Oil and gas pipeline monitoring method, device and storage medium

Abstract

The application discloses an oil and gas pipeline monitoring method, device and storage medium, relates to the technical field of pipelines, and is used for realizing real-time monitoring of oil and gas pipelines, improving the intelligent level and efficiency of oil and gas pipeline management, and improving the accuracy and timeliness of abnormal monitoring. The method comprises the following steps: acquiring 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 characteristic information of the oil and gas pipeline in different production stages; based on the production data of the current monitoring period, a digital twin model used for simulating the oil and gas pipeline is updated; based on a target monitoring rule corresponding to a production stage in which the updated digital twin model is located, the updated digital twin model is monitored, and a monitoring result of the oil and gas pipeline is obtained; the monitoring result is used for indicating whether the oil and gas pipeline has a production abnormality.

Description

Technical Field

[0001] This application relates to the field of pipeline technology, and in particular to a method, equipment and storage medium for monitoring oil and gas pipelines. Background Technology

[0002] With the expansion and increasing complexity of oil and gas pipeline networks, the safety management of oil and gas pipelines has become increasingly important. Traditional oil and gas pipeline monitoring methods rely on regular manual inspections, which are inefficient and difficult to respond to in real time. They also have drawbacks such as high investment, long construction periods, and untimely detection of safety risks and hazards, which can easily lead to safety problems. Summary of the Invention

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

[0004] To achieve the above objectives, this application adopts the following technical solution:

[0005] In a first aspect, embodiments of this application provide a method for monitoring oil and gas pipelines, comprising: acquiring 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, a digital twin model used to simulate the oil and gas pipeline is updated. Based on the target monitoring rule among the multiple monitoring rules whose corresponding production stage is the production stage of the updated digital twin model, the updated digital twin model is monitored to obtain monitoring results for the oil and gas pipeline. The monitoring results are used to indicate whether there are production anomalies in the oil and gas pipeline.

[0006] Based on this, this application can achieve real-time monitoring of oil and gas pipelines by combining the production status of oil and gas pipelines with digital twin models. This not only improves the level of intelligence and efficiency of management, but also improves the accuracy and timeliness of anomaly monitoring, avoiding the problems of large investment and long construction period caused by relying on manual methods.

[0007] In some embodiments, 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 testing stage of the oil and gas pipeline. The property characteristic monitoring rules include multiple material property parameter ranges, with different ranges corresponding to different material property levels. The temperature characteristic monitoring rules include temperature event information corresponding to each of the multiple temperature characteristic values. The temperature event information is used to indicate whether the temperature characteristic value corresponds to a temperature anomaly event. The mechanical characteristic monitoring rules include the normal pressure range of the pipeline and strain event information corresponding to each of the multiple pipeline strain change rates. The strain event information is used to indicate whether the pipeline strain change rate corresponds to a strain anomaly event.

[0008] In some embodiments, acquiring monitoring rules for the properties of oil and gas pipelines includes: acquiring the minimum material property parameters that meet the production standards for oil and gas pipelines, as well as historical material property parameters of other oil and gas pipelines; determining property parameter tolerances based on the historical material property parameters of other oil and gas pipelines; and determining multiple material property parameter ranges based on the minimum material property parameters and the property parameter tolerances.

[0009] In some embodiments, when the updated digital twin model is in a pre-production stage, monitoring the updated digital twin model to obtain monitoring results for the oil and gas pipeline includes: determining the material property level of the oil and gas pipeline in the current monitoring period by covering the material property parameter range corresponding to multiple material property levels with the material property parameter range corresponding to the updated digital twin model. Based on the material property level of the oil and gas pipeline in the current monitoring period, the monitoring results are determined.

[0010] In some embodiments, acquiring temperature characteristic monitoring rules for oil and gas pipelines includes: acquiring historical pipeline temperatures and historical temperature events at different historical moments during the heat treatment stage of other oil and gas pipelines; performing statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values; the multiple temperature characteristic values ​​including average, peak, and valley values; and determining the temperature event information corresponding to each of the multiple temperature characteristic values ​​from the historical temperature events at different historical moments.

[0011] In some embodiments, when the updated digital twin model is in a heat treatment stage of production, monitoring the updated digital twin model to obtain monitoring results for the oil and gas pipeline includes: determining a target temperature feature value from multiple temperature feature values ​​that matches the pipeline temperature of the updated digital twin model; and determining the monitoring results based on the temperature event information corresponding to the target temperature feature value.

[0012] In some embodiments, acquiring mechanical characteristic monitoring rules for oil and gas pipelines includes: acquiring historical pipeline pressure, historical pipeline strain, and historical strain events at different historical moments during the physical property testing phase of other oil and gas pipelines; dividing the historical pipeline pressure and historical pipeline strain at different historical moments to obtain historical pipeline pressure, historical pipeline strain, and historical strain events within each historical time period; determining the normal range of pipeline pressure based on the average and variance of historical pipeline pressure within each historical time period; statistically analyzing the rate of change of historical pipeline strain within each historical time period to determine multiple pipeline strain change rates; and determining 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.

