Database-based Method for Storing Oil Well Site Data

Abstract

The present invention relates to the technical field of data storage, and particularly to a method for storing oil well site data based on a database. The method includes the following steps: obtaining oil well site data; establishing an external data source; obtaining an oil well site data collection instruction; based on a preset data management system, establishing a data transmission connection between the oil well site data collection instruction and the external data source to generate a transmission connection instruction, and performing data security detection and processing on the transmission connection instruction to generate an oil well site data security connection instruction; through the full life cycle management of the oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption and other links, the present invention realizes the high-quality, integrity and security management of data, and improves the reliability and analysis value of data.

Description

Technical Field

[0001] The present invention relates to the technical field of data storage, and particularly to a method for storing oil well site data based on a database. Background Art

[0002] Early data management technologies mainly relied on traditional database systems and manual operation processes. In the initial stage, data storage and processing were mostly based on relational database management systems (RDBMS), such as IBM's DB2, Oracle, and Microsoft SQL Server. These systems organized data in tabular form, emphasizing data structuring and integrity. Early technologies had obvious limitations in dealing with large-scale data processing and real-time data analysis. Data processing was in a batch processing mode, with insufficient real-time data acquisition and update, and poor system scalability, making it difficult to meet the rapidly growing data requirements. With the progress of information technology, especially the development of Internet and big data technologies, data management technologies have gradually shifted to distributed database systems and cloud computing platforms. However, current data management technologies still face challenges. With the frequent occurrence of data leakage and cyber attack events, data security remains a major issue. With the large amount of data storage, there are also many challenges to the high load of the database. At the same time, modern data systems involve multiple data sources and formats, making data integration and consistency management increasingly complex. Summary of the Invention

[0003] Based on this, it is necessary to provide a method for storing oil well site data based on a database to solve at least one of the above technical problems.

[0004] To achieve the above object, for the method for storing oil well site data based on a database, the method includes the following steps:

[0005] Step S1: Obtain oil well site data;

[0006] Step S2: Establish an external data source; obtain an oil well site data collection instruction; based on a preset data management system, establish a data transmission connection between the oil well site data collection instruction and the external data source to generate a transmission connection instruction, and perform data security detection and processing on the transmission connection instruction to generate an oil well site data security connection instruction;

[0007] Step S3: Send the oil well site data to the external data source according to the oil well site data security connection instruction, and perform data filtering processing on the oil well site data to generate a preliminary oil well site security data set;

[0008] Step S4: Perform data preprocessing on the preliminary oil well site security data set to generate a standardized oil well site security data set;

[0009] Step S5: Establish an oil well site data storage database, and perform reinforcement processing on the oil well site data storage database to generate an encrypted oil well site database; store the standardized security data set in a preset cache database for load balancing cache processing to generate hot data and cold data of the oil well site; store the hot data and cold data of the oil well site in the encrypted oil well site database for data storage processing to obtain securely stored data, so as to implement the oil well site data storage operation.

[0010] The beneficial effects of the present invention are as follows: By acquiring the oil well site data, real-time monitoring of key on-site data is achieved, providing basic data support for subsequent analysis and decision-making. Establishing an external data source and obtaining data collection instructions through a preset data management system realizes an effective connection between the well site data and the external data source, generates a transmission connection instruction, and performs security detection processing on it to ensure the security of data during transmission, thereby generating a data security connection instruction. This process not only ensures the accuracy of data transmission but also prevents potential security threats through security detection. According to the data security connection instruction, the oil well site data is sent to the external data source and data filtering processing is performed to generate a preliminary security data set. This step effectively eliminates unnecessary or redundant data through data filtering, improving the quality and usability of the data. The preliminary security data set is preprocessed to generate a standardized security data set. The data preprocessing steps include operations such as data cleaning, missing value filling, and format unification, further improving the integrity and consistency of the data and laying a solid foundation for subsequent data analysis and applications. Establishing an oil well site data storage database and performing reinforcement processing to generate an encrypted oil well site database strengthens the security of data storage and prevents potential risks during the storage stage, such as illegal access and data leakage. At the same time, storing the standardized security data set in a preset cache database for load balancing cache processing effectively improves the response speed and processing capacity of the system. By distinguishing and storing the hot data and cold data of the oil well site respectively, the utilization of storage resources is optimized and the data access efficiency is improved. The separate storage of hot data and cold data not only optimizes performance but also reduces storage costs and improves the scalability and maintainability of the data storage system. Therefore, through the full life cycle management of the oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption and other links, the present invention realizes the high-quality, integrity and security management of data, improving the reliability and analysis value of the data. Through the full life cycle management of the oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption and other links, the present invention realizes the high-quality, integrity and security management of data, improving the reliability and analysis value of the data.

[0011] Preferably, step S2 includes the following steps:

[0012] Step S21: Establish an external data source through the cloud platform; obtain an oil well site data collection instruction;

[0013] Step S22: Use a preset data management system to perform data transmission connection processing based on the oil well site data collection instruction and the established external data source, thereby generating a data transmission connection instruction;

[0014] Step S23: Generate an oil well site data transmission security policy for the data transmission connection instruction, where the oil well site data transmission security policy includes a secure data passing policy and a security blocking policy; perform transmission path optimization processing on the data transmission connection instruction based on the secure data passing policy to execute the oil well site data transmission security policy; perform risk control monitoring processing on the data transmission connection instruction based on the security blocking policy to execute abandonment processing.

