CN110046754B - Latin hypercube sampling oil field liquid production structure optimization method, storage medium and terminal - Google Patents
Latin hypercube sampling oil field liquid production structure optimization method, storage medium and terminal Download PDFInfo
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Abstract
The invention relates to a method for optimizing a liquid production structure of a Latin hypercube sampling oil field, a storage medium and a terminal. The method comprises processing the timing and amplitude of the extraction liquid in the oil well using Latin hypercube sampling algorithm to determine a plurality of simulation schemes; respectively inputting the plurality of simulation schemes into oil reservoir numerical simulation software for simulation to obtain oil well response variables; comparing the response variable of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of the similar oil field, and screening out a simulation scheme set which meets the conditions; and processing the simulation scheme set by using a genetic algorithm to obtain an optimal extract scheme. The invention considers the oil well, the liquid extracting time, the liquid extracting amplitude and the mutual influence among all factors, realizes the simultaneous optimization of multiple factors by integrally applying a Latin hypercube sampling method, and screens and determines the optimal liquid extracting scheme by using a multi-factor genetic algorithm. The oil field can achieve high and stable yield, reduce the sewage discharge of the oil field, and finally achieve technical recovery and environmental protection development of the oil field in the economic life.
Description
Technical Field
The invention relates to the field of optimization of oilfield produced liquid structures, in particular to a method for optimizing a latin hypercube sampling oilfield produced liquid structure, a storage medium and a terminal.
Background
The optimization of the oil field liquid production structure is an economic and effective main production increasing measure for the whole life cycle of a water-drive development oil field, and the distribution of the oil field liquid production amount is related to whether the oil field can realize high and stable yield in the economic life and reach the technical recovery ratio, and whether the sewage discharge can be reduced to realize environment-friendly production. In the prior art, optimization is generally developed based on an oil well water drive theory, a multi-well liquid production structure timely optimization mathematical model and a calculation module are established through a water drive characteristic curve and a flow rate equation, the optimal liquid amount of a single well at different time is calculated, and the oil production maximization at different time stages is realized. The prior art therefore has two problems: firstly, a proper water drive curve cannot be found in the whole process of oil well production to represent the water content rising rule of the oil well; secondly, the influence of the geological oil reservoir characteristics of the oil well on the optimization effect of the liquid production structure cannot be fully considered. Therefore, the prior art can not realize the global optimization of the oil field liquid production structure, and can not realize the dual purposes of high and stable oil field yield and environment-friendly production.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method, a storage medium and a terminal for optimizing a liquid production structure of a Latin hypercube sampled oil field aiming at the defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a method for optimizing a liquid production structure of a Latin hypercube sampling oil field is constructed, and comprises the following steps:
processing the extracting liquid time and the extracting liquid amplitude of the oil well by using a Latin hypercube sampling algorithm to determine a plurality of simulation schemes, wherein the extracting liquid time is the specific water content of the oil well for improving the liquid yield, and the extracting liquid amplitude is the liquid yield difference before and after the oil well improves the liquid yield;
respectively inputting the simulation schemes into oil reservoir numerical simulation software for simulation to obtain oil well response variables;
comparing the response variable of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of a similar oil field, and screening out a simulation scheme set which meets the conditions;
and processing the simulation scheme set by using a genetic algorithm to obtain an optimal extract scheme.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampled oil field, which is disclosed by the invention, comprises the following steps of respectively inputting a plurality of simulation schemes into numerical reservoir simulation software for simulation to obtain the response variable of an oil well:
inputting the extracting liquid time, the extracting liquid amplitude, the oil deposit geological data, the fluid data, the rock fluid action data, the oil deposit initial data and the production dynamic data in each simulation scheme into oil deposit numerical simulation software for simulation to obtain oil well response variables, wherein the oil well response variables comprise oil well oil production, oil well water production, oil well liquid production, oil well water content and oil well production pressure difference.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampled oil field, provided by the invention, comprises the following steps of comparing the response variable of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of a similar oil field:
and comparing the water content of the oil well before and after the adjustment of the liquid production amount of the oil well and the change amplitude of the bottom hole pressure of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of the similar oil field.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampled oil field comprises the following steps of:
and screening out the simulation schemes of which the variation amplitude of the bottom hole pressure of the oil well is within a preset range and the water content of the oil well is reduced more, and forming the simulation scheme set.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampled oil field comprises the following steps of:
adjusting the parameter range, and screening out a simulation scheme set which accords with the adjusted parameter range.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampled oil field comprises the following steps of:
and screening and determining a reasonable simulation factor level and response variable simulation scheme set.