[0013] In some embodiments, when the updated digital twin model is in the physical property monitoring stage of production, monitoring the updated digital twin model yields monitoring results for the oil and gas pipeline. This includes: determining whether there is an anomaly in the pipeline pressure based on whether the pipeline pressure in the updated digital twin model is within the normal range; and determining whether there is an anomaly in the pipeline strain based on the pipeline strain change rate of the updated digital twin model relative to the original digital twin model, and the strain event information corresponding to each of the multiple pipeline strain change rates.

[0014] Secondly, an oil and gas pipeline monitoring device is provided, comprising: an acquisition unit and a processing unit;

[0015] The acquisition unit acquires production data of the oil and gas pipeline during the current monitoring period, as well as multiple monitoring rules corresponding to the pipeline. Different monitoring rules indicate the characteristic information of the oil and gas pipeline at different production stages. The processing unit updates the digital twin model used to simulate the oil and gas pipeline based on the production data of the current monitoring period. The processing unit also monitors the updated digital twin model based on the target monitoring rule whose corresponding production stage matches the production stage of the updated digital twin model, obtaining the monitoring results for the oil and gas pipeline. These monitoring results indicate whether there are any production anomalies in the oil and gas pipeline.

[0016] In some embodiments, 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 testing stage of the oil and gas pipeline. The property characteristic monitoring rules include multiple material property parameter ranges, with different ranges corresponding to different material property levels. The temperature characteristic monitoring rules include temperature event information corresponding to each of the multiple temperature characteristic values. The temperature event information is used to indicate whether the temperature characteristic value corresponds to a temperature anomaly event. The mechanical characteristic monitoring rules include the normal pressure range of the pipeline and strain event information corresponding to each of the multiple pipeline strain change rates. The strain event information is used to indicate whether the pipeline strain change rate corresponds to a strain anomaly event.

[0017] In some embodiments, the acquisition unit is specifically used to: acquire the minimum material property parameters that conform to the production standards for oil and gas pipelines, as well as the historical material property parameters of other oil and gas pipelines; determine the property parameter tolerance based on the historical material property parameters of other oil and gas pipelines; and determine multiple material property parameter ranges based on the minimum material property parameters and the property parameter tolerances.

[0018] In some embodiments, the processing unit is specifically configured to: determine the material property level of the oil and gas pipeline in the current monitoring period by covering the material property parameter range corresponding to the material property level in the updated digital twin model with multiple material property levels; and determine the monitoring result based on the material property level of the oil and gas pipeline in the current monitoring period.

[0019] In some embodiments, the acquisition unit is specifically configured to: acquire historical pipeline temperatures and historical temperature events at different historical moments during the heat treatment stage of other oil and gas pipelines; perform statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values; the multiple temperature characteristic values ​​include average values, peak values, and valley values; and 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 feature value from a plurality of temperature feature values ​​that matches the pipe temperature of the updated digital twin model; and determine a monitoring result based on temperature event information corresponding to the target temperature feature value.

[0021] In some embodiments, the acquisition unit is specifically configured to: acquire historical pipeline pressure, historical pipeline strain, and historical strain events at different historical moments during the physical property testing phase of other oil and gas pipelines; divide the historical pipeline pressure and historical pipeline strain at different historical moments to obtain historical pipeline pressure, historical pipeline strain, and historical strain events within each historical time period; determine the normal range of pipeline pressure based on the average and variance of historical pipeline pressure within each historical time period; statistically analyze the rate of change of historical pipeline strain within each historical time period to determine multiple pipeline strain change rates; and 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 anomaly in the pipeline pressure of the oil and gas pipeline based on whether the pipeline pressure in the updated digital twin model is within the normal range of pipeline pressure; and determine whether there is an anomaly in the pipeline strain of the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the original digital twin model, and strain event information corresponding to each of the multiple pipeline strain change rates.

[0023] Thirdly, embodiments of this application provide a computer device, including: a processor connected to a memory, the memory being used to store computer execution instructions, and the processor executing the computer execution instructions stored in the memory to cause the computer device to perform the oil and gas pipeline monitoring method as described in any of the first aspects.

[0024] Fourthly, embodiments of this application provide a computer-readable storage medium for storing computer-executable instructions, which, when executed on a computer device, cause the computer device to perform the oil and gas pipeline monitoring method as described in any of the first aspects.

[0025] Fifthly, embodiments of this application provide a computer program product, including computer execution instructions, which, when executed on a computer device, cause the computer device to perform the oil and gas pipeline monitoring method as described in any of the first aspects.

[0026] It should be understood that the technical effects of any of the implementation methods in the second to fifth aspects can be seen in the technical effects of the corresponding implementation methods in the first aspect, and will not be repeated here. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the structure of an oil and gas pipeline monitoring system provided in an embodiment of this application;

[0029] Figure 2 A schematic diagram of the structure of a computer device provided in an embodiment of this application;

[0030] Figure 3 A schematic flowchart illustrating an oil and gas pipeline monitoring method provided in this application embodiment;

[0031] Figure 4 This is a schematic diagram of the structure of an oil and gas pipeline monitoring device provided in an embodiment of this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0034] The terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

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

[0036] With the expansion and increasing complexity of oil and gas pipeline networks, the safety management of these pipelines has become increasingly important. Traditional oil and gas pipeline monitoring methods rely on periodic manual inspections, which are inefficient, lack real-time response capabilities, and suffer from drawbacks such as high investment costs, long construction periods, and delayed detection of safety risks and hazards, easily leading to safety problems. Furthermore, 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, operation, and management of oil and gas pipelines. Therefore, there is an urgent need to achieve efficient oil and gas pipeline monitoring and management.