[0015] The present invention establishes an external data source through the cloud platform and obtains an oil well site data collection instruction, providing a flexible and scalable data storage and management environment, ensuring the accurate transmission and timely response of the data collection instruction. The application of the cloud platform not only enhances the flexibility of data storage, but also supports the processing and analysis requirements of large-scale data through its powerful computing power and resource scheduling. Use a preset data management system to establish data transmission connection processing based on the oil well site data collection instruction and the external data source, thereby generating a data transmission connection instruction. This process ensures the efficient transmission of data from the well site to the external data source through systematic data management and the establishment of transmission connections. The application of the data management system effectively simplifies the data transmission process and improves the accuracy and reliability of data transmission. Generate an oil well site data transmission security policy for the data transmission connection instruction, where the security policy includes a secure data passing policy and a security blocking policy. Perform transmission path optimization processing on the data transmission connection instruction based on the secure data passing policy to execute the oil well site data transmission security policy, ensuring the optimization of the data transmission path, reducing data transmission latency and loss, thereby improving the efficiency and reliability of data transmission. Perform risk control monitoring processing on the data transmission connection instruction based on the security blocking policy to execute abandonment processing, further strengthening the security management during the data transmission process. The application of the security blocking policy effectively prevents potential data security threats and ensures the security and integrity of the data transmission process through real-time risk monitoring and control. Perform security detection processing on the data transmission connection instruction based on the oil well site data transmission security policy to generate an oil well site data security connection instruction. This step ensures the security and effectiveness of the data transmission connection instruction through systematic security detection, further improving the reliability and security of data transmission.

[0016] Preferably, step S23 includes the following steps:

[0017] Step S231: Generate an oil well site data transmission security policy for the data transmission connection instruction, where the oil well site data transmission security policy includes a secure data passing policy and a security blocking policy; based on a preset evaluation standard threshold, perform policy discrimination on the data transmission connection instruction to generate an oil well site policy discrimination result, where the oil well site policy discrimination result includes a secure data passing result and a security blocking result;

[0018] Step S232: When the oil well site policy discrimination result is a secure data passing result, apply the secure data passing policy to perform transmission path optimization processing on the data transmission connection instruction to generate path optimization data, and execute the oil well site data transmission security policy through the path optimization data;

[0019] Step S233: When the oil well site policy discrimination result is a security blocking result, apply the security blocking policy to perform risk control monitoring processing on the data transmission connection instruction to generate oil well site risk control data; perform dangerous data identification processing on the oil well site risk control data to generate oil well site identification data, and execute waste treatment.

[0020] The present invention generates an oil well site data transmission strategy for data transmission connection instructions, and formulates data transmission security strategies including a security data passing strategy and a security blocking strategy. Based on a preset evaluation standard threshold, the data transmission connection instructions are subjected to strategy discrimination to generate an oil well site strategy discrimination result, clarifying the security and risks of data during transmission. This strategy generation and discrimination process not only improves the accuracy and reliability of data transmission, but also prevents potential data security threats through refined security strategies. When the strategy discrimination result is a security data passing result, the security data passing strategy is applied to optimize the transmission path of the data transmission connection instructions, generating path-optimized data. By executing the oil well site data transmission security strategy through the path-optimized data, the optimization of the data transmission path is ensured, reducing data transmission latency and loss, and improving the efficiency and stability of data transmission. The transmission path optimization process further improves the security and reliability of data transmission by reducing unnecessary intermediate nodes and optimizing the data flow direction. When the strategy discrimination result is a security blocking result, the security blocking strategy is applied to perform risk control monitoring on the data transmission connection instructions, generating oil well site risk control data. The oil well site risk control data is subjected to dangerous data identification processing to generate oil well site identification data, and waste treatment is performed. This process ensures that dangerous data does not enter the transmission path through real-time monitoring and identification of potential risk data, further strengthening the security of data transmission. The risk control and waste treatment mechanisms not only effectively prevent data leakage and security accidents, but also ensure the security and integrity of the data transmission process through strict risk monitoring and control measures.

[0021] Preferably, step S3 includes the following steps:

[0022] Step S31: Establish a data transmission channel using the Secure Sockets Layer protocol to generate an oil well site data transmission channel;

[0023] Step S32: Send the oil well site data to an external data source through the oil well site data transmission channel to generate a data set, generating an oil well site sent data set;

[0024] Step S33: Filter out invalid data from the oil well site sent data set to generate an oil well site data filtered data set; perform security information processing on the oil well site data filtered data set to generate an oil well site preliminary security data set.

