Real-time optimization regulation and control method for oil reservoir layered injection-production scheme

Abstract

The invention provides a real-time optimization regulation and control method for an oil reservoir stratified injection and production scheme. The real-time optimization regulation and control method for the oil reservoir stratified injection and production scheme comprises the steps that 1, oil reservoir dynamic and static data are collected according to the optimization task requirement of the oil reservoir stratified injection and production scheme; 2, establishing a multi-layer oil reservoir water drive dynamic analysis model; 3, geological parameters in the multi-layer oil reservoir water drive dynamic analysis model are corrected; and step 4, optimizing a layered injection-production scheme, and generating a new production allocation / injection allocation scheme. According to the real-time optimization regulation and control method for the oil reservoir layered injection-production scheme, model parameters are corrected by applying an intelligent optimization algorithm, so that high-accuracy calculation of a water drive historical dynamic state is realized; coupling the multilayer oil reservoir water drive dynamic description model and an intelligent optimization algorithm to calculate a layered injection and production scheme, and transmitting a regulation and control signal to a layered injection and production pipe column for automatic implementation.

Description

Technical Field

[0001] The present invention relates to the technical field of oilfield exploitation, and particularly to a method for real-time optimization and regulation of reservoir layered injection-production schemes. Background Art

[0002] Domestic major old oilfields have generally entered the ultra-high water cut stage. The number of oil wells and water injection wells using layered injection-production technology strings is increasing day by day, which has become an important means to alleviate the contradictions between plane and interlayer water flooding. Due to the continuous intensification of reservoir heterogeneity, remaining oil is locally enriched, and the development dynamics change rapidly. The layered injection-production scheme needs to be optimized in real time to maximize the reservoir development effect.

[0003] Patent CN114837633A, an intelligent layered injection-production reservoir potential tapping method and system, proposes to establish a geological model and adaptively and real-time correct the parameters of the geological model to provide the real-time changing oil-water distribution conditions of each layer. The injection volume of the water injection well equipment and the oil production volume of the oil production well equipment provided for each layer section are regulated in real time to accurately control the injection volume and oil production volume of each layer. On the one hand, this method divides the injection-production unit and the layered injection volume by establishing a dynamic grid-like flow skeleton. It is difficult for the grid-like flow skeleton to accurately reflect the shape attributes of the injection-production unit. On the other hand, the method determines the injection-production scheme of each layer section by predicting the liquid production volume of a single oil well and water injection well, measuring the liquid production volume of a single oil well and water injection well, and comparing and analyzing them, and cannot consider different optimization objectives.

[0004] Patent CN112861423A, a data-driven water injection reservoir optimization method and system: execute the integrated water injection scheme and production scheme by simultaneously optimizing the layered water injection parameters and layered oil production parameters based on the reinforcement learning / deep reinforcement learning algorithm, so as to avoid independently implementing layered water injection and layered oil production to achieve injection-production balance and supply-drainage coordination. This method needs to first construct a reservoir numerical simulation model and perform a large number of reservoir numerical simulation calculations. The process of establishing the reservoir numerical simulation model is complex and cumbersome, and the reservoir numerical simulation calculation takes a long time, making the computational complexity and computational time of the entire method very long, and it is difficult to achieve the effect of real-time optimization.

[0005] Patent CN109447532A, a method for determining reservoir inter-well connectivity based on data driving: while having the same calculation accuracy of the inter-well connectivity coefficient as the traditional inter-well connectivity discrimination method, it has a better production prediction effect, and can further guide the formulation of optimization measures such as profile control and water plugging, and the historical matching and production optimization of intelligent oilfield layered injection-production. The method for determining reservoir inter-well connectivity constructed by this method can provide some valuable information for the optimization of the layered injection-production scheme, but cannot quantitatively give the layered injection-production scheme.

[0006] The above prior arts are quite different from the present invention and cannot solve the technical problems we want to address. Therefore, we have invented a new real-time optimization and control method for reservoir layered injection-production schemes. Summary of the Invention

[0007] The objective of the present invention is to provide a real-time optimization and control method for reservoir layered injection-production schemes that can achieve highly accurate calculation of water flooding historical dynamics.

[0008] The objective of the present invention can be achieved through the following technical measures: A real-time optimization and control method for reservoir layered injection-production schemes, which includes:

[0009] Step 1: Collect dynamic and static reservoir data according to the optimization task requirements of the reservoir layered injection-production scheme;

[0010] Step 2: Establish a multi-layer reservoir water drive dynamic analysis model;

[0011] Step 3: Modify the geological parameters in the multi-layer reservoir water drive dynamic analysis model;

[0012] Step 4: Optimize the layered injection-production scheme to generate a new production / injection allocation plan.

[0013] The objective of the present invention can also be achieved through the following technical measures:

[0014] In Step 1, the collected dynamic and static reservoir data includes basic reservoir information, basic information of oil and water wells, and production dynamic information of oil and water wells.

[0015] In Step 1, the basic reservoir information includes the number of layers, the number of wells, oil and water viscosities, relative permeability curves, oil price, water injection cost, and liquid production cost.

[0016] In Step 1, the basic information of oil and water wells includes well locations, effective thickness of each layer, permeability of each layer, porosity of each layer, and saturation of each layer.

[0017] In Step 1, the production dynamic information of oil and water wells includes perforation history, liquid production volume history, water cut history, and water injection volume history.

[0018] Step 2 includes:

[0019] Step 21: Calculate the well spacing, average effective thickness, average permeability, average porosity, and average saturation between each well according to the basic information of each oil and water well;

[0020] Step 22: Calculate the injection-production correspondence between each well at the current time step;

[0021] Step 23: Determine the seepage resistance in each injection-production direction and divide the reservoir into multiple injection-production units;

[0022] Step 24: Calculate the split injection volume or split liquid production volume for each injection-production unit based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation of each injection-production unit.

[0023] Step 25: Calculate the average saturation, oil production volume, water production volume, and injection volume at the end of the current time step for the injection-production unit based on the split injection volume or split liquid production volume of each injection-production unit.

[0024] Step 26: Determine whether the time step is the last one. If so, end the calculation and output the calculated oil production volume, water production volume, and injection volume; otherwise, start the next time step and return to Step 22 for iteration.

