Oil and gas field-oriented data processing method, device, equipment and storage medium

Abstract

This application provides a data processing method, apparatus, equipment, and storage medium for oil and gas field sites, relating to the field of oil and gas exploration technology. The method includes: acquiring target oil and gas data to be processed sent from the target oil and gas field, and edge nodes deployed at the target oil and gas field. Then, it determines whether each target oil and gas data meets preset processing requirements and determines the cloud computing platform to interact with the edge nodes. Further, target oil and gas data that does not meet the preset processing requirements is sent to the cloud computing platform for processing, while target oil and gas data that meets the preset processing requirements is sent to the edge nodes for processing. The method of this application improves the data processing efficiency of target oil and gas data, as well as the resource utilization rate of the cloud computing platform and edge nodes.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration technology, and in particular to a data processing method, apparatus, equipment and storage medium for oil and gas field applications. Background Technology

[0002] Oil and gas sites are typically equipped with various sensors and devices that collect a large amount of oil and gas data to reflect the environmental conditions at the site. This collected data needs to be analyzed and interpreted quickly to address dynamically changing environmental and operational conditions.

[0003] However, most oil and gas companies still rely on traditional cloud-based data processing models, especially when complex data analysis, storage, and historical data mining are required. The cloud platform receives data processing requests from the target oil and gas site, calls appropriate application software integration services to process the data based on the requests, and displays the processing results to on-site personnel.

[0004] Therefore, existing technologies suffer from low data processing efficiency and low resource utilization of cloud computing platforms. Summary of the Invention

[0005] This application provides a data processing method, apparatus, equipment, and storage medium for oil and gas field applications, in order to solve the technical problems of low data processing efficiency and low resource utilization of cloud computing platforms in the prior art.

[0006] In a first aspect, this application provides a data processing method for oil and gas field applications, including:

[0007] Acquire the target oil and gas data to be processed sent from the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site;

[0008] Determine whether each target oil and gas data meets the preset processing requirements, and determine the cloud computing platform that interacts with the edge node;

[0009] Target oil and gas data that does not meet the preset processing requirements are sent to the cloud computing platform for processing, and target oil and gas data that meets the preset processing requirements are sent to the edge node for processing.

[0010] In one possible design, sending target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and sending target oil and gas data that does meet the preset processing requirements to the edge node for processing, includes:

[0011] The target oil and gas data that does not meet the preset processing requirements is identified as the first oil and gas data, and the first oil and gas data is sent to the cloud computing platform for processing;

[0012] The target oil and gas data that meets the preset processing requirements is identified as the second oil and gas data. The application stored in the cloud computing platform for processing the second oil and gas data is identified, and the application is migrated to the edge node. Each edge node includes at least one of the applications.

[0013] Based on the application, the target edge node for processing each second oil and gas data is determined from the edge nodes, and each second oil and gas data is sent to the corresponding target edge node for processing.

[0014] In one possible design, the application for processing the second oil and gas data includes a container application that supports containerization technology, and a process application that does not support the containerization technology.

[0015] The step of determining the application stored in the cloud computing platform for processing the second oil and gas data and migrating the application to the edge node includes:

[0016] Identify the image files and application installation packages stored in the cloud computing platform; wherein, the image file represents the data set required to run the container application, and the application installation package represents the data set required to run the process application;

[0017] The image file or the application installation package is sent to the edge node to run the corresponding container application or process application.

[0018] In one possible design, sending the image file or the application installation package to the edge node to run the corresponding container application or process application includes:

[0019] Based on the configuration information of each edge node, determine whether each edge node supports the containerization technology;

[0020] Pull the image file to an edge node that supports the containerization technology, and start the image file to run the container application;

[0021] The application installation package is downloaded to an edge node that does not support the containerization technology, and the application installation package is executed to run the process application.

[0022] In one possible design, the method further includes:

[0023] Monitor the image files and application installation packages stored in the cloud computing platform;

[0024] When an update to the image file is detected, the first edge node where the container application corresponding to the updated image file is located is queried.

[0025] The updated image file is pulled to the first edge node to update the corresponding container application.

[0026] In one possible design, when an update to the application installation package is detected, the method further includes:

[0027] Query the second edge node where the process application corresponding to the updated application installation package resides;

[0028] The updated application installation package is downloaded to the second edge node to update the corresponding process application.

[0029] In one possible design, the method further includes:

[0030] Monitor the update process of the container application and / or the process application;

[0031] If an update failure is detected, the corresponding update failure information is sent to the target personnel at the target oil and gas site, and the failure handling plan based on the update failure information is obtained from the target personnel.

