Layout method and system for oil and gas pipe network, electronic equipment and storage medium

Abstract

The invention discloses a layout method and system for an oil and gas pipe network, electronic equipment and a storage medium, and relates to the technical field of pipeline layout, and the method comprises the following steps: obtaining to-be-laid area information and cost constraint conditions, and generating a first optimal solution according to layout data of a target oil and gas pipe network, and comparing the optimal solution with the actual operation cost output by the layout data planning model, and finally determining a final layout result according to the optimal solution. According to the method, the initial solution with the highest matching degree with the planning requirement can be obtained by means of big data, and the layout result of the oil-gas pipe network can better meet the requirement by combining the solution of the target function and the constraint condition.

Description

Background Art

[0002] The site selection and thermal network planning of regional integrated energy stations are one of the most noteworthy issues in the planning process of regional integrated energy stations. In the prior art, the node layout method of oil and gas pipeline networks randomly generates an initial solution, and then uses a genetic algorithm or a particle swarm algorithm to obtain the optimal solution with the lowest cost as the optimization condition.

[0003] However, the initial solution generated by the above method is too random, which will prolong the calculation iteration time, and the obtained solution cannot match the planning requirements well, and the output optimal solution lacks correction operations, resulting in inaccurate results. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a layout method, system, electronic device and storage medium for oil and gas pipeline networks, as follows: 1) In the first aspect, the present invention provides a layout method for an oil and gas pipeline network, and the specific technical solution is as follows: S1. Inputting the information of the area to be laid out and the cost constraints into the layout data planning model to obtain the layout data of the target oil and gas pipeline network; the information of the area to be laid out includes the area information and the constraints of the area to be laid out; S2. According to the layout data of the target oil and gas pipeline network, a genetic algorithm is used to obtain a first optimal solution; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the level of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; S3, calculating the total cost corresponding to the first optimal solution according to the objective function, and outputting the optimal solution when the total cost satisfies the cost constraint condition, otherwise repeating S2; S4. According to the optimal solution, determine the number of levels of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network, and the coordinate value of each node, and output the final layout result.

[0005] The beneficial effects of the layout method for oil and gas pipeline network provided by the present invention are as follows: The present invention proposes a layout method for oil and gas pipeline networks, including obtaining information on the area to be laid out and cost constraints, and performing preprocessing, generating a first optimal solution based on the layout data of the target oil and gas pipeline network, calculating the total cost corresponding to the first optimal solution, and comparing it with the actual operating cost output by the layout data planning model, outputting the optimal solution when the difference between the two is less than a preset value, otherwise repeating the iteration, and finally determining the total number of nodes of the oil and gas pipeline network to be laid out, the level of the oil and gas pipeline network, and the coordinate value of each node based on the optimal solution, and outputting the final layout result. The initial layout data can be first obtained through the layout data planning model, and then the optimal solution is obtained for the initial layout data, thereby generating the final layout result. By solving the initial layout data, the initial solution with the highest matching degree with the planning requirements can be obtained with the help of big data, and combined with the solution of the objective function and the constraints, the layout result of the oil and gas pipeline network can be made more in line with the requirements.

[0006] On the basis of the above scheme, the layout method for oil and gas pipeline network of the present invention can also be improved as follows.

[0007] Furthermore, S1 includes: S11, generating a layout area according to the information of the area to be laid out, wherein the layout area is surrounded by a plurality of boundary points and lines connecting adjacent boundary points; S12, determining the geometric center point of the layout area, and obtaining the coordinate value of the geometric center point; S13. Input the coordinate value of the geometric center point, area information, geographical location of the oil and gas pipeline network and cost constraints into the layout data planning model, output the actual layout area of ​​the oil and gas pipeline network, actual boundary point coordinates, actual oil well coordinates, actual oil and gas pipeline network level, total number of nodes at each level and actual operating cost, and obtain the layout data of the target oil and gas pipeline network.