[0025] In Step 22, calculate the injection-production correspondence between wells at the current time step based on the well positions and perforation history of each well. If there is an injection-production correspondence, set it to 1; otherwise, set it to 0.

[0026] In Step 23, determine the seepage resistance in each injection-production direction based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation in each injection-production direction at the current moment, and divide the reservoir into multiple injection-production units, each of which is a quadrilateral with an oil well and a water well at two opposite corners.

[0027] Step 3 includes:

[0028] Step 31: Set the effective thickness, permeability, and porosity of each layer of each oil well and water well equal to the initially collected values; set the relative permeability curve equal to the initially collected relative permeability curve.

[0029] Step 32: Based on the parameters set in Step 31, use the method of Step 2 to establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production volume, water production volume, and injection volume.

[0030] Step 33: Compare the differences between the calculated oil production volume, calculated water production volume, calculated injection volume and the actual oil production volume, actual water production volume, and actual injection volume of the reservoir, expressed as the mean square error value.

[0031] Step 34: Determine whether the mean square error value is less than the given value. If it is less than, it means that the given geological parameters are relatively accurate, complete the calculation and output the geological parameters; otherwise, it means that the given geological parameters are not accurate enough, and enter Step 35.

[0032] Step 35: Based on the tested geological parameters and the corresponding mean square error, use the heuristic search algorithm to automatically generate a new geological parameter scheme and return to Step 32.

[0033] Step 4 includes:

[0034] Step 41: Set the production / injection volume of each well and each interval as the optimization variables;

[0035] Step 42: Set the optimization period and the optimization objective function, which can be maximizing cumulative oil production, maximizing economic benefits, or maximizing balanced displacement;

[0036] Step 43: Set the constraint conditions including the upper and lower limit constraints of the production / injection volume of each well and each interval, the overall liquid production rate constraint of the reservoir, and the overall water injection rate constraint of the reservoir;

[0037] Step 44: Generate a set of production / injection volume plans for each well and each interval that meet the constraint conditions according to the set constraint conditions;

[0038] Step 45: According to the generated production / injection volume plans for each well and each interval, and the geological parameters determined in Step 3, establish a multi-layer reservoir water drive dynamic analysis model using the method in Step 2, complete the model calculation, and output the calculated oil production, water production, and water injection volume;

[0039] Step 46: Calculate the objective function value under the current production / injection volume plan;

[0040] Step 47: Determine whether the objective function value meets the given stopping conditions. If it meets, it means that the current production / injection volume plan is the optimal plan, complete the calculation and output; otherwise, it means that the current production / injection volume plan is not the optimal plan, and go to Step 48;

[0041] Step 48: According to the tested production / injection volume plans and the corresponding objective function values, use the heuristic search algorithm to automatically generate a new production / injection volume plan, and return to Step 45.

[0042] In Step 42, the set optimization period is between 3 days and 5 years.

[0043] In Step 47, the given stopping conditions include the maximum number of iterations and the longest calculation time.

[0044] This real-time optimization and regulation method for the reservoir layered injection-production plan further includes, after Step 4, Step 5, for real-time pushing of the layered injection-production optimization plan.

[0045] In Step 5, the optimized layered injection-production plan is pushed to reservoir engineering and technical personnel for review; if the review is passed, the layered injection-production plan is converted into a regulation signal and transmitted to the layered injection-production process string to achieve remote regulation; if the review is not passed, return to Step 1 to start over.

[0046] The object of the present invention can also be achieved by the following technical measures: a real-time optimization and control method system for reservoir layered injection-production plan, which uses the annotation method of the real-time optimization and control method for reservoir layered injection-production plan to obtain the layered injection-production plan and transmit the control signal to the layered injection-production string for automatic implementation.

[0047] In the real-time optimization and control method for reservoir layered injection-production plan of the present invention, a multi-layer reservoir water drive dynamic description model is established based on easily obtainable dynamic and static parameters of the reservoir, and intelligent optimization algorithms are applied to correct the model parameters to achieve high-accuracy calculation of the water drive historical dynamics. On this basis, different optimization objectives such as cumulative oil production, economic benefits, and balanced displacement are set, and the multi-layer reservoir water drive dynamic description model and intelligent optimization algorithms are coupled to calculate the layered injection-production plan and transmit the control signal to the layered injection-production string for automatic implementation. Brief Description of the Drawings

[0048] Figure 1 It is a flowchart of a specific embodiment of the real-time optimization and control method for reservoir layered injection-production plan of the present invention;

[0049] Figure 2 It is a schematic diagram of the liquid production history, water cut history, and water injection history of three single wells in a specific embodiment of the present invention;

[0050] Figure 3 It is a split diagram of an injection-production unit in a specific embodiment of the present invention;

[0051] Figure 4 It is a comparison diagram of calculated oil production, water production and actual oil production, water production in a specific embodiment of the present invention;

[0052] Figure 5 It is a process diagram of optimization in a specific embodiment of the present invention;

[0053] Figure 6 It is a split diagram of an injection-production unit in another specific embodiment of the present invention;

[0054] Figure 7 It is a comparison diagram of calculated oil production, water production and actual oil production, water production in another specific embodiment of the present invention;

[0055] Figure 8 It is a process diagram of optimization in another specific embodiment of the present invention;

[0056] Figure 9 It is a split diagram of an injection-production unit in yet another specific embodiment of the present invention;

[0057] Figure 10 It is a comparison diagram of calculated oil production, water production and actual oil production, water production in yet another specific embodiment of the present invention;

[0058] Figure 11 This is the optimization process diagram in another specific embodiment of the present invention. Detailed implementation manners

[0059] It should be noted that the following detailed description is exemplary and is intended to provide further illustration of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0060] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they specify the presence of features, steps, operations, and / or combinations thereof.

[0061] As Figure 1 shown, Figure 1 This is the flow chart of the real-time optimization and regulation method for the reservoir layered injection-production plan of the present invention. The real-time optimization and regulation method for the reservoir layered injection-production plan includes:

[0062] The first step: Collect the dynamic and static data of the reservoir according to the optimization task requirements of the reservoir layered injection-production plan.

[0063] 1-1: Collect the basic information of the reservoir (number of layers, number of wells, oil-water viscosity, relative permeability curve, oil price, water injection cost, liquid production cost, etc.).

[0064] 1-2: Collect the basic information of oil and water wells (well location, effective thickness of each layer, permeability of each layer, porosity of each layer, saturation of each layer, etc.).