[0025] The present invention establishes a data transmission channel through the Secure Sockets Layer / Transport Layer Security (SSL / TLS) protocol to generate an oil well site data transmission channel. Through the encrypted transmission mechanism, the confidentiality and integrity of data during transmission are ensured, preventing the data from being intercepted or tampered with during transmission. The SSL / TLS protocol ensures the privacy and security of data during transmission by establishing a secure connection, providing reliable data transmission protection. The oil well site data is sent to an external data source through the oil well site data transmission channel to generate a data set, generating an oil well site sent data set. This process realizes the efficient transmission and storage of data through a secure transmission channel. After receiving the data, the external data source organizes and classifies the original data through a systematic data set generation process to form a structured sent data set, providing basic data support for subsequent data processing and analysis. The oil well site sent data set is subjected to invalid data filtering processing to generate an oil well site data filtered data set. By filtering out invalid data, redundant and incorrect data are removed, improving the quality and accuracy of the data set. The data filtering processing effectively reduces data noise, ensuring the integrity and consistency of the data. The oil well site data filtered data set is subjected to security information processing to generate an oil well site preliminary security data set. The security information processing further enhances the security and privacy protection of the data by encrypting, anonymizing, etc. the data, ensuring the security and compliance of the data during subsequent use.

[0026] Preferably, step S32 includes the following steps:

[0027] Step S321: Package and encrypt the oil well site data through AES encryption to generate oil well site encrypted data and an oil well site decryption data packet, where the oil well site decryption data packet includes an oil well site timestamp and oil well site check code data;

[0028] Step S322: Send the oil well site encrypted data to an external data source through the oil well site data transmission channel to generate an external encrypted data set;

[0029] Step S323: Use the oil well site timestamp and oil well site check code data to decrypt the external encrypted data set to generate an oil well site sent data set.

[0030] The present invention packs and encrypts the oil well site data through the AES (Advanced Encryption Standard) encryption technology to generate the encrypted oil well site data and the decryption data packet of the oil well site, wherein the decryption data packet of the oil well site contains the timestamp and the check code data. The AES encryption technology provides a highly secure encryption mechanism, ensuring the confidentiality of the data through complex key operations and preventing unauthorized access and data leakage. The introduction of the timestamp and the check code not only guarantees the timeliness of data transmission but also provides the necessary information for subsequent decryption and data verification, ensuring the integrity and consistency of the data during the transmission process. The encrypted oil well site data is sent to an external data source through the oil well site data transmission channel to generate an external encrypted data set. The application of the data transmission channel, combined with the AES encryption technology, ensures the security and confidentiality of the data during the transmission process. Through the secure transmission channel, the data will not be intercepted or tampered with during the transmission process, further enhancing the transmission security of the data. After receiving the encrypted data, the external data source generates an external encrypted data set through systematic processing, providing a high-quality data basis for subsequent data decryption and use. The external encrypted data set is decrypted using the oil well site timestamp and the oil well site check code data to generate the oil well site sent data set. The decryption process ensures the timeliness and integrity of the data by verifying the timestamp and the check code, preventing data tampering and forgery. The timestamp ensures the real-time nature of data transmission, and the check code ensures that no errors or losses occur to the data during the transmission process through data integrity verification. The decryption process restores the original data, providing reliable data support for subsequent data analysis and processing.

[0031] Preferably, step S4 includes the following steps:

[0032] Step S41: Perform data chunking on the preliminary secure data set of the oil well site to generate the chunked data set of the oil well site;

[0033] Step S42: Perform data cleaning on the chunked data set of the oil well site to generate the cleaned data set of the oil well site; perform data enhancement on the cleaned data set of the oil well site to generate the enhanced data set of the oil well site;

[0034] Step S43: Perform data set standardization on the enhanced data set of the oil well site to obtain the standardized secure data set of the oil well site.

[0035] The present invention generates a segmented oil well site dataset by performing data chunking on the preliminary safety dataset of the oil well site. Data chunking splits a large-scale dataset into smaller and more manageable data chunks, facilitating subsequent parallel processing and analysis. This process effectively improves the efficiency of data processing through chunking technology, reduces the burden on a single computing node, and also provides flexibility for local data processing. Data cleaning is performed on the segmented oil well site dataset to generate a cleaned oil well site dataset. Data cleaning improves the accuracy and reliability of the data by removing noise, missing values, and outliers in the data. The cleaned data is cleaner and more standardized, providing a high-quality data foundation for subsequent data analysis and applications. Next, data augmentation is performed on the cleaned oil well site dataset to generate an augmented oil well site dataset. Data augmentation further enhances the richness and effectiveness of the dataset by increasing data diversity and representativeness, such as data expansion, balancing, and transformation. The augmented dataset can better represent the actual situation and improve the effects of model training and data analysis. Dataset standardization is performed on the augmented oil well site dataset to obtain a standardized safety dataset for the oil well site. Data standardization makes the dataset more standardized and consistent by unifying the measurement units, ranges, and formats of the data. The standardized data is not only convenient for integration and comparison between different data sources, but also improves the usability and interpretability of the data. Data standardization effectively reduces redundancy and inconsistency in the data, ensuring seamless connection and sharing of data between different systems and applications. Data chunking splits a large-scale dataset into smaller and more manageable data chunks, facilitating subsequent parallel processing and analysis. This process effectively improves the efficiency of data processing through chunking technology, reduces the burden on a single computing node, and also provides flexibility for local data processing. Data cleaning is performed on the segmented oil well site dataset to generate a cleaned oil well site dataset. Data cleaning improves the accuracy and reliability of the data by removing noise, missing values, and outliers in the data. The cleaned data is cleaner and more standardized, providing a high-quality data foundation for subsequent data analysis and applications. Next, data augmentation is performed on the cleaned oil well site dataset to generate an augmented oil well site dataset. Data augmentation further enhances the richness and effectiveness of the dataset by increasing data diversity and representativeness, such as data expansion, balancing, and transformation. The augmented dataset can better represent the actual situation and improve the effects of model training and data analysis. Dataset standardization is performed on the augmented oil well site dataset to obtain a standardized safety dataset for the oil well site. Data standardization makes the dataset more standardized and consistent by unifying the measurement units, ranges, and formats of the data. The standardized data is not only convenient for integration and comparison between different data sources, but also improves the usability and interpretability of the data.Standardization effectively reduces redundancy and inconsistency in data, ensuring seamless connection and sharing of data among different systems and applications.

