Oil and gas station system corrosion risk identification method based on graph theory topological structure

Abstract

The invention belongs to the technical field of pipeline maintenance, and particularly discloses an oil and gas station system corrosion risk identification method based on a graph theory topological structure, and the method comprises the steps: collecting data, determining a corrosion risk node and a connection mechanism in an oil and gas station system from the three angles of physical equipment, personnel management operation and natural environment of the oil and gas station system, and carrying out the recognition of the corrosion risk of the oil and gas station system; the method comprises the following steps: establishing an oil and gas station system corrosion risk network, collecting oil and gas station system data, carrying out risk network structure attribute analysis based on the constructed oil and gas station system corrosion risk network, and obtaining an oil and gas station system corrosion risk identification result, so that risk factors and visualization of the oil and gas station system can be identified from a system level; and risk factor importance ranking can be quantitatively carried out to qualitatively describe the importance of risk nodes in the station and increase a community structure of risk propagation, so that support is provided for decision makers and technicians for risk management and control.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline maintenance, and particularly relates to a method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure. Background Art

[0002] The integrity assessment of pipelines and equipment is an important guarantee for their safe production. It is necessary and of great significance to regularly carry out the integrity assessment of pipelines and equipment. As the integrity assessment of pipelines and equipment involves many aspects, corrosion and its damage, as well as anti-corrosion measures, are also very important factors in the integrity assessment, and are valuable for the integrity assessment of pipelines and equipment. The anti-corrosion of key facilities in the station can be considered as the result of the combined action of a three-layer network of physical equipment, personnel operation activities and the natural environment.

[0003] As a multi-layer system of physics-personnel-environment, the risk analysis of the anti-corrosion process from the perspective of local sub-processes in the ground anti-corrosion of oil and gas stations will lead to inaccurate identification of risk factors. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure to solve the problem of inaccurate identification of corrosion risks in the oil and gas station system.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] In the first aspect, the present invention provides a method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure, including:

[0007] Collecting data, and determining corrosion risk nodes and connection mechanisms in the oil and gas station system;

[0008] Based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station system, combining with the data, constructing a corrosion risk network for the oil and gas station system;

[0009] Collecting data of the oil and gas station system, and obtaining a corrosion risk identification result of the oil and gas station system based on the constructed corrosion risk network of the oil and gas station system.

[0010] Further, the collected data includes: station risk assessment reports, equipment maintenance records, HSE management personnel experience, station climate, transportation media, equipment materials, personnel organizational structure, management systems and operating procedures.

[0011] Further, the risk nodes are components, units or factors that spread risks during the operation of the oil and gas station system.

[0012] Further, analyze the risk nodes that are prone to cause corrosion in each layer of the corrosion risk network of the oil and gas station field system, determine the connection relationships between the risk nodes, and update and summarize the content and influencing factors of the risk nodes.

[0013] Further, the corrosion risk network of the oil and gas station field system includes a physical equipment layer, a personnel management operation layer, and a natural environment layer.

[0014] Further, the risk nodes in the natural environment layer include weather changes, geographical environment, and population density;

[0015] The risk nodes in the physical equipment layer include the equipment in the process system, the equipment in the auxiliary generation system, and the equipment in the utility system;

[0016] The risk nodes in the personnel management operation layer include the operation behaviors of operators, the operation behaviors of managers, and the operation behaviors of dispatchers.

[0017] Further, the analysis of the risk network structure attributes includes: analysis of network node degree indicators, analysis of network graph distance indicators, analysis of network community indicators, and analysis of network clustering coefficient indicators.

[0018] In a second aspect, the present invention provides a corrosion risk identification device for an oil and gas station field system based on a graph theory topological structure, including:

[0019] An acquisition and risk node determination module, configured to acquire data, and determine the corrosion risk nodes and connection mechanisms in the oil and gas station field system;

[0020] A risk network construction module, configured to construct a corrosion risk network of the oil and gas station field system based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station field system and in combination with the data;

[0021] A risk identification result acquisition module, configured to acquire the data of the oil and gas station field system, and obtain a corrosion risk identification result of the oil and gas station field system based on the constructed corrosion risk network of the oil and gas station field system.

[0022] In a third aspect, the present invention provides an electronic device, including a processor and a memory, and the processor is configured to execute a computer program stored in the memory to implement a corrosion risk identification method for an oil and gas station field system based on a graph theory topological structure as described in any one of the above.

[0023] In a fourth aspect, the present invention provides a computer-readable storage medium, and the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, a corrosion risk identification method for an oil and gas station field system based on a graph theory topological structure as described in any one of the above is implemented.