[0065] 1-3: Collect the production dynamic information of oil and water wells (perforation history, liquid production history, water cut history, water injection history, etc.).

[0066] The second step: Establish a multi-layer reservoir water drive dynamic analysis model.

[0067] 2-1: Calculate the well spacing, average effective thickness, average permeability, average porosity, and average saturation between each well according to the basic information of each oil and water well.

[0068] 2-2: Calculate the injection-production correspondence between each well at the current time step according to the well location and perforation history of each well. If there is an injection-production correspondence, set it to 1; otherwise, set it to 0.

[0069] 2-3: Determine the seepage resistance in each injection-production direction based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation at the current moment, and divide the reservoir into multiple injection-production units, each of which is a quadrilateral with an oil well and a water well at two opposite corners.

[0070] 2-4: Calculate the split injection volume or split liquid production volume on each injection-production unit according to the well spacing, average effective thickness, average permeability, average porosity, and average saturation of each injection-production unit.

[0071] 2-5: Calculate the average saturation, oil production, water production, and injection volume at the end of the current time step for this injection-production unit according to the split injection volume or split liquid production volume on each injection-production unit.

[0072] 2-6: Determine whether the time step is the last one. If so, end the calculation and output the calculated oil production, water production, and injection volume. Otherwise, start the next time step and return to step 2-2 for iteration.

[0073] The third step: Intelligently correct the geological parameters in the multi-layer reservoir water drive dynamic analysis model.

[0074] 3-1: Set the effective thickness, permeability, and porosity of each layer of each oil well and water well equal to the initially collected values; set the relative permeability curve equal to the initially collected relative permeability curve.

[0075] 3-2: Based on the parameters set in step 3-1, use the method of the second step to establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production, water production, and injection volume.

[0076] 3-3: Compare the differences between the calculated oil production, calculated water production, calculated injection volume and the actual oil production, actual water production, and actual injection volume of the reservoir, expressed by the mean square error value.

[0077] 3-4: Determine whether the mean square error value is less than the given value. If it is less, it means that the given geological parameters are relatively accurate, complete the calculation and output the geological parameters. Otherwise, it means that the given geological parameters are not accurate enough, and enter step 3-5.

[0078] 3-5: According to the tested geological parameters and the corresponding mean square error, use the heuristic search algorithm to automatically generate a new geological parameter scheme and return to step 3-2.

[0079] The fourth step: Optimize the layered injection-production plan.

[0080] 4-1: Set the production / injection allocation volume of each layer section of each well as the optimization variable.

[0081] 4-2: Set the optimization period, generally between 3 days and 5 years. Set the optimization objective function, which can be maximizing cumulative oil production, maximizing economic benefits, or maximizing balanced displacement.

[0082] 4-3: Set the constraint conditions including the upper and lower limit constraints of the production / injection volume of each well and each layer section, the overall liquid production rate constraint of the reservoir, and the overall water injection rate constraint of the reservoir;

[0083] 4-4: Generate a set of production / injection volume plans for each well and each layer section that meet the constraint conditions according to the set constraint conditions.

[0084] 4-5: According to the generated production / injection volume plans for each well and each layer section, and the geological parameters determined in the third step, establish a multi-layer reservoir water drive dynamic analysis model by using the method in the second step, complete the model calculation, and output the calculated oil production, water production, and water injection volume.

[0085] 4-6: Calculate the objective function value under the current production / injection volume plan.

[0086] 4-7: Determine whether the objective function value meets the given stopping conditions (the given stopping conditions include the maximum number of iterations, the longest calculation time, etc.). If it meets, it means that the current production / injection volume plan is the optimal plan, complete the calculation and output. Otherwise, it means that the current production / injection volume plan is not the optimal plan, and enter step 4-8.

[0087] 4-8: According to the tested production / injection volume plans and the corresponding objective function values, use the heuristic search algorithm to automatically generate a new production / injection volume plan and input it into step 4-5.

[0088] Step Five: Real-time push of the layered injection-production optimization plan.

[0089] 5-1: Push the optimized layered injection-production plan to the reservoir engineering and technical personnel for review.

[0090] 5-2: If the review is passed, convert the layered injection-production plan into a control signal and transmit it to the layered injection-production process string to achieve remote control. If the review is not passed, go back to step one and start over.

[0091] The present invention can establish a multi-layer reservoir water drive dynamic description model based on easily obtainable reservoir dynamic and static parameters, apply an intelligent optimization algorithm to correct the model parameters, and achieve high-accuracy calculation of the water drive historical dynamics. On this basis, different optimization objectives such as cumulative oil production, economic benefits, and balanced displacement are set, and the layered injection-production plan is calculated by coupling the multi-layer reservoir water drive dynamic description model and the intelligent optimization algorithm, and the control signal is transmitted to the layered injection-production string for automatic implementation.

[0092] The following are several specific embodiments of applying the present invention

[0093] Example 1

[0094] In a specific Example 1 of applying the present invention, taking a certain oilfield block as an example to illustrate the general steps of the present invention.

[0095] The first step: Collect dynamic and static reservoir data according to the optimization task requirements of the reservoir layered injection-production plan.

[0096] 1-1: Collect basic reservoir information: number of layers L total = 7, number of wells W total = 3, oil viscosity μo = 5.8 mPa·s, water viscosity μw = 5.8 mPa·s, oil price Co = 2700 yuan / m 3 , water injection cost Cw = 400 yuan / m 3 , liquid production cost Cl = 400 yuan / m 3 , relative permeability curves are as shown in Table 1 below.

[0097] Table 1 Relative Permeability Curve Data Table

[0098] Sw water saturation Krw relative permeability of water phase Kro relative permeability of oil phase 0.33 0.00E+00 1.00E+00 0.4 1.00E-02 5.80E-01 0.5 4.00E-02 3.70E-01 0.6 1.00E-01 1.60E-01 0.7 2.60E-01 6.00E-02 0.8 6.00E-01 2.00E-02 0.88 8.00E-01 0.00E+00

[0099] 1-2: Collect basic information of oil and water wells, including well positions, effective thicknesses of each layer, permeabilities of each layer, porosities of each layer, etc., as shown in the following table.

[0100] Table 2 Basic Information Data Table of Oil and Water Wells

[0101]

[0102] 1-3: Collect production dynamic information of oil and water wells, perforation history is as shown in the following table.

