of a variation of the oil-phase relative permeability data field with the number of capillaries;
a sixth data acquisition module configured to obtain updated data fields from the first saturation data field, first temperature data field, and first pressure data field, the aqueous phase first viscosity data field, the oil phase second viscosity data field, oil phase second saturation data field, aqueous phase second viscosity data field, and aqueous phase second saturation data field, first aqueous phase relative permeability data field, first oil phase relative permeability data field;
the control module is configured to replace the initial data field in the oil reservoir exploitation model according to the updated data field, and control the oil reservoir exploitation model to perform iterative computation within a preset time to obtain a second water-phase relative permeability and a second oil-phase relative permeability;
an optimization module configured to optimize a reservoir injection and production scheme based on the second water phase relative permeability and the second oil phase relative permeability.
9. A storage medium storing a computer program executable by one or more processors to perform the method of reservoir stimulation optimization according to any one of claims 1 to 7.
10. An electronic device comprising a memory and a processor, the memory having a computer program stored thereon, the memory and the processor being communicatively coupled to each other, the computer program, when executed by the processor, performing the method of reservoir stimulation optimization as defined in any one of claims 1 to 7.
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