[0037] This application addresses the aforementioned problems by providing a method for monitoring oil and gas pipelines. The method acquires production data of the oil and gas pipeline during the current monitoring period, along with multiple corresponding monitoring rules. Based on the production data of the current monitoring period, it updates a digital twin model used to simulate the oil and gas pipeline. Furthermore, it uses the production stage corresponding to the multiple monitoring rules as the target monitoring rule for the updated digital twin model's production stage, and then monitors the updated digital twin model to obtain monitoring results for the oil and gas pipeline. Different monitoring rules are used to indicate the characteristic information of the oil and gas pipeline at different production stages. The monitoring results are used to indicate whether there are any production anomalies in the oil and gas pipeline.

[0038] Based on this, this application can achieve real-time monitoring of oil and gas pipelines by combining the production status of oil and gas pipelines with digital twin models. This not only improves the level of intelligence and efficiency of management, but also improves the accuracy and timeliness of anomaly monitoring, avoiding the problems of large investment and long construction period caused by relying on manual methods.

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

[0040] like Figure 1 The diagram shown is a structural schematic of an oil and gas pipeline monitoring system provided in an embodiment of this application. The oil and gas pipeline monitoring system may include a computer device 101 and a data acquisition device 102.

[0041] It should be noted that the number of computer devices 101 and data acquisition devices 102 included in the above-mentioned oil and gas pipeline monitoring system is only an example, and the embodiments of this application do not limit this.

[0042] Figure 1 The computer device 101 is used to acquire production data of oil and gas pipelines at different production stages from the acquisition device 102, and maintain a digital twin model of the oil and gas pipelines to further realize the monitoring of oil and gas pipelines.

[0043] Optionally, the computer device 101 described above can be a terminal or a server. Alternatively, the computer device 101 can be located on a cloud computing platform. This application embodiment does not impose any limitations on this.

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

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

[0046] Figure 1 The data acquisition device 102 is used to collect production data of the oil and gas pipeline at different production stages and send the collected data to the computer device 101. For example, the data acquisition device 102 can be connected to various sensors deployed on the oil and gas pipeline production line via the Internet of Things (IoT) to collect production data of the oil and gas pipeline at different production stages through these sensors. These various sensors may include temperature sensors, pressure sensors, and fiber optic sensors, etc.

[0047] Optional, Figure 1 The data acquisition device 102 can be a functional module integrated into the computer device 101. Alternatively, Figure 1 The data acquisition device 102 can also be a device that is independently set up from the computer device 101. This application embodiment does not limit this.

[0048] It is easy to understand that when computer device 101 and acquisition device 102 are integrated into the same device, the communication method between computer device 101 and 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 that between computer device 101 and acquisition device 102 when they are set up independently.

[0049] In terms of hardware implementation, the aforementioned computer device 101 can be implemented through, for example... Figure 2 The structure shown is implemented as follows. Figure 2 The diagram shown is a structural schematic of a computer device provided in an embodiment of this application. Figure 2 The computer device shown may 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 via the bus 204.

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

[0051] As an example, processor 201 may include one or more CPUs, for example Figure 2 CPU0 and CPU1 are shown in the diagram.

[0052] The memory 202 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0053] In one possible implementation, the memory 202 can exist independently of the processor 201. The memory 202 can be connected to the processor 201 via a bus 204 and is used to store data, instructions, or program code. When the processor 201 calls and executes the instructions or program code stored in the memory 202, it can implement the oil and gas pipeline monitoring method provided in this application embodiment.

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

[0055] Communication interface 203 is used for connecting computer equipment to other devices via a communication network, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc. Communication interface 203 may include a receiving unit for receiving data and a transmitting unit for transmitting data.

[0056] Bus 204 can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 2 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0057] It should be pointed out that, Figure 2 The structure shown does not constitute a limitation on computer equipment, except Figure 2 In addition to the components shown, a computer device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0058] For ease of understanding, the oil and gas pipeline monitoring method provided in this application will be described in detail below with reference to the accompanying drawings.

[0059] like Figure 3 The diagram shown is a flowchart illustrating an oil and gas pipeline monitoring method provided in an embodiment of this application. Figure 3 The oil and gas pipeline monitoring method shown can be applied to the above. Figure 1 The computer equipment in the middle. This computer equipment can be based on Figure 2 The structure shown is implemented as follows. The method includes: S301-S303.

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

[0061] Oil and gas pipelines can be used to transport oil or natural gas. The production process of oil and gas pipelines can be divided into three stages: pre-production, heat treatment, and physical property testing. The pre-production stage refers to the design of the oil and gas pipeline based on standards and dimensions, as well as the selection of materials and preliminary processing. The heat treatment stage refers to the welding and annealing processes during the manufacturing process. The physical property testing stage refers to the testing of the physical properties, welding quality, and structural integrity of the oil and gas pipeline.