[0036] Preferably, step S5 includes the following steps:

[0037] Step S51: Construct a relational database for the oil well site; store the standardized safety data set in a preset cache database for load balancing cache processing to generate hot data and cold data for the oil well site;

[0038] Step S52: Conduct performance test optimization on the relational database for the oil well site to generate a performance test optimization result; optimize the relational database for the oil well site based on the performance test optimization result to generate a storage database for the oil well site; use database security reinforcement measures to reinforce the storage database for the oil well site to generate an encrypted database for the oil well site;

[0039] Step S53: Store the hot data and cold data for the oil well site in the encrypted database for the oil well site for data storage processing to generate securely stored data, completing the data storage operation for the oil well site.

[0040] The present invention provides a solid foundation for the structured storage and management of data by constructing a relational database for oil well sites. By constructing a relational database for oil well sites and storing the standardized security data set in a preset cache database for load balancing cache processing, hot data and cold data for oil well sites are generated. This process ensures the efficiency and accuracy of data storage and access. Through load balancing cache processing, hot data (data with high-frequency access) and cold data (data with low-frequency access) are effectively distinguished and processed separately, optimizing the system performance and response speed. The cache mechanism reduces the direct access pressure on the main database, improves the data access speed, and enhances the user experience. Performance testing and optimization of the relational database for oil well sites are carried out, and database optimization processing is performed based on the performance test results to generate a storage database for oil well sites. This optimization process is crucial as it ensures that the database can efficiently handle a large number of read and write requests, reducing the system response time and processing bottlenecks. Performance testing can identify potential bottlenecks in the database, and through optimization measures (such as index optimization, query optimization, resource configuration adjustment, etc.), the overall performance of the database can be further improved. The optimization processing at this stage not only enhances the processing ability of the database but also improves the stability and reliability of the system. Finally, the hot data and cold data for oil well sites are stored in an encrypted database for oil well sites for data storage processing to generate secure data storage data. This process incorporates database security reinforcement measures to provide a high level of security protection for the data. Data encryption technology protects the data from the risks of unauthorized access and data leakage, ensuring the confidentiality and integrity of the data. In addition, the generation of secure storage data completes the data storage task, providing a solid guarantee for the long-term preservation and management of the data. Through such encryption processing, the data of oil well sites is not only protected during storage but also meets strict data security compliance requirements.

[0041] Preferably, step S51 includes the following steps:

[0042] Step S511: Design the storage table structure using the entity-relationship model and perform normal form specification processing on the storage table structure to generate a normalized database; perform index constraint processing on the normalized database using MySQL commands to generate a relational database for oil well sites; perform a relational test on the relational database for oil well sites to generate a relational database for oil well sites.

[0043] Step S512: Store the standardized security data set in a preset cache database for load balancing cache processing to generate cache data for oil well sites; perform frequency data partitioning on the cache data for oil well sites based on the data update status and data access frequency to generate hot data and cold data for oil well sites;

[0044] Step S513: Perform hotspot data sharding on the hotspot data of the oil well site to generate hotspot concurrent data; perform multi-point caching on the hotspot concurrent data to complete the caching operation of the hotspot data of the oil well site; perform cold data compression on the cold data of the oil well site to generate cold compressed data of the oil well site; perform data migration on the cold compressed data of the oil well site to complete the caching operation of the cold data of the oil well site.