[0032] Secondly, this application provides a data processing device for oil and gas sites, comprising:

[0033] The acquisition module is used to acquire the target oil and gas data to be processed sent by the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site.

[0034] The determination module is used to determine whether each target oil and gas data meets the preset processing requirements and to determine the cloud computing platform that interacts with the edge node;

[0035] The processing module is used to send target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and to send target oil and gas data that meets the preset processing requirements to the edge node for processing.

[0036] In one possible design, the processing module further includes: a sending module and a migration module.

[0037] The determining module is further configured to determine target oil and gas data that does not meet the preset processing requirements as first oil and gas data;

[0038] The sending module is used to send the first oil and gas data to the cloud computing platform for processing;

[0039] The determining module is further configured to determine the target oil and gas data that meets the preset processing requirements as the second oil and gas data, and to determine the application program stored in the cloud computing platform for processing the second oil and gas data.

[0040] The migration module is used to migrate the application to the edge node; wherein each edge node includes at least one of the applications;

[0041] The determining module is further configured to determine, based on the application, a target edge node from the edge nodes for processing each second oil and gas data;

[0042] The sending module is also used to send each of the second oil and gas data to the corresponding target edge node for processing.

[0043] In one possible design, the application for processing the second oil and gas data includes a container application that supports containerization technology, and a process application that does not support the containerization technology.

[0044] The determining module is further configured to determine the image file and application installation package stored in the cloud computing platform; wherein, the image file represents the data set required to run the container application, and the application installation package represents the data set required to run the process application;

[0045] The sending module is further configured to send the image file or the application installation package to the edge node to run the corresponding container application or the process application.

[0046] In one possible design, the sending module further includes: a pull module, a startup module, a download module, and an execution module.

[0047] The determining module is also used to determine whether each edge node supports the containerization technology based on the configuration information of each edge node;

[0048] The pull module is used to pull the image file to an edge node that supports the containerization technology;

[0049] The startup module is used to start the image file to run the container application;

[0050] The download module is used to download the application installation package to an edge node that does not support the containerization technology;

[0051] The execution module is used to execute the application installation package to run the process application.

[0052] In one possible design, the processing module further includes: a monitoring module and a query module.

[0053] The monitoring module is used to monitor the image file and the application installation package stored in the cloud computing platform;

[0054] The query module is used to query the first edge node where the container application corresponding to the updated image file is located when an update is detected in the image file.

[0055] The pull module is also used to pull the updated image file to the first edge node to update the corresponding container application.

[0056] In one possible design, the query module is further configured to query the second edge node where the process application corresponding to the updated application installation package is located when an update to the application installation package is detected.

[0057] The download module is also used to download the updated application installation package to the second edge node to update the corresponding process application.

[0058] In one possible design, the monitoring module is also used to monitor the update process of the container application and / or the process application.

[0059] The sending module is also used to send corresponding update failure information to the target personnel at the target oil and gas site if an update failure is detected.

[0060] The acquisition module is also used to acquire the failure handling plan reported by the target staff based on the update failure information.

[0061] Thirdly, embodiments of this application provide an electronic device, including: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, causing the at least one processor to perform the method described in the first aspect above and various possible designs.

[0062] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the methods described in the first aspect above and various possible designs.

[0063] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect and various possible designs of the first aspect.

[0064] This application provides a data processing method, apparatus, equipment, and storage medium for oil and gas sites. It acquires target oil and gas data to be processed from the target oil and gas site, as well as edge nodes deployed at the target oil and gas site. Then, it determines whether each target oil and gas data meets preset processing requirements and identifies the cloud computing platform that interacts with the edge nodes. Further, target oil and gas data that does not meet the preset processing requirements is sent to the cloud computing platform for processing, while target oil and gas data that meets the preset processing requirements is sent to the edge nodes for processing. Thus, cloud computing and edge computing are closely integrated in the process of processing target oil and gas data from the target oil and gas site. By rationally distributing target oil and gas data between the cloud computing platform and edge nodes, cloud computing is extended to the edge nodes, achieving cloud computing decentralization and bringing efficient resource utilization. Furthermore, applying edge computing to the oil and gas site provides proximity computing and network coverage, effectively improving response speed and thus increasing the processing efficiency of target oil and gas data. Attached Figure Description

[0065] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0066] Figure 1 This is an application scenario diagram of the data processing method for oil and gas field applicable to the embodiments of this application;

[0067] Figure 2 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 1 ;

[0068] Figure 3 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 2 ;

[0069] Figure 4 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 3 ;

[0070] Figure 5 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 4 ;

[0071] Figure 6 A schematic diagram of the structure of a data processing device for oil and gas field provided in an embodiment of this application;

[0072] Figure 7 This is a hardware structure diagram of the electronic device provided in the embodiments of this application.