[0062] Computer equipment can acquire production data for oil and gas pipelines at any stage of the pipeline production process. That is, the current monitoring cycle can be at any stage, including the pre-production stage, the heat treatment stage, and the physical property testing stage.

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

[0064] If the current monitoring cycle is in the heat treatment stage, the production data of the oil and gas pipeline acquired by the computer equipment in the current monitoring cycle 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 cycle is in the physical property testing phase, the production data of the oil and gas pipeline acquired by the computer equipment during the current monitoring cycle may include data such as pipeline pressure and pipeline strain.

[0066] Furthermore, oil and gas pipelines can correspond to multiple monitoring rules. Different monitoring rules are used to indicate the characteristic information of oil and gas pipelines at different production stages. Multiple monitoring rules may include property characteristic monitoring rules corresponding to the pre-production stage of oil and gas pipelines, temperature characteristic monitoring rules corresponding to the heat treatment stage of oil and gas pipelines, and mechanical characteristic monitoring rules corresponding to the physical property testing stage of oil and gas pipelines.

[0067] The rules for monitoring material properties can include multiple ranges of material property parameters. Different ranges of material property parameters correspond to different levels of material properties.

[0068] Temperature characteristic monitoring rules can include temperature event information corresponding to each of multiple temperature characteristic values. Temperature event information is used to indicate whether any abnormal temperature events occur for the temperature characteristic values. Abnormal temperature events are events caused by abnormal pipe temperatures. For example, events caused by abnormal pipe temperatures could be material thermal failure, high-temperature oxidation, or creep.

[0069] The mechanical characteristic monitoring rules include the normal pressure range of the pipeline and strain event information corresponding to multiple pipeline strain change rates. Strain event information indicates whether an abnormal strain event exists corresponding to a pipeline strain change rate. An abnormal strain event is an event caused by abnormal pipeline strain. For example, events caused by abnormal pipeline strain can be pipeline fracture or thermomechanical fatigue.

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

[0071] In one possible approach, after acquiring production data of oil and gas pipelines during the current monitoring period, computer equipment can perform preprocessing such as data cleaning and feature extraction on the acquired production data to obtain preprocessed production data.

[0072] Furthermore, the computer equipment can convert the preprocessed production data within the current monitoring period into a two-dimensional array consisting of each production data point and the corresponding acquisition time.

[0073] For example, a two-dimensional array D1 = [Q, TM] is composed of material property parameters from the pretreatment stage. A two-dimensional array D2 = [T, TM] is composed of pipeline temperatures during welding and annealing processes in the heat treatment stage. A two-dimensional array D3 = [P, TM] is composed of pipeline pressures in the oil and gas pipeline. A two-dimensional array D4 = [S, TM] is composed of pipeline strains in the oil and gas pipeline. Where Q represents material property parameters, T represents pipeline temperature, P represents pipeline pressure, S represents pipeline strain, and TM represents the data acquisition time.

[0074] Furthermore, the computer equipment can pre-construct a digital twin model to simulate the oil and gas pipeline based on production data from historical monitoring periods. For example, the computer equipment can construct a geometric model of the oil and gas pipeline according to its design requirements, import it into the digital twin platform, and set corresponding data interfaces on the geometric model according to the deployment locations of each sensor to generate the digital twin model. Then, the computer equipment can input the generated two-dimensional array into the data interface to update the state of the digital twin model used to simulate the oil and gas pipeline. Alternatively, the computer equipment can perform visualization processing on the digital twin model.

[0075] S303. Based on the target monitoring rule that corresponds to the production stage of the updated digital twin model among multiple monitoring rules, the updated digital twin model is monitored to obtain the monitoring results of the oil and gas pipeline.

[0076] The monitoring results are used to indicate whether there are any production abnormalities in oil and gas pipelines.

[0077] The computer equipment can determine the production stage of the updated digital twin model, and use the production stage corresponding to the updated digital twin model from multiple monitoring rules as the monitoring rule for that production stage, thus defining it as the target monitoring rule. Furthermore, the computer equipment can monitor the updated digital twin model based on the target monitoring rule to obtain monitoring results for the oil and gas pipeline.

[0078] In one implementation, the computer device may be equipped with an artificial intelligence (AI) agent. The AI ​​agent can process data such as oil and gas pipeline production data based on a pre-trained AI model.

[0079] For example, computer equipment can use an AI agent to perform material property detection on an updated digital twin model in the pre-production stage based on property feature monitoring rules. As another example, computer equipment can use an AI agent to detect an updated digital twin model during welding and annealing processes based on temperature feature monitoring rules, and generate corresponding strategies. Yet another example is that computer equipment can use an AI agent to detect an updated digital twin model based on mechanical feature monitoring rules to determine if there is structural damage in oil and gas pipelines and generate corresponding strategies.

[0080] Based on this, an AI agent can be built to monitor oil and gas pipeline production data, and the trained AI model can be used to analyze the data to obtain monitoring results of oil and gas pipelines, or further generate oil and gas pipeline production and operation evaluation reports, thereby realizing performance evaluation, fault prediction and risk management of oil and gas pipelines.

[0081] Furthermore, a visual interface can be set up on the computer equipment to support interaction between maintenance personnel and the AI ​​agent, thereby enabling functions such as anomaly alarms, report analysis, and suggested execution. Maintenance personnel can promptly handle anomalies in oil and gas pipelines based on monitoring results, or the AI ​​agent can handle them autonomously.

