阅读说明：本技术 气井生产全过程的控制方法及系统 (Control method and system for whole gas well production process ) 是由 任双双 沈飞 张向阳 冯超敏 罗洪武 付占宝 肖占禄 王成 于 2020-05-09 设计创作，主要内容包括：本发明公开了一种气井生产全过程的控制方法及系统,其中,该方法包括：获得气井生产全过程中各个生产单元的实时生产数据；根据各个生产单元的实时生产数据、历史生产数据和历史生产配置参数,训练气井生产全过程的数字孪生体；其中,气井生产全过程的数字孪生体是根据各个生产单元的仿真模型,以及各个生产单元之间的关联关系建立的；根据训练后的气井生产全过程的数字孪生体,确定各个生产单元的预测生产数据；根据各个生产单元的预测生产数据,确定各个生产单元的生产配置参数,进行气井生产全过程的控制。本发明可以与实际生产密切结合,制定较优的生产措施,对风险进行事前预警,提高气井生产的效率。(The invention discloses a method and a system for controlling the whole production process of a gas well, wherein the method comprises the following steps: obtaining real-time production data of each production unit in the whole gas well production process; training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units; determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process; and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process. The invention can be closely combined with actual production, makes better production measures, performs early warning on risks in advance and improves the production efficiency of gas wells.)

1. A method for controlling the whole production process of a gas well is characterized by comprising the following steps:

obtaining real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process;

and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process.

2. The method of claim 1, wherein determining production configuration parameters for each production unit based on the predicted production data for each production unit comprises:

applying the production configuration parameters of the production units to the digital twins in the whole gas well production process, and determining predicted production data generated by the production configuration parameters of the production units;

adjusting the production configuration parameters of each production unit according to the predicted production data generated by the production configuration parameters of each production unit;

and controlling the whole gas well production process according to the adjusted production configuration parameters of each production unit.

3. The method of claim 1 wherein the digital twins for the entire course of gas well production are established as follows, including:

establishing a simulation model of each production unit;

determining the incidence relation among the simulation models of the production units according to the incidence relation among the production units;

and establishing the digital twin body of the whole gas well production process according to the simulation models of the production units and the incidence relation among the simulation models of the production units.

4. The method of claim 1, wherein training digital twins for a gas well production event based on real-time production data, historical production data, and historical production configuration parameters for each production unit comprises:

determining abnormal production data of each production unit according to the real-time production data and the historical production data of each production unit;

and training the digital twin body in the whole gas well production process based on a machine learning algorithm according to the abnormal production data, the historical production data and the historical production configuration parameters of each production unit.

5. The method of claim 4, wherein determining abnormal production data for each production unit based on real-time production data and historical production data for each production unit comprises:

comparing the real-time production data of each production unit with multiple time scales and multiple space scales according to the historical production data of each production unit;

and determining abnormal production data of each production unit according to the comparison result.

6. The method of claim 1, wherein the simulation model of the production unit comprises at least: the system comprises a shaft simulation model, a gas transmission pipe network and gas storage station library simulation model, a metering simulation model and an injection and distribution simulation model.

7. The method of claim 1, wherein obtaining real-time production data for each production unit throughout the production of the gas well comprises:

the method comprises the steps of obtaining real-time production data of each production unit in the whole gas well production process from data acquisition equipment, wherein the data acquisition equipment at least comprises the following steps: temperature sensor, pressure transmitter, flowmeter, poisonous and harmful gas sensor and remote measurement and control terminal.

8. A control system for the overall process of gas well production, comprising:

the data acquisition module is used for acquiring real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

the digital twin training module is used for training a digital twin in the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

the prediction data determining module is used for determining the prediction production data of each production unit according to the trained digital twin body in the whole gas well production process;

and the control module is used for determining the production configuration parameters of each production unit according to the predicted production data of each production unit and controlling the whole gas well production process.

9. The system of claim 8, wherein the control module is to:

applying the production configuration parameters of the production units to the digital twins in the whole gas well production process, and determining predicted production data generated by the production configuration parameters of the production units;

adjusting the production configuration parameters of each production unit according to the predicted production data generated by the production configuration parameters of each production unit;

and controlling the whole gas well production process according to the adjusted production configuration parameters of each production unit.