[0008] Further, S2 includes: S21, randomly generate L chromosomes according to the coordinates of the oil wells in the layout data and the total number of nodes at all levels to form an initial population; S22, calculate the fitness of each chromosome in the initial population, and retain the top three chromosomes with the highest fitness; S23, among the first three chromosomes, select two chromosomes in a permutation and combination manner, exchange some genes with a specified probability, and generate three first chromosomes; S24, for each first chromosome, changing part of its gene value with a specified probability to form a second chromosome, thereby forming three second chromosomes; S25, calculating the objective function value for each second chromosome respectively, and determining the second chromosome with the highest objective function value as the first target chromosome; S26, for the first target chromosome, changing part of its gene values ​​with a specified probability to form a second target chromosome; S27. Calculate the objective function value of the second target chromosome, and obtain the difference between the objective function values of the first target chromosome and the second target chromosome. If the difference is less than the preset value, determine the second target chromosome as the first optimal solution; otherwise, repeat S26.

[0009] Furthermore, the chromosome is represented as: where m represents the total number of nodes at all levels, z represents the propagation generation, represents the coordinates of the i-th oil well in the z-th generation chromosome, i = 1, 2,..., m, C z represents the z-th generation chromosome.

[0010] Furthermore, the calculation formula of the fitness function is: fitness(C z ) = exp[-(f(C z ) - f min) )] where fitness(C z ) represents the fitness of chromosome C z , f(C z ) represents the objective function value corresponding to chromosome C z , and f min represents the minimum value of the objective function in the current generation chromosome.

[0011] Furthermore, S3 includes: Determine the coordinate values of each node of the oil and gas pipeline network to be laid out from the first optimal solution, and calculate the total cost according to the coordinate values of each node, the total number of nodes, and the objective function; Compare the total cost with the actual operating cost output by the layout data planning model. When the absolute value of the difference between the two is less than the preset value, output the optimal solution; otherwise, repeat S2.

[0012] Furthermore, the calculation formula of the objective function is: where F represents the total cost, F S represents the construction cost of the oil well, F P represents the investment cost of pipeline construction, F 0t represents the production and operation cost in the t-th year, represents the annual interest rate of the loan during the service life, T represents the service life, t is a positive integer, 0 < t < T, and min F means: minimize the total cost.

[0013] 2) In the second aspect, the present invention also provides a layout system for an oil and gas pipeline network. The specific technical solution is as follows: It includes a layout data acquisition module, an optimal solution solution module, a total cost calculation and judgment module, and a final layout result acquisition module; the layout data acquisition module is used to: input the information of the area to be laid out and the cost constraints into the layout data planning model to obtain the layout data of the target oil and gas pipeline network, and the information of the area to be laid out includes the area information and constraints of the area to be laid out; The optimal solution solving module is used to: obtain the first optimal solution by using a genetic algorithm according to the layout data of the target oil and gas pipeline network; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the number of levels of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; The total cost calculation and judgment module is used to: calculate the total cost corresponding to the first optimal solution according to the objective function, and output the optimal solution when the total cost meets the cost constraint condition, otherwise repeatedly execute the layout data acquisition module; The final layout result acquisition module is used to determine the number of levels of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network, and the coordinate value of each node according to the optimal solution, and output the final layout result.

[0014] On the basis of the above scheme, the layout system for oil and gas pipeline network of the present invention can also be improved as follows.

[0015] Furthermore, the layout data acquisition module is specifically used for: Generate a layout area according to the information of the area to be laid out, wherein the layout area is surrounded by a plurality of boundary points and lines connecting adjacent boundary points; Determine the geometric center point of the layout area and obtain the coordinate value of the geometric center point; The coordinate value of the geometric center point, area information, geographical location of the oil and gas pipeline network and cost constraints are input into the layout data planning model, and the actual layout area of ​​the oil and gas pipeline network, actual boundary point coordinates, actual oil well coordinates, actual oil and gas pipeline network level, total number of nodes at each level and actual operating cost are output to obtain the layout data of the target oil and gas pipeline network.

