CN117684928B - Oil-water well production and injection collaborative optimization control system under different production modes - Google Patents
Oil-water well production and injection collaborative optimization control system under different production modes Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 220
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 161
- 238000002347 injection Methods 0.000 title claims abstract description 147
- 239000007924 injection Substances 0.000 title claims abstract description 147
- 238000005457 optimization Methods 0.000 title claims abstract description 46
- 238000011084 recovery Methods 0.000 claims abstract description 28
- 230000008901 benefit Effects 0.000 claims abstract description 24
- 238000005265 energy consumption Methods 0.000 claims description 36
- 239000007788 liquid Substances 0.000 claims description 16
- 239000002245 particle Substances 0.000 claims description 16
- 238000000605 extraction Methods 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 10
- 238000004422 calculation algorithm Methods 0.000 claims description 9
- 230000001133 acceleration Effects 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 238000004891 communication Methods 0.000 abstract description 8
- 230000006872 improvement Effects 0.000 abstract description 6
- 230000009467 reduction Effects 0.000 abstract description 5
- 238000004134 energy conservation Methods 0.000 abstract description 4
- 238000012351 Integrated analysis Methods 0.000 abstract description 3
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- 239000003129 oil well Substances 0.000 description 3
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- 238000004088 simulation Methods 0.000 description 2
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- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
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- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
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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
Technical Field
The invention belongs to the technical field of information, and particularly relates to an oil-water well production-injection collaborative optimization control system under different production modes.
Background
The oil production well and the water injection well are core production units for water drive development of oil fields, and are the most critical operation management objects for realizing efficient development of oil fields, which are manually controllable. Along with the continuous progress of oil field development work, most of oil fields in China enter the middle and later stages of development, the heterogeneity of oil reservoirs is serious, the contradiction between injection and production is prominent, the production cost is high, and the oil field development benefit is seriously affected. Therefore, aiming at different oil fields, different blocks or different development stages, the collaborative optimization system for oil-water well production and injection under different production modes is established, and has important significance for realizing energy conservation and consumption reduction, cost reduction and efficiency enhancement of the oil field and improving the economic benefit of the oil field.
At present, the association between a production well and a water injection well is established through oil reservoir numerical simulation in a single production mode, so that the optimal control of the production well and the water injection well is realized, the optimization period is long, the speed is low, the calculation complexity is high, and the global real-time optimization of an oil-water well system cannot be realized. In recent years, with the rapid development of big data and artificial intelligence technology, the oil-water well production and injection collaborative optimization under different production modes is performed by adopting a big data driving mode and utilizing a machine learning technology, so that the complexity of the system can be greatly reduced, the rapid response capability of the system is improved, and the real-time rapid global optimization of the oil-water well system is realized.
Disclosure of Invention
Aiming at the problems, the invention provides an oil-water well production-injection collaborative optimization control system under different production modes. The method can carry out the collaborative optimization of the oil-water well system production and injection under different production modes at different stages, different blocks and different stations according to the actual development requirements of the oil field, is simple to operate and easy to realize, comprehensively considers the influence of dynamic and static data on the oil-water well system, further improves the global optimization level of the oil-water well system, and is suitable for popularization and application in the oil field.
The technical scheme adopted by the invention for achieving the purpose is as follows: 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 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 production modes include an energy saving mode, a maximum production mode, and a maximum benefit mode.
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;
And 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 of the water injection well and the oil production quantity q j of the oil recovery well 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 liquid production amount 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.
The yield maximization intelligent decision unit performs the following steps:
Taking the water injection quantity i j and the oil production 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 the optimal water injection quantity i j of the water injection well and the oil production quantity q j of the oil production well 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.
The benefit maximization 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 the optimal water injection quantity i j of the water injection well and the oil production quantity q j of the oil recovery well 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.
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.
The oil-water well production and injection collaborative optimization control method under different production modes comprises 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.