10. The system of claim 8, further comprising a digital twin establishing module to:

establishing a digital twin of the gas well production overall process according to the following method, comprising:

establishing a simulation model of each production unit;

determining the incidence relation among the simulation models of the production units according to the incidence relation among the production units;

and establishing the digital twin body of the whole gas well production process according to the simulation models of the production units and the incidence relation among the simulation models of the production units.

11. The system of claim 8, wherein the digital twin training module comprises:

an abnormal data determination unit: the abnormal production data of each production unit is determined according to the real-time production data and the historical production data of each production unit;

and the digital twin training unit is used for training the digital twin in the whole gas well production process based on a machine learning algorithm according to the abnormal production data, the historical production data and the historical production configuration parameters of each production unit.

12. The system of claim 11, wherein the anomalous data determination unit is specifically configured to:

comparing the real-time production data of each production unit with multiple time scales and multiple space scales according to the historical production data of each production unit;

and determining abnormal production data of each production unit according to the comparison result.

13. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.

Technical Field

The invention relates to the technical field of oil and gas field development, in particular to a method and a system for controlling the whole production process of a gas well.

Background

Along with the continuous deepening of gas reservoir development, the number of gas wells is continuously increased, the number of low-pressure low-yield liquid gas wells is also continuously increased, a large amount of tracking, analyzing and adjusting work needs to be carried out on production measures of the gas wells in the production process of the gas wells, and in addition, the gas fields are wide in variety and fragile in ecological environment, so that the difficulty in preventing and controlling unpredictable risks is also high.

At present, although a digitalization and informatization means is adopted for gas well production, a simulation model is only established for individual production units, the guidance significance for actual production is less based on theoretical calculation, the artificial experience is mainly used when production measures are formulated and adjusted, the prevention and control of unpredictable risks are only limited to problem guidance afterwards, and the requirement for gas well production is difficult to meet.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the invention provides a control method of the whole gas well production process, which is used for improving the production efficiency of a gas well and comprises the following steps:

obtaining real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process;

and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process.

The embodiment of the invention provides a control system for the whole gas well production process, which is used for improving the production efficiency of a gas well and comprises the following components:

the data acquisition module is used for acquiring real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

the digital twin training module is used for training a digital twin in the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

the prediction data determining module is used for determining the prediction production data of each production unit according to the trained digital twin body in the whole gas well production process;

and the control module is used for determining the production configuration parameters of each production unit according to the predicted production data of each production unit and controlling the whole gas well production process.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can be run on the processor, wherein the processor realizes the control method of the whole gas well production process when executing the computer program.

The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores a computer program for executing the control method of the whole production process of the gas well.

The embodiment of the invention comprises the following steps: obtaining real-time production data of each production unit in the whole gas well production process; training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units; determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process; and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process. According to the invention, the digital twin body of the whole gas well production process can be established according to the simulation model of each production unit of the gas well, and the digital twin body is trained based on the real-time production data and the historical production data of each production unit, so that the method is closely combined with the actual production, a better production measure can be made, the risk is early warned in advance, and the production efficiency of the gas well is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

FIG. 1 is a schematic illustration of a method flow for controlling the overall process of gas well production in an embodiment of the present invention;

FIG. 2 is a schematic diagram illustrating a detailed process flow of step 102 in FIG. 1;

FIG. 3 is a schematic diagram illustrating a detailed process flow of step 104 in FIG. 1;

FIG. 4 is a flow chart of an embodiment of a method of controlling the overall process of gas well production in accordance with an embodiment of the present invention;

FIG. 5 is a schematic diagram of the control system structure for the overall process of gas well production in an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In order to solve the technical problem that the gas well production efficiency is low because the prevention and control of unpredictable risks are limited to aftermath guidance mainly based on artificial experiences in the digitization and informatization processes of gas well production, the embodiment of the invention provides a control method for the whole gas well production process, which is used for improving the gas well production efficiency, and fig. 1 is a schematic diagram of the flow of the control method for the whole gas well production process in the embodiment of the invention, and the method shown in fig. 1 comprises the following steps:

step 101: obtaining real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

step 102: training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

step 103: determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process;

step 104: and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process.