[0016] Further, the optimal solution solving module includes a first solving module, a second solving module and a third solving module; The first solution module is used to: randomly generate L chromosomes according to the coordinates of the oil wells in the layout data and the total number of nodes at all levels to form an initial population; calculate the fitness of each chromosome in the initial population, and retain the first three chromosomes with the highest fitness; select two chromosomes from the first three chromosomes in a permutation and combination manner, exchange some genes with a specified probability, and generate three first chromosomes; for each first chromosome, change its part of the gene value with a specified probability to form a second chromosome, and form three second chromosomes; for each second chromosome, calculate the objective function value respectively, and determine the second chromosome with the highest objective function value as the first target chromosome; The second solution module is used to: for the first target chromosome, change some of its gene values with a specified probability to form a second target chromosome; The third solution module is used to: calculate the objective function value of the second target chromosome, and obtain the difference between the objective function values of the first target chromosome and the second target chromosome. If the difference is less than the preset value, the second target chromosome is determined as the first optimal solution; otherwise, the second solution module is called repeatedly.

[0017] Furthermore, the chromosome is represented as: where m represents the total number of nodes at all levels, z represents the propagation generation, represents the coordinates of the i-th oil well in the z-th generation chromosome, i = 1, 2,..., m, C z represents the z-th generation chromosome.

[0018] Furthermore, the function calculation formula for fitness is: fitness(C z ) = exp[-(f(C z ) - f min )] where fitness(C z ) represents the fitness of chromosome C z , f(C z ) represents the objective function value corresponding to chromosome C z , and f min represents the minimum value of the objective function in the current generation chromosome.

[0019] Furthermore, the total cost calculation and judgment module is used to: Determine the coordinate values of each node of the oil and gas pipeline network to be laid out from the first optimal solution, and calculate the total cost according to the coordinate values of each node, the total number of nodes, and the objective function; Compare the total cost with the actual operating cost output by the layout data planning model. When the absolute value of the difference between the two is less than the preset value, the optimal solution is output; otherwise, the optimal solution solving module is called repeatedly.

[0020] Furthermore, the calculation formula for the objective function is: where F represents the total cost, F S represents the construction cost of the oil well, F P represents the pipeline construction investment cost, F 0t represents the production operation cost in the t-th year, represents the annual interest rate of the loan during the service life, T represents the service life, t is a positive integer, 0 < t < T, and min F means: minimize the total cost.

[0021] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor so that the electronic device implements any one of the above-mentioned layout methods for oil and gas pipeline networks.

[0022] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is loaded and executed by a processor so that the computer implements the above-mentioned layout method for oil and gas pipeline networks.

[0023] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 A schematic diagram of a flow chart of a layout method for an oil and gas pipeline network according to an embodiment of the present invention; Figure 2 This is a structural schematic diagram of a layout system for an oil and gas pipeline network according to an embodiment of the present invention; Figure 3 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0026] like Figure 1 As shown, a layout method for an oil and gas pipeline network according to an embodiment of the present invention comprises the following steps: S1. Input the information of the area to be laid out and the cost constraints into the layout data planning model to obtain the layout data of the target oil and gas pipeline network; the information of the area to be laid out includes the area information and constraints of the area to be laid out, and the area information refers to the area allowed for layout. The constraints include that the shape of the layout area must be square or circular, and the layout area cannot conflict with the living area, etc.

[0027] S2. According to the layout data of the target oil and gas pipeline network, a genetic algorithm is used to obtain a first optimal solution; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the level of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; S3, calculating the total cost corresponding to the first optimal solution according to the objective function, and outputting the optimal solution when the total cost satisfies the cost constraint condition, otherwise repeating S2; S4. According to the optimal solution, determine the number of levels of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network, and the coordinate value of each node, and output the final layout result.