The beneficial effects of the invention are as follows:
(1) According to the invention, the oil-water well system oil-water extraction and injection collaborative optimization control model is established based on the inter-well communication relation, the oil-water extraction well system and the water injection well system are subjected to integrated analysis and global optimization, the complex refined oil reservoir description and numerical simulation process are not needed, the inter-well communication coefficient can be quantitatively calculated only through injection and production data, the method is simple and easy to realize, the calculation complexity is low, and the method is convenient for field application of oil fields;
(2) The oil-water well production-injection collaborative optimization control system under different production modes can meet actual production requirements of an oil field in different development stages, can select a required production mode aiming at different blocks, different stations and different well groups of the oil field, and is suitable for large-area popularization and application in the oil field;
(3) According to the selected oil field production mode, based on oil gas production big data, a collaborative optimization control scheme can be rapidly customized, so that the energy conservation, consumption reduction, quality improvement and efficiency improvement of the oil field are realized, and the oil field recovery ratio and economic benefit are improved.
Drawings
Fig. 1 is a schematic diagram of an oil-water well production-injection collaborative optimization control system under different production modes according to an embodiment of the invention.
Fig. 2 is a schematic diagram of a control method of an intelligent control module of an oil-water well system according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
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.
As shown in fig. 1, the oil-water well production-injection collaborative optimization control system of the embodiment is as follows.
The invention relates to an oil-water well production-injection collaborative optimization control system under different production modes, which comprises the following steps:
The production mode selection module of the oil-water well system: according to the actual production requirements of the oil field, corresponding production modes are selected according to different blocks, different stations or different development stages of the oil field. The production modes include specifically an energy saving mode, a maximum production mode, and a maximum benefit mode.
An intelligent decision-making module of the oil-water well system: the method comprises an energy consumption minimization intelligent decision unit, a yield maximization intelligent decision unit and a benefit maximization intelligent decision unit. And determining an oil-water well system mining-injection collaborative optimization objective function, an optimization model decision variable, an oil-water well system constraint condition and a model solving method according to the intelligent decision units corresponding to the production modes, and giving an optimal decision result.
The objective function of the intelligent decision unit for minimizing the energy consumption is to minimize the ton oil energy consumption of the oil-water well system, and the expression is as follows:
Wherein: w inj is the energy consumption of the water injection system, kW.h; w prod is the energy consumption of the oil extraction system, KW.h; q oil is the oil production of the oil-water well system in a given time range, and t.
The water injection system energy consumption W inj, the oil recovery system energy consumption W prod and the oil recovery quantity Q oil can be respectively expressed as:
Wherein: i j is the water injection quantity of the j-th water injection well, and t/d; q j is the liquid production amount of the j-th oil production well, and t/d; alpha is the water injection energy consumption weight; beta is the oil extraction energy consumption weight; ρ is the injection water density, kg/m 3;Pj is the injection pressure of the j-th water injection well, and MPa; p j is the bottom hole flow pressure of the j-th water injection well and MPa; h j is the depth of the j-th oil production well, m; h is the gravity acceleration, and m/s 2,fj is the water content of the j-th oil well; m is the number of water injection wells; n is the number of oil recovery wells.
The objective function of the yield maximization intelligent decision unit is the maximization of the oil production of the oil-water well system in a given time range, and the expression is:
Wherein: q j is the oil production quantity of the j-th oil production well, and t/d; 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.
The objective function of the benefit maximization intelligent decision unit 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 oil price, USD/t, R w is water injection cost, USD/t; i j is the water injection quantity of the j-th water injection well, and t/d; m is the number of water injection wells in the oil-water well system.
Further, optimization model decision variables are determined. Decision variables refer to the quantities to be determined relating to constraints and objective functions involved in the optimization problem. The manually controllable decision variables in the optimization problem are the water injection quantity of the water injection well and the liquid production quantity of the oil extraction well.
Further, an optimization model constraint condition is determined: the constraint condition is a value range constraint condition of each factor associated with the objective function in the optimization problem. The optimization model constraint conditions comprise a water injection system constraint condition, an oil extraction system constraint condition and an inter-well communication relation constraint condition.
The constraint conditions of the water injection system comprise water injection pipe network flow balance constraint, water injection pipeline flow constraint, injection pressure constraint during operation of a water injection well and water injection well shaft flow characteristic constraint, and the expression is as follows:
Wherein: i is total water injection quantity, t/d; i min is the minimum feasible water injection quantity of the water injection well, t/d; i max is the maximum feasible water injection quantity of the water injection well, t/d; p min is the lower limit of the running pressure of the water injection well and MPa; p max is the upper limit of the operation pressure of the water injection well and MPa; f iw is a pressure drop equation set of pipe flow in a water injection well shaft, Q iw is a flow vector at the outlet of the water injection well shaft, P iw is a pressure vector at the inlet of the water injection well shaft, and P iw is a pressure vector at the outlet of the water injection well shaft.