[0082] For example, the AI ​​agent can classify the risks present in the oil and gas pipeline production and operation evaluation report. If a fault has occurred, the AI ​​agent can notify maintenance personnel to carry out repairs through a visual interface. If no fault has occurred, the AI ​​agent can adjust the parameters of the oil and gas pipeline production line to prevent faults from occurring.

[0083] In one embodiment, during step S301 above, when the computer device acquires multiple monitoring rules corresponding to the oil and gas pipeline, it can also acquire historical production data of other oil and gas pipelines. Furthermore, the computer device can preprocess the historical production data of other oil and gas pipelines based on the division of production stages, such as removing invalid, abnormal, or duplicate data points through mathematical statistics, and performing feature extraction. Subsequently, the computer device can establish multiple monitoring rules based on the preprocessed historical production data. These other oil and gas pipelines can be those that have completed production and installation and are in use, possessing the same design specifications as the oil and gas pipeline.

[0084] In one embodiment, when the computer device acquires the monitoring rules for the properties and characteristics of oil and gas pipelines in S301 above, this application embodiment provides an optional implementation method, including: S3011-S3013.

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

[0086] For example, computer equipment can obtain oil and gas pipeline design specifications and determine the implementation standards for oil and gas pipeline production materials based on these specifications, thereby obtaining the minimum implementation standards for production materials to meet the design specifications, i.e., the minimum material property parameters.

[0087] Furthermore, maintenance personnel can pre-set historical material property parameters of other oil and gas pipelines in the storage module configured on the computer equipment. When needed, the computer equipment can retrieve these historical material property parameters from the pre-set storage module. These historical material property parameters of other oil and gas pipelines refer to the material property parameters of the production materials of other oil and gas pipelines that have already been manufactured, such as yield strength, elastic modulus, or elongation.

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

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

[0090] S3013. Based on the minimum material property parameters and the property parameter tolerance, determine multiple material property parameter ranges.

[0091] For example, multiple material property parameter ranges may include a first range, a second range, a third range, and a fourth range. Material property grades may 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 the range of parameters that are greater than or equal to the sum of the minimum material property parameter and three times the property parameter tolerance. The material property level corresponding to the first interval can be the first level.

[0093] The second interval can be a range of parameters that are less than the sum of the minimum material property parameter and three times the property parameter tolerance, and greater than or equal to the sum of the minimum material property parameter and two times the property parameter tolerance. The material property level corresponding to the second interval can be the second level.

[0094] The third interval can be a range of parameters that are less than the sum of the minimum material property parameter and twice the property parameter tolerance, and greater than or equal to the sum of the minimum material property parameter and one property parameter tolerance. The material property level corresponding to the third interval can be the third level.

[0095] The fourth interval can be the range of parameters less than the sum of the minimum material property parameter and one property parameter tolerance. The material property level corresponding to the fourth interval can be the fourth level.

[0096] In one embodiment, when the updated digital twin model is in the pre-production stage of production, and the computer equipment monitors the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, this application embodiment provides an optional implementation method, including: S3031-S3032.

[0097] S3031. The material property level of the updated digital twin model is determined by covering the material property parameter range corresponding to the material property level among multiple material property levels.

[0098] S3032. Determine the monitoring results based on the material property level of the oil and gas pipeline in the current monitoring cycle.

[0099] Based on this, if the material property parameters of the updated digital twin model are in the first range, the computer equipment can determine that the material property level of the oil and gas pipeline in the current monitoring period is level one, and determine that the monitoring result is that there are no production anomalies. Alternatively, the computer equipment can mark the production materials of the oil and gas pipeline in the current monitoring period as superior materials.

[0100] If the material property parameters of the updated digital twin model fall within the second range, the computer equipment can determine that the material property level of the oil and gas pipeline in the current monitoring period is level two, and determine that the monitoring result indicates no production anomalies. Alternatively, the computer equipment can mark the production materials of the oil and gas pipeline in the current monitoring period as good quality materials.

[0101] If the material property parameters of the updated digital twin model fall within the third interval, the computer equipment can determine that the material property level of the oil and gas pipeline in the current monitoring period is level three, and confirm that there are no production anomalies. Alternatively, the computer equipment can mark the production materials of the oil and gas pipeline in the current monitoring period as optional materials. Furthermore, the computer equipment can re-sample and inspect the same batch of production materials to avoid the presence of substandard materials.

[0102] If the updated material property parameters of the digital twin model fall within the fourth interval, the computer equipment can determine that the material property level of the oil and gas pipeline in the current monitoring period is level four, and identify the monitoring result as indicating a production anomaly. Alternatively, the computer equipment can mark the production materials of the oil and gas pipeline in the current monitoring period as substandard. Furthermore, the computer equipment can perform full-scale testing on the same batch of production materials to prevent the presence of other substandard materials.

[0103] In one embodiment, when the computer device acquires the temperature characteristic monitoring rules of the oil and gas pipeline in S301 above, this application embodiment provides an optional implementation method, including: S3014-S3016.

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

[0105] Optionally, historical temperature events can be material thermal failures, high-temperature oxidation, or creep events that occurred in other oil and gas pipelines at historical moments.