[0028] Optionally, in the above technical solution, S1 includes: S11, generating a layout area according to the information of the area to be laid out, wherein the layout area is surrounded by a plurality of boundary points and lines connecting adjacent boundary points; S12, determining the geometric center point of the layout area, and obtaining the coordinate value of the geometric center point; S13. Input the coordinate value of the geometric center point, area information, geographical location of the oil and gas pipeline network and cost constraints into the layout data planning model, output the actual layout area of ​​the oil and gas pipeline network, actual boundary point coordinates, actual oil well coordinates, actual oil and gas pipeline network level, total number of nodes at each level and actual operating cost, and obtain the layout data of the target oil and gas pipeline network.

[0029] The layout data includes the coordinates of the oil well nodes, the levels of the pipeline network, and the total number of nodes at each level.

[0030] Among them, the level of the pipeline network refers to the first-level pipeline network, the second-level pipeline network, etc., and the lower-level pipeline network is a sub-branch of the upper-level pipeline network.

[0031] In one embodiment of the present invention, the layout data planning model is trained and obtained in the following manner: S111. Obtain sample data.

[0032] The sample data includes information about existing oil and gas pipeline networks. The information includes the geographical location of the existing oil and gas pipeline network, the planned layout area, the cost budget, the coordinates of the planned geometric center point of the area to be laid out, as well as the actual layout area of ​​the existing oil and gas pipeline network, the actual boundary point coordinates, the coordinates of the actual oil well nodes, the actual number of pipeline levels, the total number of nodes at each level, and the actual operating cost.

[0033] S112. According to the sample data, a 4-input 6-output convolutional neural network is trained to obtain a layout data planning model.

[0034] Taking the geographical location of the existing oil and gas pipeline network, the planned layout area, the cost budget, and the coordinate values of the planned geometric center point of the area to be laid out as the input of the model, and taking the actual layout area of the oil and gas pipeline network, the coordinates of the actual boundary points, the coordinates of the actual oil well nodes, the actual number of pipeline levels, the total number of nodes at each level, and the actual operating cost as the output, training a convolutional neural network model to obtain a layout data planning model.

[0035] Optionally, in the above technical solution, S2 includes: S21. According to the coordinates of the oil wells in the layout data and the total number of nodes at each level, randomly generate L chromosomes to form an initial population, that is, generate an initial population according to the layout data.

[0036] Among them, the chromosome is expressed as: Among them, m represents the total number of nodes at each level, z represents the propagation generation, represents the coordinates of the i-th oil well in the z-th generation chromosome, i = 1, 2,..., m, C z represents the z-th generation chromosome.

[0037] S22. Calculate the fitness of each chromosome in the initial population, and retain the top 3 chromosomes with the highest fitness; Among them, the function calculation formula of the fitness is: fitness(C z ) = exp[-(f(C z ) - f min )] Among them, fitness(C z ) represents the fitness of chromosome C z , f(C z ) represents the objective function value corresponding to chromosome C z , f min represents the minimum value of the objective function in the current generation of chromosomes.

[0038] Among them, taking the lowest total cost as the optimization goal, the objective function is formed as follows: Among them, F represents the total cost, F S represents the construction cost of the oil well, F P represents the pipeline construction investment cost, F 0t represents the production operation cost in the t-th year, represents the annual interest rate of the loan during the service life, T represents the service life, t is a positive integer, 0 < t < T, min F means: minimizing the total cost.

[0039] The units of the above-mentioned expenses are all ten thousand yuan, and the units of the above-mentioned periods are all years.

[0040] The specific calculation method of the above fees is as follows: The cost of oil well construction S for: F ij For Node The cost of the node represents the oil and gas processing node of the jth oil well in the i-th level pipeline network, N refers to the total number of pipeline levels, m i Represents the number of oil wells in the i-th level pipeline network.