Further, the method for optimizing the liquid production structure of the Latin hypercube sampling oil field, which is disclosed by the invention, comprises the following steps of:
and processing the extracting time and the extracting amplitude of each analog scheme in the analog scheme set one by utilizing a genetic algorithm to obtain an optimal extracting scheme.
Further, the method for optimizing the liquid production structure of the latin hypercube sampling oil field, which is provided by the invention, comprises the following steps of processing the liquid extraction time and the liquid extraction amplitude of each simulation scheme in the simulation scheme set one by utilizing a genetic algorithm to obtain the optimal liquid extraction scheme:
selecting one of the simulation schemes;
inputting a problem parameter set into the simulation scheme to calculate the fitness;
judging whether the fitness meets a preset condition or not;
if yes, taking the simulation scheme as an optimal extraction scheme;
if not, selecting another simulation scheme in the simulation scheme set, and executing the calculation of fitness by inputting the problem parameter set into the simulation scheme.
In addition, the invention also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the method for optimizing the liquid production structure of the Latin hypercube sampling oilfield is realized.
In addition, the invention also provides a terminal which comprises a processor, wherein the processor is used for realizing the steps of the method for optimizing the liquid production structure of the Latin hypercube sampling oil field when executing the computer program stored in the memory.
The implementation of the method for optimizing the liquid production structure of the Latin hypercube sampled oil field, the storage medium and the terminal has the following beneficial effects: the method comprises processing the timing and amplitude of the extraction liquid in the oil well using Latin hypercube sampling algorithm to determine a plurality of simulation schemes; respectively inputting the plurality of simulation schemes into oil reservoir numerical simulation software for simulation to obtain oil well response variables; comparing the response variable of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of the similar oil field, and screening out a simulation scheme set which meets the conditions; and processing the simulation scheme set by using a genetic algorithm to obtain an optimal extract scheme. The invention considers the oil well, the liquid extracting time, the liquid extracting amplitude and the mutual influence among all factors, realizes the simultaneous optimization of multiple factors by integrally applying a Latin hypercube sampling method, and screens and determines the optimal liquid extracting scheme by using a multi-factor genetic algorithm. The oil field can achieve high and stable yield, reduce the sewage discharge of the oil field, and finally achieve technical recovery and environmental protection development of the oil field in the economic life.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a method for optimizing a liquid production structure of a Latin hypercube sampled oil field according to an embodiment;
FIG. 2 is a flow chart of a genetic algorithm provided by an embodiment;
fig. 3 is a schematic structural diagram of a terminal according to an embodiment.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
Examples
Referring to fig. 1, the method for optimizing the liquid production structure of the latin hypercube sampled oil field of the embodiment includes:
and S1, processing the liquid extracting time and liquid extracting amplitude of the oil well by using a Latin hypercube sampling algorithm to determine a plurality of simulation schemes, wherein the liquid extracting time is the specific water content of the oil well for improving the liquid yield, the liquid extracting amplitude is the liquid yield difference before and after the oil well for improving the liquid yield, and each simulation scheme comprises a group of liquid extracting time and liquid extracting amplitude.
S2, inputting the simulation schemes into oil reservoir numerical simulation software respectively for simulation to obtain oil well response variables;
s3, comparing the response variable of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of a similar oil field, and screening out a simulation scheme set meeting the conditions;
and S4, processing the simulation scheme set by using a genetic algorithm to obtain an optimal extract scheme.
Further, in the method for optimizing the liquid production structure of the latin hypercube sampled oil field according to the embodiment, the step of inputting a plurality of simulation schemes into the numerical reservoir simulation software respectively for simulation to obtain the response variable of the oil well comprises:
and inputting the extracting liquid time, the extracting liquid amplitude, the oil reservoir geological data, the fluid data, the rock fluid action data, the oil reservoir initial data and the production dynamic data in each simulation scheme into oil reservoir numerical simulation software for simulation to obtain oil well response variables, wherein the oil well response variables comprise oil well oil production, oil well water production, oil well liquid production, oil well water content and oil well production pressure difference.