[0045] In the present invention, by using the entity-relationship model to design the storage table structure and performing normalization processing on it, a normalized database is generated. This process ensures the rationality and consistency of the database structure. By normalization processing, data redundancy and inconsistency are reduced, and the storage structure of the data is optimized. Using MySQL commands to perform index constraint processing on the normalized database not only enhances the query efficiency of the database but also ensures data integrity and consistency. Finally, the relational database of the oil well site generated through relational testing has an optimized storage structure and efficient data management capabilities, and can support complex query and data operation requirements. Storing the standardized security data set in a preset cache database and performing load balancing caching processing generates the cached data of the oil well site. In this way, hotspot data and cold data are effectively partitioned and processed, thereby optimizing data access performance. Based on the data update status and access frequency, the cached data of the oil well site is partitioned by frequency data to further generate the hotspot data and cold data of the oil well site. This strategy ensures the efficient access and storage of data. Hotspot data (data with high access frequency) can be quickly accessed and processed, while cold data (data with low access frequency) is appropriately stored to optimize resource utilization. Perform hotspot data sharding on the hotspot data of the oil well site to generate hotspot concurrent data. This process disperses the storage of hotspot data through data sharding technology, significantly improving the concurrent data processing ability and the response speed of the system. The multi-point caching of hotspot data completes the caching operation of the hotspot data of the oil well site, effectively improving the access efficiency of the system and the data reading and writing speed. At the same time, perform compression processing on the cold data of the oil well site to generate cold compressed data of the oil well site. By data compression technology, the storage occupancy and transmission bandwidth of the data are reduced, further optimizing the use of storage resources. The migration processing of cold data ensures the efficient management of cold data in long-term storage and completes the caching operation of the cold data of the oil well site.

[0046] Preferably, step S52 includes the following steps:

[0047] Step S521: Perform performance test optimization on the relational database of the oil well site to generate performance test optimization results; based on the performance test optimization results, perform optimization processing on the relational database of the oil well site to generate a storage database for the oil well site; perform database data segmentation on the storage database of the oil well site to generate segmented data for the oil well site.

[0048] Step S522: Encrypt the oil well site segmentation data using the AES encryption algorithm to generate encrypted oil well site data and an AES key;

[0049] Step S523: Protect and manage the encrypted oil well site data and the AES key to generate an encrypted oil well site database.

[0050] In the present invention, performance testing and optimization are carried out on the relational database of the oil well site to generate performance testing and optimization results. The performance testing and optimization simulate the actual workload, evaluate the response time, throughput, and resource utilization rate of the database, identify performance bottlenecks and optimization opportunities. Based on the performance testing and optimization results, the relational database of the oil well site is optimized to generate a storage database for the oil well site. This process effectively improves the performance and efficiency of the database by adjusting database configuration parameters, optimizing query execution plans, and index strategies, ensuring the high efficiency of data storage and access. Subsequently, database data segmentation processing is carried out on the storage database of the oil well site to generate oil well site segmentation data. Data segmentation further improves the efficiency of data processing, reduces the burden on a single computing node, and provides flexibility for local data processing by splitting large-scale data sets into smaller and more manageable data blocks. The oil well site segmentation data is encrypted using the AES encryption algorithm to generate encrypted oil well site data and an AES key. The AES (Advanced Encryption Standard) encryption algorithm provides a highly secure encryption mechanism, ensuring data confidentiality through complex key operations, preventing unauthorized access and data leakage. The encrypted data is effectively protected during transmission and storage, enhancing data security and confidentiality. The generation and management of the AES key are also crucial for data decryption and access, ensuring the availability and integrity of the encrypted data. The encrypted oil well site data and the AES key are protected and managed to generate an encrypted oil well site database. Key management ensures the security and confidentiality of the AES key through secure storage and access control, preventing data security risks caused by key leakage. The encrypted database ensures data confidentiality and integrity during storage through multi-level security protection mechanisms, including data encryption, access control, and audit logs. By effectively managing keys and encrypting data, a highly secure data storage environment is established, providing a solid guarantee for the data security of enterprises.

[0051] Preferably, step S53 includes the following steps:

[0052] Step S531: Preset the data integrity threshold for the oil well site; Store the hot data and cold data of the oil well site in the encrypted oil well site database to generate oil well site storage data;

[0053] Step S532: Compare and process the data stored in the oil well site with the data integrity threshold of the oil well site. When the stored safety data is less than the data integrity threshold of the oil well site, the standardized safety data set is determined to be missing storage data, and the missing storage data is processed for data clearing; when the stored safety data is greater than or equal to the data integrity threshold of the oil well site, the standardized safety data set is determined to be stored information data;

[0054] Step S533: Perform supervised learning processing on the stored information data to generate secure storage data;

[0055] Step S534: Securely store the secure storage data in the database to complete the data storage operation of the oil well site.

[0056] The present invention generates the data stored in the oil well site by presetting the data integrity threshold of the oil well site and storing the hot data and cold data of the oil well site in the encrypted database of the oil well site. The preset data integrity threshold provides a clear standard for the quality detection of data storage. By comparing the actual result of data storage with the threshold, the integrity and accuracy of the data are ensured. Compare and process the data stored in the oil well site with the data integrity threshold of the oil well site. When the stored safety data is less than the data integrity threshold of the oil well site, the standardized safety data set is determined to be missing storage data, and the missing storage data is processed for data clearing. This process avoids the negative impact of low-quality data on subsequent analysis and decision-making by clearing incomplete or missing data, ensuring the high quality and consistency of the data in the database. When the stored safety data is greater than or equal to the data integrity threshold of the oil well site, the standardized safety data set is determined to be stored information data. Through this process, high-quality data can be effectively filtered out, providing a reliable data basis for subsequent supervised learning and secure storage. Perform supervised learning processing on the stored information data to generate secure storage data. Supervised learning builds a model by training historical data and labeled data, identifies and corrects potential problems and anomalies in the data, and improves the quality and accuracy of the data. Through supervised learning processing, the quality of the data is further improved, ensuring the integrity and reliability of the stored data, and providing high-quality data support for data application and analysis. Securely store the secure storage data in the database to complete the data storage operation of the oil well site. Secure storage ensures the security and confidentiality of the data during the storage process through measures such as data encryption, access control, and security auditing. Database secure storage not only guarantees the confidentiality and integrity of the data, but also prevents data leakage, tampering, and unauthorized access through a multi-level security protection mechanism, improving the security and reliability of data storage.

