CN117684928B - A coordinated optimization control system for oil and water well production and injection under different production modes - Google Patents

Abstract

The invention provides an oil-water well production-injection collaborative optimization control system under different production modes, and belongs to the technical field of information. The oil-water well production and injection collaborative optimization control system under different production modes comprises an oil-water well system production mode selection module, an oil-water well system intelligent decision module and an oil-water well system intelligent control module. The invention establishes the oil-water well system production-injection collaborative optimization control model based on the well-to-well communication relation, performs integrated analysis and global optimization on the oil-production well system and the water injection well system, can meet the actual production requirements of the oil field in different development stages, can select the required production modes aiming at different blocks, different stations and different well groups of the oil field, and is suitable for large-area popularization in the oil field. According to the selected oil field production mode, based on oil gas production big data, an optimal control scheme can be quickly customized, so that the energy conservation, consumption reduction, quality improvement and efficiency improvement of the oil field are realized, the recovery ratio of the oil field is improved, the oil gas development cost is reduced, and the economic benefit of the oil field is improved.

Description

A coordinated optimization control system for oil and water well production and injection under different production modes

Technical Field

The present invention belongs to the field of information technology, and in particular relates to a coordinated optimization control system for oil and water well production and injection under different production modes.

Background technique

Oil production wells and water injection wells are the core production units of water-driven oilfields, and are also the most critical operational management objects that can be controlled by humans to achieve efficient development of oilfields. With the continuous development of oilfields, most of my country's oilfields have entered the middle and late stages of development. The reservoir heterogeneity is serious, the contradiction between injection and production is prominent, and the production cost remains high, which seriously affects the benefits of oilfield development. Therefore, for different oilfields, different blocks or different development stages, it is of great significance to establish a coordinated optimization system for oil and water well production and injection under different production modes to achieve energy conservation and consumption reduction, reduce costs and increase efficiency, and improve the economic benefits of oilfields.

At present, oil fields mainly establish the relationship between oil production wells and water injection wells through reservoir numerical simulation under a single production mode, so as to achieve the optimization control of oil production wells and water injection wells. The optimization cycle is long, the speed is slow, and the calculation complexity is high, and it is impossible to achieve the global real-time optimization of the oil and water well system. In recent years, with the rapid development of big data and artificial intelligence technology, the use of big data driven methods and machine learning technology to carry out the coordinated optimization of oil and water well production and injection under different production modes can greatly reduce the complexity of the system, improve the system's rapid response capability, and achieve real-time and rapid global optimization of the oil and water well system.

Summary of the invention

In view of the above problems, the present invention provides a control system for oil and water well production and injection coordination optimization under different production modes. This method can be used to coordinate the optimization of oil and water well system production and injection under different production modes in different stages, different blocks, and different plants and stations according to the actual development needs of the oil field. It is simple to operate and easy to implement. At the same time, it comprehensively considers the impact of dynamic and static data on the oil and water well system, further improves the global optimization level of the oil and water well system, and is suitable for promotion and application in oil fields.

The technical solution adopted by the present invention to achieve the above-mentioned purpose is: a coordinated optimization control system for oil and water well production and injection under different production modes, including an oil and water well system production mode selection module, an oil and water well system intelligent decision-making module, and an oil and water well system intelligent control module;

The oil-water well system production mode selection module is used to receive different selected production modes;

The oil-water well system intelligent decision-making module is used to make intelligent decisions according to the production mode selected by the oil-water well system production mode selection module, and transmit the decision results to the oil-water well system intelligent control module;

The oil-water well system intelligent control module is used to control the liquid production of the oil production well and the water injection volume of the water injection well according to the decision result.

The production modes include energy-saving mode, maximum production mode and maximum benefit mode.

The oil and water well system intelligent decision-making module includes:

An energy consumption minimization intelligent decision-making unit is used to make energy consumption minimization decisions in energy-saving mode and transmit the decision results to the oil and water well system intelligent control module;

The production maximization intelligent decision-making unit is used to make production maximization decisions under the maximum production mode and transmit the decision results to the oil and water well system intelligent control module;

The benefit maximization intelligent decision-making unit is used to make benefit maximization decisions in the maximum benefit mode and transmit the decision results to the oil and water well system intelligent control module.