[0103] Table 3 Production Dynamic Information Data Table of Oil and Water Wells

[0104]

[0105] Liquid production volume history, water cut history, water injection volume history are as attached Figure 2 .

[0106] The second step: Establish a multi-layer reservoir water drive dynamic analysis model.

[0107] 2-1: Calculate the well spacing, average effective thickness, average permeability, average porosity, and average saturation between each well according to the basic information of each oil and water well.

[0108] Calculation formula for well spacing between each well:

[0109]

[0110] Where, d i,j,lThe well spacing between the i-th well and the j-th well in the l-th layer, X i,l and X j,l are the X coordinates of the i-th well and the j-th well in the l-th layer respectively, and Y i,l and Y j,l are the Y coordinates of the i-th well and the j-th well in the l-th layer respectively.

[0111] Calculation formulas for the average effective thickness, permeability, porosity, and saturation between wells:

[0112]

[0113] Among them, K i,j,l is the average permeability between the i-th well and the j-th well in the l-th layer, and K i,l and K j,l are the permeabilities of the i-th well and the j-th well in the l-th layer respectively. In the formula, K can be replaced by the effective thickness H, porosity Φ, and saturation S w .

[0114] 2-2: Calculate the injection-production correspondence between wells at the current time step based on the well positions and perforation histories of each well. If there is an injection-production correspondence, set it to 1; otherwise, set it to 0.

[0115] 2-3: Determine the seepage resistance in each injection-production direction based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation in each injection-production direction at the current moment, and divide the reservoir into multiple injection-production units. The splitting coefficient of each injection-production unit is determined by the following formula:

[0116]

[0117] In the formula, θ i,j,l is the splitting angle of the injection-production unit between the i-th well and the j-th well in the l-th layer; R i,j,l is the seepage resistance between the i-th well and the j-th well in the l-th layer; Δp i,j,l is the injection-production pressure difference between the i-th well and the j-th well in the l-th layer; m is the corresponding number of wells, and n is the corresponding number of layers.

[0118] Each injection-production unit is a quadrilateral, with an oil well and a water well at two opposite corners, as shown in the appendix Figure 3 .

[0119] 2-4: Calculate the split injection volume or split liquid production volume on each injection-production unit, as follows:

[0120] q i,j,l =q i θ i,j,l

[0121] In the formula, q i,j,lis the split injection or split production liquid volume of the i-th well and the j-th well in the l-th layer; q i is the injection or production liquid volume of the i-th well.

[0122] Calculate the average saturation, oil production, water production, and injection volume at the end of the current time step for this injection-production unit as follows:

[0123]

[0124] In the formula, S wi,j,l is the average saturation of the i-th well and the j-th well in the l-th layer. f w is the water cut curve function calculated based on the relative permeability curve, r is the displacement front distance, r w is the wellbore diameter.

[0125] 2 - 5: Determine whether the time step ends. If it ends, output the calculated oil production FOPR, water production FWPR, and injection volume FWIR. Otherwise, start the next time step and return to step 2 - 2 for iteration.

[0126] Step 3: Intellectually correct the geological parameters in the multi-layer reservoir water drive dynamic analysis model.

[0127] 3 - 1: Set the effective thickness H, permeability K, and porosity Φ of each layer of each oil well and water well equal to the initially collected values; set the relative permeability curve equal to the initially collected relative permeability curve, and its characteristic parameter is Kr.

[0128] 3 - 2: Establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and injection volume FWIR.

[0129] 3 - 3: Compare the differences between the calculated oil production FOPR, calculated water production FWPR, calculated injection volume FWIR and the actual oil production FOPRH, actual water production FWPRH, and actual injection volume FWIRH of the reservoir, as shown in the appendix Figure 4 indicated, expressed by the mean square error value MSE.

[0130] 3 - 4: Determine whether the mean square error value is less than the given value. If it is less, it means that the given geological parameters are relatively accurate, complete the calculation and output the geological parameters. Otherwise, it means that the given geological parameters are not accurate enough, and enter step 3 - 5.

[0131] 3 - 5: According to the tested geological parameters and the corresponding mean square errors, use the heuristic search algorithm to automatically generate a new geological parameter scheme. The scheme update formula is as follows:

[0132]

[0133] Among them, ΔH, ΔK, ΔΦ, and ΔKr are the update step sizes of H, K, Φ, and Kr this time. Depending on the selected heuristic search algorithm, the calculation results of ΔH, ΔK, ΔΦ, and ΔKr are different. Here, the CMA-ES algorithm is selected. After the update, H, K, Φ, and Kr return to step 3-2.

[0134] Step 4: Optimization of the layered injection-production plan.

[0135] 4-1: Set the production / injection rate Q of each well and each interval as the optimization variable, and set the constraint conditions including the upper and lower limit constraints of the production / injection rate of each well and each interval, the overall liquid production rate constraint of the reservoir, and the overall water injection rate constraint of the reservoir, as follows:

[0136]

[0137] Among them, q i is the production / injection rate of the i-th interval, q min is the minimum production / injection rate, q max is the maximum production / injection rate, Q prod is the overall liquid production rate of the reservoir, Q inj is the overall water injection rate of the reservoir.

[0138] 4-2: Set the optimization period, generally between 3 days and 5 years. Here, 2 years is selected. Set the optimization objective function, which can be maximizing cumulative oil production, maximizing economic benefits, or maximizing balanced displacement. The calculation formulas for different objective functions are as follows:

[0139] Maximizing cumulative oil production:

[0140]

[0141] Maximizing economic benefits:

[0142]

[0143] Maximizing balanced displacement, that is, minimizing the saturation standard deviation:

[0144]

[0145] 4-4: According to the set constraint conditions, generate a set of production / injection rate plans Q for each well and each interval that meet the constraint conditions.

[0146] 4-5: According to the generated production / injection rate plans for each well and each interval, and the geological parameters determined in step 3, establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and water injection FWIR.

[0147] 4 - 6: Calculate the objective function value under the current production and injection allocation plan. Here, maximizing economic benefits is selected, and the objective function value is the NPV.

[0148] 4 - 7: Determine whether the objective function value meets the given stopping condition. If it does, it means the current production and injection allocation plan is the optimal plan, complete the calculation and output. Otherwise, it means the current production and injection allocation plan is not the optimal plan, and go to step 4 - 8.

