Oil reservoir microbial oil extraction and displacement numerical simulation method and system, electronic equipment and medium

Abstract

The invention relates to an oil reservoir microbial oil extraction and displacement numerical simulation method, system electronic equipment and a medium, and belongs to the technical field of oil and gas development. The method comprises the following steps: constructing an oil reservoir microorganism reaction kinetic equation according to an experiment result of an oil reservoir microorganism ternary oil recovery system; based on production dynamic history fitting in the steam injection development stage, oil reservoir characteristic parameters after steam flooding are determined; based on the oil reservoir microorganism reaction kinetic equation, the oil reservoir three-dimensional geologic model and the oil reservoir characteristic parameters after steam flooding, oil reservoir microorganism cold production oil displacement is simulated; and obtaining an oil reservoir microbial cold production oil displacement scheme according to the simulation result of microbial cold production oil displacement. According to the method, the oil reservoir microbial reaction kinetic equation is determined, then oil reservoir microbial oil displacement numerical simulation is achieved, meanwhile, the steam injection development stage production dynamic history fitting technology is combined, oil reservoir characteristic parameters after steam displacement are determined, and the actual oil reservoir condition is fully reduced during oil reservoir microbial oil displacement digital simulation.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas development technology, and specifically relates to a numerical simulation method for reservoir microbial recovery and displacement, system electronic equipment, and media. Background Technology

[0002] Studies have shown that oil reservoirs in areas unaffected or minimally affected by steam contain abundant oil-producing bacteria, providing a basis for endogenous microbial mobilization. Utilizing microorganisms to replace steam in crude oil development can create a green, low-carbon, and economically efficient crude oil extraction method. However, due to the complex microbial community structure and residual oil distribution after steam displacement, the effectiveness of microbial enhanced oil recovery (MEOR) varies significantly across different regions, and effective methods for controlling injection and production parameters in field implementation are lacking. To improve the efficiency of parameter control in field MEOR implementation, numerical simulation technology is generally used to establish reasonable injection and production parameters and control strategies for MEOR under different residual oil distribution patterns after steam injection development. This provides guidance for field MEOR implementation, thereby improving the oil displacement efficiency at different development stages of MEOR cold recovery.

[0003] Microbial enhanced oil recovery (DEOR) in the later stages of shallow crude oil steam injection development faces two main challenges. Challenge 1: Due to the high-temperature displacement effect of steam, the types and abundance of oil-producing bacteria decrease after steam injection in different areas, and their degradation function declines, making it more difficult to reactivate and reuse endogenous bacteria within the reservoir. This necessitates simulation and optimization of a reasonable pretreatment process for the microbial community. Challenge 2: The development of water washing channels formed by steam leads to a more fragmented state of residual oil, requiring optimization of well network adjustments and water flooding / channeling control, among other technologies, to improve the efficiency of DEOR. However, existing numerical simulation techniques for microbial cold recovery lack supporting technologies for improving DEOR efficiency under the complex microbial community structure and residual oil conditions in the later stages of crude oil steam injection development. Summary of the Invention

[0004] To address the above problems, this invention provides a numerical simulation method for reservoir microbial enhanced oil recovery and displacement, as well as system electronic equipment and media.

[0005] The first objective of this invention is to provide a numerical simulation method for reservoir microbial enhanced oil recovery (EOR), comprising:

[0006] Based on the experimental results of the reservoir microbial ternary oil recovery system, a reservoir microbial reaction kinetic equation was constructed.

[0007] Based on the historical fitting of production dynamics during the steam injection development stage, characteristic parameters of the reservoir after steam flooding were determined.

[0008] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reservoir microbial cold recovery oil displacement was simulated.

[0009] Based on the simulation results of microbial cold recovery oil recovery, a microbial cold recovery oil recovery scheme for oil reservoirs was obtained.

[0010] In a specific embodiment of the present invention, the step of constructing reservoir microbial reaction kinetic equations based on the experimental results of the reservoir microbial ternary oil recovery system includes:

[0011] Experiments were conducted on a ternary oil recovery system based on reservoir microorganisms.

[0012] Based on the experimental results of the reservoir microbial ternary oil recovery system, the microbial reaction kinetic components and parameters of each component in the reservoir hydrocarbon degradation and directed activation mechanism were determined.

[0013] By combining the microbial reaction kinetic components of reservoir hydrocarbon degradation and directed activation mechanisms, a reservoir microbial reaction kinetic equation is established.

[0014] In a specific embodiment of the present invention, the experiment of the reservoir microbial ternary oil recovery system includes:

[0015] Microbial functional bacteria screening experiment based on the properties of crude oil in the target reservoir and the characteristics of microbial community structure in the reservoir environment;

[0016] Activating nutrient screening experiments were conducted based on the selected functional microorganisms and crude oil from the target reservoir.

[0017] An auxiliary activator screening experiment was conducted based on the selected functional microorganisms, the selected activating nutrients, and the target reservoir crude oil.

[0018] In a specific embodiment of the present invention, the microbial reaction kinetic components include microorganisms, heavy oil, light oil, nutrients, carbon source, biosurfactant, foam, methane, carbon dioxide and water.

[0019] In a specific embodiment of the present invention, the reservoir microbial reaction kinetic equations include: microbial reproduction reaction kinetic equations, microbial degradation equations of heavy oil components, microbial self-generated foam oil equations, foam oil elimination and destruction equations, and microbial death and hydrolysis equations.

[0020] In a specific embodiment of the present invention, the reservoir characteristic parameters after steam flooding include the reserves of each oil layer, the amount produced, the remaining oil reserves, and the degree of recovery.

[0021] In a specific embodiment of the present invention, based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, a simulation of reservoir microbial cold recovery and oil displacement is performed, including:

[0022] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding were simulated.

[0023] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different injection and production well patterns in reservoir microbial cold recovery were simulated under the same reservoir pretreatment process parameters.

[0024] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different microbial circulation injection and production process parameters in reservoir microbial cold recovery were simulated under the same reservoir pretreatment process parameters and injection-production well pattern.

[0025] In a specific embodiment of the present invention, the step of simulating the reinjection and displacement effects of different reservoir pretreatment process parameters in microbial recovery and flooding based on reservoir microbial reaction kinetics equations, three-dimensional geological models of the reservoir, and reservoir characteristic parameters after steam flooding includes:

[0026] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reinjection and displacement effect of single wells with different pretreatment injection amounts of microorganisms before microbial reinjection and displacement was simulated under the same pretreatment simmering time.

[0027] Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different pretreatment well-steaming times were simulated under the same pretreatment injection volume of microorganisms in a single well before microbial reinjection and displacement.

[0028] Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different sealing pretreatment schemes around the injection well were simulated under the same microbial pretreatment injection volume and the same well-sinking time before microbial reinjection and displacement.

[0029] In a specific embodiment of the present invention, the step of simulating the microbial cyclic injection-production process in reservoir microbial cold recovery based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters and injection-production well network, includes:

[0030] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different injection rates in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, injection-production well pattern, production-injection ratio, reinjection fluid bacterial concentration, reinjection temperature, and injection method.

[0031] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different production-injection ratios in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, reinjection fluid bacterial concentration, reinjection temperature, and injection method.

[0032] Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different reinjection fluid bacterial concentrations in the microbial circulation injection and production process was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature, and injection method.