The energy consumption minimization intelligent decision-making unit performs the following steps:

The water injection volume i _j and oil production volume q _j are taken as particles, and the fitness function is determined according to the objective function and constraint conditions of minimizing the energy consumption per ton of oil in the oil-water well system. The particle swarm algorithm is used to solve it, and the optimal water injection volume i _j of the water injection well and the liquid production volume q _j of the oil production well are obtained as the decision results;

Among them, the objective function is to minimize the energy consumption per ton of oil in the oil-water well system, and the expression is:

Where: _Winj is the energy consumption of the water injection system; _Wprod is the energy consumption of the oil production system; _Qoil is the oil production of the oil and water well system within a given time range;

Among them, the energy consumption of water injection system _Winj , the energy consumption of oil production system _Wprod , and the _oil production Qoil are expressed as:

Wherein: i _j is the injection volume of the jth water injection well; q _j is the liquid production volume of the jth oil production well; α is the water injection energy consumption weight; β is the oil production energy consumption weight; ρ is the injected water density; P _j is the injection pressure of the jth water injection well; p _j is the bottom hole flowing pressure of the jth water injection well; H _j is the depth of the jth oil production well; g is the gravitational acceleration, f _j is the water content of the jth oil production well; M is the number of water injection wells; N is the number of oil production wells.

The production maximization intelligent decision-making unit performs the following steps:

The water injection volume i _j and the oil production volume q _j are taken as particles, and the fitness function is determined according to the objective function and constraint conditions of maximizing the oil production of the oil-water well system. The particle swarm algorithm is used to solve it, and the optimal water injection volume i _j of the water injection well and the liquid production volume q _j of the oil production well are obtained as the decision results;

Among them, the objective function is to maximize the oil production of the oil and water well system within a given time range, and the expression is:

Where: _qj is the oil production of the jth oil well; N is the number of oil wells in the oil-water well system; _t0 is the initial time, and t is the current time.

The benefit maximization intelligent decision-making unit performs the following steps:

The water injection volume i _j and oil production volume q _j are taken as particles, and the fitness function is determined according to the objective function and constraint conditions of maximizing the production efficiency of the oil and water well system. The particle swarm algorithm is used to solve it, and the optimal water injection volume i _j of the water injection well and the liquid production volume q _j of the oil production well are obtained as the decision results;

Among them, the objective function is to maximize the production efficiency of the oil and water well system within a given time range, and the expression is:

Where: _Ro is the oil price, _Rw is the water injection cost; i _j is the water injection volume of the jth injection well; M is the number of injection wells in the oil-water well system.

The oil and water well system intelligent control module comprises:

The oil well control unit is used to realize the variable speed operation of the oil well motor through the frequency converter according to the oil well production volume in the decision result, so as to control the oil well flushing frequency and the oil well production;

The water injection well control unit is used to adjust the opening of the control valve through the flow automatic controller according to the water injection volume of the water injection well in the decision result, so as to control the water injection volume of the water injection well.

A method for coordinated optimization control of oil and water well production and injection under different production modes comprises the following steps:

The oil and water well system production mode selection module receives different selected production modes;

The intelligent decision-making module of the oil-water well system makes an intelligent decision according to the production mode selected by the production mode selection module of the oil-water well system, and transmits the decision result to the intelligent control module of the oil-water well system;

The intelligent control module of the oil and water well system controls the liquid production of the oil production well and the water injection volume of the water injection well according to the decision results.

The beneficial effects of the present invention are as follows:

(1) The present invention establishes a coordinated optimization control model for oil and water well system production and injection based on the well-to-well connectivity relationship, integrates the oil production well system and the water injection well system for analysis and global optimization, does not require complex and refined reservoir description and numerical simulation processes, and can quantitatively calculate the well-to-well connectivity coefficient only through injection and production data. The method is simple and easy to implement, has low computational complexity, and is convenient for on-site application in oil fields;

(2) The oil-water well production and injection coordinated optimization control system under different production modes established by the present invention can meet the actual production needs of oil fields at different development stages, and can select the required production mode for different blocks, different stations, and different well groups in the oil field, which is suitable for large-scale promotion and application in oil fields;

(3) According to the selected oil field production mode and based on the big data of oil and gas production, a collaborative optimization control plan can be quickly customized to achieve energy conservation and consumption reduction, improve quality and efficiency, and increase oil field recovery rate and economic benefits.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a coordinated optimization control system for oil and water well production and injection under different production modes provided by an embodiment of the present invention.

