Oil and gas pipeline monitoring method and equipment and storage medium

Abstract

The invention discloses an oil and gas pipeline monitoring method and device and a storage medium, relates to the technical field of pipelines, and is used for monitoring oil and gas pipelines in real time, improving the intelligent level and efficiency of oil and gas pipeline management and improving the accuracy and timeliness of abnormity monitoring. The method comprises the steps of obtaining production data of an oil and gas pipeline in a current monitoring period and a plurality of monitoring rules corresponding to the oil and gas pipeline; different monitoring rules are used for indicating feature information of the oil and gas pipeline in different production stages; based on the production data of the current monitoring period, updating a digital twinborn model for simulating the oil and gas pipeline; monitoring the updated digital twin model based on a target monitoring rule of which the corresponding production stage in the plurality of monitoring rules is the production stage of the updated digital twin model, and obtaining a monitoring result of the oil and gas pipeline; the monitoring result is used for indicating whether the oil-gas pipeline has abnormal production.

Description

Technical Field

[0001] This application relates to the technical field of pipelines, and in particular, to a method, device, and storage medium for monitoring oil and gas pipelines. Background Art

[0002] With the expansion of the oil and gas pipeline network and the increase in complexity, the safety management of oil and gas pipelines has become increasingly important. Traditional oil and gas pipeline monitoring methods rely on manual regular inspections, which are inefficient and difficult to respond in real time, and have defects such as large investment, long construction period, and untimely discovery of safety risks and potential hazards, and are prone to causing safety problems. Summary of the Invention

[0003] The purpose of this application is to provide a method, device, and storage medium for monitoring oil and gas pipelines, aiming to achieve real-time monitoring of oil and gas pipelines, improve the intelligent level and efficiency of oil and gas pipeline management, and the accuracy and timeliness of abnormal monitoring.

[0004] To achieve the above object, this application adopts the following technical solutions:

[0005] In a first aspect, an embodiment of this application provides a method for monitoring oil and gas pipelines, including: obtaining production data of an oil and gas pipeline in a current monitoring period, and a plurality of monitoring rules corresponding to the oil and gas pipeline. Different monitoring rules are used to indicate characteristic information of the oil and gas pipeline in different production stages. Based on the production data in the current monitoring period, update a digital twin model for simulating the oil and gas pipeline. Based on a target monitoring rule among the plurality of monitoring rules whose corresponding production stage is the production stage in which the updated digital twin model is located, monitor the updated digital twin model to obtain a monitoring result of the oil and gas pipeline. The monitoring result is used to indicate whether there is a production anomaly in the oil and gas pipeline.

[0006] Based on this, this application can combine the production status of the oil and gas pipeline with the digital twin model to achieve real-time monitoring of the oil and gas pipeline, not only improving the intelligent level and efficiency of management, but also improving the accuracy and timeliness of abnormal monitoring, and avoiding problems such as large investment and long construction period caused by the manual-dependent method.

[0007] In some embodiments, the multiple monitoring rules include a property characteristic monitoring rule corresponding to the pre-production stage of the oil and gas pipeline, a temperature characteristic monitoring rule corresponding to the heat treatment stage of the oil and gas pipeline, and a mechanical characteristic monitoring rule corresponding to the physical property detection stage of the oil and gas pipeline. The property characteristic monitoring rule includes multiple material property parameter intervals, and different material property parameter intervals correspond to different material property grades. The temperature characteristic monitoring rule includes temperature event information corresponding to each of the multiple temperature characteristic values. The temperature event information is used to indicate whether a temperature anomaly event corresponds to the temperature characteristic value. The mechanical characteristic monitoring rule includes a normal pipeline pressure interval and strain event information corresponding to each of the multiple pipeline strain change rates. The strain event information is used to indicate whether a strain anomaly event corresponds to the pipeline strain change rate.

[0008] In some embodiments, obtaining the property characteristic monitoring rule of the oil and gas pipeline includes: obtaining the lowest material property parameter that meets the production standard of the oil and gas pipeline, and the historical material property parameters of other oil and gas pipelines. Based on the historical material property parameters of other oil and gas pipelines, determine the property parameter tolerance. Based on the lowest material property parameter and the property parameter tolerance, determine multiple material property parameter intervals.

[0009] In some embodiments, when the production stage of the updated digital twin model is the pre-production stage, monitoring the updated digital twin model to obtain the monitoring result of the oil and gas pipeline includes: determining the material property grade corresponding to the material property parameter interval covering the material property parameter of the updated digital twin model among the multiple material property grades as the material property grade of the oil and gas pipeline in the current monitoring cycle. Determine the monitoring result according to the material property grade of the oil and gas pipeline in the current monitoring cycle.

[0010] In some embodiments, obtaining the temperature characteristic monitoring rule of the oil and gas pipeline includes: obtaining the historical pipeline temperature and historical temperature events of other oil and gas pipelines at different historical times during the heat treatment stage. Statistically process the historical pipeline temperatures at different times to determine multiple temperature characteristic values. The multiple temperature characteristic values include an average value, a peak value, and a valley value. Determine the temperature event information corresponding to each of the multiple temperature characteristic values from the historical temperature events at different historical times.

[0011] In some embodiments, when the production stage of the updated digital twin model is the heat treatment stage, monitoring the updated digital twin model to obtain the monitoring result of the oil and gas pipeline includes: determining a target temperature characteristic value that matches the pipeline temperature of the updated digital twin model from the multiple temperature characteristic values. Determine the monitoring result according to the temperature event information corresponding to the target temperature characteristic value.

[0012] In some embodiments, obtaining the mechanical characteristic monitoring rules for an oil and gas pipeline includes: obtaining the historical pipeline pressure, historical pipeline strain, and historical strain events of other oil and gas pipelines at different historical moments during the physical property detection stage. Dividing the historical pipeline pressure and historical pipeline strain at different historical moments to obtain the historical pipeline pressure, historical pipeline strain, and historical strain events within each of multiple historical time periods. Based on the average value and variance of the historical pipeline pressure within each historical time period, determining the normal range of pipeline pressure. Statistically analyzing the change rate of the historical pipeline strain within each historical time period to determine multiple pipeline strain change rates. Based on the historical strain events within each historical time period, determining the strain event information corresponding to each of the multiple pipeline strain change rates.