[0073] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0074] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0075] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented, for example, in orders other than those illustrated or described herein.

[0076] In this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in 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.

[0077] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0078] The oil and gas industry typically needs to process large amounts of complex oil and gas data, including geological data, production data, and equipment monitoring data. This data requires in-depth analysis and historical data mining to optimize production, predict equipment failures, and improve safety. Due to the complexity and typically large volume of this oil and gas data, it has traditionally relied on the powerful computing capabilities of cloud computing platforms to handle this task.

[0079] It should be understood that cloud computing platforms typically have powerful computing and storage capabilities, making them suitable for handling large-scale data analysis, complex computing tasks, and the storage and mining of historical data. They are capable of centrally managing and processing large numbers of data requests.

[0080] In traditional cloud computing models, all data processing tasks are centralized on a cloud computing platform. Data is collected from other sources (such as sensors and equipment at oil and gas sites) and then transmitted over a network to a remote cloud computing platform. The cloud computing platform is responsible for performing complex data analysis, processing, and storage tasks. After processing, the results are transmitted back to personnel at the oil and gas site to facilitate decision-making and operations.

[0081] However, transmitting large amounts of data to cloud computing platforms for processing can lead to latency, especially under poor network conditions or with massive data volumes. This latency can impact decision-making and response. Furthermore, since all data must be transmitted to the cloud over the network, any network issues will directly affect the speed and efficiency of data processing.

[0082] In addition, all data processing tasks are centralized on the cloud computing platform, meaning that regardless of the importance or urgency of the data, all data is transmitted to the cloud for processing. This centralized processing may lead to overuse or uneven utilization of resources in the cloud computing platform; for example, the cloud computing platform may be overloaded at some times and idle at other times.

[0083] To address the aforementioned technical problems, the inventors, while researching the data processing process of cloud computing platforms, discovered that if all data processing tasks were sent to the cloud computing platform, not only might network issues affect data processing efficiency, but simple tasks might also consume the cloud computing platform's resources, while complex tasks would not be processed in a timely manner. Based on this, considering that not all data processing tasks require the high-performance computing capabilities of the cloud computing platform, the inventors adopted a collaborative approach between the cloud computing platform and edge nodes, processing some simple, real-time-critical data processing tasks at the edge nodes. This approach reduces the amount of data that needs to be transmitted to the cloud computing platform, rationally allocates data processing tasks, fully utilizes the resources of both the cloud computing platform and edge nodes, and improves the overall system's data processing efficiency.

[0084] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0085] In one possible implementation, Figure 1 This diagram illustrates an application scenario for the data processing method for oil and gas field operations, applicable to embodiments of this application. For example... Figure 1 As shown, a cloud-edge collaborative environment is formed based on a cloud computing platform and edge nodes deployed at the target oil and gas site. The edge nodes can be deployed on industrial control computers, industrial gateways, or other devices at the target oil and gas site; no specific restrictions are imposed here.

[0086] Specifically, a large number of applications are managed and scheduled by deploying Kubernetes clusters in a cloud computing platform. However, since Kubernetes clusters do not directly support the scheduling of edge nodes, the distributed edge computing platform KubeEdge is used to extend the capabilities of Kubernetes clusters to edge nodes, allowing users to run and manage applications on edge nodes. This, in turn, builds a scheduling system by integrating the cloud computing platform and edge nodes through the Kubernetes cluster.

[0087] It should be understood that KubeEdge provides the fundamental guarantee for the collaborative working mechanism between the cloud computing platform and edge nodes. Specifically, secure communication between the cloud computing platform and edge nodes is achieved by deploying KubeEdge's cloud core on the cloud computing platform and KubeEdge's edge core on the edge nodes.

[0088] Cloud Core interacts with the Kubernetes cluster via its Application Programming Interface (API) to manage and coordinate edge nodes and their applications. Edge Core manages and runs applications on the edge nodes and communicates with Cloud Core to receive instructions and synchronize status. Specifically, Cloud Core receives scheduling instructions from the Kubernetes cluster and forwards them to the corresponding Edge Cores on the edge nodes, enabling the Kubernetes cluster to indirectly manage applications on the edge nodes through Cloud Core.

[0089] It should be noted that Edge Core relies on containerization technology to manage and run applications. Therefore, Edge Core can only be deployed on edge nodes that support containerization technology, and only containerized applications that support containerization technology can run on edge nodes that support containerization technology.