[0033] Based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different injection methods in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature and reinjection fluid bacterial concentration.

[0034] Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different reinjection temperatures in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection fluid bacterial concentration, and injection method.

[0035] In a specific embodiment of the present invention, obtaining a reservoir microbial cold recovery oil recovery scheme based on the simulation results of microbial cold recovery oil recovery includes:

[0036] Based on the simulation results of reservoir pretreatment process, the process parameters of reservoir pretreatment process in microbial recovery and flooding are determined.

[0037] Based on the simulation results of injection-production well pattern adjustment, the injection-production well pattern in reservoir microbial recovery and flooding is determined;

[0038] Based on the simulation results of the microbial cyclic injection and production process in microbial enhanced oil recovery (EOR), the process parameters of the microbial cyclic injection and production process in EOR are determined.

[0039] The second objective of this invention is to provide a numerical simulation system for reservoir microbial enhanced oil recovery and displacement, comprising:

[0040] The dynamics module is used to construct reservoir microbial reaction kinetic equations based on the experimental results of the reservoir microbial ternary oil recovery system.

[0041] Feature module: used to determine reservoir characteristic parameters after steam flooding based on the historical fitting of production dynamics during the steam injection development stage;

[0042] Simulation module: Used to simulate reservoir microbial cold recovery based on reservoir microbial reaction kinetic equations, three-dimensional geological models of the reservoir, and reservoir characteristic parameters after steam flooding;

[0043] Acquisition Module: Used to obtain reservoir microbial cold recovery and oil displacement schemes based on the simulation results of microbial cold recovery and oil displacement.

[0044] In a specific embodiment of the present invention, the simulation module includes a pretreatment process simulation submodule, an injection-production well network simulation submodule, and a circulation process simulation submodule;

[0045] The pretreatment process simulation submodule is used to simulate the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding.

[0046] The injection-production well network simulation submodule is used to simulate the reinjection and displacement effects of different injection-production well networks in reservoir microbial cold recovery and displacement under the same reservoir pretreatment process parameters, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding.

[0047] The circulation process simulation submodule is used to simulate the reinjection and displacement effects of different microbial circulation injection and production process parameters in reservoir microbial cold recovery, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters and injection-production well pattern.

[0048] A third object of the present invention is to provide an electronic device comprising: a processor coupled to a memory;

[0049] The memory is used to store computer programs;

[0050] The processor is configured to execute the computer program stored in the memory, so that the electronic device performs the method described above.

[0051] A fourth object of the present invention is to provide a computer-readable storage medium storing a program or instructions that, when executed on a computer, cause the computer to perform the method described above.

[0052] The beneficial effects of this invention are:

[0053] The present invention relates to a reservoir microbial enhanced oil recovery (EOR) numerical simulation method, system electronic equipment, and media. Based on experiments with a ternary reservoir microbial enhanced oil recovery system, the method determines the reservoir microbial reaction kinetic equation, thereby realizing the numerical simulation of reservoir microbial enhanced oil recovery. At the same time, it combines the production dynamic history fitting technology of the steam injection development stage to determine the reservoir characteristic parameters after steam flooding, so as to improve the full reproduction of the actual reservoir conditions during the numerical simulation of reservoir microbial enhanced oil recovery and improve the accuracy of subsequent numerical simulations.

[0054] Secondly, in the subsequent numerical simulation of reservoir microbial enhanced oil recovery, different reservoir pretreatment process parameters, different injection and production well patterns and microbial circulation injection and production process parameters were simulated respectively, thereby obtaining a better reservoir microbial enhanced oil recovery scheme.

[0055] The method provided by this invention was implemented in the typical Keqian 10 well area of ​​the oil reservoir and the following findings were made:

[0056] After the numerical simulation scheme was implemented, the effective functional bacteria concentration in the produced liquid reached a consistency rate of over 80%.

[0057] After optimizing the bacterial concentration of the produced fluid from the microbial enhanced oil reservoir, it is reinjected to reduce the cost of microbial enhanced oil recovery (below $45 / barrel) and does not generate waste liquid discharge.

[0058] Microbial cold extraction reduces steam input, resulting in significant carbon reduction, energy saving, and efficiency improvement;

[0059] Microbial pretreatment technology is used, along with hot water at a temperature not exceeding 60℃ for microbial reinjection and displacement, which effectively improves the efficiency of microbial oil recovery under the complex microbial community structure and residual oil distribution conditions after heavy oil steam injection development, increasing the recovery rate by 5%-10%.

[0060] The application of the present invention can realize the secondary development of the remaining reserves of heavy oil shut-down wells.

[0061] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1A flowchart of a numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to an embodiment of the present invention is shown;

[0064] Figure 2 This diagram shows the remaining oil saturation field of the second reservoir in the Keqian 10 well area, a typical oil reservoir according to an embodiment of the present invention.

[0065] Figure 3 This paper presents a comparison of daily and cumulative oil production under different injection volumes of microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0066] Figure 4 This diagram illustrates the relationship between cumulative oil production and recovery rate under different injection volumes of microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0067] Figure 5 This diagram illustrates the molar ratio distribution of microorganisms in a typical reservoir, Keqian 10 well area, under different pretreatment injection volumes for 60 days of well simmering, according to an embodiment of the present invention.

[0068] Figure 6 This diagram shows the molar ratio distribution of biogas in a typical reservoir, Keqian 10 well area, under different pretreatment injection volumes for 60 days of well simmering, according to an embodiment of the present invention.

[0069] Figure 7 This paper presents a comparison of daily and cumulative oil production from microbial displacement at different well-sinking times in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0070] Figure 8 This diagram illustrates the relationship between cumulative oil production and recovery rate of microbial displacement at different well-sinking times in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0071] Figure 9 A plan view showing the distribution of microbial molar ratios at different well-sinking times in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0072] Figure 10 A plan view showing the biogas molar ratio distribution at different simmering times in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0073] Figure 11 A comparison diagram of crude oil viscosity at different incubation times in an indoor experiment of an activation system for crude oil from the Qigu Formation reservoir in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention, is shown.

[0074] Figure 12 A daily oil production comparison chart of the injection well plugging scheme of the reverse five-point well pattern in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention, is shown.

[0075] Figure 13This diagram illustrates the relationship between cumulative oil production and recovery rate of microbial displacement in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0076] Figure 14 This figure shows a comparison of daily oil production from microbial displacement at different plugging radii in the typical reservoir Keqian 10 well area according to an embodiment of the present invention;

[0077] Figure 15 A comparison chart of microbial displacement oil recovery rates at different plugging radii is shown in the typical reservoir Keqian 10 well area according to an embodiment of the present invention;

[0078] Figure 16 A comparison chart of daily oil production from microbial reinjection and displacement of the reverse nine-point and reverse five-point well networks in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0079] Figure 17 A comparison chart of cumulative oil production from microbial reinjection and displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0080] Figure 18 The diagram shows the microbial concentration field after 6 months of displacement using a reverse nine-spot well pattern and a reverse five-spot well pattern in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0081] Figure 19 This diagram shows the biogas concentration field after 6 months of displacement using a reverse nine-spot well pattern and a reverse five-spot well pattern in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0082] Figure 20 A comparison chart of daily oil production indicators in 2020 and 2021 for the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0083] Figure 21 This diagram shows a comparison of daily oil production from microbial displacement at different injection rates in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0084] Figure 22 A comparison chart of daily oil production at different production-injection ratios in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0085] Figure 23 This diagram illustrates the relationship between the production-injection ratio and the cumulative oil production and recovery rate during the prediction period in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0086] Figure 24 This figure shows a comparison of daily oil production from different injection fluid concentrations and microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0087] Figure 25This figure shows a comparison of cumulative oil production from different injection fluid bacterial concentrations and microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0088] Figure 26 The relationship between cumulative oil production and recovery rate of different reinjection fluid bacterial concentrations and microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention is shown.