[0149] 4 - 8: According to the tested production and injection allocation plans and their corresponding objective function values, use the heuristic search algorithm to automatically generate a new production and injection allocation plan. The plan update formula is as follows:

[0150] Q = Q + ΔQ

[0151] where ΔQ is the update step size of Q this time. According to different selected heuristic search algorithms, the calculation result of ΔQ is different. Here, the CMA - ES algorithm is selected. After updating, Q is input to step 4 - 5. The iterative optimization process is as shown in the appendix Figure 5 As shown, with the progress of optimization, the cumulative oil production of the plan continuously increases, and the cumulative water production continuously decreases, indicating that the plan continuously improves with the progress of the optimization process.

[0152] Step 5: Real - time push of the layered injection - production optimization plan.

[0153] 5 - 1: Push the optimized layered injection - production plan to reservoir engineering technicians for review.

[0154] 5 - 2: If the review is passed, convert the layered injection - production plan into a control signal and transmit it to the layered injection - production string to achieve remote control. If the review is not passed, go back to step one to start over.

[0155] Example 2

[0156] In the specific Example 2 of applying the present invention, take a certain oilfield block as an example to illustrate the general steps of the present invention.

[0157] Step 1: Collect the dynamic and static data of the reservoir according to the requirements of the reservoir layered injection - production plan optimization task.

[0158] 1 - 1: Collect the basic information of the reservoir: the number of layers L total = 7, the number of wells W total = 19, the oil viscosity μo = 5.8 mPa·s, the water viscosity μw = 1 mPa·s, the oil price Co = 2700 yuan / m 3 , the water injection cost Cw = 400 yuan / m 3 , the liquid production cost Cl = 400 yuan / m 3 , and the relative permeability curve is the same as that in Example 1.

[0159] 1 - 2: Collect basic information of oil and water wells, including well location, effective thickness of each layer, permeability of each layer, porosity of each layer, etc., as shown in the following table.

[0160] Table 4 Data Sheet of Basic Information of Oil and Water Wells

[0161]

[0162] 1 - 3: Collect production dynamic information of oil and water wells. The perforation history is shown in the following table.

[0163] Table 5 Data Sheet of Production Dynamic Information of Oil and Water Wells

[0164] DATE WNAME 1 2 3 4 5 6 7 2013-05-25 00:00:00 WX6 1 1 1 0 1 0 0 2013-04-02 00:00:00 WX11 0 1 1 0 1 0 0 2015-06-05 00:00:00 WX11 0 0 0 0 0 0 1 2013-04-02 00:00:00 WX12 0 0 0 0 1 0 1 2020-01-24 00:00:00 WX12 0 1 1 0 1 0 1

[0165] Step 2: Establish a multi - layer reservoir water drive dynamic analysis model.

[0166] 2 - 1: Calculate the well spacing, average effective thickness, average permeability, average porosity, and average saturation between wells based on the basic information of each oil and water well.

[0167] Calculation formula for well spacing between wells:

[0168]

[0169] where d i,j,l is the well spacing between the i - th well and the j - th well in the l - th layer, X i,l , X j,l are the X - coordinates of the i - th well and the j - th well in the l - th layer respectively, and Y i,l , Y j,l are the Y - coordinates of the i - th well and the j - th well in the l - th layer respectively.

[0170] Calculation formulas for average effective thickness, permeability, porosity, and saturation between wells:

[0171]

[0172] where K i,j,l is the average permeability between the i - th well and the j - th well in the l - th layer, K i,l , K j,l are the permeabilities of the i - th well and the j - th well in the l - th layer respectively. In the formula, K can be replaced by effective thickness H, porosity Φ, and saturation S w .

[0173] 2 - 2: Calculate the injection - production correspondence between wells at the current time step based on the well locations and perforation history of each well. If there is an injection - production correspondence, set it to 1; otherwise, set it to 0.

[0174] 2-3: Determine the seepage resistance in each injection-production direction based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation at the current moment, and divide the reservoir into multiple injection-production units. The splitting coefficient of each injection-production unit is determined by the following formula:

[0175]

[0176] In the formula, θ i,j,l is the splitting angle of the injection-production unit between the i-th well and the j-th well in the l-th layer; R i,j,l is the seepage resistance between the i-th well and the j-th well in the l-th layer; Δp i,j,l is the injection-production pressure difference between the i-th well and the j-th well in the l-th layer; m is the corresponding number of wells, and n is the corresponding number of layers.

[0177] Each injection-production unit is a quadrilateral, with an oil well and a water well at two opposite corners, as shown in the appendix Figure 6 .

[0178] 2-4: Calculate the split injection volume or split liquid production volume on each injection-production unit, as follows:

[0179] q i,j,l = q i θ i,j,l

[0180] In the formula, q i,j,l is the split injection volume or split liquid production volume between the i-th well and the j-th well in the l-th layer; q i is the injection volume or liquid production volume of the i-th well.

[0181] Calculate the average saturation, oil production, water production, and injection volume at the end of the current time step on this injection-production unit, as follows:

[0182]

[0183] In the formula, S wi,j,l is the average saturation between the i-th well and the j-th well in the l-th layer. f w is the water cut curve function calculated according to the relative permeability curve, r is the displacement front distance, and r w is the wellbore diameter.

[0184] 2-5: Judge whether the time step ends. If it ends, output the calculated oil production FOPR, water production FWPR, and injection volume FWIR. Otherwise, start the next time step and return to step 2-2 for iteration.

[0185] Step 3: Intelligently correct the geological parameters in the multi-layer reservoir water drive dynamic analysis model.

[0186] 3-1: Set the effective thickness H, permeability K, and porosity Φ of each layer of each oil and water well equal to the initially collected values; set the relative permeability curve equal to the initially collected relative permeability curve, and its characteristic parameter is Kr.

[0187] 3-2: Establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and water injection volume FWIR.

[0188] 3-3: Compare the differences between the calculated oil production FOPR, calculated water production FWPR, calculated water injection volume FWIR and the actual oil production FOPRH, actual water production FWPRH, and actual water injection volume FWIRH of the reservoir, as shown in the appendix Figure 7 and expressed by the mean square error value MSE.