FIG. 2 is a schematic diagram of a control method of an intelligent control module of an oil-water well system provided by an embodiment of the present invention.

Detailed ways

The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

The present invention establishes a coordinated optimization control model for oil and water well system production and injection based on the well-to-well connectivity relationship, integrates the oil production well system and the water injection well system for analysis and global optimization, can meet the actual production needs of oil fields at different development stages, can select the required production mode for different blocks, different stations, and different well groups in the oil field, and is suitable for large-scale promotion in oil fields. According to the selected oil field production mode, based on the big data of oil and gas production, the optimization control scheme can be quickly customized to achieve energy saving and consumption reduction, quality improvement and efficiency enhancement in the oil field, improve the oil field recovery rate, reduce the cost of oil and gas development, and enhance the economic benefits of the oil field.

As shown in FIG1 , the oil-water well production and injection coordinated optimization control system of this embodiment is described as follows.

The oil and water well production and injection coordinated optimization control system under different production modes of the present invention includes:

Oil and water well system production mode selection module: According to the actual production needs of the oil field, select the corresponding production mode for different blocks, different stations or different development stages of the oil field. The production mode specifically includes energy-saving mode, maximum production mode and maximum benefit mode.

Intelligent decision-making module for oil and water well system: including intelligent decision-making unit for minimizing energy consumption, intelligent decision-making unit for maximizing output, and intelligent decision-making unit for maximizing benefits. According to the intelligent decision-making units corresponding to each production mode, the oil and water well system production and injection collaborative optimization objective function, optimization model decision variables, oil and water well system constraints and model solution methods are determined to give the optimal decision result.

The objective function of the energy consumption minimization intelligent decision-making unit is to minimize the energy consumption per ton of oil in the oil and water well system, and the expression is:

Where: _Winj is the energy consumption of the water injection system, kW·h; _Wprod is the energy consumption of the oil production system, kW·h; _Qoil is the oil production of the oil-water well system within a given time range, t.

The energy consumption of water injection system W _inj , the energy consumption of oil production system W _prod , and the oil production Q _oil can be expressed as:

In the formula: i _j is the injection volume of the jth water injection well, t/d; q _j is the liquid production volume of the jth oil production well, t/d; α is the water injection energy consumption weight; β is the oil production energy consumption weight; ρ is the injected water density, kg/m ³ ; P _j is the injection pressure of the jth water injection well, MPa; p _j is the bottom hole flowing pressure of the jth water injection well, MPa; H _j is the depth of the jth oil production well, m; h is the acceleration of gravity, m/s ² , f _j is the water content of the jth oil production well; M is the number of water injection wells; N is the number of oil production wells.

The objective function of the production maximization intelligent decision-making unit is to maximize the oil production of the oil and water well system within a given time range, and the expression is:

Where: _qj is the oil production of the jth oil well, t/d; N is the number of oil wells in the oil-water well system, _t0 is the initial time, and t is the current time.

The objective function of the benefit maximization intelligent decision-making unit is to maximize the production benefit of the oil and water well system within a given time range, and the expression is:

Where: _Ro is the oil price, USD/t, _Rw is the water injection cost, USD/t; i _j is the water injection volume of the jth injection well, t/d; M is the number of injection wells in the oil-water well system.

Furthermore, the decision variables of the optimization model are determined. Decision variables refer to the quantities to be determined related to the constraints and the objective function involved in the optimization problem. The artificially controllable decision variables in the above optimization problem are the injection volume of the water injection well and the liquid production of the oil production well.

Furthermore, the optimization model constraints are determined: the constraints are the value range restrictions of various factors associated with the objective function in the optimization problem. The above optimization model constraints include water injection system constraints, oil production system constraints and well connectivity constraints.