[0024] The beneficial effects of the present invention are as follows:

[0025] The present invention collects data, starts from three aspects of the physical equipment of the oil and gas station system, personnel management operations, and natural environment, determines the corrosion risk nodes and connection mechanisms in the oil and gas station system, establishes a corrosion risk network for the oil and gas station system, collects data of the oil and gas station system, analyzes the risk network structure attributes based on the constructed corrosion risk network of the oil and gas station system, obtains the corrosion risk identification results of the oil and gas station system, can identify the risk factors and visualize them at the system level, and can quantitatively rank the importance of risk factors, so as to qualitatively describe the importance of risk nodes in the station and increase the community structure of risk propagation, providing support for decision-makers and technicians in risk control. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0027] Figure 1 is a schematic flow chart of a method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure of the present invention

[0028] Figure 2 is a schematic diagram of the topological structure of the corrosion risk network of the oil and gas station system of the present invention;

[0029] Figure 3 is a schematic diagram of the module of a device for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure of the present invention;

[0030] Figure 4 is a block diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments. It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other.

[0032] The following detailed descriptions are all exemplary descriptions, aiming to provide further detailed descriptions of the present invention. Unless otherwise specified, all technical terms adopted by the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention.

[0033] Embodiment 1

[0034] As Figure 1 shown, a method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure includes:

[0035] S1: Collect data, and determine the corrosion risk nodes and connection mechanisms in the oil and gas station system;

[0036] The collected data includes: station risk assessment reports, equipment maintenance records, the experience of HSE management personnel, station climate, transportation medium, equipment materials, personnel organizational structure, management systems, and operating procedures, etc.

[0037] Taking a natural gas treatment station as an example, during the anti-corrosion process from the raw gas of the gathering and transportation pipeline to the first external transportation station, risk node identification is carried out. The risk nodes involved include: external coating risks of pipeline facilities, internal and external anti-corrosion risks of pressure vessels, external cathodic protection risks, and corrosion inhibitor injection process risks in pipelines and other typical processes. It involves the synergistic effects of physical equipment, personnel operations, and the natural environment, and can be divided into 5 subsystems according to functional attributes.

[0038] Functional attributes refer to the functional roles in the oil and gas station. The 5 subsystems are the oil and gas pipeline transportation and ancillary facilities system, the pressure vessel storage system, the station staff system, the central control monitoring and engineer station system, and the station natural environment system;

[0039] The oil and gas pipeline transportation and ancillary facilities system includes: gathering and transportation pipelines, pipeline ancillary facilities such as valves, flanges, elbows, etc.;

[0040] The pressure vessel storage system includes: three-phase separators, sewage tanks, buffer tanks, cryogenic separators, and nitrogen generation stations;

[0041] The station staff system includes: production process technicians, contractors, safety management personnel, and business and technical personnel;

[0042] The central control monitoring and engineer station system includes: interlock instrument logic setting system, central control command communication system, transmission system, closed-circuit television monitoring system, transmission system, communication maintenance system, etc.;

[0043] The station natural environment system includes: natural weather conditions, such as wind, rain, snow, fog, and harsh weather conditions such as sand and dust.

[0044] The oil and gas pipeline transportation and ancillary facilities system and the pressure vessel storage system correspond to the physical equipment layer; the station staff system and the central control monitoring and engineer station system correspond to the personnel management and operation layer; the station natural environment system corresponds to the natural environment layer.

[0045] Components, units, or factors in the oil and gas station system that may spread risks during operation are called the risk nodes of the oil and gas station. The content mentioned in the above multiple subsystems are all risk nodes. The topological structure of the mutual influence of risk nodes is the corrosion risk network of the oil and gas station system, and the physical-personnel-environment risk network exists widely.

[0046] The risk nodes of the oil and gas station system change. Processes involving anti-corrosion risks, such as the peeling of the coating of physical equipment, coating blistering, improper installation of pipe segments due to pipeline corrosion, stratification of corrosion inhibitors, and uneven coating paint ratio, will all lead to equipment corrosion.

[0047] Analyze the risk nodes that are prone to cause corrosion in each layer of the corrosion risk network of the oil and gas station system, determine the connection relationships between the risk nodes, and update and summarize the content and influencing factors of the risk nodes.