[0013] In some embodiments, when the production stage of the updated digital twin model is the physical property monitoring stage, monitoring the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, including: determining whether there is an abnormal pipeline pressure in the oil and gas pipeline based on whether the pipeline pressure of the updated digital twin model is within the normal range of pipeline pressure. Determining whether there is an abnormal pipeline strain in the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update, and the strain event information corresponding to each of the multiple pipeline strain change rates.

[0014] In a second aspect, an oil and gas pipeline monitoring device is provided, including: an acquisition unit and a processing unit;

[0015] The acquisition unit is configured to acquire the production data of the oil and gas pipeline in the current monitoring cycle, as well as multiple monitoring rules corresponding to the oil and gas pipeline. Different monitoring rules are used to indicate the characteristic information of the oil and gas pipeline in different production stages. The processing unit is configured to update the digital twin model used to simulate the oil and gas pipeline based on the production data in the current monitoring cycle. The processing unit is further configured to monitor the updated digital twin model based on the target monitoring rule among the multiple monitoring rules, where the corresponding production stage is the production stage of the updated digital twin model, to obtain the monitoring results of the oil and gas pipeline. The monitoring results are used to indicate whether there is a production anomaly in the oil and gas pipeline.

[0016] In some embodiments, the multiple monitoring rules include a property characteristic monitoring rule corresponding to the pre-production stage of the oil and gas pipeline, a temperature characteristic monitoring rule corresponding to the heat treatment stage of the oil and gas pipeline, and a mechanical characteristic monitoring rule corresponding to the physical property detection stage of the oil and gas pipeline. The property characteristic monitoring rule includes multiple material property parameter intervals, and different material property parameter intervals correspond to different material property grades. The temperature characteristic monitoring rule includes temperature event information corresponding to each of the multiple temperature characteristic values. The temperature event information is used to indicate whether a temperature anomaly event corresponds to the temperature characteristic value. The mechanical characteristic monitoring rule includes a normal pipeline pressure range and strain event information corresponding to each of the multiple pipeline strain change rates. The strain event information is used to indicate whether a strain anomaly event corresponds to the pipeline strain change rate.

[0017] In some embodiments, the acquisition unit is specifically configured to: acquire the lowest material property parameter that meets the production standard of the oil and gas pipeline and the historical material property parameters of other oil and gas pipelines. Based on the historical material property parameters of other oil and gas pipelines, determine the property parameter tolerance. Based on the lowest material property parameter and the property parameter tolerance, determine multiple material property parameter intervals.

[0018] In some embodiments, the processing unit is specifically configured to: use the material property grade corresponding to the material property parameter interval that covers the material property parameters of the updated digital twin model among the multiple material property grades as the material property grade of the oil and gas pipeline in the current monitoring period. Determine the monitoring result according to the material property grade of the oil and gas pipeline in the current monitoring period.

[0019] In some embodiments, the acquisition unit is specifically configured to: acquire the historical pipeline temperature and historical temperature events of other oil and gas pipelines at different historical moments during the heat treatment stage. Perform statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values. The multiple temperature characteristic values include an average value, a peak value, and a valley value. Determine the temperature event information corresponding to each of the multiple temperature characteristic values from the historical temperature events at different historical moments.

[0020] In some embodiments, the processing unit is specifically configured to: determine a target temperature characteristic value that matches the pipeline temperature of the updated digital twin model from the multiple temperature characteristic values. Determine the monitoring result according to the temperature event information corresponding to the target temperature characteristic value.

[0021] In some embodiments, the acquisition unit is specifically configured to: acquire the historical pipeline pressure, historical pipeline strain, and historical strain events of other oil and gas pipelines at different historical moments during the physical property detection stage. Divide the historical pipeline pressure and historical pipeline strain at different historical moments to obtain the historical pipeline pressure, historical pipeline strain, and historical strain events within each of multiple historical time periods. Determine the normal pipeline pressure range based on the average value and variance of the historical pipeline pressure within each historical time period. Statistically analyze the change rate of the historical pipeline strain within each historical time period to determine multiple pipeline strain change rates. Determine the strain event information corresponding to each of the multiple pipeline strain change rates based on the historical strain events within each historical time period.

[0022] In some embodiments, the processing unit is specifically configured to: determine whether there is an abnormal pipeline pressure in the oil and gas pipeline based on whether the pipeline pressure of the updated digital twin model is within the normal pipeline pressure range. Determine whether there is an abnormal pipeline strain in the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update, and the strain event information corresponding to each of the multiple pipeline strain change rates.

[0023] In a third aspect, an embodiment of the present application provides a computer device, including: a processor, the processor is connected to a memory, the memory is used to store computer execution instructions, and the processor executes the computer execution instructions stored in the memory so that the computer device executes the oil and gas pipeline monitoring method according to any one of the first aspect.

[0024] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer execution instructions. When the computer execution instructions run on a computer device, the computer device is caused to execute the oil and gas pipeline monitoring method according to any one of the first aspect.

[0025] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer execution instructions. When the computer execution instructions run on a computer device, the computer device is caused to execute the oil and gas pipeline monitoring method according to any one of the first aspect.

[0026] It should be understood that the technical effects brought by any implementation manner in the second aspect to the fifth aspect can be referred to the technical effects brought by the corresponding implementation manner in the first aspect, which will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0028] Figure 1 This is a schematic structural diagram of an oil and gas pipeline monitoring system provided by an embodiment of the present application;

[0029] Figure 2 This is a schematic structural diagram of a computer device provided by an embodiment of the present application;

[0030] Figure 3 This is a schematic flowchart of an oil and gas pipeline monitoring method provided by an embodiment of the present application;

[0031] Figure 4 This is a schematic structural diagram of an oil and gas pipeline monitoring device provided by an embodiment of the present application. Detailed implementation manners

[0032] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0033] In the embodiments of the present application, the term "including", "comprising" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the presence of additional identical elements in the process, article or device including the element.

[0034] Words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0035] First, a brief introduction to the application scenarios involved in the present application will be given.

[0036] With the expansion of the oil and gas pipeline network and the increase in complexity, the safety management of oil and gas pipelines has become increasingly important. Traditional monitoring methods for oil and gas pipelines rely on regular manual inspections, which are inefficient and difficult to respond in real time. There are defects such as large investment, long construction period, and failure to detect safety risks and potential hazards in a timely manner, which are likely to cause safety problems. Moreover, with the development of new technologies such as the Internet of Things, big data, and artificial intelligence, intelligent management has become an important direction for the construction and operation management of oil and gas pipelines. Therefore, it is urgent to achieve efficient monitoring and management of oil and gas pipelines.