[0089] Figure 27 This figure shows a comparison of the average daily oil production per well in the typical reservoir Keqian 10 well area according to an embodiment of the present invention;

[0090] Figure 28 This figure shows a comparison of daily oil production from different displacement methods using microbial displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0091] Figure 29 This diagram shows the microbial concentration field during 6 months of continuous microbial reinjection and displacement in the Keqian 10 well area of ​​a typical reservoir according to an embodiment of the present invention.

[0092] Figure 30 This diagram shows the microbial concentration field during 12 months of continuous microbial reinjection and displacement in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0093] Figure 31 This diagram shows the biogas concentration field during 6 months of continuous microbial reinjection and displacement in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0094] Figure 32 This diagram shows the biogas concentration field during 12 months of continuous microbial reinjection and displacement in the Keqian 10 well area, a typical reservoir according to an embodiment of the present invention.

[0095] Figure 33 This figure shows a comparison of daily oil production from microbial displacement at different injection temperatures in the typical reservoir Keqian 10 well area according to an embodiment of the present invention.

[0096] Figure 34 A framework diagram of a reservoir microbial enhanced oil recovery and displacement numerical simulation system according to an embodiment of the present invention is shown;

[0097] Figure 35 A frame diagram of an electronic device according to an embodiment of the present invention is shown;

[0098] In the diagram: Power module 1; Feature module 2; Simulation module 3; Acquisition module 4; Electronic device 300; Processor 301; Memory 302. Detailed Implementation

[0099] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0100] like Figure 1 As shown, a numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to an embodiment of the present invention includes:

[0101] S1. Based on the experimental results of the reservoir microbial ternary oil recovery system, construct the reservoir microbial reaction kinetic equation;

[0102] S2. Based on the historical fitting of production dynamics during the steam injection development stage, determine the characteristic parameters of the reservoir after steam flooding.

[0103] S3. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reservoir microbial cold recovery oil displacement was simulated.

[0104] S4. Based on the simulation results of microbial cold recovery and oil displacement, obtain the reservoir microbial cold recovery and oil displacement scheme.

[0105] In some embodiments of the present invention, step S1 includes:

[0106] S1-1. Conduct experiments on a reservoir microbial ternary oil recovery system;

[0107] S1-2. Based on the experimental results of the reservoir microbial ternary oil recovery system, determine the microbial reaction kinetic components and parameters of each component in the reservoir hydrocarbon degradation and directed activation mechanism.

[0108] S1-3. Microbial reaction kinetics components that combine reservoir hydrocarbon degradation and directional activation mechanisms are used to establish reservoir microbial reaction kinetic equations.

[0109] In step S1-1, the experiment of the reservoir microbial ternary enhanced oil recovery system includes:

[0110] i. Screening experiments for functional microorganisms based on the properties of crude oil in the target reservoir and the characteristics of the microbial community structure in the reservoir environment:

[0111] For example, the microbial functional bacteria screening experiment:

[0112] Experimental conditions: 5% crude oil (by mass), 5% bacterial inoculum (logarithmic growth phase), cultured in a shaker at 37℃ and 220r for one week;

[0113] Screening criteria: After shaking culture, the crude oil is selected based on its emulsification effect, with the selection criteria being that the aqueous phase is turbid and the crude oil is dispersed into an emulsion.

[0114] ii. Screening experiments for activating nutrients were conducted based on the selected functional microorganisms and the target reservoir crude oil:

[0115] For example, the activator screening experiment:

[0116] Experimental conditions: 5% crude oil inoculum, 5% (logarithmic growth phase), cultured on a shaker at 37℃ and 220 rpm for one week;

[0117] Screening criteria: Add a single activating nutrient and observe the changes in crude oil properties. Test the growth characteristics, emulsification characteristics and bacterial concentration of microbial agents under different activating nutrient conditions. Screening is carried out using emulsification and dispersion effect, bacterial concentration and degradation rate of crude oil as evaluation indicators.

[0118] iii. To better leverage the effects of microbial strains, indoor optimization of auxiliary activators was conducted. Based on the screened functional microorganisms and screened activating nutrients, oil products were evaluated using different strains + targeted activators + auxiliary activators. The optimal auxiliary activator was determined based on changes in crude oil composition, emulsification characteristics, crude oil degradation rate, and changes in interfacial tension after crude oil degradation.

[0119] Based on experimental data from the reservoir microbial ternary enhanced oil recovery system experiment, the microbial reaction kinetic components and parameters of each component in the reservoir hydrocarbon degradation and directed activation mechanism were determined, thus completing step S1-2:

[0120] For example, the microbial reaction kinetic components include microorganisms, heavy oil, light oil, nutrients, carbon source, biosurfactant, foam, methane, carbon dioxide and water, and the parameters of each component are shown in Table 1.

[0121] Table 1

[0122]

[0123] Based on step S1-2, and combining the microbial reaction kinetic components of the reservoir hydrocarbon degradation and directed activation mechanism, the reservoir microbial reaction kinetic equation is established, thus completing step S1-3:

[0124] Based on the requirements of establishing the simulation in the CMG thermal recovery and chemical flooding module of reservoir numerical simulation software (the requirements are well known in this technical field and will not be repeated here), reservoir microbial reaction kinetic equations are established to finely describe the production, reproduction, degradation, gas production and death processes of microorganisms, namely, microbial reproduction reaction kinetic equations, oil heavy component microbial degradation equations, microbial self-generated foam oil equations, foam oil elimination and collapse equations and microbial death and hydrolysis equations. For example, the microbial reproduction reaction kinetic equation is shown in equation (3), the oil heavy component microbial degradation equation is shown in equation (4), the microbial self-generated foam oil equation is shown in equation (5), the foam oil elimination and collapse equation is shown in equation (6), and the microbial death and hydrolysis equation is shown in equation (7).

[0125] Reaction Equation 1: Microorganisms multiply and produce surfactants and biogas;

[0126] Due to microorganisms (C 4-7 H 7-10 O 1-3 N), carbon source (C6H) 12 O6(1%)+C 18-60 H 30-116 O 2-5 (10%), biosurfactant (C) 16-32 H 30-58 O 7-13 The molecular formulas are all very complex. In the embodiments of this invention, the coefficients of the microbial reaction kinetic equation are mainly balanced by tracking the number of carbon atoms and the average molecular weight.

[0127] Among them, the average number of carbon atoms of microorganisms is 6, the average molecular weight is 120, the carbon source is a mixture of glucose and blended oil, the average number of carbon atoms is 28, the average molecular weight is 462, the average number of carbon atoms of surfactants is 32, the average molecular weight is 650, and the biogas is CH4 and CO2, both of which have 1 carbon atom and molecular weights of 16 and 44, respectively.