[0041] Pipeline construction investment cost F p The pipeline construction cost F p1 and the cost of the anti-corrosion insulation layer p2 The specific calculation method is as follows: F p1 =(a0+a1×M)×l×10 -3 a0 is the cost of survey, design and construction of pipeline per unit length, unit is 10,000 yuan / km, a1 is the price of pipe per unit weight, unit is 10,000 yuan / ton, M is the weight of pipe per unit length, unit is ton / km, l is the pipe length, unit is meter. It should be noted that a0 is an evaluation value, a1 and M are parameter values ​​corresponding to the pipe.

[0042] F p2 =(M B +M F ×M S )×10 -4 M B is the cost of the insulation layer, M F is the cost of auxiliary materials, M S is the construction cost, M B 、M F and M S Obtained through calculation of the structural parameters of the pipe.

[0043] Therefore, the pipeline construction investment cost F p The calculation method is as follows: Where, j represents the jth oil well in the i-th level pipeline network, k represents the kth oil and gas processing node in the jth oil well in the i-th level pipeline network, ξ ijk Indicates the connection relationship between different oil and gas processing nodes in different oil wells of different levels. If there is a connection relationship, the value is 1, otherwise it is 0. P1ijkis the pipeline construction cost of the kth oil and gas processing node of the jth oil well in the i-th level pipeline network, F P2ijk It is the cost of the anti-corrosion insulation layer of the kth oil and gas processing node of the jth oil well in the i-th level pipeline network.

[0044] The constraints for solving the objective function include the processing capacity constraints of the station and the production operation process constraints, as follows: Processing capacity constraints of the station: in, Refers to the liquid production of the kth oil and gas processing node in the i-1th level pipeline network, Refers to the processing capacity of the jth oil well in the i-th level pipeline network.

[0045] Production operation process constraints: 1) Temperature constraints upon entry: T i ≥[T0] Among them, T i is the crude oil inlet temperature of the i-th level pipeline network, T0 is the allowable crude oil inlet temperature, [T0] is: round T0, the crude oil inlet temperature is usually 3 to 5°C above the crude oil freezing point.

[0046] 2) Minimum pit stop pressure constraint: The crude oil inlet pressure must be greater than a certain value, and the preferred minimum inlet pressure is 0.3MPA.

[0047] 3) Wellhead back pressure constraint: P i ≤[P0] P i is the wellhead back pressure value of each oil well in the i-th level pipeline network, P0 is the allowable value of the inlet back pressure, [P0] means rounding P0, for heavy oil fields, P0 is 1.5MPA.

[0048] S23, among the first three chromosomes, select two chromosomes in a permutation and combination manner, exchange some genes with a specified probability, and generate three first chromosomes; S24, for each first chromosome, changing part of its gene value with a specified probability to form a second chromosome, thereby forming three second chromosomes; S25, calculating the objective function value for each second chromosome respectively, and determining the second chromosome with the highest objective function value as the first target chromosome; S26, for the first target chromosome, changing part of its gene values ​​with a specified probability to form a second target chromosome; S27, calculating the objective function value of the second target chromosome, and obtaining the difference between the objective function values ​​of the first target chromosome and the second target chromosome. If the difference is less than a preset value, the second target chromosome is determined as the first optimal solution, otherwise S26 is repeated.

[0049] Due to the randomness of the genetic algorithm, each iteration will get different results according to the same specified probability, thus obtaining a different first optimal solution.

[0050] Optionally, in the above technical solution, S3 includes: Determine the coordinate values ​​of each node of the oil and gas pipeline network to be laid out from the first optimal solution, and calculate the total cost according to the coordinate values ​​of each node, the total number of nodes and the objective function; The total cost is compared with the actual operating cost output by the layout data planning model. When the absolute value of the difference between the two is less than the preset value, the optimal solution is output, otherwise S2 is repeated.