[0037] In view of the above problems, this application provides a method for monitoring oil and gas pipelines, which can obtain the production data of the oil and gas pipelines in the current monitoring period, as well as multiple monitoring rules corresponding to the oil and gas pipelines. Based on the production data in the current monitoring period, it updates the digital twin model used to simulate the oil and gas pipelines, and further monitors the updated digital twin model based on the target monitoring rule corresponding to the production stage in which the updated digital twin model is located among the multiple monitoring rules, to obtain the monitoring results of the oil and gas pipelines. Among them, different monitoring rules are used to indicate the characteristic information of the oil and gas pipelines in different production stages. The monitoring results are used to indicate whether there are production anomalies in the oil and gas pipelines.

[0038] Based on this, this application can combine the production status of the oil and gas pipelines with the digital twin model to achieve real-time monitoring of the oil and gas pipelines, which not only improves the intelligent level and efficiency of management, but also improves the accuracy and timeliness of anomaly monitoring, and avoids problems such as large investment and long construction period caused by the manual-dependent method.

[0039] Next, a brief introduction to the implementation environment (implementation architecture) involved in this application is given.

[0040] As Figure 1 shown, it is a schematic structural diagram of an oil and gas pipeline monitoring system provided by an embodiment of this application. The oil and gas pipeline monitoring system may include a computer device 101 and a collection device 102.

[0041] It should be noted that the numbers of the computer device 101 and the collection device 102 included in the above oil and gas pipeline monitoring system are only examples, and this application embodiment does not limit this.

[0042] Figure 1 The computer device 101 in

[0043] is used to obtain the production data of the oil and gas pipelines in different production stages from the collection device 102 and maintain the digital twin model of the oil and gas pipelines, so as to further achieve the monitoring of the oil and gas pipelines.

[0044] When the computer device 101 is a terminal, the terminal can be a personal computer such as a desktop computer, a tablet computer, and a laptop computer, or can also be a remote terminal, a user terminal (terminal equipment, TE), a mobile device, etc. The present application does not limit the form of the terminal.

[0045] When the computer device 101 is a server, the server can be a single server (such as a cloud server), or can also be a server cluster composed of multiple servers. The server cluster can also be referred to as a computer device cluster. In some embodiments, the server cluster can also be a distributed cluster. The present application does not limit the form of the server.

[0046] Figure 1 The acquisition device 102 therein is used to acquire production data of the oil and gas pipeline at different production stages, and send the acquired production data of the oil and gas pipeline at different production stages to the computer device 101. For example, the acquisition device 102 can be connected to a variety of sensors deployed on the oil and gas pipeline production line based on the Internet of Things to acquire production data of the oil and gas pipeline at different production stages through the variety of sensors. The variety of sensors can include a temperature sensor, a pressure sensor, an optical fiber sensor, etc.

[0047] Optionally, Figure 1 the acquisition device 102 therein can be a functional module integrated within the computer device 101. Or, Figure 1 the acquisition device 102 therein can also be a device independently set up with the computer device 101. The embodiments of the present application do not limit this.

[0048] It is easy to understand that when the computer device 101 and the acquisition device 102 are integrated within the same device, the communication method between the computer device 101 and the acquisition device 102 is the communication between internal modules of the device. In this case, the communication process between the two is the same as "the communication process between the computer device 101 and the acquisition device 102 when they are independently set up".

[0049] In terms of hardware implementation, the above computer device 101 can be implemented through a structure as Figure 2 shown. As Figure 2 shown, it is a schematic structural diagram of a computer device provided by an embodiment of the present application. Figure 2 The computer device shown can include: a processor 201, a memory 202, a communication interface 203, and a bus 204. The processor 201, the memory 202, and the communication interface 203 can be connected through the bus 204.

[0050] The processor 201 is the control center of the computer device, which can be a general-purpose central processing unit (CPU), or other general-purpose processors, etc. Among them, the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0051] As an example, the processor 201 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 shown in

[0052] The memory 202 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but not limited thereto.

[0053] In a possible implementation, the memory 202 can exist independently of the processor 201. The memory 202 can be connected to the processor 201 through the bus 204 for storing data, instructions, or program code. When the processor 201 calls and executes the instructions or program code stored in the memory 202, the oil and gas pipeline monitoring method provided by the embodiments of the present application can be implemented.

[0054] In another possible implementation, the memory 202 can also be integrated with the processor 201.

[0055] The communication interface 203 is used for the computer device to connect to other devices through a communication network, and the communication network can be an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc. The communication interface 203 can include a receiving unit for receiving data and a sending unit for sending data.

[0056] The bus 204 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. This bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 2 only a thick line is used to represent it in Figure 2 , but it does not mean that there is only one bus or one type of bus.

[0057] It should be noted that Figure 2 the structure shown in Figure 2 does not constitute a limitation on the computer device. Except Figure 2 for the components shown, the computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0058] For the sake of easy understanding, the oil and gas pipeline monitoring method provided by this application will be specifically introduced below in conjunction with the accompanying drawings.

[0059] As Figure 3 shown, it is a schematic flowchart of an oil and gas pipeline monitoring method provided by an embodiment of this application. Figure 3 The shown oil and gas pipeline monitoring method can be applied to the computer device in the above Figure 1 Figure 1 . This computer device can be implemented based on the structure shown in Figure 2 Figure 2 . This method includes: S301 - S303.

[0060] S301. Obtain the production data of the oil and gas pipeline in the current monitoring period, as well as a plurality of monitoring rules corresponding to the oil and gas pipeline.

[0061] Among them, the oil and gas pipeline can be a pipeline for transporting oil or natural gas, etc. The production process of the oil and gas pipeline can be divided into a pre - production stage, a heat treatment stage, and a physical property detection stage. The pre - production stage refers to the stage of designing the material properties, standards, dimensions, etc. of the oil and gas pipeline, as well as implementing material selection and preliminary processing, etc. The heat treatment stage refers to the stage of performing welding and annealing processes during the manufacturing process of the oil and gas pipeline. The physical property detection stage refers to the stage of detecting the physical properties, welding quality, and structural integrity, etc. of the oil and gas pipeline.