[0128] Therefore, the carbon atom equilibrium equation is shown in equation (1):

[0129] X1×M+Y1×28G+Z1×0H=A1×6M+B1×32S+C1×1J+D1×1E(1)

[0130] In equation (1), X1, Y1, Z1, A1, B1, C1 and D1 are coefficients to be determined, M represents microorganisms, G represents carbon source, H represents water, S represents surfactant, J represents methane and E represents carbon dioxide.

[0131] The molecular weight equilibrium equation is shown in equation (2):

[0132] X1×120M+Y1×462G+Z1×18H=A1×120M+B1×650S+C1×16J+D1×44E (2)

[0134] In equation (2), X1, Y1, Z1, A1, B1, C1 and D1 are coefficients to be determined, M represents microorganisms, G represents carbon source, H represents water, S represents surfactant, J represents methane and E represents carbon dioxide.

[0135] Without considering changes in oil layer temperature, the activation energy is 0, microbial reproduction is mainly affected by the concentration of nutrient solution, and the reaction order is 1.

[0136] Through calculation, the kinetic equation for the microbial reproduction response was determined as shown in equation (3):

[0137] 1.0Microbe+1.0Glucose+1.0NaNO3+5.723H2O→

[0138] 1.5Microbe+0.5Surf+3.0CO2+1.0NaNO3+3.0CH4(3)

[0139] In formula (3), Microbe represents microorganisms, Glucose represents nutrient solution, and Surf represents surfactant. Microbial degradation of heavy oil components (colloids, asphaltenes):

[0140] The molecular weight of crude oil obtained by WinPro fitting in the laboratory was 404.4. The experiment was conducted in the laboratory to determine the four components of crude oil. The heavy component (rubber and asphaltenes) was 36.8 wt% with an average molecular weight of 660, and the light component (saturated hydrocarbons and aromatic hydrocarbons) was 63.2 wt% with an average molecular weight of 330.

[0141] The microbial degradation equation for heavy oil components was calculated as shown in equation (4):

[0142] 1.0Microbe+1.0Hevy→1.0Microbe+2.0Lite (4)

[0143] In formula (4), Hevy is heavy oil and Lite is light oil;

[0144] Equation (4) has an activation energy of 0 without considering changes in oil layer temperature. During the degradation of heavy oil, the microorganisms phagocytose and break the chain, neither reproduce nor die, and the reaction order is 1.

[0145] Microbial self-generating foam oil:

[0146] After biogas is produced inside the formation, the light components of crude oil are more easily transported. Since each gas molecule has an equal probability of forming foam oil with light oil (only a physical change), the viscosity of the foam oil is significantly reduced. Without considering the merging of bubbles to form large bubbles, the foaming condition is that the molar percentage of the grid gas phase is greater than 50%. Since all biogas can foam, in order to reduce the reaction equations, it is assumed that each bubble is of the same type of component. The chemical equation (5) is still used in the CMG simulator:

[0147] 1.0CH4+1.0CO2+1.0Lite→2.0Foam (5)

[0148] In equation (5), Foam refers to foam;

[0149] Equation (5) has an activation energy of 0 and a reaction order of 1 if the temperature of the oil layer is not considered.

[0150] Foam oil elimination and destruction:

[0151] After bubbles are generated inside the formation, they migrate to the low-gas-content grid. When the gas phase molar percentage is less than 20%, the foam oil begins to break down until it disappears. At the same time, the gas concentration at that location gradually increases. The CMG simulator still uses chemical equation (6):

[0152] 2.0Foam→1.0CH4+1.0CO2+1.0Lite (6)

[0153] Equation (6) has an activation energy of 0 and a reaction order of 1 if the temperature of the oil layer is not considered.

[0154] Microbial death and hydrolysis are shown in equation (7):

[0155] 1.0 Microbe → 6.667 H2O (7)

[0156] Equation (7) has an activation energy of 0 and a reaction order of 1 if the temperature of the oil layer is not considered.

[0157] In step S2, the operation of fitting the production dynamic history during the steam injection development stage is exemplarily as follows:

[0158] i. Establish a three-dimensional geological model of the reservoir based on its geological parameters;

[0159] ii. Combining the reservoir's three-dimensional geological model and the numerical simulation model for steam injection development, as well as the historical production data of the reservoir's steam injection development stage, complete the dynamic historical fitting of the production during the steam injection development stage;

[0160] Purpose and Process of Historical Data Fitting: To verify the reliability of the established three-dimensional geological model of the reservoir and to conduct subsequent research, it is necessary to fit the steam injection and production history of the steam injection and production wells in the established three-dimensional geological model of the reservoir. The fitting parameters are the oil production and water production of a single well. Based on the analysis of the dynamic characteristics of steam injection and production wells and steam channeling characteristics in the three-dimensional geological model of the reservoir, parameters such as the endpoint values ​​of the expression for the flow conductivity and relative permeability of the steam channel are repeatedly adjusted. When the relative error of the three-dimensional geological model of the reservoir and the production of fluid and oil of a single well is less than 10%, the production history of the model is fitted, indicating that the geological model established in this simulation basically conforms to the actual situation of the reservoir, and its calculation results are reliable. The characteristic parameters of the target reservoir after steam flooding are obtained. The characteristic parameters of the reservoir after steam flooding include the reserves, production, remaining oil reserves, and recovery degree of each oil layer.

[0161] In this embodiment of the invention, the production dynamic history of a reservoir in a certain area (the typical reservoir Keqian 10 well area) was fitted during the steam injection development stage, and the results are shown in Table 2.

[0162] Table 2

[0163] Fitted output <![CDATA[Fitted production (×10 4 t)]]> <![CDATA[Actual output (×10 4 t)]]> Relative error (%) Cumulative liquid production 46.68 47.51 1.7 Cumulative oil production 6.97 7 0.4

[0164] Therefore, based on the data in Table 2, the historical fitting of the production dynamics during the steam injection development stage of the typical Keqian 10 well area was completed. At this time, the remaining oil saturation field map of the second reservoir in the typical Keqian 10 well area is as follows: Figure 2 As shown, by Figure 2 By determining the reserves, production, remaining oil reserves, and recovery rate of the second reservoir, and by analogy, the reserves, production, remaining oil reserves, and recovery rate of each reservoir in the typical Keqian 10 well area can be obtained. The obtained data is shown in Table 3, thus completing step S2.

[0165] Table 3

[0166]

[0167] After completing step S2, proceed to step S3, which includes:

[0168] S3-1. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, simulate the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding. That is, establish a reservoir microbial recovery and flooding digital simulation model by combining the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, and use the reservoir microbial recovery and flooding digital simulation model to simulate the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding.