[0106] S3015. Statistical processing is performed on the historical pipeline temperatures at different times to determine multiple temperature characteristic values.

[0107] Among them, multiple temperature characteristics include average, peak and valley values.

[0108] Computer equipment can divide historical pipe temperatures at different times according to time. For example, the historical pipe temperatures T' at different times can be represented as [T'1, T'2, ..., T'n]. The division is as follows: the historical pipe temperature for the first time period is T'1, represented as [T'1, T'2, ..., T't1]. The historical pipe temperature for the second time period is T'2, represented as [T't1, T't1+1, ..., T't2]. The historical pipe temperature for the third time period is T'3, represented as [T't2, T't2+1, ..., T't3]. The historical pipe temperature for the fourth time period is T'4, represented as [T't3, T't3+1, ..., T't4]. Where T't1 represents the historical pipe temperature at time t1, T't2 represents the historical pipe temperature at time t2, T't3 represents the historical pipe temperature, and T't4 represents the historical pipe temperature.

[0109] Furthermore, the computer equipment can calculate the average historical pipe temperature over each time period, obtaining E(T'1), E(T'2), E(T'3), and E(T'4). Here, E(T'1) represents the average temperature over the first time period, E(T'2) represents the average temperature over the second time period, E(T'3) represents the average temperature over the third time period, and E(T'4) represents the average temperature over the fourth time period. Further, the computer equipment can perform an average averaging calculation on the average values ​​over each time period to determine the typical temperature value E(T') for the heat treatment stage.

[0110] Furthermore, the computer equipment can analyze the rate of change of historical pipeline temperature over time to identify the peak and valley values ​​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 equipment can obtain three temperature characteristic values: typical temperature value E(T'), peak temperature T'MAX, and valley temperature T'MIN.

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

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

[0114] If a temperature feature value corresponds to a historical temperature event that is an abnormal event, the computer device can determine that there is an abnormal event corresponding to that temperature feature value. That is, the temperature event information of that temperature feature value is used to indicate that there is an abnormal event.

[0115] If a temperature feature value corresponds to a normal historical temperature event, or if there is no corresponding historical temperature event, the computer device can determine that the temperature feature value does not correspond to an abnormal event. That is, the temperature event information of the temperature feature value is used to indicate that there is no corresponding abnormal event.

[0116] In one embodiment, when the updated digital twin model is in the heat treatment stage of production, and the computer device monitors the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, this application embodiment provides an optional implementation method, including: S3033-S3034.

[0117] S3033, Determine the target temperature feature value from multiple temperature feature values ​​that matches the pipe temperature of the updated digital twin model.

[0118] S3034. Determine the monitoring results based on the temperature event information corresponding to the target temperature characteristic value.

[0119] For example, if the temperature event information corresponding to the target temperature feature value indicates that there is no corresponding abnormal temperature event, the computer equipment 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 anomaly event, the computer equipment determines that there is an abnormal strain in the oil and gas pipeline.

[0121] In one embodiment, when the computer device acquires the mechanical characteristic monitoring rules of the oil and gas pipeline in S301 above, this application embodiment provides an optional implementation method, including: S3017-S30111.

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

[0123] Optionally, historical strain events can be other oil and gas pipeline events such as pipeline rupture or thermomechanical fatigue that occurred at historical moments.

[0124] S3018. 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 in each historical time period.

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

[0126] For example, computer equipment can calculate the expected value of the average historical pipeline pressure over various historical time periods. This expected value of the average historical pipeline pressure over various historical time periods can be used to reflect the general level of pipeline pressure.

[0127] Computer equipment can calculate the expected value of the variance of historical pipeline pressure over various historical time periods. This expected value of the variance of historical pipeline pressure over various historical time periods can be used to reflect fluctuations in pipeline pressure.

[0128] Furthermore, the computer equipment can determine that the left endpoint of the normal pipeline pressure range is the difference between the expected average of historical pipeline pressure in each historical time period and the expected variance of historical pipeline pressure in each historical time period, and the right endpoint of the normal pipeline pressure range is the sum of the expected average of historical pipeline pressure in each historical time period and the expected variance of historical pipeline pressure in each historical time period. This indicates the extreme values ​​of pipeline pressure, reflecting the maximum bearing capacity and possible risk points of oil and gas pipelines.

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

[0130] S30111. Based on historical strain events within each historical time period, determine the strain event information corresponding to the strain change rate of multiple pipelines.

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

[0132] In one embodiment, when the updated digital twin model is in the physical property monitoring stage of production, and the computer equipment monitors the updated digital twin model to obtain the monitoring results of the oil and gas pipeline, this application embodiment provides an optional implementation method, including: S3035-S3036.

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

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

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

[0136] S3036. Based on the pipeline strain change rate of the updated digital twin model relative to the original digital twin model, and the strain event information corresponding to each of the multiple pipeline strain change rates, determine whether there is pipeline strain anomaly in the oil and gas pipeline.

[0137] For example, if the strain event information corresponding to the pipeline strain change rate in the updated digital twin model relative to the original digital twin model indicates that there is no corresponding abnormal strain event, then the computer equipment 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 in the updated digital twin model relative to the original digital twin model indicates the existence of a corresponding strain anomaly event, then the computer equipment determines that there is a pipeline strain anomaly in the oil and gas pipeline.