As shown in fig. 1, an embodiment of the present invention is implemented by: obtaining real-time production data of each production unit in the whole gas well production process; training a digital twin body of the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units; determining the predicted production data of each production unit according to the trained digital twin body in the whole gas well production process; and determining the production configuration parameters of each production unit according to the predicted production data of each production unit, and controlling the whole gas well production process. According to the invention, the digital twin body of the whole gas well production process can be established according to the simulation model of each production unit of the gas well, and the digital twin body is trained based on the real-time production data and the historical production data of each production unit, so that the method is closely combined with the actual production, a better production measure can be made, the risk is early warned in advance, and the production efficiency of the gas well is improved.

In one embodiment, step 101 may comprise:

the method comprises the steps of obtaining real-time production data of each production unit in the whole gas well production process from data acquisition equipment, wherein the data acquisition equipment at least comprises the following steps: temperature sensor, pressure transmitter, flowmeter, poisonous and harmful gas sensor and remote measurement and control terminal.

In specific implementation, in step 101, various data acquisition devices in the acquisition layer of the internet of things may be used, for example: the system comprises a temperature sensor, a pressure transmitter, a flowmeter, a toxic and harmful gas sensor, a remote measurement and control terminal and other sensors, wherein the temperature sensor, the pressure transmitter, the flowmeter, the toxic and harmful gas sensor and the remote measurement and control terminal are used for acquiring real-time production data of each production unit in a gas well production field, and a gas production well is used for acquiring gas; the injection well is used for providing power for the gas production well; the metering chamber is used for counting gas; the injection and distribution room is used for controlling water injection; the transfer station and the united station are used for transporting, storing and filtering gas, and can also store real-time production data in an implementation database.

In one embodiment, before training 102 the digital twins of the whole gas well production process, the method may further include: establishing a digital twin body of the whole process of gas well production according to the following steps:

step 201: establishing a simulation model of each production unit;

step 202: determining the incidence relation among the simulation models of the production units according to the incidence relation among the production units;

step 203: and establishing a digital twin body of the whole gas well production process according to the simulation models of the production units and the incidence relation among the simulation models of the production units.

In one embodiment, the simulation model of the production unit comprises at least: the system comprises a shaft simulation model, a metering simulation model, an injection and distribution simulation model and a gas transmission pipe network and gas storage station library simulation model.

During specific implementation, the simulation model of each production unit can be obtained from a simulation model library, wherein the shaft simulation model is used for simulating a gas production well and an injection well, the metering simulation model can be metering software used for simulating a metering room, the injection and distribution simulation model can be injection and distribution software used for simulating an injection and distribution room, the simulation models of the gas transmission pipe network and the gas storage station library are used for simulating a transfer station and a combined station, the digital twin body of the whole gas well production process can be a digital simulation model of the whole gas well production process established based on the simulation models of the production units, the stratum seepage model and the incidence relation among the production units on the production site, and the whole process of actual gas well production can be simulated in a virtual space.

Fig. 2 is a schematic diagram of a specific flow of step 102 in fig. 1, and as shown in fig. 2, step 102 may include:

step 1021: determining abnormal production data of each production unit according to the real-time production data and the historical production data of each production unit;

step 1022: and training the digital twin body in the whole gas well production process based on a machine learning algorithm according to the abnormal production data, the historical production data and the historical production configuration parameters of each production unit.

In one embodiment, the step 1021 may include:

comparing the real-time production data of each production unit with multiple time scales and multiple space scales according to the historical production data of each production unit;

and determining abnormal production data of each production unit according to the comparison result.

In step 1021, the real-time production data of each production unit of the gas well may be obtained through the real-time database, and the historical production data and the historical production configuration parameters of each production unit of the gas well may be obtained through the historical database, where the historical production data may be historical dynamic data of each production unit of the gas well, and the historical configuration parameters may be historical measure data for establishing the gas well, and may include parameters such as a historical measure design scheme, a historical measure implementation scheme, and a historical measure effect, and may also include other parameters, which is not limited in this disclosure. The data volume of the real-time production data is large and complicated in scale, so that the real-time production data of each production unit can be compared in multiple time scales and multiple space scales according to the historical production data of each production unit and the data conversion rule, statistics and analysis are carried out on the comparison results, abnormal production data of each production unit are determined, the abnormal production data are used as key parameters to participate in the training of the digital twin body in the whole process of the subsequent gas well production, and the trained digital twin body can be closely combined with actual production. In step 1022, the digital twins in the whole gas well production process can be trained based on an intelligent learning algorithm according to the abnormal production data, the historical production data and the historical production configuration parameters of each production unit, so that the digital twins capable of reflecting the actual production situation can be obtained, and the diagnosis, prediction, measure formulation and effect evaluation of the carrier of the digital twins can be performed in real time.