[0090] Considering that some edge nodes have low-configuration devices that cannot install container runtime environments such as Docker that support containerization technologies, lightweight edge controllers can be deployed to manage and run applications. Lightweight edge controllers consume fewer resources, do not rely on containerization technology, and are compatible with most operating systems. It should be understood that on edge nodes that do not support containerization technology, process applications that also do not support containerization technology run.

[0091] Interpretive configuration files related to container applications are stored in the image repository server of the cloud computing platform, while configuration files related to process applications are stored in the file server of the cloud computing platform.

[0092] In addition, data related to user login and permissions is stored in the cloud computing platform's data cache server, while business data is stored in the database server. The data server is also configured with a primary server and a backup server. The primary server handles all requests and tasks, while the backup server remains on standby, monitoring the primary server's operation. If the primary server fails or requires maintenance, the backup server will automatically or manually take over the primary server's work to ensure the continuity and stability of the cloud computing platform.

[0093] Furthermore, the cloud computing platform also deploys a cloud-edge collaborative control service, which, along with the Kubernetes cluster and CLUD Core, resides on the platform's console server. This cloud-edge collaborative control service not only assists the Kubernetes cluster and CLUD Core in managing and coordinating edge nodes and their applications, but also provides functions such as user authentication and resource monitoring.

[0094] based on Figure 1 As shown in the application scenario, this application embodiment also provides a data processing method for oil and gas field. Figure 2 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 1 ,like Figure 2 As shown, this data processing method for oil and gas sites includes:

[0095] S201. Obtain the target oil and gas data to be processed sent by the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site.

[0096] Understandably, directly deploying edge nodes to target oil and gas sites could lead to security vulnerabilities. Therefore, edge nodes need to be registered and configured before deployment. Registration ensures that edge nodes are correctly identified and integrated into the cloud-edge collaborative environment, guaranteeing effective communication between the edge nodes and the cloud computing platform.

[0097] For example, in combination Figure 1 In the application scenario shown, after logging into the cloud-edge collaborative control service, users can register edge nodes using the registration and management function provided by the service. Specifically, Figure 3 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 2 ,like Figure 3 As shown, the registration process for edge nodes includes the following steps:

[0098] Step a1: The user logs in to the cloud-edge collaborative control service;

[0099] Step a2: The user clicks "Register Edge Node" through the cloud-edge collaborative control service;

[0100] Step a3: The user enters the edge node name and selects the edge node type through the cloud-edge collaborative control service, and clicks Next.

[0101] Among them, the edge node type is either supporting containerization technology or not supporting containerization technology.

[0102] Step a4: The cloud-edge collaborative control service saves the edge node information filled in by the user and generates the configuration file package for the edge node, as well as the component installation package for Edge Core or the installation package for the lightweight edge controller.

[0103] For explanation purposes, if the edge node supports containerization technology, an Edge Core component installation package will be generated; if the edge node does not support containerization technology, a lightweight edge controller installation package will be generated.

[0104] Step a5: The user downloads the configuration file package and the Edge Core component installation package or the lightweight edge controller installation package from the cloud-edge collaborative control service and sends them to the edge node;

[0105] Step a6: The staff responsible for the edge nodes begin preparing the basic environment, installing the basic environment according to the installation manual requirements, or troubleshooting any problems encountered during installation.

[0106] Step a7: The edge node decompresses and installs the copied configuration file package, as well as the Edge Core component installation package or the lightweight edge controller installation package;

[0107] If the installation is successful, proceed to step a8; if the installation fails, return to step a6.

[0108] Step a8: Run Edge Core or a lightweight edge controller in the edge node and establish a connection with the cloud computing platform;

[0109] Step a9: The cloud-edge collaborative control service communicates with the edge nodes and monitors the edge nodes;

[0110] Step a10: Users view monitoring information through the cloud-edge collaborative control service.

[0111] In terms of interpretation, the cloud-edge collaborative control service continuously monitors the operation of edge nodes and their applications, allowing users to intuitively see all managed edge nodes, understand their status in a timely manner, and take appropriate actions. For example, users can easily filter edge nodes using query conditions such as status and time.

[0112] Specifically, users can view the registration status of edge nodes and monitor their operational status through the collaborative control service, such as server memory, disk utilization, CPU, and operating system name within the edge nodes. Users can also delete, upgrade, enable, and disable edge nodes through the collaborative control service, and further deploy, upgrade, start, stop, and delete applications within the edge nodes.

[0113] S202. Determine whether each target oil and gas data meets the preset processing requirements, and determine the cloud computing platform that interacts with the edge nodes.