The constraints of the water injection system include the flow balance constraint of the water injection network, the flow constraint of the water injection pipeline, the injection pressure constraint when the water injection well is running, and the flow characteristic constraint of the water injection well. The expression is:

In the formula: I is the total water injection volume, t/d; i _min is the minimum feasible water injection volume of the injection well, t/d; i _max is the maximum feasible water injection volume of the injection well, t/d; P _min is the lower limit of the operating pressure of the injection well, MPa; P _max is the upper limit of the operating pressure of the injection well, MPa; _Fiw is the pressure drop equation group of the pipe flow in the wellbore of the injection well, _Qiw is the flow vector at the outlet of the wellbore of the injection well, _Piw is the pressure vector at the inlet of the wellbore of the injection well, and p _iw is the pressure vector at the outlet of the wellbore of the injection well.

The constraints of the oil production system include the constraints on the flow value of the oil well and the flow characteristics of the oil production system, and the expression is:

Wherein: q _min is the minimum liquid production of the oil well, t/d; q _max is the maximum liquid production of the oil well, t/d; F _oe is the flow equation of the multiphase flow in the wellbore of the oil well, Q _oe is the flow vector at the inlet and outlet of the oil production system, P _oe is the pressure vector at the inlet and outlet of the oil production system, and T _oe is the temperature vector at the inlet and outlet of the oil production system.

The constraint expression of well connectivity is:

Where: i _k (t) is the cumulative water injection of the kth water injection well, t/d; q _j (t) is the cumulative liquid production of the jth oil production well, t/d; M represents the number of water injection wells around the oil production well, λ _kj is the well-to-well connectivity coefficient between the kth water injection well and the jth oil production well; τ _kj is the time constant between the kth water injection well and the jth oil production well; is the bottom hole flowing pressure of the jth oil production well, MPa; _tn is the development time, d; _t0 is the initial development time, d; _Δtl represents the sampling interval, n is the sampling number.

Furthermore, the optimization model solving method is determined: for the above optimization problems, the particle swarm algorithm is used to solve the energy consumption optimization problem, the maximum output problem and the maximum benefit problem.

Step 4: Use particle swarm algorithm to solve the energy consumption optimization problem of oil and water well system. The optimization model composed of decision variables, objective function of minimizing energy consumption per ton of oil, water injection system constraints, oil production system constraints and well connectivity constraints is solved iteratively using particle swarm algorithm until the optimal water injection volume of water injection wells and liquid production volume of oil production wells are obtained.

According to the optimal parameter combination of water injection rate and liquid production rate obtained by particle swarm algorithm, the water injection rate of water injection wells and the liquid production rate of oil production wells are controlled to minimize the energy consumption of the oil and water well system.

Intelligent control module of oil and water well system: including oil production well control unit and water injection well control unit. According to the optimal decision result made by the intelligent decision module of oil and water well system, the liquid production volume of oil production well and the water injection volume of water injection well are controlled, as shown in Figure 2.

The oil well control unit controls the reasonable level of liquid production based on the results of intelligent decision-making, and realizes variable speed operation of the oil well motor through the frequency converter, thereby controlling the flushing frequency of the oil well and the output of the oil well. The water injection well control unit controls the reasonable level of water injection based on the results of intelligent decision-making, and adjusts the opening of the control valve through the flow automatic control instrument, thereby controlling the water injection volume of the water injection well.

Claims (6)

1. The oil-water well production and injection collaborative optimization control system under different production modes is characterized by comprising an oil-water well system production mode selection module, an oil-water well system intelligent decision module and an oil-water well system intelligent control module;

the production mode selection module of the oil-water well system is used for receiving different selected production modes;

The intelligent decision-making module of the oil-water well system is used for making an intelligent decision according to the production mode selected by the production mode selection module of the oil-water well system and transmitting a decision result to the intelligent control module of the oil-water well system;

The intelligent control module of the oil-water well system is used for controlling the liquid production amount of the oil production well and the water injection amount of the water injection well according to the decision result;

the intelligent decision module of the oil-water well system comprises:

the energy consumption minimization intelligent decision unit is used for making an energy consumption minimization decision in an energy-saving mode and transmitting a decision result to the intelligent control module of the oil-water well system;

The yield maximization intelligent decision unit is used for making yield maximization decision in a maximum yield mode and transmitting decision results to the intelligent control module of the oil-water well system;