[0062] The computer device can obtain the production data of the oil and gas pipeline at any stage during the production process of the oil and gas pipeline. That is, the current monitoring period can be in any one of the pre - production stage, the heat treatment stage, and the physical property detection stage.

[0063] If the current monitoring period is in the pre-production stage, the production data of the oil and gas pipeline obtained by the computer device in the current monitoring period may include data such as the material property parameters of the production materials of the oil and gas pipeline.

[0064] If the current monitoring period is in the heat treatment stage, the production data of the oil and gas pipeline obtained by the computer device in the current monitoring period may include data such as the pipeline temperature during the welding or annealing process of the oil and gas pipeline.

[0065] If the current monitoring period is in the physical property detection stage, the production data of the oil and gas pipeline obtained by the computer device in the current monitoring period may include data such as the pipeline pressure and pipeline strain of the oil and gas pipeline.

[0066] Furthermore, the oil and gas pipeline may correspond to multiple monitoring rules. Different monitoring rules are used to indicate the characteristic information of the oil and gas pipeline in different production stages. The multiple monitoring rules may include a property characteristic monitoring rule corresponding to the pre-production stage of the oil and gas pipeline, a temperature characteristic monitoring rule corresponding to the heat treatment stage of the oil and gas pipeline, and a mechanical characteristic monitoring rule corresponding to the physical property detection stage of the oil and gas pipeline.

[0067] The property characteristic monitoring rule may include multiple intervals of material property parameters. Different intervals of material property parameters correspond to different material property grades.

[0068] The temperature characteristic monitoring rule may include temperature event information corresponding to multiple temperature characteristic values. The temperature event information is used to indicate whether there is a temperature abnormal event for the temperature characteristic value. The temperature abnormal event is an event caused by the abnormal pipeline temperature. For example, the event caused by the abnormal pipeline temperature may be material thermal failure, or high-temperature oxidation and creep, etc.

[0069] The mechanical characteristic monitoring rule includes a normal interval of pipeline pressure, and strain event information corresponding to multiple pipeline strain change rates. The strain event information is used to indicate whether there is a corresponding strain abnormal event for the pipeline strain change rate. The strain abnormal event is an event caused by the abnormal pipeline strain. For example, the event caused by the abnormal pipeline strain may be pipeline fracture or thermo-mechanical fatigue, etc.

[0070] S302. Update the digital twin model used to simulate the oil and gas pipeline based on the production data of the current monitoring period.

[0071] In an implementable manner, after the computer device obtains the production data of the oil and gas pipeline in the current monitoring period, it may perform preprocessing such as data cleaning and feature extraction on the obtained production data to obtain the preprocessed production data.

[0072] Furthermore, the computer device may convert the preprocessed production data in the current monitoring period to obtain a two-dimensional array composed of each production data and the acquisition time corresponding to each production data.

[0073] For example, a two-dimensional array D1 = [Q, TM] consisting of material property parameters in the preprocessing stage. A two-dimensional array D2 = [T, TM] consisting of the pipeline temperature during welding and annealing in the heat treatment stage. A two-dimensional array D3 = [P, TM] consisting of the pipeline pressure of the oil and gas pipeline. A two-dimensional array D4 = [S, TM] consisting of the pipeline strain of the oil and gas pipeline. Wherein, Q is the material property parameter. T is the pipeline temperature. P is the pipeline pressure. S is the pipeline strain. TM is the acquisition time.

[0074] Moreover, the computer device can pre-construct a digital twin model for simulating the oil and gas pipeline according to the production data of the oil and gas pipeline in the historical monitoring period. For example, the computer device can construct a geometric model of the oil and gas pipeline according to the design requirements of the oil and gas pipeline, import it into the digital twin platform, and correspondingly set data interfaces on the geometric model according to the deployment positions of each sensor to generate a digital twin model. Furthermore, the computer device can input the generated two-dimensional array into the data interface to update the state of the digital twin model for simulating the oil and gas pipeline. Or further, the computer device can perform visualization processing on the digital twin model.

[0075] S303. Monitor the updated digital twin model based on the target monitoring rule corresponding to the production stage in which the updated digital twin model is located among multiple monitoring rules, and obtain the monitoring result of the oil and gas pipeline.

[0076] The monitoring result is used to indicate whether there is a production anomaly in the oil and gas pipeline.

[0077] The computer device can determine the production stage in which the updated digital twin model is located, and determine the monitoring rule corresponding to the production stage in which the updated digital twin model is located among multiple monitoring rules as the target monitoring rule. Furthermore, the computer device can monitor the updated digital twin model based on the target monitoring rule to obtain the monitoring result of the oil and gas pipeline.

[0078] In one implementation, an artificial intelligence (AI) agent can be configured in the computer device. The AI agent can process the production data of the oil and gas pipeline, etc. based on a pre-trained AI model.

[0079] For example, the computer device can use the AI agent to detect the material properties of the updated digital twin model in the pre-production stage based on the property feature monitoring rules. For another example, the computer device can use the AI agent to detect the updated digital twin model during the welding and annealing processes based on the temperature feature monitoring rules and generate corresponding strategies. For yet another example, the computer device can use the AI agent to detect the updated digital twin model based on the mechanical feature monitoring rules to determine whether there is structural damage to the oil and gas pipeline and generate corresponding strategies.

[0080] Based on this, the production data of the oil and gas pipeline can be monitored by setting up an AI agent, and the trained AI model can be used for analysis to obtain the monitoring results of the oil and gas pipeline, or further generate an evaluation report on the production operation of the oil and gas pipeline, so as to realize performance evaluation, fault prediction, risk management, etc. of the oil and gas pipeline.

[0081] Furthermore, a visualization interface can be set on the computer device to support the interaction between the operation and maintenance personnel and the AI agent, so as to realize functions such as abnormal alarm, report analysis, and suggestion execution. The operation and maintenance personnel can handle the abnormalities of the oil and gas pipeline in a timely manner according to the monitoring results, or the AI agent can also handle them by itself.

[0082] For example, the AI agent can classify the risks in the evaluation report on the production operation of the oil and gas pipeline. If a fault has occurred, the AI agent can notify the operation and maintenance personnel through the visualization interface for repair. If no fault has occurred, the AI agent can adjust the parameters of the oil and gas pipeline production line to avoid the occurrence of faults.