[0057] The beneficial effects of the present invention are as follows: By acquiring oil well site data, real-time monitoring of key on-site data is achieved, providing basic data support for subsequent analysis and decision-making. Establishing an external data source and obtaining data collection instructions through a preset data management system realizes an effective connection between well site data and the external data source, generates a transmission connection instruction, and performs security detection and processing on it to ensure the security of data during transmission, thereby generating a data security connection instruction. This process not only ensures the accuracy of data transmission but also prevents potential security threats through security detection. According to the data security connection instruction, the oil well site data is sent to the external data source and data filtering processing is performed to generate a preliminary secure data set. This step effectively eliminates unnecessary or redundant data through data filtering, improving the quality and usability of the data. Data preprocessing is performed on the preliminary secure data set to generate a standardized secure data set. The data preprocessing steps include operations such as data cleaning, missing value filling, and format unification, further improving the integrity and consistency of the data and laying a solid foundation for subsequent data analysis and applications. Establishing an oil well site data storage database and performing reinforcement processing to generate an encrypted oil well site database strengthens the security of data storage and prevents potential risks during the storage stage, such as illegal access and data leakage. At the same time, storing the standardized secure data set in a preset cache database for load balancing cache processing effectively improves the response speed and processing capacity of the system. By distinguishing between hot data and cold data in the oil well site and storing them separately, the utilization of storage resources is optimized, and the data access efficiency is improved. The separate storage of hot data and cold data not only optimizes performance but also reduces storage costs and improves the scalability and maintainability of the data storage system. Therefore, through the full life cycle management of oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption, the present invention realizes the management of high-quality, integrity, and security of data, improving the reliability and analysis value of the data. Through the full life cycle management of oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption, the present invention realizes the management of high-quality, integrity, and security of data, improving the reliability and analysis value of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 FIG. is a schematic flow chart of the steps of a method for storing oil well site data based on a database;

[0059] Figure 2 is Figure 1 a detailed implementation step flow chart of step S2 in;

[0060] Figure 3 is Figure 1 a detailed implementation step flow chart of step S4 in;

[0061] Figure 4 For Figure 1 a detailed implementation step flow diagram of step S5 in

[0062] The realization, functional features and advantages of the present invention will be further described in conjunction with embodiments with reference to the accompanying drawings. Specific implementation manners

[0063] The technical method of the present invention patent will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0064] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0065] It should be understood that although terms such as "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be called the second unit, and similarly the second unit may be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0066] To achieve the above object, please refer to Figures 1 to 4 , a method for storing oil well site data based on a database, the method comprising the following steps:

[0067] Step S1: Obtain oil well site data;

[0068] Step S2: Establish an external data source; obtain an oil well site data collection instruction; establish a data transmission connection between the oil well site data collection instruction and the external data source based on a preset data management system, generate a transmission connection instruction, and perform data security detection processing on the transmission connection instruction to generate an oil well site data security connection instruction;

[0069] Step S3: Send the oil well site data to an external data source according to the oil well site data security connection instruction, and perform data filtering processing on the oil well site data to generate a preliminary oil well site security data set;

[0070] Step S4: Perform data preprocessing on the preliminary oil well site security data set to generate a standardized oil well site security data set;

[0071] Step S5: Establish an oil well site data storage database, and perform reinforcement processing on the oil well site data storage database to generate an encrypted oil well site database; Store the standardized security data set in a preset cache database for load balancing cache processing to generate hot oil well site data and cold oil well site data; Store the hot oil well site data and cold oil well site data in the encrypted oil well site database for data storage processing to obtain securely stored data, so as to implement the oil well site data storage operation.

[0072] The beneficial effects of the present invention are as follows: By acquiring oil well site data, real-time monitoring of key on-site data is achieved, providing basic data support for subsequent analysis and decision-making. Establishing an external data source and obtaining data collection instructions through a preset data management system realizes an effective connection between well site data and the external data source, generates a transmission connection instruction, and performs security detection and processing on it to ensure the security of data during transmission, thereby generating a data security connection instruction. This process not only ensures the accuracy of data transmission but also prevents potential security threats through security detection. According to the data security connection instruction, the oil well site data is sent to the external data source and data filtering processing is performed to generate a preliminary secure data set. This step effectively eliminates unnecessary or redundant data through data filtering, improving the quality and usability of the data. Data preprocessing is performed on the preliminary secure data set to generate a standardized secure data set. The data preprocessing steps include operations such as data cleaning, missing value filling, and format unification, further improving the integrity and consistency of the data and laying a solid foundation for subsequent data analysis and applications. Establishing an oil well site data storage database and performing reinforcement processing to generate an encrypted oil well site database strengthens the security of data storage and prevents potential risks during the storage stage, such as illegal access and data leakage. At the same time, the standardized secure data set is stored in a preset cache database for load balancing cache processing, effectively improving the response speed and processing capacity of the system. By distinguishing between hot data and cold data in the oil well site and storing them separately, the utilization of storage resources is optimized, and the data access efficiency is improved. The separate storage of hot data and cold data not only optimizes performance but also reduces storage costs and improves the scalability and maintainability of the data storage system. Therefore, through the full life cycle management of oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption, the present invention realizes high-quality, integrity, and security management of data, improving the reliability and analysis value of the data. Through the full life cycle management of oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption, the present invention realizes high-quality, integrity, and security management of data, improving the reliability and analysis value of the data.