[0114] The preset processing requirements can be data complexity requirements, real-time requirements, computing resource requirements, security and privacy requirements, network bandwidth and latency requirements, etc., without specific restrictions.

[0115] S203. Send target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and send target oil and gas data that meets the preset processing requirements to the edge node for processing.

[0116] Specifically, target oil and gas data that does not meet the preset processing requirements are identified as first oil and gas data and sent to the cloud computing platform for processing; target oil and gas data that meets the preset processing requirements are identified as second oil and gas data and sent to the edge node for processing.

[0117] For example, the first type of oil and gas data can be data from complex tasks, data with low real-time requirements, data from resource-intensive tasks, or data that does not contain sensitive information. The second type of oil and gas data can be data from simple filtering or aggregation tasks, data that requires real-time processing, data containing sensitive information, data with limited network bandwidth, or data with high latency.

[0118] Understandably, cloud computing platforms typically process data through applications. With the addition of edge nodes, some applications from the cloud computing platform need to be migrated to these edge nodes to handle data processing. Specifically, the applications stored in the cloud computing platform for processing the second oil and gas data are identified, and these applications are migrated to the edge nodes, where each edge node includes at least one application. Based on the applications, target edge nodes are determined from among the edge nodes to process each piece of the second oil and gas data, and each piece of the second oil and gas data is sent to the corresponding target edge node for processing.

[0119] Interpretive, each edge node has at least one application for processing secondary oil and gas data, and these applications are responsible for processing specific types of secondary oil and gas data. Faced with multiple secondary oil and gas data, the application may analyze the characteristics and processing requirements of each secondary oil and gas data, and then select the most suitable edge node (target edge node) to process the corresponding secondary oil and gas data.

[0120] Since the applications processing the second oil and gas data include containerized applications that support containerization and process applications that do not, and edge nodes also include both containerized and non-containerized types, the processing of the second oil and gas data is completed by running containerized applications on edge nodes that support containerization and process applications on edge nodes that do not support containerization.

[0121] It's important to note that cloud computing platforms do not store running instances of container applications / process applications themselves, but rather image files of container applications or application installation packages for process applications. Image files represent the data set required to run a container application, while application installation packages represent the data set required to run a process application.

[0122] Therefore, it is necessary to identify the image files and application installation packages stored in the cloud computing platform, and send the image files or application installation packages to the edge nodes to run the corresponding container applications or process applications.

[0123] Specifically, based on the configuration information of each edge node, it is determined whether each edge node supports containerization technology. The image file is pulled to an edge node that supports containerization technology and started to run the container application. The application installation package is downloaded to an edge node that does not support containerization technology and executed to run the in-process application.

[0124] In one possible implementation, combining Figure 1 The application scenarios shown are as follows: Figure 4 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 3 .like Figure 4 As shown, the deployment process for a container application includes the following steps:

[0125] Step b1: The user selects an edge node that supports containerization technology through the cloud-edge collaborative control service and clicks "Deploy Application".

[0126] For example, users can input the name and description of a specified container application through the cloud-edge collaborative control service, and select edge nodes that support containerization technology. The cloud-edge collaborative control service will automatically filter out eligible edge nodes, such as those that are running and have already deployed Edge Core and support containerization technology. Users then select the image file and version to upload, configure the required resources (CPU and memory resources), and can configure port mappings.

[0127] Step b2: The cloud-edge collaborative control service saves the deployment information of the container application entered by the user and calls the edge node interface;

[0128] Step b3: Receive deployment information for the container application via Edge Core and begin deploying the container application;

[0129] Step b4: Edge Core pulls the corresponding image files from the image repository server.

[0130] The image repository server interacts with Edge Core via API, which helps to efficiently manage and distribute image files between the cloud computing platform and edge nodes.

[0131] Step b5: Edge Core installs and starts the container application based on the container application's deployment information, and monitors and records the container application's running status.

[0132] If deployment fails, proceed to step b6; if deployment succeeds, proceed to step b7.

[0133] Step b6: Obtain the reason for deployment failure through Edge Core and report it to the cloud-edge collaborative control service, then proceed to step b7;

[0134] Step b7: The cloud-edge collaborative control service obtains the deployment status of the container application.

[0135] Step b8: Users can view the deployment status of container applications through the cloud-edge collaborative control service;

[0136] Step b9: In case of deployment failure, users can check the reason for the deployment failure and handle it through the cloud-edge collaborative control service.