[0083] In one embodiment, in the above S301, when the computer device obtains multiple monitoring rules corresponding to the oil and gas pipeline, it can obtain the historical production data of other oil and gas pipelines. And the computer device can preprocess the historical production data of other oil and gas pipelines according to the division of the production stage of the oil and gas pipeline, such as removing invalid, abnormal or duplicate data points through mathematical statistics, and feature extraction, etc. Furthermore, the computer device can establish multiple monitoring rules based on the preprocessed historical production data. Among them, other oil and gas pipelines can be oil and gas pipelines that have completed production, installation and use and have the same design specifications as the oil and gas pipeline.

[0084] In one embodiment, in the above S301, that is, when the computer device obtains the property feature monitoring rules of the oil and gas pipeline, an optional implementation manner provided by the embodiment of the present application includes: S3011-S3013.

[0085] S3011. Obtain the minimum material property parameters that meet the production standards of the oil and gas pipeline, and the historical material property parameters of other oil and gas pipelines.

[0086] For example, a computer device can obtain the design specifications of an oil and gas pipeline, and determine the implementation standards of the production materials for the oil and gas pipeline according to the design specifications of the oil and gas pipeline, so as to obtain the lowest implementation standards for the production materials to meet the design specifications, that is, the lowest material property parameters.

[0087] Moreover, the operation and maintenance personnel can pre-set the historical material property parameters of other oil and gas pipelines in the storage module configured by the computer device. When needed, the computer device can read the historical material property parameters of other oil and gas pipelines from the pre-set storage module. The historical material property parameters of other oil and gas pipelines are the material property parameters of the production materials of other oil and gas pipelines that have been completed. Such as yield strength, elastic modulus or elongation, etc.

[0088] S3012. Determine the property parameter tolerance based on the historical material property parameters of other oil and gas pipelines.

[0089] For example, the computer device can determine the standard deviation of the historical material property parameters of other oil and gas pipelines, and determine this standard deviation as the property parameter tolerance.

[0090] S3013. Determine multiple material property parameter intervals based on the lowest material property parameters and the property parameter tolerance.

[0091] For example, the multiple material property parameter intervals can include a first interval, a second interval, a third interval and a fourth interval. The material property grades can be divided into a first grade, a second grade, a third grade and a fourth grade. The first grade is higher than the second grade. The second grade is higher than the third grade. The third grade is higher than the fourth grade.

[0092] The first interval can be a parameter range greater than or equal to the sum between the lowest material property parameter and three times the property parameter tolerance. The material property grade corresponding to the first interval can be the first grade.

[0093] The second interval can be a parameter range less than the sum between the lowest material property parameter and three times the property parameter tolerance and greater than or equal to the sum between the lowest material property parameter and two times the property parameter tolerance. The material property grade corresponding to the second interval can be the second grade.

[0094] The third interval can be a parameter range less than the sum between the lowest material property parameter and two times the property parameter tolerance and greater than or equal to the sum between the lowest material property parameter and one time the property parameter tolerance. The material property grade corresponding to the third interval can be the third grade.

[0095] The fourth interval can be a parameter range less than the sum between the lowest material property parameter and one time the property parameter tolerance. The material property grade corresponding to the fourth interval can be the fourth grade.

[0096] In one embodiment, when the production stage of the updated digital twin model is the pre-production stage, and the computer device monitors the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, an optional implementation provided by the embodiments of the present application includes: S3031 - S3032.

[0097] S3031. Determine the material property grade of the oil and gas pipeline in the current monitoring period by using the material property grade corresponding to the material property parameter interval in multiple material property grades to cover the material property parameters of the updated digital twin model.

[0098] S3032. Determine the monitoring results according to the material property grade of the oil and gas pipeline in the current monitoring period.

[0099] Based on this, if the material property parameters of the updated digital twin model are in the first interval, the computer device can determine that the material property grade of the oil and gas pipeline in the current monitoring period is the first grade, and determine that the monitoring result is that there is no production anomaly. Or further, the computer device can mark the production material of the oil and gas pipeline in the current monitoring period as high-quality material.

[0100] If the material property parameters of the updated digital twin model are in the second interval, the computer device can determine that the material property grade of the oil and gas pipeline in the current monitoring period is the second grade, and determine that the monitoring result is that there is no production anomaly. Or further, the computer device can mark the production material of the oil and gas pipeline in the current monitoring period as good-quality material.

[0101] If the material property parameters of the updated digital twin model are in the third interval, the computer device can determine that the material property grade of the oil and gas pipeline in the current monitoring period is the third grade, and determine that the monitoring result is that there is no production anomaly. Or further, the computer device can mark the production material of the oil and gas pipeline in the current monitoring period as optional material. And the computer device can conduct sampling inspection on the production materials of the same batch again to avoid the existence of unqualified materials.

[0102] If the material property parameters of the updated digital twin model are in the fourth interval, the computer device can determine that the material property grade of the oil and gas pipeline in the current monitoring period is the fourth grade, and determine that the monitoring result is that there is a production anomaly. Or further, the computer device can mark the production material of the oil and gas pipeline in the current monitoring period as unqualified material. And the computer device can conduct full-quantity inspection on the production materials of the same batch to avoid the existence of other unqualified materials.

[0103] In one embodiment, in the above S301, that is, when the computer device obtains the temperature characteristic monitoring rule of the oil and gas pipeline, an optional implementation provided by the embodiments of the present application includes: S3014 - S3016.

[0104] S3014. Obtain the historical pipeline temperatures and historical temperature events of other oil and gas pipelines at different historical moments during the heat treatment stage.

[0105] Optionally, the historical temperature event can be a material thermal failure that occurred to other oil and gas pipelines at a historical moment, or events such as high-temperature oxidation and creep.

[0106] S3015. Perform statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values.

[0107] Among them, the multiple temperature characteristic values include the average value, peak value, and valley value.

[0108] The computer device can divide the historical pipeline temperatures at different moments according to time. For example, the historical pipeline temperatures T' at different moments can be expressed as [T'1, T'2,..., T'n]. It is divided into that the historical pipeline temperature in the first time period is T'1, expressed as [T'1, T'2,..., T't1]. The historical pipeline temperature in the second time period is T'2, expressed as [T't1, T't1 + 1,..., T't2]. The historical pipeline temperature in the third time period is T'3, expressed as [T't2, T't2 + 1,..., T't3]. The historical pipeline temperature in the fourth time period is T'4, expressed as [T't3, T't3 + 1,..., T't4]. Among them, T't1 represents the historical pipeline temperature at the t1 moment. T't2 represents the historical pipeline temperature at the t2 moment. T't3 represents the historical pipeline temperature. T't4 represents the historical pipeline temperature.