[0169] Step S3-1 includes:

[0170] S3-1-i. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different pre-treatment injection volumes of microorganisms in a single well before microbial reinjection and displacement are simulated under the same pre-treatment well-sinking time. For example:

[0171] The reinjection and displacement effects of microbial pretreatment in single wells with an injection volume of 200-500 m³ before microbial reinjection and displacement are shown in the figure below. The daily oil production comparison for different injection volumes of microbial displacement is also shown in the figure. Figure 3 As shown in Figure a, the cumulative oil production from microbial displacement with different injection volumes... Figure 3 As shown in Figure b, the relationship between cumulative oil production and recovery rate under different injection volumes of microbial displacement is as follows: Figure 4 As shown in the figure, the molar ratio distribution of microorganisms after 60 days of well simmering with different pretreatment injection volumes is shown in the figure. Figure 5 As shown in the figure, the molar ratio distribution of biogas after 60 days of well simmering with different pretreatment injection volumes is as follows: Figure 6 As shown;

[0172] according to Figures 3-6 The simulation results shown indicate that the injection volume is between 300-400m³. 3 The results were good. After 60 days of pretreatment and well simmering, the microbial diffusion radius reached 25m, and the recovery rate was predicted to be around 12% in 5 years.

[0173] After microorganisms are injected into the formation, they are activated and multiply under formation conditions. The longer the well is shut-in, the larger the diffusion radius of the microorganisms. However, due to the limited pretreatment volume, it is necessary to make a comprehensive judgment based on the microbial reproduction rate, influence range, and reinjection displacement effect of different well shut-in times. That is, to proceed to step S3-1-ii, based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, to simulate the reinjection displacement effect of different pretreatment shut-in times under the same pretreatment injection volume of microorganisms in a single well before microbial reinjection displacement. For example:

[0174] The simulation compared the injection volume of 400m. 3 The effects of microbial reinjection and displacement under different well-sinking times are shown in the figure below. The daily oil production comparison chart for microbial displacement under different well-sinking times is as follows. Figure 7 As shown in Figure a, the cumulative oil production comparison chart for microbial displacement at different well-sinking times is as follows. Figure 7 As shown in Figure b, the relationship between cumulative oil production and recovery rate due to microbial displacement under different well-sinking times is as follows: Figure 8 As shown in the figure, the distribution of microbial molar ratios at different well-steaming times is as follows: Figure 9 As shown in the figure, the distribution of biogas molar ratio at different well-steaming times is shown in the figure. Figure 10 As shown;

[0175] according to Figures 7-10The simulation results show that the longer the well is shut-in time, the better the microbial oil displacement effect. When the well shut-in time is greater than 60 days, the diffusion rate of microorganisms slows down. When the well shut-in time is around 60 days, the predicted microbial cold recovery rate is 12%. Increasing the well shut-in time does not significantly improve the recovery rate.

[0176] Figure 11 The diagram shows a comparison of crude oil viscosity at different incubation times in the indoor experiment of the activation system of crude oil in the Qigu Formation reservoir of the Keqian 10 well area. The oil displacement effect data at different incubation times are shown in Table 4.

[0177] Table 4

[0178]

[0179] from Figure 11 As can be seen from the data, with the extension of the cultivation days (the cultivation days in the indoor experiment are equivalent to the well-sinking time in the field test or the microbial displacement data simulation), the crude oil emulsification and viscosity reduction characteristics are obvious, the crude oil components are transformed from high carbon chains to low carbon chains, and the degree of crude oil viscosity reduction gradually increases. The simulated oil displacement results show that the longer the well-sinking time, the better the microbial oil displacement effect. When the well-sinking time is about 60 days, the microbial cold recovery rate can reach 23.08%. Considering the differences between formation conditions and experimental conditions, and combined with the field test results in the Keqian 10 well area, the well-sinking time is designed to be between 2 and 3 months. The actual well opening time is determined according to the changes in oil well pressure and gas production.

[0180] The data in Table 4 shows that the longer the culture period (the culture period in the indoor experiment is equivalent to the well-clogging time in the field test or the microbial displacement data simulation), the better the microbial oil displacement effect. When the well-clogging time is about 60 days, the microbial cold recovery rate can reach 23.08%. Considering the differences between formation conditions and experimental conditions, and combined with the field test results in the Keqian 10 well area mentioned above, the well-clogging time is designed to be between 2 and 3 months. The actual well opening time is determined according to the changes in well pressure and gas production.

[0181] S3-1-iii. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different sealing pretreatment schemes for the steam channel around the injection well are simulated under the same pretreatment injection volume and the same well-sinking time for single wells before microbial reinjection and displacement. For example:

[0182] Using a reverse 5-point well pattern, direct microbial pretreatment and reinjection displacement were performed on the reinjection wells. The effects of this approach were compared with two other methods: directly applying microbial pretreatment and reinjection displacement to the injection wells using the reverse 5-point well pattern, and plugging the high-yield oil layers near the injection well. The daily oil production comparison chart for the reverse 5-point well pattern injection well plugging method is shown below. Figure 12 As shown, the relationship between cumulative oil production and recovery rate of pretreatment methods via microbial displacement is as follows: Figure 13 As shown;

[0183] from Figure 12 As can be seen from the data, sealing the high-permeability channels around the injection well can increase the range of microbial displacement and the probability of microorganisms coming into contact with the remaining oil in the formation, thereby increasing the utilization of the remaining oil.

[0184] from Figure 13 As can be seen from the data, during the 5-year production period, the microbial reinjection and displacement scheme using the plugging method produced a cumulative oil production of 31,049 tons, which was 9,283 tons more than the direct injection microbial displacement scheme, and improved the recovery rate by 4.46%.

[0185] A simulation comparing the microbial flooding efficiency of four different schemes with a plugging radius of 10-30m in the later stage of steam flooding reinjection wells with no plugging was conducted. The comparison included the effect of different plugging radii on the daily oil production replaced by microbial flooding. Figure 14 As shown in the figure, the comparison of microbial displacement oil recovery rates with different plugging radii is as follows: Figure 15 As shown in Table 5, the cumulative oil production and recovery rate over the 5-year prediction period for different plugging radii are compared.

[0186] Table 5

[0187]

[0188]

[0189] from Figure 14 , Figure 15 As can be seen from Table 4, the larger the plugging radius, the higher the cumulative oil production and the higher the recovery rate over the 5-year prediction period. When the plugging scale is greater than 20m, the increase in oil production decreases. Therefore, considering a recovery rate of 35-40%, the plugging radius should be 15-20m when microbial reinjection is used for displacement.

[0190] The reasons for the above steps S3-1-i and S3-1-ii are as follows: In the later stages of reservoir steam flooding, the distribution of microbial communities in the reservoir environment becomes complex due to the influence of high-temperature steam displacement. Different degrees of steam sweep and microbial reservoir conditions result in varying degrees of microbial reservoir conditions. In areas where steam displacement is relatively weak, there is a certain abundance of oil-producing functional bacteria in the formation environment. However, as the degree of steam displacement increases, the abundance of these bacteria decreases or even disappears completely. Considering the characteristics of changes in microbial community structure after reservoir steam injection development, a microbial reservoir pretreatment technology is adopted, and a reasonable microbial reservoir pretreatment process is designed to ensure that favorable conditions for dominant microbial reservoir conditions are formed in the reservoir environment, which is beneficial to improving the efficiency of microbial oil displacement.

[0191] The reason for the above step S3-1-iii is that the near-wellbore area of ​​injection and production wells is highly active, which increases the probability of microorganisms coming into contact with crude oil and improves the efficiency of subsequent microbial displacement. It is necessary to seal the gas channel and void volume that have been formed.