The benefit maximization intelligent decision unit is used for making benefit maximization decision under the maximum benefit mode and transmitting the decision result to the intelligent control module of the oil-water well system;

the energy consumption minimization intelligent decision unit performs the following steps:

taking the water injection quantity i _j and the oil recovery quantity q _j as particles, determining a fitness function according to an objective function and a constraint condition of oil-water well system ton oil energy consumption minimization, and solving by using a particle swarm algorithm to obtain the optimal water injection quantity i _j and the optimal oil recovery quantity q _j as decision results;

Wherein, objective function is oil-water well system ton oil energy consumption minimization, and the expression is:

Wherein: w _inj is the energy consumption of the water injection system; w _prod is the energy consumption of the oil extraction system; q _oil is the oil production of the oil-water well system in a given time range;

Wherein, water injection system energy consumption W _inj, oil recovery system energy consumption W _prod, oil recovery Q _oil represent respectively:

Wherein: i _j is the water injection quantity of the j-th water injection well; q _j is the oil production of the j-th oil production well; alpha is the water injection energy consumption weight; beta is the oil extraction energy consumption weight; ρ is the injection water density; p _j is the injection pressure of the j-th water injection well; p _j is the bottom hole flow pressure of the j-th water injection well; h _j is the depth of the j-th oil production well; g is gravity acceleration, and f _j is the water content of the j-th oil production well; m is the number of water injection wells; n is the number of oil recovery wells.

2. The collaborative optimization control system for oil and water well production and injection in different production modes according to claim 1, wherein the production modes include an energy saving mode, a maximum production mode and a maximum benefit mode.

3. The oil-water well production and injection collaborative optimization control system according to claim 1, wherein the yield maximizing intelligent decision unit performs the following steps:

Taking the water injection quantity i _j and the oil recovery quantity q _j as particles, determining a fitness function according to an objective function and a constraint condition of oil production maximization of an oil-water well system, and solving by using a particle swarm algorithm to obtain an optimal water injection well i _j and an optimal oil recovery quantity q _j as decision results;

the objective function is the maximization of oil production of the oil-water well system in a given time range, and the expression is:

Wherein: q _j is the oil production of the j-th oil production well; n is the number of oil recovery wells in the oil-water well system, t ₀ is the initial time, and t is the current time.

4. The collaborative optimization control system for oil-water well production and injection in different production modes according to claim 1, wherein the benefit maximizing intelligent decision unit performs the following steps:

Taking the water injection quantity i _j and the oil recovery quantity q _j as particles, determining a fitness function according to an objective function and a constraint condition of the production benefit maximization of the oil-water well system, and solving by using a particle swarm algorithm to obtain an optimal water injection well i _j and an optimal oil recovery quantity q _j as decision results;

the objective function is the maximization of the production benefit of the oil-water well system in a given time range, and the expression is:

Wherein: r _o is the oil price, R _w is the water injection cost; i _j is the water injection quantity of the j-th water injection well; m is the number of water injection wells in the oil-water well system.

5. The oil-water well production and injection collaborative optimization control system under different production modes according to claim 1, wherein the intelligent control module of the oil-water well system comprises:

The oil production well control unit is used for realizing variable-speed operation of the oil production well motor through the frequency converter according to the liquid production amount of the oil production well in the decision result, so as to control the stroke frequency of the oil production well and the oil production yield;

and the water injection well control unit is used for controlling the water injection amount of the water injection well by adjusting the opening of the valve of the control valve through the flow automatic controller according to the water injection amount of the water injection well in the decision result.

6. The oil-water well production and injection collaborative optimization control method under different production modes is applied to the oil-water well production and injection collaborative optimization control system under different production modes as claimed in claim 1, and is characterized by comprising the following steps:

The production mode selection module of the oil-water well system receives the selected different production modes;

the intelligent decision-making module of the oil-water well system makes an intelligent decision according to the production mode selected by the production mode selection module of the oil-water well system, and transmits a decision result to the intelligent control module of the oil-water well system;

And the intelligent control module of the oil-water well system controls the liquid production amount of the oil production well and the water injection amount of the water injection well according to the decision result.