[0137] Understandably, there are multiple edge nodes capable of running container applications, and the cloud-edge collaborative control service can monitor the container applications on each edge node. The application details in the cloud-edge collaborative control service show the status of the container applications on each edge node, and the corresponding CPU and memory monitoring can also be viewed by filtering by edge node. In this way, users can take appropriate actions based on the different information from each edge node.

[0138] In addition to monitoring container applications, users can also start, stop, upgrade, and delete related container applications. For user convenience, users can also view all container applications and instances under each edge node in the application details of the cloud-edge collaborative control service, including instance statistics and specific status. Monitoring and managing process applications is similar in principle to container applications and will not be elaborated upon further.

[0139] For example, the cloud-edge collaborative control service continuously acquires monitoring logs from container applications, such as CPU and memory usage. These logs are stored on the cloud computing platform for subsequent analysis. If a container application fails to deploy or run, the cloud-edge collaborative control service will display the specific reason for the failure.

[0140] It should be noted that the deployment prerequisites for the above container application are: (1) the edge node has been registered and the edge node connection is normal; (2) the image file has been uploaded to the image repository server.

[0141] Explain that the cloud computing platform adopts a multi-tenant design and provides image file management functionality. Users can manage image files, performing operations such as uploading, querying, deleting, copying, downloading, and modifying them. In addition to uploading packaged image files to the image repository server within the cloud computing platform, users can also use public images within the image repository server, such as database, cache, and proxy images.

[0142] In another possible implementation, combining Figure 1The application scenarios shown are as follows: Figure 5 A flowchart illustrating the data processing method for oil and gas field applications provided in this application. Figure 4 .like Figure 5 As shown, the deployment process of a process application includes the following steps:

[0143] Step c1: The user selects an edge node that does not support containerization technology through the cloud-edge collaborative control service and clicks "Deploy Application";

[0144] Step c2: The cloud-edge collaborative control service saves the deployment information of the process application entered by the user and calls the edge node interface;

[0145] Step c3: Receive the deployment information of the process application through the lightweight edge controller and begin deploying the process application;

[0146] Step c4: The lightweight edge controller downloads the corresponding application installation package from the file server.

[0147] The file server interacts with the lightweight edge controller via an API.

[0148] Step c5: The lightweight edge controller installs and starts the process application based on the process application's deployment information, and monitors and records the process application's running status.

[0149] If deployment fails, proceed to step c6; if deployment succeeds, proceed to step c7.

[0150] Step c6: Obtain the reason for deployment failure through the lightweight edge controller and report it to the cloud-edge collaborative control service, then proceed to step c7;

[0151] Step c7: The cloud-edge collaborative control service obtains the deployment status of the process application;

[0152] Step c8: Users can view the deployment status of process applications through the cloud-edge collaborative control service;

[0153] Step c9: If deployment fails, users can check the reason for the failure and take action through the cloud-edge collaborative control service.

[0154] It should be noted that the deployment of the above process application is subject to the following conditions: (1) the edge node has been registered and the edge node connection is normal; (2) the application installation package has been uploaded to the file server.

[0155] Therefore, users can start, stop, upgrade, and delete container applications / process applications through the cloud-edge collaborative control service. In one possible implementation, after a user uploads a new version of the image file corresponding to the container application, or a new version of the application installation package corresponding to the process application, the edge node will reprocess it according to the latest version configuration. Simultaneously, the cloud computing platform will save the new version information of the image file / application installation package and continuously monitor the update status of the container applications / process applications on the edge nodes. If the update fails, the system will attempt to update again, and the user can see the specific reason for the update failure and take appropriate action.

[0156] Understandably, continuous monitoring of the update process is necessary to ensure its smooth operation. If issues or performance degradation are detected in the new version, the update strategy should be adjusted promptly, such as modifying configurations or ports, pausing the upgrade, or rolling back to the old version. Throughout the update process, the availability and stability of the container application / process application should be the primary objective.

[0157] In one possible implementation, image files and application installation packages stored in the cloud computing platform are monitored. When an update to an image file is detected, the system queries the first edge node where the container application corresponding to the updated image file resides. The updated image file is then pulled to the first edge node to update the corresponding container application. When an update to an application installation package is detected, the system queries the second edge node where the process application corresponding to the updated application installation package resides. The updated application installation package is then downloaded to the second edge node to update the corresponding process application.

[0158] Furthermore, the update process of container applications and / or process applications is monitored. If an update failure is detected, the corresponding update failure information is sent to the target personnel at the target oil and gas site, and the failure handling plan based on the feedback from the target personnel is obtained.