Further, in the method for optimizing a liquid production structure of a latin hypercube sampled oil field of the present embodiment, the comparing the response variable of the oil well with the historical liquid production structure of the oil field to which the response variable of the oil well belongs or the historical liquid production structure of a similar oil field includes:
and comparing the water content of the oil well before and after the adjustment of the liquid production amount of the oil well and the change amplitude of the bottom hole pressure of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of the similar oil field.
Further, in the method for optimizing the liquid production structure of the latin hypercube sampled oil field of the embodiment, the step of screening out a simulation scheme set meeting the conditions comprises:
and screening out the simulation schemes that the variation amplitude of the bottom hole pressure of the oil well is within the preset range and the water content of the oil well is reduced more, and forming a simulation scheme set.
Further, in the method for optimizing the liquid production structure of the latin hypercube sampled oil field of the embodiment, the step of screening out a simulation scheme set meeting the conditions comprises:
adjusting the parameter range, and screening out a simulation scheme set which accords with the adjusted parameter range.
Further, in the method for optimizing the liquid production structure of the latin hypercube sampled oil field of the embodiment, the step of screening out a simulation scheme set meeting the conditions comprises:
and screening and determining a reasonable simulation factor level and response variable simulation scheme set.
Further, the method for optimizing the liquid production structure of the latin hypercube sampled oil field according to the embodiment, wherein the scheme for obtaining the optimal liquid extraction by processing the simulation scheme set by using the genetic algorithm comprises the following steps:
and (3) processing the extracting time and the extracting amplitude of each analog scheme in the analog scheme set one by utilizing a genetic algorithm to obtain an optimal extracting scheme.
Examples
Referring to fig. 2, the difference from the above embodiment is that, in the method for optimizing the latin hypercube sampling oilfield fluid production structure according to the present embodiment, the step of processing the fluid extraction time and the fluid extraction amplitude of each simulation scheme in the simulation scheme set one by using a genetic algorithm to obtain the optimal fluid extraction scheme includes:
s41, selecting one simulation scheme from the simulation schemes;
s42, inputting the problem parameter set into the simulation scheme to calculate the fitness;
and S43, judging whether the fitness meets a preset condition, wherein the preset condition can be determined according to an empirical value.
S44, if the fitness meets the preset condition, taking the simulation scheme as the optimal extract scheme;
and S45, if the fitness does not meet the preset condition, selecting another simulation scheme in the simulation scheme set, and executing the calculation of the fitness by inputting the problem parameter set into the simulation scheme.
The embodiment also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the method for optimizing the liquid production structure of the latin hypercube sampling oilfield is realized.
The embodiment also provides a terminal, which comprises a processor, wherein the processor is used for implementing the steps of the method for optimizing the liquid production structure of the latin hypercube sampled oil field when executing the computer program stored in the memory.
Referring now to fig. 3, a block diagram of a terminal 300 suitable for use in implementing embodiments of the present invention is shown. The terminal device in the embodiments of the present invention may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like. The terminal shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, the terminal 300 may include a processing device (e.g., a central processing unit, a graphic processor, etc.) 301 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage device 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for the operation of the terminal 300 are also stored. The processing device 301, the ROM302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the terminal 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 illustrates a terminal 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 309, or installed from the storage means 308, or installed from the ROM 302. The computer program, when executed by the processing device 301, performs the above-described functions defined in the methods of embodiments of the present invention.
It should be noted that the computer readable medium of the present invention can be a computer readable signal medium or a computer storage medium or any combination of the two. A computer storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of computer storage media may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the terminal; or may exist separately and not be assembled into the terminal.
The computer readable medium carries one or more programs which, when executed by the terminal, cause the terminal to: acquiring at least two internet protocol addresses; sending a node evaluation request comprising the at least two internet protocol addresses to node evaluation equipment, wherein the node evaluation equipment selects the internet protocol addresses from the at least two internet protocol addresses and returns the internet protocol addresses; receiving an internet protocol address returned by the node evaluation equipment; wherein the obtained internet protocol address indicates an edge node in the content distribution network.