[0051] The present invention proposes a layout method for oil and gas pipeline networks, including obtaining information on the area to be laid out and cost constraints, and performing preprocessing, generating a first optimal solution based on the layout data of the target oil and gas pipeline network, calculating the total cost corresponding to the first optimal solution, and comparing it with the actual operating cost output by the layout data planning model, outputting the optimal solution when the difference between the two is less than a preset value, otherwise repeating the iteration, and finally determining the total number of nodes of the oil and gas pipeline network to be laid out, the level of the oil and gas pipeline network, and the coordinate value of each node based on the optimal solution, and outputting the final layout result. The initial layout data can be first obtained through the layout data planning model, and then the optimal solution is obtained for the initial layout data, thereby generating the final layout result. By solving the initial layout data, the initial solution with the highest matching degree with the planning requirements can be obtained with the help of big data, and combined with the solution of the objective function and the constraints, the layout result of the oil and gas pipeline network can be made more in line with the requirements.

[0052] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0053] like Figure 2As shown, a layout system 200 for an oil and gas pipeline network according to an embodiment of the present invention comprises a layout data acquisition module 201, an optimal solution solving module 202, a total cost calculation and judgment module 203, and a final layout result acquisition module 204; the layout data acquisition module 201 is used to: input the information of the area to be laid out and the cost constraint conditions into the layout data planning model to obtain the layout data of the target oil and gas pipeline network, and the information of the area to be laid out includes the area information and the constraint conditions of the area to be laid out; The optimal solution solving module 202 is used to: use a genetic algorithm to find a first optimal solution according to the layout data of the target oil and gas pipeline network; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the level of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; The total cost calculation and judgment module 203 is used to: calculate the total cost corresponding to the first optimal solution according to the objective function, and output the optimal solution when the total cost meets the cost constraint condition, otherwise repeatedly execute the layout data acquisition module 201; The final layout result acquisition module 204 is used to determine the level of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network and the coordinate value of each node according to the optimal solution, and output the final layout result.

[0054] Optionally, in the above technical solution, the layout data acquisition module 201 is specifically used for: Generate a layout area according to the information of the area to be laid out, wherein the layout area is surrounded by a plurality of boundary points and lines connecting adjacent boundary points; Determine the geometric center point of the layout area and obtain the coordinate value of the geometric center point; The coordinate value of the geometric center point, area information, geographical location of the oil and gas pipeline network and cost constraints are input into the layout data planning model, and the actual layout area of ​​the oil and gas pipeline network, actual boundary point coordinates, actual oil well coordinates, actual oil and gas pipeline network level, total number of nodes at each level and actual operating cost are output to obtain the layout data of the target oil and gas pipeline network.

[0055] Optionally, in the above technical solution, the optimal solution solving module 202 includes a first solving module, a second solving module and a third solving module; The first solution module is used to: randomly generate L chromosomes according to the coordinates of the oil wells in the layout data and the total number of nodes at all levels to form an initial population; calculate the fitness of each chromosome in the initial population, and retain the first three chromosomes with the highest fitness; select two chromosomes from the first three chromosomes in a permutation and combination manner, exchange some genes with a specified probability, and generate three first chromosomes; for each first chromosome, change its part of the gene value with a specified probability to form a second chromosome, and form three second chromosomes; for each second chromosome, calculate the objective function value respectively, and determine the second chromosome with the highest objective function value as the first target chromosome; The second solution module is used to: for the first target chromosome, change part of its gene values ​​with a specified probability to form a second target chromosome; The third solution module is used to calculate the objective function value of the second target chromosome and obtain the difference between the objective function values ​​of the first target chromosome and the second target chromosome. If the difference is less than a preset value, the second target chromosome is determined as the first optimal solution, otherwise the second solution module is repeatedly called.

[0056] Optionally, in the above technical solution, the chromosome is represented as: Among them, m represents the total number of nodes at each level, z represents the number of propagation generations, represents the coordinates of the i-th oil well in the z-th generation chromosome, i = 1, 2, ..., m, C z Represents the chromosome of generation z.