[0192] S3-2. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, the reinjection and displacement effects of different injection-production well patterns in reservoir microbial cold recovery are simulated, for example:

[0193] Numerical simulation studies of the Qigu Formation reservoir in the Keqian 10 well area show that after long-term steam drive, the steam injection wells and surrounding vertical wells are connected at different layers, the oil saturation is below 0.2, and the remaining oil is mainly distributed between wells or around early water-channeling wells.

[0194] The simulation compared the implementation of microbial reinjection displacement on the basis of the original steam-driven inverted nine-spot well pattern and the initial formation of an inverted five-spot well pattern by converting the corner wells of the original inverted nine-spot well pattern into an inverted five-spot well pattern. During the simulation, 400m³ of microbial injection was injected into a single well in the three-dimensional geological model of the reservoir. 3 After 60 days of microbial well-sealing, the well was reopened for production and reinjection, achieving a displacement effect of a production-injection ratio of 1.1. The comparison of daily oil production simulation results for microbial reinjection displacement in inverted nine-spot and inverted five-spot well patterns is shown in the figure below. Figure 16 As shown in the figure, the comparison of the simulation results (cumulative oil production) of microbial reinjection displacement in inverted nine-point and inverted five-point well patterns is as follows. Figure 17 As shown, the microbial concentration field diagrams after 6 months of displacement using the reverse nine-point well network and the reverse five-point well network are as follows. Figure 18 As shown, Figure 18 In the middle, 'a' represents the microbial concentration field diagram after six months of displacement using the anti-nine-point well network. Figure 18 In the image, b is the microbial concentration field map after 6 months of displacement using the inverted five-spot well pattern. The biogas concentration field maps after 6 months of displacement using the inverted nine-spot well pattern and the inverted five-spot well pattern are shown below. Figure 19 As shown, Figure 19 Map 'a' shows the biogas concentration field after June, created by the anti-nine-point well network displacement. Figure 19 Map b shows the biogas concentration field after 6 months of displacement using the anti-five-point well network.

[0195] from Figure 16-17 As can be seen, the residual oil saturation is low and the formation deficit is large within a certain range around the original steam injection wells of the reverse nine-point well network. Therefore, when the reverse nine-point well network is used for reinjection and displacement, the microorganisms flow along the original high-permeability channels during the displacement process, and the residual oil is less utilized, resulting in a long displacement time and low microbial oil displacement efficiency. However, after the well network is converted and the reverse five-point well network is used for displacement, the oil saturation around the original steam injection wells continues to decrease, and the residual oil around the newly injected microbial solution wells decreases significantly. This shows that the reverse five-point well network can better improve the utilization of residual oil in the formation and improve the oil displacement efficiency of microorganisms. In the 5-year simulation comparison, the reverse five-point well network produced a cumulative oil of 25,840 tons, with a recovery rate of 12.4%, which is 5,240 tons more than the reverse nine-point well network, increasing the recovery rate by 2.5%.

[0196] Figure 18-19As can be seen from the data, the microbial reach of the reverse five-point well pattern is larger than that of the reverse nine-point well pattern, therefore its oil displacement efficiency is higher than that of the reverse nine-point well pattern.

[0197] Furthermore, field microbial trials have shown that microbial reinjection and displacement using the reverse five-point well pattern can achieve good results. In 2018, a field trial of 9 injections and 23 productions using microbial cold recovery was implemented at stations 41#-44# in the southern part of the Keqian 10 well area. Based on the remaining oil distribution characteristics, the well pattern was adjusted, and the corner wells of the original reverse nine-point well pattern were converted for injection. The daily oil production indicators of the test area in 2020 and 2021 are shown in the following figure. Figure 20 As shown, from Figure 20 As can be seen, the average daily oil production of a single well can reach 0.5-0.6 t / d in the first year of reinjection displacement, indicating that the conversion of well pattern can improve the utilization of remaining oil and the efficiency of microbial oil displacement to a greater extent.

[0198] S3-3. Based on the reservoir microbial reaction kinetics equation, the three-dimensional geological model of the reservoir, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters and injection-production well network, simulate the reinjection and displacement effects of different microbial circulation injection-production process parameters in reservoir microbial cold recovery, including:

[0199] S3-3-i. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, injection-production well pattern, production-injection ratio, reinjection fluid bacterial concentration, reinjection temperature, and injection method, the reinjection displacement effect of different injection rates in microbial cyclic injection-production is simulated, for example:

[0200] The injection-production ratio of the reverse five-point well network is 1:1. The injection rate is high and the fluid production rate is high. It is easy to form a breakthrough in high-permeability reservoirs, which reduces the efficiency of microbial sweep. If the injection rate is too low, it is also not conducive to microbial oil displacement. Therefore, choosing an appropriate injection rate is particularly important.

[0201] The effects of microbial oil displacement were simulated and compared under injection rates of 15 t / d, 20 t / d, and 25 t / d. The daily oil production comparison chart for different injection rates is shown below. Figure 21 As shown in Table 6, the cumulative oil production and recovery rate over the 5-year prediction period for different reinjection rates are compared.

[0202] Table 6

[0203]

[0204] from Figure 21As shown in Table 5, the initial production is higher as the reinjection rate gradually increases. However, if the injection rate is too high, it is easy to form a local breakthrough, and the efficiency of microbial oil displacement will decrease. It is better to control the injection rate at 20t / d. The cumulative oil production in the predicted 5-year period is 25,060t, and the recovery rate is 12.05%.

[0205] S3-3-ii. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, reinjection fluid bacterial concentration, reinjection temperature, and injection method, the reinjection displacement effect of different production-injection ratios in microbial cyclic injection-production is simulated, for example:

[0206] Five scenarios were simulated with production-injection ratios of 0.9, 1.0, 1.1, 1.2, and 1.5. The daily oil production comparison chart for each production-injection ratio is shown below. Figure 22 As shown in the figure, the relationship between the production-injection ratio and the cumulative oil production and recovery rate during the forecast period is as follows: Figure 23 As shown;

[0207] from Figure 22-23 As can be seen, the initial production is higher as the production-injection ratio gradually increases. When the production-injection ratio is 1.5, the daily oil production reaches its peak and then decreases rapidly. The increase in total production gradually decreases as the production-injection ratio increases. When the production-injection ratio is 1.2, the cumulative oil production in the forecast period of 5 years is 26,413 tons, with a recovery rate of 12.7%. When the production-injection ratio is 1.5, the cumulative oil production is 25,500 tons, with a recovery rate of 12.2%. It is better to control the production-injection ratio at around 1.2. In the initial stage, the ratio to make up for the formation deficit can be appropriately controlled between 1.0 and 1.1.

[0208] S3-3-iii. Based on the reservoir microbial reaction kinetics equation, the three-dimensional geological model of the reservoir, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature, and injection method, the reinjection displacement effect of different reinjection fluid bacterial concentrations in microbial circulation injection-production is simulated, for example:

[0209] Using a combination of numerical simulation and experimental evaluation, the relationship between the concentration of reagents in different sluice blocks of the reinjection system and the enhanced oil recovery rate was compared. Specifically, the effect of different bacterial concentrations in the reinjection fluid on daily oil production through microbial displacement was investigated. Figure 24 As shown, the cumulative oil production from microbial displacement with different reinjection fluid concentrations... Figure 25 As shown, the relationship between cumulative oil production and recovery rate of different reinjection fluid bacterial concentrations and microbial displacement is as follows: Figure 26 As shown;

[0210] from Figure 24-26It can be seen that as the bacterial concentration of the reinjected fluid gradually increases, the initial output, cumulative output and recovery rate are higher. When the bacterial concentration is greater than 3.0%, increasing the bacterial concentration will result in a smaller increase in output. From an economic point of view, it is better to control the bacterial concentration at around 3.0%.