[0109] Furthermore, the computer device can calculate the average value of the historical pipeline temperatures within each time period to obtain E(T'1), E(T'2), E(T'3), and E(T'4). Among them, E(T'1) represents the average value in the first time period. E(T'2) represents the average value in the second time period. E(T'3) represents the average value in the third time period. E(T'4) represents the average value in the fourth time period. Further, the computer device can calculate the average value of the average values within each time period to determine the typical temperature value E(T') of the heat treatment stage.

[0110] And, the computer device can analyze the change rate of the historical pipeline temperature over time to identify the peak value and valley value in each historical pipeline temperature, and obtain the temperature peak value T'MAX and the temperature valley value T'MIN.

[0111] In this way, the computer device can obtain three temperature characteristic values: the typical temperature value E(T'), the temperature peak value T'MAX, and the temperature valley value T'MIN.

[0112] S3016. Determine the temperature event information corresponding to each of multiple temperature characteristic values from historical temperature events at different historical moments.

[0113] For example, the computer device can determine the historical temperature events that occurred during the corresponding process of each temperature characteristic value from historical temperature events at different historical moments.

[0114] If the historical temperature event that occurred during the corresponding process of a temperature characteristic value is an abnormal event, the computer device can determine that there is an abnormal event corresponding to the temperature characteristic value, that is, the temperature event information of the temperature characteristic value is used to indicate the existence of an abnormal event.

[0115] If the historical temperature event that occurred during the corresponding process of a temperature characteristic value is a normal event, or there is no corresponding historical temperature event, the computer device can determine that there is no abnormal event corresponding to the temperature characteristic value, that is, the temperature event information of the temperature characteristic value is used to indicate the non - existence of an abnormal event.

[0116] In one embodiment, when the production stage where the updated digital twin model is located is the heat treatment stage, and the computer device monitors the updated digital twin model and obtains the monitoring result of the oil and gas pipeline, an optional implementation manner provided by the embodiments of the present application includes: S3033 - S3034.

[0117] S3033. Determine a target temperature characteristic value that matches the pipeline temperature of the updated digital twin model from multiple temperature characteristic values.

[0118] S3034. Determine the monitoring result according to the temperature event information corresponding to the target temperature characteristic value.

[0119] For example, if the temperature event information corresponding to the target temperature characteristic value indicates the non - existence of a corresponding temperature abnormal event, the computer device determines that there is no abnormality in the oil and gas pipeline.

[0120] If the temperature event information corresponding to the target temperature characteristic value indicates the existence of a corresponding temperature abnormal event, the computer device determines that there is a pipeline strain abnormality in the oil and gas pipeline.

[0121] In one embodiment, in S301 above, that is, when the computer device obtains the mechanical characteristic monitoring rules of the oil and gas pipeline, an optional implementation manner provided by the embodiments of the present application includes: S3017 - S30111.

[0122] S3017. Obtain the historical pipeline pressure, historical pipeline strain, and historical strain events of other oil and gas pipelines at different historical moments during the physical property detection stage.

[0123] Optionally, the historical strain event may be an event such as pipeline fracture or thermo-mechanical fatigue that occurred in other oil and gas pipelines at historical moments.

[0124] S3018. Divide the historical pipeline pressures and historical pipeline strains at different historical moments to obtain the historical pipeline pressures, historical pipeline strains, and historical strain events within each historical time period among multiple historical time periods.

[0125] S3019. Determine the normal range of pipeline pressure based on the average value and variance of the historical pipeline pressures within each historical time period.

[0126] For example, the computer device can calculate the expectation of the average value of the historical pipeline pressures within each historical time period. The expectation of the average value of the historical pipeline pressures within each historical time period can be used to reflect the general level of pipeline pressure.

[0127] The computer device can calculate the expectation of the variance of the historical pipeline pressures within each historical time period. The expectation of the variance of the historical pipeline pressures within each historical time period can be used to reflect the fluctuation of pipeline pressure.

[0128] Furthermore, the computer device can determine that the left endpoint of the normal range of pipeline pressure is the difference obtained by subtracting the expectation of the variance of the historical pipeline pressures within each historical time period from the expectation of the average value of the historical pipeline pressures within each historical time period, and the right endpoint of the normal range of pipeline pressure is the sum value obtained by adding the expectation of the variance of the historical pipeline pressures within each historical time period to the expectation of the average value of the historical pipeline pressures within each historical time period, so as to indicate the extreme values of pipeline pressure and reflect the maximum bearing capacity and possible risk points of the oil and gas pipeline.

[0129] S30110. Statistically analyze the change rates of the historical pipeline strains within each historical time period to determine multiple pipeline strain change rates.

[0130] S30111. Determine the strain event information corresponding to each of the multiple pipeline strain change rates based on the historical strain events within each historical time period.

[0131] Based on this, the computer device can calculate the change rates of the historical strain data for different historical time periods respectively, and determine different abnormal events corresponding to the oil and gas pipeline based on different pipeline strain change rates.

[0132] In one embodiment, when the production stage of the updated digital twin model is the physical property monitoring stage, and the computer device monitors the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, an optional implementation manner provided by the embodiments of the present application includes: S3035 - S3036.

[0133] S3035. Determine whether there is an abnormal pipeline pressure in the oil and gas pipeline based on whether the pipeline pressure of the updated digital twin model is within the normal pipeline pressure range.

[0134] For example, if the pipeline pressure of the updated digital twin model is not within the normal pipeline pressure range, the computer device determines that there is an abnormal pipeline pressure in the oil and gas pipeline.

[0135] If the pipeline pressure of the updated digital twin model is within the normal pipeline pressure range, the computer device determines that there is no abnormal pipeline pressure in the oil and gas pipeline.

[0136] S3036. Determine whether there is an abnormal pipeline strain in the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update, and the strain event information corresponding to each of the multiple pipeline strain change rates.

[0137] For example, if the strain event information corresponding to the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update indicates that there is no corresponding strain abnormal event, the computer device determines that there is no abnormal pipeline strain in the oil and gas pipeline.