[0057] Optionally, in the above technical solution, the function calculation formula of fitness is: fitness(C z )=exp[-(f(C z )-f min )] Among them, fitness(C z ) indicates chromosome C z The fitness of f(C z ) indicates chromosome C z The corresponding objective function value, f min Represents the minimum value of the objective function in the current generation of chromosomes.

[0058] Optionally, in the above technical solution, the total cost calculation and judgment module 203 is used to: Determine the coordinate values ​​of each node of the oil and gas pipeline network to be laid out from the first optimal solution, and calculate the total cost according to the coordinate values ​​of each node, the total number of nodes and the objective function; Compare the total cost with the actual operating cost output by the layout data planning model. When the absolute value of the difference between the two is less than the preset value, output the optimal solution; otherwise, repeatedly call the optimal solution solving module 202.

[0059] Optionally, in the above technical solution, the calculation formula of the objective function is: where F represents the total cost, F S represents the construction cost of the oil well, F P represents the pipeline construction investment cost, F 0t represents the production operation cost in the t-th year, represents the annual interest rate of the loan during the service life, T represents the service life in years, t is a positive integer, 0 < t < T, and min F means: minimize the total cost.

[0060] It should be noted that the beneficial effects of the layout system 200 for oil and gas pipeline networks provided in the above embodiments are the same as those of the above layout method for oil and gas pipeline networks, and will not be elaborated here. In addition, when the system provided in the above embodiments realizes its functions, only the above-mentioned division of each functional module is used as an example. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the system can be divided into different functional modules according to the actual situation to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments, which will not be elaborated here.

[0061] As Figure 3 shown, an electronic device 300 according to an embodiment of the present invention includes a processor 320. The processor 320 is coupled to a memory 310, and at least one computer program 330 is stored in the memory 310. The at least one computer program 330 is loaded and executed by the processor 320 so that the electronic device 300 implements any one of the above layout methods for oil and gas pipeline networks. Specifically: The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein at least one computer program 330 is stored in the one or more memories 310, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any one of the layout methods for oil and gas pipeline networks provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The electronic device 300 may also include other components for realizing device functions, which will not be described in detail here. The electronic device may specifically be a computer, etc.

[0062] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements any of the above-mentioned layout methods for oil and gas pipeline networks.

[0063] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0064] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes any of the above-mentioned layout methods for an oil and gas pipeline network.

[0065] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0066] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0067] Any combination of one or more computer-readable media can be used. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0068] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A layout method for an oil and gas pipeline network, characterized in that: include: S1. Inputting the information of the area to be laid out and the cost constraints into the layout data planning model to obtain the layout data of the target oil and gas pipeline network; the information of the area to be laid out includes the area information and the constraints of the area to be laid out; S2. According to the layout data of the target oil and gas pipeline network, a genetic algorithm is used to obtain a first optimal solution; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the level of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; S3, calculating the total cost corresponding to the first optimal solution according to the objective function, and outputting the optimal solution when the total cost satisfies the cost constraint condition, otherwise repeating S2; S4. According to the optimal solution, determine the level of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network, and the coordinate value of each node, and output the final layout result.

2. A layout method for an oil and gas pipeline network according to claim 1, characterized in that: The S1 includes: S11, generating a layout area according to the information of the area to be laid out, wherein the layout area is surrounded by a plurality of boundary points and lines connecting adjacent boundary points; S12, determining the geometric center point of the layout area, and obtaining the coordinate value of the geometric center point; S13. Input the coordinate value of the geometric center point, the area information, the geographical location of the oil and gas pipeline network and the cost constraint conditions into the layout data planning model, output the actual layout area of ​​the oil and gas pipeline network, the actual boundary point coordinates, the coordinates of the actual oil wells, the actual level of the oil and gas pipeline network, the total number of nodes at each level and the actual operating cost, and obtain the layout data of the target oil and gas pipeline network.