[0189] 3-4: Judge whether the mean square error value is less than the given value. If it is less, it means that the given geological parameters are relatively accurate, complete the calculation and output the geological parameters. Otherwise, it means that the given geological parameters are not accurate enough, and go to step 3-5.

[0190] 3-5: According to the tested geological parameters and the corresponding mean square errors, use the heuristic search algorithm to automatically generate a new geological parameter scheme. The scheme update formula is as follows:

[0191]

[0192] where ΔH, ΔK, ΔΦ, and ΔKr are the update steps of H, K, Φ, and Kr this time. According to different selected heuristic search algorithms, the calculation results of ΔH, ΔK, ΔΦ, and ΔKr are different. Here, the CMA-ES algorithm is selected. After updating, H, K, Φ, and Kr return to step 3-2.

[0193] Step 4: Optimization of the layered injection-production scheme.

[0194] 4-1: Set the production / injection allocation volume of each well and each layer section as the optimization variable; specifically as follows:

[0195]

[0196] where q i is the production / injection allocation volume of the i-th layer section, q min is the minimum production / injection allocation volume, q max is the maximum production / injection allocation volume, Q prod is the total liquid production rate of the reservoir, and Q inj is the total water injection rate of the reservoir.

[0197] 4-2: Set the optimization period, generally between 3 days and 5 years. Here, 2 years is selected. Set the optimization objective function, which can be maximizing cumulative oil production, maximizing economic benefits, or maximizing balanced displacement. The calculation formulas for different objective functions are as follows:

[0198] Maximizing cumulative oil production:

[0199]

[0200] Maximizing economic benefits:

[0201]

[0202] Maximizing balanced displacement, that is, minimizing the saturation standard deviation:

[0203]

[0204] 4-3: Set the constraint conditions including the upper and lower limit constraints of the production / injection volume of each well and each interval, the overall liquid production rate constraint of the reservoir, and the overall water injection rate constraint of the reservoir;

[0205] 4-4: According to the set constraint conditions, generate a set of production / injection volume plans Q for each well and each interval that meet the constraint conditions.

[0206] 4-5: According to the generated production / injection volume plans for each well and each interval, and the geological parameters determined in step three, establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and water injection volume FWIR.

[0207] 4-6: Calculate the objective function value under the current production / injection volume plan. Here, maximizing economic benefits is selected, and the objective function value is NPV.

[0208] 4-7: Judge whether the objective function value meets the given stopping condition. If it meets, it means that the current production / injection volume plan is the optimal plan, complete the calculation and output. Otherwise, it means that the current production / injection volume plan is not the optimal plan, and enter step 4-8.

[0209] 4-8: According to the tested production / injection volume plans and the corresponding objective function values, use the heuristic search algorithm to automatically generate a new production / injection volume plan. The plan update formula is as follows:

[0210] Q = Q + ΔQ

[0211] where ΔQ is the update step size of Q this time. According to different selected heuristic search algorithms, the calculation result of ΔQ is different. Here, the CMA-ES algorithm is selected. After updating, Q is input into step 4-5. The iterative optimization process is as attached Figure 8As shown, with the optimization process, the cumulative oil production of the plan continuously increases, and the cumulative water production continuously decreases, indicating that the plan continuously improves its effectiveness with the progress of the optimization process.

[0212] Step 5: Real-time push of the layered injection-production optimization plan.

[0213] 5-1: The optimized layered injection-production plan is pushed to reservoir engineering technicians for review.

[0214] 5-2: If the review is passed, the layered injection-production plan is converted into a control signal and transmitted to the layered injection-production string to achieve remote control. If the review fails, return to Step 1 and start over.

[0215] Example 3

[0216] In the specific Example 3 of applying the present invention, a certain oilfield block is taken as an example to illustrate the general steps of the present invention.

[0217] Step 1: Collect dynamic and static reservoir data according to the requirements of the reservoir layered injection-production plan optimization task.

[0218] 1-1: Collect basic reservoir information: number of layers L total = 10, number of wells W total = 28, oil viscosity μo = 1.44 mPa·s, water viscosity μw = 1 mPa·s, oil price Co = 2700 yuan / m 3 , water injection cost Cw = 400 yuan / m 3 , liquid production cost Cl = 400 yuan / m 3 , and the relative permeability curve is the same as that in Example 1.

[0219] 1-2: Collect basic information of oil wells and water wells, including well positions, effective thickness of each layer, permeability of each layer, porosity of each layer, etc., as shown in the following table.

[0220] Table 6 Data table of basic information of oil wells and water wells

[0221]

[0222]

[0223] 1-3: Collect production dynamic information of oil wells and water wells. The perforation history is as shown in the following table.

[0224] Table 7 Data table of production dynamic information of oil wells and water wells

[0225] DATE WNAME 1 2 3 4 5 6 7 8 9 10 1968-12-01 00:00:00 WB8 0 0 1 1 1 1 0 1 1 1 1984-10-01 00:00:00 WB8-1 0 0 0 0 0 0 0 1 1 1 1990-08-01 00:00:00 WB8-1 0 0 0 1 1 0 0 1 1 1 1992-06-01 00:00:00 WB8-1 1 0 0 1 1 0 0 0 0 0 1994-12-01 00:00:00 WB8-1 1 0 0 1 1 0 0 1 1 1 1984-11-01 00:00:00 WB8-4 0 0 1 0 1 1 0 0 0 0 1986-04-01 00:00:00 WB8-4 0 0 1 0 1 1 0 1 1 0

[0226] Step 2: Establish a multi-layer reservoir water drive dynamic analysis model.

[0227] 2-1: Calculate the well spacing, average effective thickness, average permeability, average porosity, and average saturation between each pair of wells based on the basic information of oil and water wells in each well.

[0228] The calculation formula for the well spacing between each pair of wells:

[0229]

[0230] Among them, d i,j,l is the well spacing between the i-th well and the j-th well in the l-th layer, X i,l , X j,l are the X coordinates of the i-th well and the j-th well in the l-th layer respectively, and Y i,l , Y j,l are the Y coordinates of the i-th well and the j-th well in the l-th layer respectively.

[0231] The calculation formulas for the average effective thickness, permeability, porosity, and saturation between each pair of wells:

[0232]

[0233] Among them, K i,j,l is the average permeability between the i-th well and the j-th well in the l-th layer, K i,l , K j,l are the permeabilities of the i-th well and the j-th well in the l-th layer respectively. In the formula, K can be replaced by the effective thickness H, porosity Φ, and saturation S w .