[0073] In an embodiment of the present invention, referring to Figure 1 as described, it is a schematic diagram of the step flow of the method for storing oil well site data based on a database according to the present invention. In this example, the method for storing oil well site data based on a database includes the following steps:

[0074] Step S1: Acquire oil well site data;

[0075] In the embodiments of the present invention, various sensors and data acquisition devices are deployed in the oil well site. These devices can monitor and record various physical parameters of the well site, such as pressure, temperature, flow rate, liquid level, and composition. These sensors transmit real-time data to the centralized control system through wireless or wired networks.

[0076] Step S2: Establish an external data source; obtain the oil well site data acquisition instruction; based on the preset data management system, establish a data transmission connection between the oil well site data acquisition instruction and the external data source, generate a transmission connection instruction, and perform data security detection and processing on the transmission connection instruction, so as to generate an oil well site data security connection instruction;

[0077] In the embodiments of the present invention, establishing an external data source requires configuring data source information through a data management system, including data source type (such as database, data lake, cloud storage), connection parameters (such as URL, port, username, and password), and data access permissions. Through these configuration information, the data management system ensures that it can correctly and reliably access and manage the external data source. Obtaining the oil well site data acquisition instruction is realized through an integrated data acquisition platform. This platform can receive and process the acquisition instructions from the well site, and these instructions include the objectives, time range, acquisition frequency, and specific requirements for data format of data acquisition. Based on these acquisition instructions, the data management system establishes a data transmission connection with the external data source through the preset data transmission protocol and communication standard. During the establishment of the data transmission connection, the data management system generates a transmission connection instruction and, through a series of data security detection and processing, ensures the security and reliability of the transmission connection. Data security detection and processing include encrypting the transmission connection instruction, authentication, and permission verification. The encryption process uses the TLS (Transport Layer Security Protocol) encryption technology to ensure the confidentiality and integrity of the transmitted data. Authentication and permission verification prevent unauthorized access and data leakage through the authentication mechanism and access control policy, ensuring that only authenticated users and devices can establish a data transmission connection. Finally, after data security detection and processing, an oil well site data security connection instruction is generated. This instruction not only contains the specific parameters and configurations of the transmission connection but also attaches security verification information to ensure the security and reliability of the data during transmission.

[0078] Step S3: Send the oil well site data to the external data source according to the oil well site data security connection instruction, and perform data filtering processing on the oil well site data to generate a preliminary secure data set of the oil well site;

[0079] In an embodiment of the present invention, based on the data security connection instruction of the oil well site, a secure data transmission channel is established using the Secure Transfer Protocol (TLS). The transmission channel ensures that the data is protected from eavesdropping, tampering, and forgery security threats during transmission, ensuring the integrity and confidentiality of the data. The data transmission uses an efficient transmission protocol such as HTTP, combined with data compression technology (such as GZIP), to improve the transmission efficiency and reduce bandwidth consumption. After the data transmission is completed, the received oil well site data is subjected to data filtering processing. Data filtering processing is an important step in data preprocessing, aiming to screen the data, remove invalid, duplicate, and abnormal data, so as to generate a high-quality data set. Through rule verification and statistical analysis, the accuracy and reliability of the data are verified. After the data filtering processing, a preliminary secure data set of the oil well site is generated.

[0080] Step S4: Perform data preprocessing on the preliminary secure data set of the oil well site to generate a standardized secure data set of the oil well site;

[0081] In an embodiment of the present invention, data cleaning is the first step in data preprocessing, aiming to remove noise, errors, duplicates, and missing values existing in the preliminary secure data set. Specific technical means include using data cleaning tools (OpenRefine). These tools and scripts can identify and delete outliers, null values, and duplicate values in the data through rule definition, pattern recognition, and automated processing. Next is data transformation, aiming to convert the data in the preliminary secure data set into a unified format and unit. Data transformation can include data type conversion, unit conversion, and date format conversion. This process can be achieved through data transformation tools (Informatica) to ensure the comparability and processability of the data in a unified format. Data normalization is an important step in data preprocessing, aiming to convert the data into a standardized form for subsequent processing and analysis. The normalization process includes data standardization and data normalization. Data standardization is to convert data with different ranges and distributions into data with the same scale, using the Min - Max normalization method. Data normalization is to scale the data to a specific range (such as between 0 and 1) to eliminate the influence between data with different scales. The normalization process can be achieved through data processing libraries (such as Scikit - learn in Python). Finally is data integration, aiming to integrate the data from multiple data sources into a unified data integration platform. Data integration includes steps of data matching, data merging, and data deduplication. Data matching is to match the relevant data in different data sources according to a unique identifier (such as device ID or sensor ID). Data merging is to merge the matched data into a comprehensive data set, removing duplicate and redundant data. Data integration can be achieved through ETL (Extract, Transform, Load) tools.