In specific implementation, in step 103, the production data of each production unit may be predicted based on the digital twin of the whole gas well production process trained in step 102, with the gas well as the production fluid migration, production fluid inflow pipeline and station library as the center.

Fig. 3 is a schematic diagram illustrating a specific flow of step 104 in fig. 1, and as shown in fig. 3, in an embodiment, step 104 may include:

step 1041: applying the production configuration parameters of each production unit to the digital twin body in the whole gas well production process, and determining the predicted production data generated by the production configuration parameters of each production unit;

step 1042: adjusting the production configuration parameters of each production unit according to the predicted production data generated by the production configuration parameters of each production unit;

step 1043: and controlling the whole gas well production process according to the adjusted production configuration parameters of each production unit.

In step 104, production configuration parameters of each production unit may be formulated according to the predicted production data in step 103, where the production configuration parameters may be production measures, and may include scheduling parameters, risk early warning parameters, production processes, and other measure parameters, and these parameters may trigger workflows or management flows of a plurality of functional modules in an actual production process, for example, functional modules such as capacity construction, production scheduling, production monitoring, equipment management, mine authority management, aid decision, security organization, and emergency management may be included. In the control of the whole gas well production process, because the gas well production process is dynamically changed, the production configuration parameters of each production unit need to be evaluated and adjusted to formulate the optimal production configuration parameters, the production configuration parameters of each production unit can be firstly applied to the digital twins of the whole gas well production process, the operation cycle of the digital twins is set, the predicted production data of each production unit based on the production configuration parameters is output, then the predicted production data is compared with the expected results of the production configuration parameters, the production measure effect evaluation, the well condition diagnosis and the risk early warning are carried out according to the comparison results, the production configuration parameters of each production unit are further adjusted, the operation is executed in a circulating manner until the optimal production configuration parameters are obtained, and thus the closed-loop control of the whole gas well production process can be realized, and finally, feeding the optimal production configuration parameters back to the actual gas well production system, and further optimizing and adjusting the production configuration parameters of the digital twin and each unit according to real-time production data generated by the actual gas well production system.

The following is a specific example to facilitate an understanding of how the invention may be practiced.

Fig. 4 is a flowchart of a specific embodiment of a method for controlling the overall gas well production process in the embodiment of the present invention, as shown in fig. 4, including the following steps:

the first step is as follows: collecting real-time production data of each production unit of a gas well production field through various data collection devices in an Internet of things collection layer, and storing the real-time production data into a real-time database;

the second step is that: acquiring a simulation model of each production unit from a simulation model library, and establishing a digital twin body of the whole gas well production process by combining a stratum seepage model and an incidence relation between the production units on a production site;

the third step: the method comprises the steps that real-time production data of each production unit of the gas well are obtained through a real-time database, and historical production data and historical production measure data of each production unit of the gas well are obtained through a historical database;

the fourth step: according to the historical production data of each production unit and the data conversion rule, comparing the real-time production data of each production unit in a multi-time scale and a multi-space scale, counting and analyzing the comparison result, and determining the abnormal production data of each production unit;

the fifth step: according to abnormal production data, historical production data and historical production measure data of each production unit, a digital twin body of the whole gas well production process is trained on the basis of an intelligent learning algorithm, and diagnosis, prediction, measure formulation and effect evaluation can be carried out on well conditions in real time;

and a sixth step: the method comprises the following steps of taking a gas well as a center, taking production fluid migration, production fluid inflow pipelines and a station library as processes, and predicting production data of each production unit based on a trained digital twin body of the whole gas well production process;

the seventh step: according to the predicted production data, producing measures of all the production units are made, the producing measures of all the production units are applied to digital twins in the whole gas well production process, the operation cycle of the digital twins is set, and the predicted production data, generated based on the producing measures, of all the production units are output;

eighth step: comparing the predicted production data with the expected results of the production measures, performing production measure effect evaluation, well condition diagnosis and risk early warning according to the comparison results, further adjusting the production measures of each production unit, and executing the seventh step to the eighth step in a circulating manner until the optimal production measures are obtained;

the ninth step: and feeding back the optimal production measures to an actual gas well production system, triggering the working flows or management flows of a plurality of functional modules in the actual production process, circularly executing the first step to the eighth step, and continuously adjusting the production measures of the digital twin body and each unit.