[0234] 2-2: Calculate the injection-production correspondence between each pair of wells at the current time step based on the well positions and perforation histories of each well. If there is an injection-production correspondence, set it to 1; otherwise, set it to 0.

[0235] 2-3: Determine the seepage resistance in each injection-production direction based on the well spacing, average effective thickness, average permeability, average porosity, and average saturation in each injection-production direction at the current moment, and divide the reservoir into multiple injection-production units. The splitting coefficient of each injection-production unit is determined according to the following formula:

[0236]

[0237] In the formula, θ i,j,l is the splitting angle of the injection-production unit between the i-th well and the j-th well in the l-th layer; R i,j,l is the seepage resistance between the i-th well and the j-th well in the l-th layer; Δp i,j,l is the injection-production pressure difference between the i-th well and the j-th well in the l-th layer; m is the corresponding number of wells, and n is the corresponding number of layers.

[0238] Each injection-production unit is a quadrilateral, with an oil well and a water well at two opposite corners, as shown in the appendix Figure 9 .

[0239] 2 - 4: Calculate the split injection volume or split production fluid volume for each injection - production unit as follows:

[0240] q i,j,l = q i θ i,j,l

[0241] In the formula, q i,j,l is the split injection volume or split production fluid volume of the i - th well and the j - th well in the l - th layer; q i is the injection volume or production fluid volume of the i - th well.

[0242] Calculate the average saturation, oil production, water production, and injection volume at the end of the current time step for this injection - production unit as follows:

[0243]

[0244] In the formula, S wi,j,l is the average saturation of the i - th well and the j - th well in the l - th layer. f w is the water - cut curve function calculated according to the relative permeability curve, r is the displacement front distance, and r w is the wellbore diameter.

[0245] 2 - 5: Judge whether the time step ends. If it ends, output the calculated oil production FOPR, water production FWPR, and injection volume FWIR. Otherwise, start the next time step and return to step 2 - 2 for iteration.

[0246] The third step: Intelligently correct the geological parameters in the multi - layer reservoir water drive dynamic analysis model.

[0247] 3 - 1: Set the effective thickness H, permeability K, and porosity Φ of each layer of each oil well and water well equal to the initially collected values; set the relative permeability curve equal to the initially collected relative permeability curve, and its characteristic parameter is Kr.

[0248] 3 - 2: Establish a multi - layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and injection volume FWIR.

[0249] 3 - 3: Compare the differences between the calculated oil production FOPR, calculated water production FWPR, calculated injection volume FWIR and the actual oil production FOPRH, actual water production FWPRH, and actual injection volume FWIRH of the reservoir, as shown in the appendix Figure 10 and expressed by the mean square error value MSE.

[0250] 3 - 4: Judge whether the mean square error value is less than the given value. If it is less than, it means that the given geological parameters are relatively accurate, complete the calculation and output the geological parameters. Otherwise, it means that the given geological parameters are not accurate enough, and enter step 3 - 5.

[0251] 3 - 5: Based on the tested geological parameters and the corresponding mean square errors, use the heuristic search algorithm to automatically generate a new geological parameter scheme. The scheme update formula is as follows:

[0252]

[0253] Among them, ΔH, ΔK, ΔΦ, and ΔKr are the update steps of H, K, Φ, and Kr this time. According to different selected heuristic search algorithms, the calculation results of ΔH, ΔK, ΔΦ, and ΔKr are different. Here, the CMA - ES algorithm is selected. After the update, H, K, Φ, and Kr return to step 3 - 2.

[0254] Step 4: Optimization of the layered injection - production scheme.

[0255] 4 - 1: Set the production / injection allocation for each well and each interval as the optimization variables; specifically as follows:

[0256]

[0257] Among them, q i is the production / injection allocation of the i - th interval, q min is the minimum production / injection allocation, q max is the maximum production / injection allocation, Q prod is the overall liquid production rate of the reservoir, Q inj is the overall water injection rate of the reservoir.

[0258] 4 - 2: Set the optimization period, generally between 3 days and 5 years. Here, 2 years is selected. Set the optimization objective function, which can be maximizing cumulative oil production, maximizing economic benefits, or maximizing balanced displacement. The calculation formulas for different objective functions are as follows:

[0259] Maximizing cumulative oil production:

[0260]

[0261] Maximizing economic benefits:

[0262]

[0263] Maximizing balanced displacement, that is, minimizing the saturation standard deviation:

[0264]

[0265] 4 - 3: Set the constraint conditions including the upper and lower limit constraints of the production / injection allocation for each well and each interval, the overall liquid production rate constraint of the reservoir, and the overall water injection rate constraint of the reservoir;

[0266] 4-4: Generate a set of production / injection rate plans Q for each well and each interval that meet the set constraints.

[0267] 4-5: Based on the generated production / injection rate plans for each well and each interval, and the geological parameters determined in Step 3, establish a multi-layer reservoir water drive dynamic analysis model, complete the model calculation, and output the calculated oil production FOPR, water production FWPR, and injection volume FWIR.

[0268] 4-6: Calculate the objective function value under the current production / injection rate plan. Here, maximizing economic benefits is selected, and the objective function value is NPV.

[0269] 4-7: Determine whether the objective function value meets the given stopping condition. If it does, it means the current production / injection rate plan is the optimal plan, complete the calculation and output. Otherwise, it means the current production / injection rate plan is not the optimal plan, and go to Step 4-8.

[0270] 4-8: Based on the tested production / injection rate plans and their corresponding objective function values, use the heuristic search algorithm to automatically generate a new production / injection rate plan. The plan update formula is as follows:

[0271] Q = Q + ΔQ

[0272] where ΔQ is the update step size of Q this time. Depending on the selected heuristic search algorithm, the calculation result of ΔQ is different. Here, the CMA-ES algorithm is selected. After the update, Q is input into Step 4-5. The iterative optimization process is as shown in the appendix Figure 11 As shown, with the progress of optimization, the cumulative oil production of the plan continuously increases, and the cumulative water production continuously decreases, indicating that the plan continuously improves with the progress of the optimization process.

[0273] Fifth step: Real-time push of the stratified injection-production optimization plan.

[0274] 5-1: Push the optimized stratified injection-production plan to reservoir engineering technicians for review.