[0138] If the strain event information corresponding to the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update indicates that there is a corresponding strain abnormal event, the computer device determines that there is an abnormal pipeline strain in the oil and gas pipeline.

[0139] In each of the above embodiments of the present application, it is possible to support obtaining real-time production data by dividing the production stage of the oil and gas pipeline, which not only improves production efficiency and safety, but also helps with quality control and predictive maintenance. At the same time, it can also support the realization of digital management and real-time dynamic management of the oil and gas pipeline, providing a basis for the full-process digital management of oil and gas pipeline production, helping to realize the online twin of business management and data dynamic interaction, and improving the management level.

[0140] Moreover, by combining the production status of the oil and gas pipeline with the digital twin model and integrating advanced calculation models, the behavior of the oil and gas pipeline can be simulated and visualized, which not only improves the intelligent level of management, but also provides strong technical support for the safe and efficient operation of the oil and gas pipeline.

[0141] Furthermore, by building an AI intelligent agent to monitor real-time production data, manual intervention is reduced, and production efficiency and management quality are improved. Based on the integration of intelligent operation and maintenance technology, it can promote the digital transformation of the oil and gas industry and lay a technical foundation for realizing intelligent pipelines.

[0142] Moreover, by combining the AI agent with the digital twin model of the oil and gas pipeline to monitor the production process of the oil and gas pipeline, the current state of the oil and gas pipeline production, the production operation evaluation report, and the operation and maintenance strategy are more intuitively displayed, enabling the operation and maintenance personnel to interact with the AI agent through the visualization interface to receive alarms, analyze reports, and execute suggestions, etc.

[0143] The above mainly introduced the solution of the embodiment of the present application from the perspective of the method. It can be understood that in order for the computer device to implement the above functions, it includes at least one of the corresponding hardware structures and software modules for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0144] The embodiments of the present application can divide the computer device into functional units according to the above method examples. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. It should be noted that the division of units in the embodiments of the present application is illustrative, only a logical function division, and there can be other division methods in actual implementation.

[0145] Exemplarily, as Figure 4 shown, it is a schematic structural diagram of an oil and gas pipeline monitoring device provided by an embodiment of the present application. The oil and gas pipeline monitoring device includes: an acquisition unit 401 and a processing unit 402.

[0146] The acquisition unit 401 is used to acquire the production data of the oil and gas pipeline in the current monitoring period, as well as a plurality of monitoring rules corresponding to the oil and gas pipeline. Different monitoring rules are used to indicate the characteristic information of the oil and gas pipeline in different production stages. The processing unit 402 is used to update the digital twin model for simulating the oil and gas pipeline based on the production data in the current monitoring period. The processing unit 402 is further used to monitor the updated digital twin model based on the target monitoring rule in the plurality of monitoring rules whose corresponding production stage is the production stage where the updated digital twin model is located, and obtain the monitoring result of the oil and gas pipeline. The monitoring result is used to indicate whether there is a production anomaly in the oil and gas pipeline.

[0147] In some embodiments, the multiple monitoring rules include a property characteristic monitoring rule corresponding to the pre-production stage of the oil and gas pipeline, a temperature characteristic monitoring rule corresponding to the heat treatment stage of the oil and gas pipeline, and a mechanical characteristic monitoring rule corresponding to the physical property detection stage of the oil and gas pipeline. The property characteristic monitoring rule includes multiple material property parameter intervals, and different material property parameter intervals correspond to different material property grades. The temperature characteristic monitoring rule includes temperature event information corresponding to multiple temperature characteristic values. The temperature event information is used to indicate whether a temperature anomaly event corresponds to the temperature characteristic value. The mechanical characteristic monitoring rule includes a normal pipeline pressure interval and strain event information corresponding to multiple pipeline strain change rates. The strain event information is used to indicate whether a strain anomaly event corresponds to the pipeline strain change rate.

[0148] In some embodiments, the obtaining unit 401 is specifically configured to: obtain the lowest material property parameter that meets the production standard of the oil and gas pipeline, and the historical material property parameters of other oil and gas pipelines. Based on the historical material property parameters of other oil and gas pipelines, determine the property parameter tolerance. Based on the lowest material property parameter and the property parameter tolerance, determine multiple material property parameter intervals.

[0149] In some embodiments, the processing unit 402 is specifically configured to: determine the material property grade of the oil and gas pipeline in the current monitoring period by using the material property grade that covers the material property parameters of the updated digital twin model with the corresponding material property parameter interval among the multiple material property grades. Determine the monitoring result according to the material property grade of the oil and gas pipeline in the current monitoring period.

[0150] In some embodiments, the obtaining unit 401 is specifically configured to: obtain the historical pipeline temperature and historical temperature events at different historical moments of other oil and gas pipelines in the heat treatment stage. Perform statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values. The multiple temperature characteristic values include an average value, a peak value, and a valley value. Determine the temperature event information corresponding to each of the multiple temperature characteristic values from the historical temperature events at different historical moments.

[0151] In some embodiments, the processing unit 402 is specifically configured to: determine a target temperature characteristic value that matches the pipeline temperature of the updated digital twin model from the multiple temperature characteristic values. Determine the monitoring result according to the temperature event information corresponding to the target temperature characteristic value.

[0152] In some embodiments, the acquisition unit 401 is specifically configured to: acquire the historical pipeline pressure, historical pipeline strain, and historical strain events of other oil and gas pipelines at different historical moments during the physical property detection stage. Divide the historical pipeline pressure and historical pipeline strain at different historical moments to obtain the historical pipeline pressure, historical pipeline strain, and historical strain events within each historical time period among multiple historical time periods. Determine the normal pipeline pressure range based on the average value and variance of the historical pipeline pressure within each historical time period. Statistically analyze the change rate of the historical pipeline strain within each historical time period to determine multiple pipeline strain change rates. Determine the strain event information corresponding to each of the multiple pipeline strain change rates based on the historical strain events within each historical time period.

[0153] In some embodiments, the processing unit 402 is specifically configured to: determine whether there is an abnormal pipeline pressure in the oil and gas pipeline based on whether the pipeline pressure of the updated digital twin model is within the normal pipeline pressure range. Determine whether there is an abnormal pipeline strain in the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update, and the strain event information corresponding to each of the multiple pipeline strain change rates.