The constraint conditions of the oil extraction system comprise the constraint of the oil extraction well flow value and the constraint of the oil extraction system flow characteristic, and the expression is as follows:
Wherein: q min is the minimum liquid production amount of the oil production well, t/d; q max is the maximum liquid production amount of the oil well, t/d; f oe is the flow equation of the multiphase pipe flow of the oil well shaft, Q oe is the flow vector at the inlet and outlet of the oil recovery system, P oe is the pressure vector at the inlet and outlet of the oil recovery system, and T oe is the temperature vector at the inlet and outlet of the oil recovery system.
The inter-well communication relationship constraint expression is:
Wherein: i k (t) is the accumulated water injection quantity of the kth water injection well, t/d; q j (t) is the accumulated liquid yield of the j-th oil production well, and t/d; m represents the number of water injection wells around the oil extraction well, and lambda kj is the interwell communication coefficient of the kth water injection well and the jth oil extraction well; τ kj is the time constant between the kth water injection well and the jth production well; The bottom hole flow pressure of the j-th oil production well is MPa; t n is development time, d; t 0 is the initial development time, d; Δt l represents the sampling interval, and n is the number of samples.
Further, determining an optimization model solving method: aiming at the optimization problem, solving an energy consumption optimization problem, a maximum yield problem and a maximum benefit problem by adopting a particle swarm algorithm.
Step 4: and solving the problem of optimizing the energy consumption of the oil-water well system by adopting a particle swarm algorithm. And carrying out iterative solution on an optimization model consisting of decision variables, ton oil energy consumption minimization objective functions, water injection system constraints, oil production system constraints and inter-well communication relation constraints by using a particle swarm algorithm until optimal water injection rate of the water injection well and optimal oil production rate parameters of the oil production well are obtained.
And controlling the water injection rate of the water injection well and the liquid production rate of the oil extraction well according to the optimal parameter combination of the water injection rate and the liquid production rate obtained by the particle swarm optimization, so that the energy consumption of the oil-water well system is minimized.
Intelligent control module of oil-water well system: comprises a production well control unit and a water injection well control unit. And controlling the liquid production amount of the oil production well and the water injection amount of the water injection well according to the optimal decision result formulated by the intelligent decision module of the oil-water well system, as shown in figure 2.
The oil production well control unit controls reasonable liquid production level based on intelligent decision results, and realizes variable-speed operation of the oil production well motor through the frequency converter, so that the stroke frequency of the oil production well is controlled, and the oil production is controlled. The water injection well control unit controls reasonable water injection level based on intelligent decision results, and the opening of the valve of the control valve is adjusted through the flow automatic controller, so that the water injection amount of the water injection well is controlled.
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.
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| RU2109131C1 (en) * | 1996-02-05 | 1998-04-20 | Сумбат Набиевич Закиров | Method for development of oil-gas deposits |
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| CN110795893A (en) * | 2019-11-07 | 2020-02-14 | 中国石油化工股份有限公司 | Energy consumption integral optimization method for water injection development oil field injection and production system |
| CN112836349A (en) * | 2021-01-08 | 2021-05-25 | 中国石油大学(北京) | Injection-production joint debugging intelligent decision method and system based on shaft parameters |
| CN112922569A (en) * | 2021-02-07 | 2021-06-08 | 西安石油大学 | Method for determining optimal operation state of pressurization and partial pressure mode of oil field water injection pipe network |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2109131C1 (en) * | 1996-02-05 | 1998-04-20 | Сумбат Набиевич Закиров | Method for development of oil-gas deposits |
| CN110439515A (en) * | 2019-06-24 | 2019-11-12 | 中国石油化工股份有限公司 | Note adopts parameter optimization method and device |
| CN110795893A (en) * | 2019-11-07 | 2020-02-14 | 中国石油化工股份有限公司 | Energy consumption integral optimization method for water injection development oil field injection and production system |
| CN112836349A (en) * | 2021-01-08 | 2021-05-25 | 中国石油大学(北京) | Injection-production joint debugging intelligent decision method and system based on shaft parameters |
| CN112922569A (en) * | 2021-02-07 | 2021-06-08 | 西安石油大学 | Method for determining optimal operation state of pressurization and partial pressure mode of oil field water injection pipe network |
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