Alternatively, the computer readable medium carries one or more programs which, when executed by the terminal, cause the terminal to: receiving a node evaluation request comprising at least two internet protocol addresses; selecting an internet protocol address from the at least two internet protocol addresses; returning the selected internet protocol address; wherein the received internet protocol address indicates an edge node in the content distribution network.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present invention may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".
Examples
The prior art is simple, convenient and easy to implement, and has wide application, but the practical application effect of the method is restricted by the problems of the method. A multi-well liquid production structure real-time optimization mathematical model and a calculation module are established through a water flooding characteristic curve and a flow splitting equation, the optimal liquid quantity of a single well at different time is calculated, and the maximization of the oil production quantity at different time stages is realized. The prior art has two problems, one is that a proper water drive curve can not be found to represent the water content rising rule of all oil wells in the whole production process; secondly, the influence of the geological oil reservoir characteristics of the oil well on the optimization effect of the liquid production structure cannot be fully considered. Therefore, the prior art can not realize the global optimization of the oil field liquid production structure, and can not realize the dual purposes of high and stable oil field yield and environment-friendly production. The application effect of the prior art in a certain water-flooding oil field is as follows: under the condition that the fixed liquid yield of a 24-hole oil well is 4.3 ten thousand square/day, the liquid production structure is optimized and adjusted by applying the prior art, the annual oil increasing amplitude is gradually reduced, the oil increasing amount is only 1.4 ten thousand square at most annually, the daily average water content is only reduced by 0.1%, the 5-year accumulated oil increasing amount is only 4.67 ten thousand square, the average single-hole accumulated oil increasing amount is 0.19 ten thousand square/hole, and a certain water-reducing and oil-increasing effect is achieved.
The invention has good trial effect on the Panyu oil field group in the east of the south China sea. After systematic research and implementation of the liquid production structure optimization work of the wine field group, the yield of each oil field is decreased progressively and obviously, the purposes of high and stable yield of the oil field and sewage discharge reduction are achieved, and the win-win situation of high-efficiency production and environmental development of the oil field is realized. The experimental device, totally 65 oil wells implement the production liquid structure adjustment 164 well times, average single well accumulated oil is 0.48 ten thousand square/mouth, accumulated oil is 31.4 ten thousand square, directly create economic benefits about 7.7 hundred million RMB. Wherein, the natural reduction rates of the wine production field 4-2/5-1 oil field in the main oil field are 39.7% and 34.8% respectively before the liquid production structure is adjusted, and after the liquid production structure is adjusted for two years, the reduction rates are respectively reduced to 13.1% and 18.2%; after the liquid production structure of the 5 oil fields of the wine tank 10-2 is adjusted in 2015, the total liquid amount of the oil fields is reduced by 636 square/day, the water content is reduced by 4 percent, the oil amount is increased by 64 square/day, the oil is increased by 1.7 ten thousand square, and the 14.2 ten thousand square of accumulated emission-reduction sewage is realized.
The invention is compared with the prior art:
the method is different in basis: the prior art is based on the water drive theory of an oil well, and only extrapolates the future dynamics according to the current oil well dynamics; the invention is based on the numerical reservoir simulation model of the meticulous geological reservoir research, also consider the influence of geological reservoir characteristic on future dynamics on the basis of considering the current oil well dynamics, and apply the existing liquid production structure optimization engineering experience to develop the scheme screening to the simulation operation result, ensure the engineering rationality of the simulation optimization scheme;
the optimization modes are different: in the prior art, single-factor optimization is usually carried out on three factors, namely an oil well, opportunity and amplitude; the method considers the oil well, the opportunity, the amplitude and the mutual influence among all factors, determines the level of the factors by integrally applying a Latin hypercube sampling method, and realizes the simultaneous optimization of multiple factors;
the optimization algorithm is different: in the prior art, the oil production efficiency of an oil well (the oil yield of the unit volume of the oil well) is generally ranked according to the height to determine a recommended scheme; the invention applies a genetic algorithm considering multiple factors to screen and determine a recommended scheme.