[0154] For the specific descriptions of the above optional manners, reference may be made to the foregoing method embodiments, which will not be elaborated herein. In addition, the explanations and beneficial effects of any of the above-provided computer devices can be referred to the corresponding method embodiments above, and will not be elaborated.

[0155] The embodiment of the present application further provides a readable storage medium, on which a computer program is stored. When the computer program runs on a computer device, the computer device is enabled to execute the method performed by any of the above-provided computer devices.

[0156] For the explanations and beneficial effects of the relevant content in any of the above-provided readable storage media, reference may be made to the corresponding embodiments above, which will not be elaborated herein.

[0157] The embodiments of the present application also provide a computer program product containing instructions. When the instructions run on a computer device, the computer device is enabled to execute any one of the methods in the above embodiments. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer device, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer device may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a readable storage medium or transmitted from one readable storage medium to another. For example, the computer instructions may be transmitted from a website, a computer, a server, or a data center to another website, a computer, a server, or a data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The readable storage medium may be any available medium that can be accessed by the computer device or a data storage device such as a server or a data center that includes one or more integrated media. The available medium may be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), etc.

[0158] It should be noted that the devices for storing computer instructions or computer programs provided in the embodiments of the present application, such as but not limited to, the above-mentioned memory, readable storage medium, etc., are all non-transitory.

[0159] The above are only the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for monitoring an oil and gas pipeline, characterized in that: include: Acquire production data of the oil and gas pipeline in the current monitoring period, and multiple monitoring rules corresponding to the oil and gas pipeline; different monitoring rules are used to indicate characteristic information of the oil and gas pipeline at different production stages; Based on the production data of the current monitoring period, updating the digital twin model used to simulate the oil and gas pipeline; Based on the target monitoring rule in which the corresponding production stage among the multiple monitoring rules is the production stage in which the updated digital twin model is located, the updated digital twin model is monitored to obtain the monitoring results of the oil and gas pipeline; the monitoring results are used to indicate whether there is a production abnormality in the oil and gas pipeline.

2. The method according to claim 1, characterized in that The multiple monitoring rules include property characteristic monitoring rules corresponding to the pre-production stage of the oil and gas pipeline, temperature characteristic monitoring rules corresponding to the heat treatment stage of the oil and gas pipeline, and mechanical characteristic monitoring rules corresponding to the physical property detection stage of the oil and gas pipeline; the property characteristic monitoring rules include multiple material property parameter intervals, and different material property parameter intervals correspond to different material property levels; the temperature characteristic monitoring rules include temperature event information corresponding to multiple temperature characteristic values; the temperature event information is used to indicate whether the temperature characteristic value corresponds to the existence of an abnormal temperature event; the mechanical characteristic monitoring rules include a normal pipeline pressure interval, and strain event information corresponding to multiple pipeline strain change rates; the strain event information is used to indicate whether the pipeline strain change rate corresponds to the existence of an abnormal strain event.

3. The method according to claim 2, characterized in that Obtaining the property characteristics monitoring rules of the oil and gas pipeline, including: Obtain the minimum material property parameters that meet the oil and gas pipeline production standards, as well as the historical material property parameters of other oil and gas pipelines; Determining a property parameter tolerance based on historical material property parameters of the other oil and gas pipelines; The plurality of material property parameter intervals are determined based on the minimum material property parameter and the property parameter tolerance.

4. The method according to claim 2, characterized in that: In the case where the production stage of the updated digital twin model is the pre-production stage, the updated digital twin model is monitored to obtain the monitoring result of the oil and gas pipeline, including: Overlaying the material property level of the material property parameter of the updated digital twin model with the corresponding material property parameter intervals in the plurality of material property levels, and determining the material property level of the oil and gas pipeline in the current monitoring period; The monitoring result is determined according to the material property level of the oil and gas pipeline in the current monitoring cycle.

5. The method according to claim 2, characterized in that: Obtaining the temperature characteristic monitoring rules of the oil and gas pipeline includes: Obtain historical pipeline temperatures and historical temperature events of other oil and gas pipelines at different historical moments during the heat treatment stage; Performing statistical processing on the historical pipeline temperatures at different times to determine the multiple temperature characteristic values; the multiple temperature characteristic values ​​include an average value, a peak value, and a valley value; The temperature event information corresponding to each of the plurality of temperature characteristic values ​​is determined from historical temperature events at different historical moments.

6. The method according to claim 2, characterized in that In the case where the production stage of the updated digital twin model is the heat treatment stage, the updated digital twin model is monitored to obtain the monitoring result of the oil and gas pipeline, including: Determining a target temperature characteristic value that matches the pipeline temperature of the updated digital twin model from the multiple temperature characteristic values; The monitoring result is determined according to the temperature event information corresponding to the target temperature characteristic value.

7. The method according to claim 2, characterized in that Obtaining the mechanical characteristics monitoring rules of the oil and gas pipeline includes: Obtain historical pipeline pressure, historical pipeline strain and historical strain events of other oil and gas pipelines at different historical moments during the physical property detection stage; The historical pipeline pressure and historical pipeline strain at different historical moments are divided to obtain the historical pipeline pressure, historical pipeline strain and historical strain events in each of multiple historical time periods; Determining the normal range of the pipeline pressure based on the average value and variance of the historical pipeline pressure in each historical time period; Counting the change rates of historical pipeline strains in each historical time period to determine the multiple pipeline strain change rates; Based on the historical strain events in each historical time period, strain event information corresponding to each of the plurality of pipeline strain change rates is determined.

8. The method according to claim 2, characterized in that: In the case where the production stage of the updated digital twin model is the physical property monitoring stage, the updated digital twin model is monitored to obtain the monitoring result of the oil and gas pipeline, including: Determine whether the pipeline pressure of the oil and gas pipeline is abnormal based on whether the pipeline pressure of the updated digital twin model is within the normal pipeline pressure range; Based on the pipeline strain change rate of the updated digital twin model relative to the digital twin model before the update, and the strain event information corresponding to each of the multiple pipeline strain change rates, it is determined whether the oil and gas pipeline has pipeline strain anomaly.

9. A computer device, characterized in that: include: A processor, wherein the processor is connected to a memory, the memory is used to store computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory so that the computer device executes the oil and gas pipeline monitoring method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: Used to store computer execution instructions, when the computer execution instructions are executed on a computer device, the computer device executes the oil and gas pipeline monitoring method according to any one of claims 1 to 8.

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