Based on the same inventive concept, the embodiment of the invention also provides a control device for the whole production process of the gas well, and the control device is as follows. Because the principle of solving the problems by the device is similar to that of the method, the implementation of the device can be referred to the implementation of the method, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 5 is a schematic diagram of the structure of a control system for the overall process of gas well production according to an embodiment of the present invention, and as shown in fig. 5, the system includes:

the data acquisition module 01 is used for acquiring real-time production data of each production unit in the whole gas well production process; wherein the production unit comprises at least: the system comprises a gas production well, an injection well, a metering room, an injection and distribution room, a transfer station and a combined station;

the digital twin training module 02 is used for training a digital twin in the whole gas well production process according to the real-time production data, the historical production data and the historical production configuration parameters of each production unit; the digital twin body of the whole gas well production process is established according to the simulation model of each production unit and the incidence relation among the production units;

the prediction data determining module 03 is used for determining the prediction production data of each production unit according to the trained digital twin body of the whole gas well production process;

and the control module 04 is used for determining the production configuration parameters of each production unit according to the predicted production data of each production unit and controlling the whole gas well production process.

In one embodiment, the data collection module 01 is specifically configured to:

the method comprises the steps of obtaining real-time production data of each production unit in the whole gas well production process from data acquisition equipment, wherein the data acquisition equipment at least comprises the following steps: temperature sensor, pressure transmitter, flowmeter, poisonous and harmful gas sensor and remote measurement and control terminal.

In one embodiment, the simulation model of the production unit in the digital twin training module 02 includes at least: the system comprises a shaft simulation model, a metering simulation model, an injection and distribution simulation model and a gas transmission pipe network and gas storage station library simulation model.

In one embodiment, the system further comprises: a digital twin establishing module 05 for:

a digital twin of the whole process of gas well production is established according to the following method, comprising:

establishing a simulation model of each production unit;

determining the incidence relation among the simulation models of the production units according to the incidence relation among the production units;

and establishing a digital twin body of the whole gas well production process according to the simulation models of the production units and the incidence relation among the simulation models of the production units.

In one embodiment, digital twin training module 02 includes:

the abnormal data determination unit 021: the abnormal production data of each production unit is determined according to the real-time production data and the historical production data of each production unit;

and the digital twin training unit 022 is used for training the digital twin of the whole gas well production process based on a machine learning algorithm according to the abnormal production data, the historical production data and the historical production configuration parameters of each production unit.

In one embodiment, the abnormal data determining unit 021 is specifically configured to:

comparing the real-time production data of each production unit with multiple time scales and multiple space scales according to the historical production data of each production unit;

and determining abnormal production data of each production unit according to the comparison result.

In one embodiment, the control module 04 is specifically configured to:

applying the production configuration parameters of each production unit to the digital twin body in the whole gas well production process, and determining the predicted production data generated by the production configuration parameters of each production unit;

adjusting the production configuration parameters of each production unit according to the predicted production data generated by the production configuration parameters of each production unit;

and controlling the whole gas well production process according to the adjusted production configuration parameters of each production unit.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can be run on the processor, wherein the processor realizes the control method of the whole gas well production process when executing the computer program.

The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores a computer program for executing the control method of the whole production process of the gas well.

In summary, the control method and the control system for the whole gas well production process provided by the embodiment of the invention have the following advantages:

(1) the real-time production data of each production unit in the gas well production field can be collected through various data collection devices in the collection layer of the Internet of things, and the real-time production data is closely combined with actual production;

(2) by combining historical production data, historical measure data, a physical simulation technology, real-time production data and an intelligent learning algorithm, a digital twin body of the whole gas well production process is established and trained, and a digital simulation model of the whole gas well production process which accords with actual production can be obtained;

(3) the method has the advantages that the gas well is taken as a center, production fluid migration and production fluid inflow pipelines and a station library are taken as processes, production data of each production unit are predicted based on a trained digital twin body of the whole gas well production process, production measure effect evaluation, well condition diagnosis and risk early warning are further carried out, superior production measures can be made, risk early warning is carried out in advance, gas well production efficiency is improved, continuous learning and optimization can be realized, and various production environments are adapted.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and variations of the embodiment of the present invention may occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.