The invention considers the oil well, the liquid extracting time, the liquid extracting amplitude and the mutual influence among all factors, realizes the simultaneous optimization of multiple factors by integrally applying a Latin hypercube sampling method, and screens and determines the optimal liquid extracting scheme by using a multi-factor genetic algorithm. The oil field can achieve high and stable yield, reduce the sewage discharge of the oil field, and finally achieve technical recovery and environmental protection development of the oil field in the economic life.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (3)
1. A method for optimizing a liquid production structure of a Latin hypercube sampled oil field is characterized by comprising the following steps:
processing the extracting liquid time and the extracting liquid amplitude of the oil well by using a Latin hypercube sampling algorithm to determine a plurality of simulation schemes, wherein the extracting liquid time is the specific water content of the oil well for improving the liquid yield, and the extracting liquid amplitude is the liquid yield difference before and after the oil well improves the liquid yield;
inputting the extracting liquid time, the extracting liquid amplitude, the oil deposit geological data, the fluid data, the rock fluid action data, the oil deposit initial data and the production dynamic data in each simulation scheme into oil deposit numerical simulation software for simulation to obtain oil well response variables, wherein the oil well response variables comprise oil well oil production, oil well water production, oil well liquid production, oil well water content and oil well production pressure difference;
comparing the water content of the oil well and the change amplitude of the bottom hole pressure of the oil well before and after the adjustment of the liquid production amount of the oil well with the historical liquid production structure of the oil field or the historical liquid production structure of the similar oil field, and screening out a simulation scheme set meeting the conditions; the screening of the simulation scheme set meeting the conditions comprises the following steps: screening out simulation schemes of which the variation amplitude of the bottom hole pressure of the oil well is within a preset range and the water content of the oil well is reduced more, and forming a simulation scheme set; adjusting the parameter range, and screening out a simulation scheme set which accords with the adjusted parameter range; screening and determining a reasonable simulation factor level and a simulation scheme set of response variables;
processing the simulation scheme set by using a genetic algorithm to obtain an optimal extract solution scheme, wherein the processing of the simulation scheme set by using the genetic algorithm to obtain the optimal extract solution scheme comprises the following steps:
selecting one of the simulation schemes;
inputting a problem parameter set into the simulation scheme to calculate the fitness;
judging whether the fitness meets a preset condition or not;
if yes, taking the simulation scheme as an optimal extraction scheme;
if not, selecting another simulation scheme in the simulation scheme set, and executing the calculation of fitness by inputting the problem parameter set into the simulation scheme.
2. A computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the method for optimizing a fluid production configuration of a latin hypercube sampled oilfield as recited in claim 1.
3. A terminal comprising a processor for implementing the steps of the method for optimizing a fluid production configuration of a latin hypercube sampled oilfield as recited in claim 1 when executing a computer program stored in memory.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021645A (en) * | 2016-05-06 | 2016-10-12 | 北京航空航天大学 | An aero-engine compressor performance reliability design method |
| CN106919756A (en) * | 2017-03-01 | 2017-07-04 | 中国海洋石油总公司 | A kind of steam soak injection parameter optimization method based on approximate model |
| CN108804382A (en) * | 2018-05-22 | 2018-11-13 | 合肥工业大学 | A kind of automatic reverse method of parameter and device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2720117C (en) * | 2008-05-05 | 2017-11-28 | Exxonmobil Upstream Research Company | Systems, methods, and computer program products for modeling dynamic systems by visualizing a parameter space and narrowing the parameter space |
| CN105625992A (en) * | 2014-11-07 | 2016-06-01 | 中国石油化工股份有限公司 | Reasonable liquid extracting method specific to roof ridge fault block oil reservoir |
| CN105626036B (en) * | 2014-11-07 | 2019-05-31 | 中国石油化工股份有限公司 | A kind of reasonable Liquid output reservoir engineering calculation method of determining oil reservoir |
-
2019
- 2019-03-29 CN CN201910251443.0A patent/CN110046754B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021645A (en) * | 2016-05-06 | 2016-10-12 | 北京航空航天大学 | An aero-engine compressor performance reliability design method |
| CN106919756A (en) * | 2017-03-01 | 2017-07-04 | 中国海洋石油总公司 | A kind of steam soak injection parameter optimization method based on approximate model |
| CN108804382A (en) * | 2018-05-22 | 2018-11-13 | 合肥工业大学 | A kind of automatic reverse method of parameter and device |
Non-Patent Citations (1)
| Title |
|---|
| 海相砂岩稠油油藏产液结构优化研究;黄军立;《长江大学学报（自科版）》;20170810;第69-72页 * |
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