[0211] Table 7 shows the comparative data of bacterial concentration from field tests and monitoring. The chart showing the comparative data of average daily oil production per well from field tests and monitoring is shown below. Figure 27 As shown;

[0212] Table 7

[0213]

[0214] From Table 7 and Figure 27 It can also be seen that maintaining a reasonable bacterial concentration above 3.0% results in a good microbial oil displacement effect.

[0215] S3-3-iv. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature, and reinjection fluid bacterial concentration, the reinjection displacement effect of different injection methods in microbial cyclic injection-production is simulated, for example:

[0216] Based on the concentration of microbial agents in the produced fluid during the cyclic injection and production process, and considering both the improvement of microbial reservoir utilization and economic efficiency, an alternating microbial and water displacement method was adopted to maximize the utilization of the existing underground microbial reservoir. Therefore, simulations compared the effects of continuous microbial reinjection for 6 months and 12 months after microbial pretreatment, followed by a slug-type displacement method involving microbial and produced fluid reinjection. The alternating microbial and produced fluid reinjection slug method involved injecting microbial agents for 3 months followed by 3 months of produced fluid injection. The daily oil production from microbial displacement was compared between different displacement methods, for example... Figure 28 As shown, the microbial concentration field diagram after 6 months of continuous microbial reinjection and displacement is as follows. Figure 29 As shown in the figure, the microbial concentration field diagram after 12 months of continuous microbial reinjection and displacement is as follows. Figure 30 As shown in the figure, the biogas concentration field diagram after 6 months of continuous microbial reinjection and displacement is as follows. Figure 31 As shown in the figure, the biogas concentration field diagram after 12 months of continuous microbial reinjection and displacement is as follows. Figure 32 As shown in Table 8, the cumulative oil production and recovery rate over the 5-year prediction period for different injection methods are compared.

[0217] Table 8

[0218]

[0219] from Figure 29-32As can be seen from the data, continuous displacement has a high cumulative production and high recovery rate, but its economic efficiency is worse than that of slug displacement. In the slug displacement method, continuous injection for 12 months followed by slug displacement is better than 6 months. After 12 months of continuous displacement, the microbial concentration field shows that the injection and production wells have basically formed a connection. Under the condition of maintaining a certain concentration of bacterial agent in the produced fluid, after 12 months of continuous microbial displacement, the microbial oil exchange rate is maintained well by adopting the method of alternating injection of microorganisms and water, and its economic efficiency is good. As can be seen from Table 8, in the 5 years of comparison, the cumulative oil production was 23,250t, the recovery rate was 11.18%, and the microbial oil exchange rate was 5.45t / t.

[0220] S3-3-iv. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection fluid bacterial concentration, and injection method, the reinjection displacement effect at different reinjection temperatures in microbial cyclic injection-production is simulated, for example:

[0221] Temperature is a key factor affecting crude oil viscosity and fluidity. Table 9 (Crude Oil Viscosity-Temperature Relationship) shows that as temperature increases, crude oil viscosity decreases. Therefore, the microbial displacement effect was simulated and compared at reinjection fluid temperatures of 30℃, 40℃, and 50℃. The daily oil production comparison chart for microbial displacement at different injection temperatures is shown below. Figure 33 Table 10 shows the relationship between cumulative oil production and recovery rate under different injection temperatures and microbial displacement.

[0222] Table 9

[0223] Temperature (°C) 21158 Crude Oil 30 13612 40 5663 60 1478

[0224] Table 10

[0225] Temperature (°C) Cumulative oil production (t) Recovery rate (%) 30 18770 9.02 40 22050 10.6 50 25254 12.14

[0226] from Figure 33 As can be seen from Table 1, when the reinjection temperature increased from 30℃ to 50℃, the cumulative oil production increased by 6484t, and the recovery rate increased by 3.12%. Therefore, within the temperature range for microbial reproduction (below 60℃), under certain conditions, surface heating reinjection to assist microbial cold recovery is more conducive to achieving the oil displacement effect of high viscosity crude oil.

[0227] In some embodiments of the present invention, step S4 includes:

[0228] S4-1. Based on the simulation results of the reservoir pretreatment process, determine the process parameters of the reservoir pretreatment process in the microbial recovery and displacement process, namely, the injection volume, simmering time and sealing pretreatment scheme of the gas channel around the injection well determined according to the simulation results of step S3-1.

[0229] S4-2. Based on the simulation results of the injection-production well pattern adjustment, determine the injection-production well pattern in reservoir microbial production and flooding, that is, the injection-production well pattern determined based on the simulation results of step S3-2;

[0230] S4-3. Based on the simulation results of the microbial circulation injection and production process in microbial recovery and flooding, determine the process parameters of the microbial circulation injection and production process in microbial recovery and flooding of reservoirs, namely, the production-injection ratio, reinjection fluid bacterial concentration, reinjection temperature, injection method and injection rate in the microbial circulation injection and production process determined based on the simulation results in step S3-3.

[0231] The combination of the above parameters yields a complete reservoir microbial cold recovery and oil displacement scheme.

[0232] like Figure 34 As shown, a reservoir microbial enhanced oil recovery (EOR) numerical simulation system according to an embodiment of the present invention includes:

[0233] Power Module 1: Used to construct reservoir microbial reaction kinetic equations based on the results of experiments on the reservoir microbial ternary oil recovery system;

[0234] Feature module 2: Used to determine reservoir characteristic parameters after steam flooding based on the historical fitting of production dynamics during the steam injection development stage;

[0235] Simulation Module 3: Used to simulate reservoir microbial cold recovery based on reservoir microbial reaction kinetics equations, three-dimensional geological models of the reservoir, and reservoir characteristic parameters after steam flooding;

[0236] Module 4: Used to obtain reservoir microbial cold recovery and oil recovery schemes based on the simulation results of microbial cold recovery and oil recovery.

[0237] In some embodiments of the present invention, the simulation module 3 includes a pretreatment process simulation submodule, an injection-production well network simulation submodule, and a circulation process simulation submodule;

[0238] The pretreatment process simulation submodule is used to simulate the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding.

[0239] The injection-production well network simulation submodule is used to simulate the reinjection and displacement effects of different injection-production well networks in reservoir microbial cold recovery and displacement under the same reservoir pretreatment process parameters, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding.

[0240] The circulation process simulation submodule is used to simulate the reinjection and displacement effects of different microbial circulation injection and production process parameters in reservoir microbial cold recovery, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters and injection-production well pattern.

[0241] like Figure 35 As shown, in some embodiments of the present invention, an electronic device is provided, the electronic device 300 including: a processor 301 coupled to a memory 302;

[0242] The memory 302 is used to store computer programs;

[0243] The processor 301 is configured to execute the computer program stored in the memory 302, so that the electronic device performs the method described in the above embodiments.

[0244] In some embodiments of the present invention, a computer-readable storage medium is provided that stores a program or instructions that, when executed on a computer, cause the computer to perform the methods described in the above embodiments.