[0139] In the above embodiments of this application, real-time production data can be obtained by dividing the production stages of oil and gas pipelines. This 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 digital management and real-time dynamic management of oil and gas pipelines, providing a foundation for the digital management of the entire oil and gas pipeline production process. It also helps to realize online twins of business management and dynamic data interaction, thereby improving the management level.

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

[0141] Furthermore, by building an AI-powered intelligent agent to monitor real-time production data, manual intervention is reduced, improving production efficiency and management quality. The integration of intelligent operation and maintenance technologies can drive the digital transformation of the oil and gas industry and lay the technological foundation for realizing smart pipelines.

[0142] Furthermore, by combining AI agents with digital twin models of oil and gas pipelines to monitor the production process of oil and gas pipelines, the current status of oil and gas pipeline production, production operation evaluation reports, and operation and maintenance strategies are displayed more intuitively. This enables operation and maintenance personnel to interact with AI agents through a visual interface to receive alarms, analyze reports, and implement suggestions.

[0143] The foregoing primarily describes the solutions of the embodiments of this application from a methodological perspective. It is understood that, in order to achieve the above-described functions, the computer device includes at least one of the hardware structures and software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0144] This application embodiment can divide a computer device into functional units based on the above method examples. For example, each function can be divided into its own functional units, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0145] For example, such as Figure 4 The diagram shown is a structural schematic of an oil and gas pipeline monitoring device provided in an embodiment of this 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 production data of the oil and gas pipeline in the current monitoring period, 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 at different production stages. The processing unit 402 is used to update the digital twin model used to simulate the oil and gas pipeline based on the production data of the current monitoring period. The processing unit 402 is also used to monitor the updated digital twin model based on the target monitoring rule that corresponds to the production stage of the updated digital twin model among the multiple monitoring rules, to obtain the monitoring results of the oil and gas pipeline. The monitoring results are used to indicate whether there are any production anomalies in the oil and gas pipeline.

[0147] In some embodiments, 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 testing stage of the oil and gas pipeline. The property characteristic monitoring rules include multiple material property parameter ranges, with different ranges corresponding to different material property levels. The temperature characteristic monitoring rules include temperature event information corresponding to each of the multiple temperature characteristic values. The temperature event information is used to indicate whether the temperature characteristic value corresponds to a temperature anomaly event. The mechanical characteristic monitoring rules include the normal pressure range of the pipeline and strain event information corresponding to each of the multiple pipeline strain change rates. The strain event information is used to indicate whether the pipeline strain change rate corresponds to a strain anomaly event.

[0148] In some embodiments, the acquisition unit 401 is specifically used to: acquire the minimum material property parameters that meet the production standards for oil and gas pipelines, as well as the historical material property parameters of other oil and gas pipelines; determine the property parameter tolerance based on the historical material property parameters of other oil and gas pipelines; and determine multiple material property parameter ranges based on the minimum material property parameters and the property parameter tolerances.

[0149] In some embodiments, the processing unit 402 is specifically configured to: determine the material property level of the oil and gas pipeline in the current monitoring period by covering the material property parameter range corresponding to the material property level in the updated digital twin model with the material property parameter range corresponding to the multiple material property levels; and determine the monitoring result based on the material property level of the oil and gas pipeline in the current monitoring period.

[0150] In some embodiments, the acquisition unit 401 is specifically used to: acquire historical pipeline temperatures and historical temperature events at different historical moments during the heat treatment stage of other oil and gas pipelines; perform statistical processing on the historical pipeline temperatures at different moments to determine multiple temperature characteristic values; the multiple temperature characteristic values ​​include average values, peak values, and valley values; and 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 feature value from a plurality of temperature feature values ​​that matches the pipe temperature of the updated digital twin model; and determine a monitoring result based on temperature event information corresponding to the target temperature feature value.

[0152] In some embodiments, the acquisition unit 401 is specifically used to: acquire historical pipeline pressure, historical pipeline strain, and historical strain events at different historical moments during the physical property testing phase of other oil and gas pipelines; divide the historical pipeline pressure and historical pipeline strain at different historical moments to obtain historical pipeline pressure, historical pipeline strain, and historical strain events within each historical time period; determine the normal range of pipeline pressure based on the average and variance of historical pipeline pressure within each historical time period; statistically analyze the rate of change of historical pipeline strain within each historical time period to determine multiple pipeline strain change rates; and 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 anomaly in the oil and gas pipeline based on whether the pipeline pressure in the updated digital twin model is within the normal range of pipeline pressure; and determine whether there is an anomaly in the oil and gas pipeline based on the pipeline strain change rate of the updated digital twin model relative to the original digital twin model, and strain event information corresponding to each of the multiple pipeline strain change rates.

[0154] For a detailed description of the above-mentioned optional methods, please refer to the foregoing method embodiments, which will not be repeated here. Furthermore, the explanation of any of the computer devices provided above and the description of their beneficial effects can be found in the corresponding method embodiments described above, and will not be repeated here.

[0155] This application also provides a readable storage medium storing a computer program that, when run on a computer device, causes the computer device to perform any of the methods described above.