[0159] This application provides a data processing method for oil and gas sites, which acquires target oil and gas data to be processed from the target oil and gas site, as well as edge nodes deployed at the target oil and gas site. Then, it determines whether each target oil and gas data meets preset processing requirements and identifies the cloud computing platform that interacts with the edge nodes. Further, it sends the first oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and identifies the target oil and gas data that meets the preset processing requirements as the second oil and gas data. It identifies a container application or process application in the cloud computing platform for processing the second oil and gas data, wherein the container application supports containerization technology, while the process application does not. Running the container application on edge nodes that support containerization technology and running the process application on edge nodes that do not support containerization technology provides greater adaptability to edge nodes and operating environments. Further, based on the container application or process application, it identifies the target edge node for processing the second oil and gas data from all edge nodes, and sends each piece of second oil and gas data to the corresponding target edge node for processing. Thus, it is evident that cloud computing and edge computing are tightly integrated in the process of processing target oil and gas data from the target oil and gas site. By rationally distributing target oil and gas data between the cloud computing platform and edge nodes, cloud computing is extended to edge nodes, achieving cloud computing decentralization and bringing about efficient resource utilization. Furthermore, applying edge computing to oil and gas fields provides proximity computing and network coverage, effectively improving response speed and thus increasing the processing efficiency of target oil and gas data.

[0160] Figure 6 A schematic diagram of the data processing device for oil and gas field applications provided in this application is shown below. Figure 6 As shown, the data processing device 600 for oil and gas sites includes: an acquisition module 601, a determination module 602, and a processing module 603;

[0161] The acquisition module 601 is used to acquire the target oil and gas data to be processed sent by the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site.

[0162] The determination module 602 is used to determine whether each target oil and gas data meets the preset processing requirements and to determine the cloud computing platform that interacts with the edge nodes;

[0163] The processing module 603 is used to send target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and to send target oil and gas data that meets the preset processing requirements to the edge node for processing.

[0164] In one possible design, processing module 603 further includes: sending module 604 and migration module 605.

[0165] The determination module 602 is also used to determine the target oil and gas data that does not meet the preset processing requirements as the first oil and gas data;

[0166] The sending module 604 is used to send the first oil and gas data to the cloud computing platform for processing.

[0167] The determination module 602 is also used to determine the target oil and gas data that meets the preset processing requirements as the second oil and gas data, and to determine the application program stored in the cloud computing platform for processing the second oil and gas data.

[0168] Migration module 605 is used to migrate applications to edge nodes; wherein each edge node includes at least one application;

[0169] The determination module 602 is also used to determine, based on the application, the target edge node from the edge nodes for processing each second oil and gas data;

[0170] The sending module 604 is also used to send each second oil and gas data to the corresponding target edge node for processing.

[0171] In one possible design, the application used to process the second oil and gas data includes a container application that supports containerization technology, and a process application that does not support containerization technology.

[0172] The determination module 602 is also used to determine the image files and application installation packages stored in the cloud computing platform; wherein, the image file represents the set of data required to run the container application, and the application installation package represents the set of data required to run the process application;

[0173] The sending module 604 is also used to send image files or application installation packages to edge nodes to run the corresponding container application or process application.

[0174] In one possible design, the sending module 604 further includes: a pull module 606, a startup module 607, a download module 608, and an execution module 609.

[0175] The determination module 602 is also used to determine whether each edge node supports containerization technology based on the configuration information of each edge node;

[0176] Pull module 606 is used to pull image files to edge nodes that support containerization technology;

[0177] Startup module 607 is used to start an image file to run a container application;

[0178] Download module 608 is used to download the application installation package to edge nodes that do not support containerization technology;

[0179] Execution module 609 is used to execute the application installation package to run the process application.

[0180] In one possible design, the processing module 603 further includes: a monitoring module 610 and a query module 611.

[0181] The monitoring module 610 is used to monitor the image files and application installation packages stored in the cloud computing platform.

[0182] The query module 611 is used to query the first edge node where the container application corresponding to the updated image file is located when an update is detected.

[0183] Pull module 606 is also used to pull updated image files to the first edge node to update the corresponding container application.

[0184] In one possible design, the query module 611 is also used to query the second edge node where the process application corresponding to the updated application installation package is located when an update to the application installation package is detected.

[0185] Download module 608 is also used to download the updated application installation package to the second edge node to update the corresponding process application.

[0186] In one possible design, the monitoring module 610 is also used to monitor the update process of container applications and / or process applications.

[0187] The sending module 604 is also used to send corresponding update failure information to the target personnel at the target oil and gas site if an update failure is detected.

[0188] The acquisition module 601 is also used to acquire the failure handling plan based on the update failure information feedback from the target staff.