3. A layout method for oil and gas pipeline network according to claim 2, characterized in that: The S2 includes: S21, randomly generating L chromosomes according to the coordinates of the oil wells in the layout data and the total number of nodes at each level to form an initial population; S22, calculating the fitness of each chromosome in the initial population, and retaining the top three chromosomes with the highest fitness; S23, selecting two chromosomes from the first three chromosomes in a permutation and combination manner, exchanging some genes with a specified probability, and generating three first chromosomes; S24. For each of the first chromosomes, change part of its gene value with a specified probability to form a second chromosome, thereby forming three second chromosomes; S25, calculating the objective function value for each second chromosome respectively, and determining the second chromosome with the highest objective function value as the first target chromosome; S26. For the first target chromosome, change part of its gene values ​​with a specified probability to form a second target chromosome; S27, calculating the objective function value of the second target chromosome, and obtaining the difference between the objective function values ​​of the first target chromosome and the second target chromosome. If the difference is less than a preset value, the second target chromosome is determined as the first optimal solution, otherwise S26 is repeated.

4. A layout method for oil and gas pipeline network according to claim 3, characterized in that: Chromosomes are represented as: Among them, m represents the total number of nodes at each level, z represents the number of propagation generations, represents the coordinates of the i-th oil well in the z-th generation chromosome, i = 1, 2, ..., m, C z Represents the chromosome of generation z.

5. A layout method for oil and gas pipeline network according to claim 4, characterized in that: The function calculation formula of fitness is: fitness(C z )=exp[-(f(C z )-f min )] Among them, fitness(C z ) indicates chromosome C z The fitness of f(C z ) indicates chromosome C z The corresponding objective function value, f min Represents the minimum value of the objective function in the current generation of chromosomes.

6. A layout method for oil and gas pipeline network according to claim 5, characterized in that: The S3 includes: Determine the coordinate values ​​of each node of the oil and gas pipeline network to be laid out from the first optimal solution, and calculate the total cost according to the coordinate values ​​of each node, the total number of nodes and the objective function; The total cost is compared with the actual operating cost output by the layout data planning model, and when the absolute value of the difference between the two is less than a preset value, the optimal solution is output, otherwise, S2 is repeatedly executed.

7. A layout method for oil and gas pipeline network according to claim 6, characterized in that: The calculation formula of the objective function is: Among them, F represents the total cost, F S represents the construction cost of the oil well, F P represents the pipeline construction investment cost, F 0t represents the production operation cost in the t-th year, represents the annual interest rate of the loan during the service life, T represents the service life, t is a positive integer, 0 < t < T, and min F means: minimizing the total cost.

8. A layout system for oil and gas pipeline network, characterized in that: It includes a layout data acquisition module, an optimal solution solution module, a total cost calculation and judgment module, and a final layout result acquisition module; The layout data acquisition module is used to input the information of the area to be laid out and the cost constraints into the layout data planning model to obtain the layout data of the target oil and gas pipeline network, wherein the information of the area to be laid out includes the area information and the constraints of the area to be laid out; the optimal solution solving module is used to use a genetic algorithm to obtain a first optimal solution according to the layout data of the target oil and gas pipeline network; the layout data of the target oil and gas pipeline network includes the coordinates of the oil wells, the level of the oil and gas pipeline network, and the total number of nodes at each level; the first optimal solution includes the coordinate values ​​of each node in the oil and gas pipeline network to be laid out; The total cost calculation and judgment module is used to: calculate the total cost corresponding to the first optimal solution according to the objective function, and output the optimal solution when the total cost meets the cost constraint condition, otherwise repeatedly execute the layout data acquisition module; The final layout result acquisition module is used to determine the level of the oil and gas pipeline network to be laid out, the total number of nodes at each level of the oil and gas pipeline network and the coordinate value of each node according to the optimal solution, and output the final layout result.

9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device implements a layout method for an oil and gas pipeline network as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor so that the computer implements a layout method for an oil and gas pipeline network as described in any one of claims 1 to 7.

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