[0275] 5-2: If the review is passed, convert the stratified injection-production plan into a control signal and transmit it to the stratified injection-production string to achieve remote control. If the review is not passed, go back to Step 1 and start over.

[0276] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0277] Except for the technical features described in the specification, all are well-known technologies to those skilled in the art.

Claims

1. A real-time optimization and control method for reservoir stratified injection and production scheme, characterized in that: The real-time optimization and control method of the reservoir stratified injection and production scheme includes: Step 1: Collect dynamic and static data of the reservoir according to the requirements of the reservoir stratified injection and production plan optimization task; Step 2, establishing a multi-layer reservoir water drive state analysis model; Step 3, correcting geological parameters in the multi-layer reservoir water drive state analysis model; Step 4: Optimize the stratified injection-production plan and generate a new production / injection volume plan.

2. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: In step 1, the collected dynamic and static data of the oil reservoir include basic information of the oil reservoir, basic information of oil and water wells, and dynamic production information of oil and water wells.

3. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 2, characterized in that: In step 1, the basic information of the reservoir includes the number of layers, the number of wells, the viscosity of oil and water, the relative permeability curve, the oil price, the water injection cost, and the liquid production cost.

4. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 2, characterized in that: In step 1, the basic information of oil and water wells includes well location, effective thickness of each layer, permeability of each layer, porosity of each layer, and saturation of each layer.

5. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 2, characterized in that: In step 1, the production dynamic information of oil and water wells includes perforation history, liquid production history, water content history, and water injection history.

6. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: Step 2 includes: Step 21, calculating the well spacing, average effective thickness, average permeability, average porosity, and average saturation between each well based on the basic information of each oil and water well; Step 22, calculating the injection-production correspondence between each well at the current time step; Step 23, determining the seepage resistance in each injection and production direction, and dividing the reservoir into a plurality of injection and production units; Step 24, calculating the split water injection volume or split liquid production volume of each injection and production unit according to the well spacing, average effective thickness, average permeability, average porosity, and average saturation of each injection and production unit; Step 25, according to the split water injection volume or split liquid production volume of each injection-production unit, calculate the average saturation, oil production, water production, and water injection volume of the injection-production unit at the end of the current time step; Step 26, determine whether the time step is the last time step. If so, end the calculation and output the calculated oil production, water production, and water injection volume; otherwise, start the next time step and return to step 22 for iteration.

7. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 6, characterized in that: In step 22, the injection-production correspondence between the wells at the current time step is calculated according to the well positions and perforation histories of the wells. If there is an injection-production correspondence, it is set to 1, otherwise it is set to 0.

8. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 6, characterized in that: In step 23, the seepage resistance in each injection and production direction is determined according to the well spacing, average effective thickness, average permeability, average porosity, and average saturation in each injection and production direction at the current moment, and the oil reservoir is divided into multiple injection and production units, each of which is a quadrilateral, with two diagonals representing an oil well and a water well, respectively.

9. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: Step 3 includes: Step 31: setting the effective thickness of each layer, the permeability of each layer, and the porosity of each layer of each oil and water well to the values ​​initially collected; setting the phase permeability curve to the phase permeability curve initially collected; Step 32: According to the parameters set in step 31, a multi-layer reservoir water drive state analysis model is established using the method in step 2, the model calculation is completed, and the calculated oil production, water production, and water injection volume are output; Step 33: Compare the differences between the calculated oil production, the calculated water production, the calculated water injection volume and the actual oil production, the actual water production and the actual water injection volume of the reservoir, and express them in a mean square error value; Step 34: Determine whether the mean square error value is less than a given value. If so, it means that the geological parameters are relatively accurate, and the calculation is completed and the geological parameters are output; otherwise, it means that the geological parameters are not accurate enough, and go to step 35; Step 35: Based on the geological parameters that have been tested and the corresponding mean square errors, a new geological parameter scheme is automatically generated using a heuristic search algorithm, and the process returns to step 32.

10. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: Step 4 includes: Step 41: setting the production / injection amount of each well and each layer as the optimization variable; Step 42: setting the optimization cycle and the optimization objective function, which may be maximizing the cumulative oil production, maximizing the economic benefit, and maximizing the balanced displacement; Step 43: setting constraints including upper and lower limits of production / injection amount of each well and each layer, overall liquid production rate constraint of the reservoir, and overall water injection rate constraint of the reservoir; Step 44: according to the set constraints, generate a set of production / injection allocation plans for each well and each layer section that meet the constraints; Step 45: Based on the generated production / injection allocation scheme for each well and each layer, and the geological parameters determined in step 3, a multi-layer reservoir water drive state analysis model is established using the method in step 2, the model calculation is completed, and the calculated oil production, water production, and water injection volume are output; Step 46: Calculate the objective function value under the current production allocation / injection allocation plan; Step 47: Determine whether the objective function value satisfies the given stop condition. If so, it means that the current production / injection amount allocation scheme is the optimal scheme, and the calculation is completed and output; otherwise, it means that the current production / injection amount allocation scheme is not the optimal scheme, and go to step 48; Step 48: Based on the production allocation / injection volume scheme that has been tested and the corresponding objective function value, a new production allocation / injection volume scheme is automatically generated using a heuristic search algorithm, and the process returns to step 45.

11. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 10, characterized in that: In step 42, the optimization period is set between 3 days and 5 years.

12. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 10, characterized in that: In step 47, the given stopping conditions include the maximum number of iterations and the maximum calculation time.

13. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: The method for real-time optimization and control of the reservoir stratified injection and production scheme also includes, after step 4, step 5, real-time push of the stratified injection and production optimization scheme.

14. The method for real-time optimization and control of reservoir stratified injection and production scheme according to claim 1, characterized in that: In step 5, the optimized stratified injection and production plan is pushed to the reservoir engineering technicians for review; if the review is passed, the stratified injection and production plan is converted into a control signal and transmitted to the stratified injection and production process string to achieve remote control; if the review is not passed, return to step 1 and repeat it.

15. A real-time optimization and control method system for reservoir stratified injection and production scheme, characterized in that: The system for real-time optimization and control method of reservoir stratified injection and production scheme adopts the real-time optimization and control method labeling method of reservoir stratified injection and production scheme described in any one of claims 1 to 4 to obtain the stratified injection and production scheme and transmits the control signal to the stratified injection and production string for automatic implementation.

Images