[0189] The data processing apparatus for oil and gas sites provided in this application can be used to execute the data processing method for oil and gas sites in any of the above embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0190] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented by processing element calls to software, while others are implemented in hardware. Additionally, these modules can be fully or partially integrated together, or implemented independently. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through the integrated logic circuits in the hardware of the processor element or through software instructions.

[0191] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 7 As shown, the electronic device may include: a transceiver 71, a processor 72, and a memory 73.

[0192] Processor 72 executes computer execution instructions stored in memory, causing processor 72 to perform the scheme in the above embodiments. Processor 72 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0193] The memory 73 is connected to the processor 72 via the system bus and completes communication between them. The memory 73 is used to store computer program instructions.

[0194] Transceiver 71 can be used to communicate and interact with other devices.

[0195] The system bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus. Transceivers are used to enable communication between database access devices and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and may also include non-volatile memory.

[0196] The electronic device provided in this application embodiment can be used to execute the method provided in any of the above embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0197] This application also provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the methods provided in any of the above embodiments.

[0198] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can implement the method provided in any of the above embodiments.

[0199] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0200] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0201] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0202] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0203] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0204] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0205] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0206] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0207] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0208] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0209] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A data processing method for oil and gas field operations, characterized in that, include: Acquire the target oil and gas data to be processed sent from the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site; Determine whether each target oil and gas data meets the preset processing requirements, and determine the cloud computing platform that interacts with the edge node; Target oil and gas data that does not meet the preset processing requirements are sent to the cloud computing platform for processing, and target oil and gas data that meets the preset processing requirements are sent to the edge node for processing.

2. The method according to claim 1, characterized in that, The step of sending target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and sending target oil and gas data that meets the preset processing requirements to the edge node for processing, includes: The target oil and gas data that does not meet the preset processing requirements is identified as the first oil and gas data, and the first oil and gas data is sent to the cloud computing platform for processing; The target oil and gas data that meets the preset processing requirements is identified as the second oil and gas data. The application stored in the cloud computing platform for processing the second oil and gas data is identified, and the application is migrated to the edge node. Each edge node includes at least one of the applications. Based on the application, the target edge node for processing each second oil and gas data is determined from the edge nodes, and each second oil and gas data is sent to the corresponding target edge node for processing.

3. The method according to claim 2, characterized in that, The application used to process the second oil and gas data includes a container application that supports containerization technology and a process application that does not support containerization technology. The step of determining the application stored in the cloud computing platform for processing the second oil and gas data and migrating the application to the edge node includes: Identify the image files and application installation packages stored in the cloud computing platform; wherein, the image file represents the data set required to run the container application, and the application installation package represents the data set required to run the process application; The image file or the application installation package is sent to the edge node to run the corresponding container application or process application.

4. The method according to claim 3, characterized in that, Sending the image file or the application installation package to the edge node to run the corresponding container application or process application includes: Based on the configuration information of each edge node, determine whether each edge node supports the containerization technology; Pull the image file to an edge node that supports the containerization technology, and start the image file to run the container application; The application installation package is downloaded to an edge node that does not support the containerization technology, and the application installation package is executed to run the process application.

5. The method according to any one of claims 3 or 4, characterized in that, The method further includes: Monitor the image files and application installation packages stored in the cloud computing platform; When an update to the image file is detected, the first edge node where the container application corresponding to the updated image file is located is queried. The updated image file is pulled to the first edge node to update the corresponding container application.

6. The method according to claim 5, characterized in that, When an update to the application installation package is detected, the method further includes: Query the second edge node where the process application corresponding to the updated application installation package resides; The updated application installation package is downloaded to the second edge node to update the corresponding process application.

7. The method according to any one of claims 3 to 6, characterized in that, The method further includes: Monitor the update process of the container application and / or the process application; If an update failure is detected, the corresponding update failure information is sent to the target personnel at the target oil and gas site, and the failure handling plan based on the update failure information is obtained from the target personnel.

8. A data processing device for oil and gas field applications, characterized in that, include: The acquisition module is used to acquire the target oil and gas data to be processed sent by the target oil and gas site, as well as the edge nodes deployed at the target oil and gas site. The determination module is used to determine whether each target oil and gas data meets the preset processing requirements and to determine the cloud computing platform that interacts with the edge node; The processing module is used to send target oil and gas data that does not meet the preset processing requirements to the cloud computing platform for processing, and to send target oil and gas data that meets the preset processing requirements to the edge node for processing.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the data processing method for oil and gas sites 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 computer-executable instructions, which, when executed by a processor, are used to implement the data processing method for oil and gas field as described in any one of claims 1 to 7.

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