[0048] S2: As Figure 2 shown, based on the identified risk nodes and combined with data, establish a corrosion risk network for the oil and gas station system;

[0049] Combined with on-site risk assessment reports, equipment maintenance records, the experience of HSE management personnel, station climate, transportation media, equipment materials, personnel organizational structure, management systems, and operating procedures and other data, extract risk nodes and establish a three-layer corrosion risk network topology structure for the oil and gas station system based on physics-personnel-environment.

[0050] The corrosion risk network of the oil and gas station system includes a physical equipment layer, a personnel management and operation layer, and a natural environment layer;

[0051] The risk nodes in the natural environment layer include weather changes, geographical environment, and population density;

[0052] The risk nodes in the physical equipment layer include equipment in the process system, equipment in the auxiliary generation system, and equipment in the utility system;

[0053] The risk nodes in the personnel management and operation layer include the operation behaviors of operators, the operation behaviors of management personnel, and the operation behaviors of dispatching personnel.

[0054] S3: Collect data on the oil and gas station system, and conduct an analysis of the risk network structure attributes based on the constructed corrosion risk network of the oil and gas station system to obtain the corrosion risk identification results of the oil and gas station system;

[0055] Analysis of the network node degree index; the node degree reflects the number of neighborhood nodes of the global node. In the corrosion risk network of the oil and gas station system, the magnitude of the node degree value can measure the importance and influence range of the node. The larger the node degree, the stronger the ability of the risk node to affect the neighborhood nodes in the corrosion risk network topology structure of the oil and gas station system, and the more critical it is in network propagation, indicating that this risk node is a key risk factor.

[0056] Analysis of network graph distance metrics: The network graph distance metrics include Betweenness Centrality, Closeness-Centrality, Harmonic Closeness Centrality, and Eccentricity;

[0057] When the network graph distance metric is Betweenness Centrality, the object of description is the frequency of risk nodes appearing on the shortest paths in the network and the network function effect of risk nodes;

[0058] When the network graph distance metrics are Closeness-Centrality and Harmonic Closeness Centrality, the object of description is the reciprocal of the shortest average distance from a given starting risk node to all other risk nodes, and the network central position of risk nodes;

[0059] When the network graph distance metric is Eccentricity, the object of description is the distance from a given starting risk node to the farthest risk node;

[0060] The larger the values of the above three types of network graph distance metrics, the greater the possibility and tightness of connections between risk nodes, indicating that the risk node has a close relationship with its neighborhood nodes and is also a key risk factor in the risk network.

[0061] Analysis of network community metrics. The smallest unit for risk propagation in the network is the network community structure. Network communities have similar functions, risk nodes within the community are closely connected, risk nodes outside the community are sparsely connected, and there are bridging risk nodes between communities. In the corrosion risk network of oil and gas station systems, each subsystem forms a community on its own.

[0062] The network community structure specifically refers to the above-mentioned five subsystems. Risk nodes within each subsystem are closely connected, and risk nodes outside the system are sparsely connected.

[0063] Analysis of network clustering coefficient metrics. The degree of aggregation between risk nodes is related to the network clustering coefficient. The larger the network clustering coefficient, the greater the possibility of risk node aggregation, that is, the greater the possibility of connections between nodes.

[0064] The method of complex networks used in the present invention has advantages in risk factor analysis compared with traditional safety assessment methods such as fault tree, HAZOP analysis, and STAMP. The advantages are that the identification of system-level risks is more comprehensive, and the risk analysis method of complex networks penetrates into each risk node of the system. The proposed method plays a role in terms of risk identification object, ranking of the importance of operation risk factors, and risk factor identification results. It identifies the location of corrosion risks in oil and gas stations at the system level based on qualitative and quantitative analysis, and improves the risk factor identification effect from the perspective of processes.

[0065] Embodiment 2

[0066] As Figure 3 shown, based on the same inventive concept as the above embodiment, the present invention further provides a corrosion risk identification device for an oil and gas station system based on a graph theory topological structure, including:

[0067] An acquisition and risk node determination module, configured to acquire data, and determine corrosion risk nodes and connection mechanisms in the oil and gas station system;

[0068] A risk network construction module, configured to construct a corrosion risk network for the oil and gas station system based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station system, in combination with the data;

[0069] A risk identification result acquisition module, configured to acquire oil and gas station system data, and obtain a corrosion risk identification result for the oil and gas station system based on the constructed corrosion risk network for the oil and gas station system.

[0070] Embodiment 3

[0071] As Figure 4 shown, the present invention further provides an electronic device 100 for implementing a corrosion risk identification method for an oil and gas station system based on a graph theory topological structure;

[0072] The electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on at least one processor 102, and at least one communication bus 104.