[0245] According to embodiments of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, electronic device, or apparatus.

[0246] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A numerical simulation method for reservoir microbial enhanced oil recovery and displacement, characterized in that, include: Based on the experimental results of the reservoir microbial ternary oil recovery system, a reservoir microbial reaction kinetic equation was constructed. Based on the historical fitting of production dynamics during the steam injection development stage, characteristic parameters of the reservoir after steam flooding were determined. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reservoir microbial cold recovery oil displacement was simulated. Based on the simulation results of microbial cold recovery oil recovery, a microbial cold recovery oil recovery scheme for oil reservoirs was obtained.

2. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 1, characterized in that, Based on the experimental results of the reservoir microbial ternary oil recovery system, the reservoir microbial reaction kinetic equations are constructed, including: Experiments were conducted on a ternary oil recovery system based on reservoir microorganisms. Based on the experimental results of the reservoir microbial ternary oil recovery system, the microbial reaction kinetic components and parameters of each component in the reservoir hydrocarbon degradation and directed activation mechanism were determined. By combining the microbial reaction kinetic components of reservoir hydrocarbon degradation and directed activation mechanisms, a reservoir microbial reaction kinetic equation is established.

3. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 2, characterized in that, The experiment on the reservoir microbial ternary enhanced oil recovery system includes: Microbial functional bacteria screening experiment based on the properties of crude oil in the target reservoir and the characteristics of microbial community structure in the reservoir environment; Activating nutrient screening experiments were conducted based on the selected functional microorganisms and crude oil from the target reservoir. An auxiliary activator screening experiment was conducted based on the selected functional microorganisms, the selected activating nutrients, and the target reservoir crude oil.

4. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 2, characterized in that, The microbial reaction kinetic components include microorganisms, heavy oil, light oil, nutrients, carbon source, biosurfactant, foam, methane, carbon dioxide, and water.

5. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 1, characterized in that, The reservoir microbial reaction kinetic equations include: microbial reproduction reaction kinetic equation, microbial degradation equation of heavy oil components, microbial self-generated foam oil equation, foam oil elimination and destruction equation, and microbial death and hydrolysis equation.

6. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 1, characterized in that, The reservoir characteristic parameters after steam flooding include the reserves, production, remaining oil reserves, and recovery rate of each oil layer.

7. A numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to any one of claims 1-6, characterized in that, Based on reservoir microbial reaction kinetics equations, a three-dimensional geological model of the reservoir, and reservoir characteristic parameters after steam flooding, a simulation of reservoir microbial cold recovery and oil displacement is conducted, including: Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding were simulated. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different injection and production well patterns in reservoir microbial cold recovery were simulated under the same reservoir pretreatment process parameters. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different microbial circulation injection and production process parameters in reservoir microbial cold recovery were simulated under the same reservoir pretreatment process parameters and injection-production well pattern.

8. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 7, characterized in that, The simulation of the reinjection and displacement effects of different reservoir pretreatment process parameters in microbial recovery and flooding, based on reservoir microbial reaction kinetics equations, three-dimensional geological models of the reservoir, and reservoir characteristic parameters after steam flooding, includes: Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reinjection and displacement effect of single wells with different pretreatment injection amounts of microorganisms before microbial reinjection and displacement was simulated under the same pretreatment simmering time. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different pretreatment well-steaming times were simulated under the same pretreatment injection volume of microorganisms in a single well before microbial reinjection and displacement. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, the reinjection and displacement effects of different sealing pretreatment schemes around the injection well were simulated under the same microbial pretreatment injection volume and the same well-sinking time before microbial reinjection and displacement.

9. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 7, characterized in that, The process, based on reservoir microbial reaction kinetics equations, a three-dimensional geological model of the reservoir, and reservoir characteristic parameters after steam flooding, simulates a microbial cyclic injection-production process in cold-production oil recovery under the same reservoir pretreatment process parameters and injection-production well network. This includes: Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different injection rates in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, injection-production well pattern, production-injection ratio, reinjection fluid bacterial concentration, reinjection temperature, and injection method. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different production-injection ratios in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, reinjection fluid bacterial concentration, reinjection temperature, and injection method. Based on the reservoir microbial reaction kinetics equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different reinjection fluid bacterial concentrations in the microbial circulation injection and production process was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature, and injection method. Based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different injection methods in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, same injection-production well pattern, injection rate, production-injection ratio, reinjection temperature and reinjection fluid bacterial concentration. Based on the reservoir microbial reaction kinetic equation, the reservoir three-dimensional geological model, and the reservoir characteristic parameters after steam flooding, the reinjection displacement effect of different reinjection temperatures in microbial cyclic injection and production was simulated under the same reservoir pretreatment process parameters, the same injection-production well pattern, injection rate, production-injection ratio, reinjection fluid bacterial concentration, and injection method.

10. The numerical simulation method for reservoir microbial enhanced oil recovery and displacement according to claim 1, characterized in that, The process of obtaining a reservoir microbial cold recovery oil recovery scheme based on the simulation results includes: Based on the simulation results of reservoir pretreatment process, the process parameters of reservoir pretreatment process in microbial recovery and flooding are determined. Based on the simulation results of injection-production well pattern adjustment, the injection-production well pattern in reservoir microbial recovery and flooding is determined; Based on the simulation results of the microbial cyclic injection and production process in microbial enhanced oil recovery (EOR), the process parameters of the microbial cyclic injection and production process in EOR are determined.

11. A numerical simulation system for reservoir microbial enhanced oil recovery and displacement, characterized in that, include: The dynamics module is used to construct reservoir microbial reaction kinetic equations based on the experimental results of the reservoir microbial ternary oil recovery system. Feature module: used to determine reservoir characteristic parameters after steam flooding based on the historical fitting of production dynamics during the steam injection development stage; Simulation module: Used to simulate reservoir microbial cold recovery based on reservoir microbial reaction kinetic equations, three-dimensional geological models of the reservoir, and reservoir characteristic parameters after steam flooding; Acquisition Module: Used to obtain reservoir microbial cold recovery and oil displacement schemes based on the simulation results of microbial cold recovery and oil displacement.

12. The reservoir microbial enhanced oil recovery and displacement numerical simulation system according to claim 11, characterized in that, The simulation module includes a pretreatment process simulation submodule, an injection-production well network simulation submodule, and a circulation process simulation submodule; The pretreatment process simulation submodule is used to simulate the reinjection and displacement effects of different reservoir pretreatment process parameters in reservoir microbial recovery and flooding based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding. The injection-production well network simulation submodule is used to simulate the reinjection and displacement effects of different injection-production well networks in reservoir microbial cold recovery and displacement under the same reservoir pretreatment process parameters, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model and reservoir characteristic parameters after steam flooding. The circulation process simulation submodule is used to simulate the reinjection and displacement effects of different microbial circulation injection and production process parameters in reservoir microbial cold recovery, based on the reservoir microbial reaction kinetic equation, reservoir three-dimensional geological model, and reservoir characteristic parameters after steam flooding, under the same reservoir pretreatment process parameters and injection-production well pattern.

13. An electronic device, characterized in that, include: Processor, the processor being coupled to memory; The memory is used to store computer programs; The processor is configured to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 10.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 10.

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