[0156] For explanations of the relevant content and descriptions of the beneficial effects of any of the above-mentioned readable storage media, please refer to the corresponding embodiments described above, which will not be repeated here.

[0157] This application also provides a computer program product containing instructions that, when executed on a computer device, cause the computer device to perform any of the methods described 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, all or part of the flow or function according to the embodiments of this application is generated. The computer device may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a readable storage medium or transmitted from one readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The readable storage medium may be any available medium accessible to the computer device or may include one or more data storage devices such as servers or data centers that can be integrated with the medium. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), etc.

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

[0159] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of monitoring an oil and gas pipeline, characterized by, The method comprises the following steps: acquiring 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; updating a digital twin model used to simulate the oil and gas pipeline based on the production data in the current monitoring period; monitoring the updated digital twin model based on a target monitoring rule corresponding to a production stage in which the updated digital twin model is located among the plurality of monitoring rules, 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; the plurality of monitoring rules comprise a property characteristic monitoring rule corresponding to a pre-production stage of the oil and gas pipeline, a temperature characteristic monitoring rule corresponding to a heat treatment stage of the oil and gas pipeline, and a mechanical characteristic monitoring rule corresponding to a physical property detection stage of the oil and gas pipeline; the property characteristic monitoring rule comprises a plurality of material property parameter intervals, different material property parameter intervals correspond to different material property grades; the temperature characteristic monitoring rule comprises a plurality of temperature characteristic values each corresponding to temperature event information; the temperature event information is used to indicate whether the temperature characteristic value corresponds to a temperature anomaly event; the mechanical characteristic monitoring rule comprises a pipeline pressure normal interval and a plurality of pipeline strain change rates each corresponding to strain event information; the strain event information is used to indicate whether the pipeline strain change rate corresponds to a strain anomaly event; acquiring the property characteristic monitoring rule of the oil and gas pipeline comprises: acquiring a minimum material property parameter meeting an oil and gas pipeline production standard and historical material property parameters of other oil and gas pipelines; determining a property parameter tolerance based on the historical material property parameters of the other oil and gas pipelines; determining the plurality of material property parameter intervals based on the minimum material property parameter and the property parameter tolerance; in a case where the production stage in which the updated digital twin model is located is the pre-production stage, the monitoring of the updated digital twin model to obtain the monitoring result of the oil and gas pipeline comprises: determining a material property grade of the oil and gas pipeline in the current monitoring period by covering a material property parameter of the updated digital twin model with a corresponding material property parameter interval in a plurality of material property grades; determining the monitoring result according to the material property grade of the oil and gas pipeline in the current monitoring period.

2. The method of claim 1, wherein, acquiring the temperature characteristic monitoring rule of the oil and gas pipeline comprises: acquiring historical pipeline temperatures and historical temperature events of other oil and gas pipelines at different historical times in a heat treatment stage; statistically processing the historical pipeline temperatures at the different historical times to determine a plurality of temperature characteristic values; the plurality of temperature characteristic values comprise an average value, a peak value and a valley value; determining temperature event information corresponding to each of the plurality of temperature characteristic values from the historical temperature events at the different historical times.

3. The method of claim 1, wherein, in a case where the production stage in which the updated digital twin model is located is the heat treatment stage, the monitoring of the updated digital twin model to obtain the monitoring result of the oil and gas pipeline comprises: determining, from the plurality of temperature characteristic values, a target temperature characteristic value matching a pipeline temperature of the updated digital twin model; determining the monitoring result according to temperature event information corresponding to the target temperature characteristic value.

4. The method of claim 1, wherein, obtaining a mechanical characteristic monitoring rule of the oil and gas pipeline, including: obtaining historical pipeline pressure, historical pipeline strain and historical strain event of other oil and gas pipelines at different historical moments in the physical property detection stage; dividing the historical pipeline pressure, the historical pipeline strain and the historical strain event at different historical moments to obtain the historical pipeline pressure, the historical pipeline strain and the historical strain event in each historical time period in the plurality of historical time periods; determining the pipeline pressure normal interval based on the average value and the variance of the historical pipeline pressure in each historical time period; statistically determining the plurality of pipeline strain change rates by statistically determining the change rate of the historical pipeline strain in each historical time period; determining strain event information corresponding to each of the plurality of pipeline strain change rates based on the historical strain event in each historical time period.

5. The method of claim 1, wherein, In a case where the production stage in which the updated digital twin model is located is the physical property monitoring stage, the monitoring of the updated digital twin model to obtain the monitoring result of the oil and gas pipeline includes: determining whether the oil and gas pipeline has pipeline pressure abnormality based on whether the pipeline pressure of the updated digital twin model is in the pipeline pressure normal interval; determining whether the oil and gas pipeline has pipeline strain abnormality 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 plurality of pipeline strain change rates.

6. A computer device, comprising: including: a processor connected with a memory, the memory being used to store computer execution instructions, the processor executing the computer execution instructions stored in the memory to enable the computer device to execute the oil and gas pipeline monitoring method according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, a computer readable storage medium for storing computer execution instructions, when the computer execution instructions run on a computer device, enabling the computer device to execute the oil and gas pipeline monitoring method according to any one of claims 1-5.

Images