[0073] The memory 101 can be used to store the computer program 103. The processor 102 realizes the steps of the corrosion risk identification method for an oil and gas station system based on a graph theory topological structure in Embodiment 1 by running or executing the computer program stored in the memory 101, and by calling the data stored in the memory 101.

[0074] The memory 101 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the electronic device 100 (such as audio data, etc.). In addition, the memory 101 can include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0075] At least one processor 102 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or the processor 102 may also be any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and connects various parts of the entire electronic device 100 using various interfaces and lines.

[0076] The memory 101 in the electronic device 100 stores multiple instructions to implement a corrosion risk identification method for an oil and gas station system based on a graph theory topology. The processor 102 can execute the multiple instructions to achieve:

[0077] Collect data, and determine corrosion risk nodes and connection mechanisms in the oil and gas station system;

[0078] Based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station system, combined with the data, construct a corrosion risk network for the oil and gas station system;

[0079] Collect data of the oil and gas station system, and based on the constructed corrosion risk network of the oil and gas station system, obtain the corrosion risk identification result of the oil and gas station system.

[0080] Embodiment 4

[0081] If the modules / units integrated in the electronic device 100 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, and Read-Only Memory (ROM).

[0082] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0083] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0084] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0085] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, so that the instructions executed on the computer or other programmable devices provide steps for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0086] In the description of this specification, the descriptions referring to terms such as "an embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific implementation manners of the present invention, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure, characterized in that, Including: Collect data, and determine the corrosion risk nodes and connection mechanisms in the oil and gas station system; Based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station system, and combined with the data, construct the corrosion risk network of the oil and gas station system; Collect the data of the oil and gas station system, and based on the constructed corrosion risk network of the oil and gas station system, obtain the corrosion risk identification result of the oil and gas station system.

2. The corrosion risk identification method for an oil and gas station system based on a graph theory topological structure according to claim 1, wherein The collected data includes: station risk assessment reports, equipment maintenance records, the experience of HSE management personnel, station climate, transportation medium, equipment materials, personnel organizational structure, management systems, and operating procedures.

3. A corrosion risk identification method for an oil and gas station system based on a graph theory topological structure according to claim 1, characterized in that The risk nodes are components, units, or factors that spread risks during the operation of the oil and gas station system.

4. A method for identifying corrosion risks in an oil and gas station system based on a graph theory topological structure according to claim 1, characterized in that, Analyze the risk nodes that are prone to cause corrosion in each layer of the corrosion risk network of the oil and gas station system, determine the connection relationships between the risk nodes, and update and summarize the content and influencing factors of the risk nodes.

5. The corrosion risk identification method for an oil and gas station system based on a graph theory topological structure according to claim 4, wherein The corrosion risk network of the oil and gas station system includes a physical equipment layer, a personnel management and operation layer, and a natural environment layer.

6. The corrosion risk identification method for an oil and gas station system based on a graph theory topological structure according to claim 5, wherein The risk nodes in the natural environment layer include weather changes, geographical environment, and population density; The risk nodes in the physical equipment layer include the equipment in the process system, the equipment in the auxiliary generation system, and the equipment in the utility system; The risk nodes in the personnel management and operation layer include the operation behaviors of operators, the operation behaviors of management personnel, and the operation behaviors of dispatching personnel.

7. A corrosion risk identification method for an oil and gas station system based on a graph theory topological structure according to claim 1, characterized in that The analysis of the risk network structure attributes includes: analysis of network node degree indicators, analysis of network diagram distance indicators, analysis of network community indicators, and analysis of network clustering coefficient indicators.

8. An oil and gas station system corrosion risk identification device based on a graph theory topological structure, characterized in that, Including: A data collection and risk node determination module, which is used to collect data and determine the corrosion risk nodes and connection mechanisms in the oil and gas station system; A risk network construction module, which is used to construct the corrosion risk network of the oil and gas station system based on the determined corrosion risk nodes and connection mechanisms in the oil and gas station system and combined with the data; A risk identification result acquisition module, which is used to collect the data of the oil and gas station system and obtain the corrosion risk identification result of the oil and gas station system based on the constructed corrosion risk network of the oil and gas station system.

9. An electronic device, characterized in that, Including a processor and a memory, the processor is used to execute the computer program stored in the memory to implement a method for identifying the corrosion risk of an oil and gas station system based on the graph theory topological structure as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, it implements a method for identifying the corrosion risk of an oil and gas station system based on the graph theory topological structure as described in any one of claims 1 to 7.

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