[0082] Step S5: Establish an oil well site data storage database, and perform reinforcement processing on the oil well site data storage database to generate an encrypted oil well site database; store the standardized security data set in a preset cache database for load balancing cache processing to generate hot data and cold data of the oil well site; store the hot data and cold data of the oil well site in the encrypted oil well site database for data storage processing to obtain securely stored data, so as to implement the oil well site data storage operation.

[0083] In the embodiments of the present invention, establishing an oil well site data storage database usually adopts a relational database management system (RDBMS). These systems allow defining complex data table structures, indexes, and constraint conditions to support efficient data storage and retrieval. The design of the database includes normalization processing to reduce data redundancy and improve data consistency, thereby optimizing the storage structure and query efficiency. The technical means for performing reinforcement processing on the oil well site data storage database include data encryption, access control, and audit logs, etc. Data encryption technologies (such as AES, RSA algorithms) ensure the confidentiality of data during static storage and transmission, preventing data from being accessed or tampered with by unauthorized users. The access control mechanism ensures that only authorized users can access sensitive data through user authentication (such as user name and password, two-factor authentication) and permission management (such as role-based permission assignment). The audit log function records the access and modification operations of the database, helps track data usage, and supports compliance requirements and security audits. Storing the standardized security data set in a preset cache database for load balancing cache processing involves using a memory cache system (such as Redis, Memcached) to improve the data access speed and the system's response ability. The load balancing technology evenly distributes data access requests to multiple cache nodes through a distributed cache architecture and scheduling algorithms (such as round-robin, least connections), thereby preventing a single-point bottleneck and improving the scalability and performance of the system. The design of the cache system optimizes the access efficiency of hot data, enabling frequently accessed data to quickly respond to user requests. The storage processing of hot data and cold data of the oil well site involves data hierarchical management. Hot data (i.e., frequently accessed data) is processed in the cache database for easy retrieval and efficient read and write operations. Cold data (i.e., infrequently accessed data) is transferred to long-term storage solutions, such as a distributed file system (such as HDFS) or low-cost archival storage, to save storage resources and reduce costs. Finally, the hot data and cold data of the oil well site are stored in the encrypted database to ensure that all data is uniformly encrypted and protected.

[0084] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0085] Step S21: Establish an external data source through the cloud platform; obtain the oil well site data collection instruction;

[0086] Step S22: Use the preset data management system to perform data transmission connection processing based on the oil well site data collection instruction and the established external data source, so as to generate a data transmission connection instruction;

[0087] Step S23: Generate an oil well site data transmission security policy for the data transmission connection instruction, where the oil well site data transmission security policy includes a secure data passing policy and a security blocking policy; perform transmission path optimization processing on the data transmission connection instruction based on the secure data passing policy to execute the oil well site data transmission security policy; perform risk control monitoring processing on the data transmission connection instruction based on the security blocking policy to execute the abandonment processing.

[0088] Step S24: Perform security detection processing on the data transmission connection instruction based on the oil well site data transmission security policy to generate an oil well site data security connection instruction.

[0089] In the embodiments of the present invention, an external data source is established through a cloud platform. The specific technical means include creating and configuring data storage resources using cloud computing services (such as Amazon Web Services). The S3 service provided by the cloud platform can be used to store and manage large-scale oil well site data. Through the cloud platform, elastic storage and on-demand expansion of data can be achieved, ensuring the flexibility and scalability of data storage. In this process, access permissions and security policies need to be configured to ensure the security and reliability of the data source. Using a preset data management system to perform data transmission connection processing with the external data source according to the oil well site data collection instruction, generating a data transmission connection instruction. The data management system (Apache Kafka) is used to manage and schedule data transmission tasks. The specific technical means include data source connection configuration, establishment of data transmission pipelines, and setting of transmission parameters. By writing data transmission scripts or configuring data transmission tasks, efficient transmission of data from the oil well site collection equipment to the external data source is ensured. In this process, an appropriate data transmission protocol (HTTPS) needs to be selected to ensure the security and reliability of data transmission. Generating an oil well site data transmission strategy for the data transmission connection instruction, generating a data transmission security strategy. The data transmission security strategy includes a secure data passing strategy and a security blocking strategy. The specific technical means include policy generation and optimization based on rules and algorithms. The secure data passing strategy is used to ensure legal and secure data transmission. Policy generation can be achieved through machine learning algorithms and rule engines, and Bayesian networks or decision tree models are used to optimize the data transmission path. The transmission path optimization process calculates the best transmission path, reduces transmission latency and network congestion, and improves data transmission efficiency. The security blocking strategy is used to identify and block potential security threats. The specific technical means include the configuration and management of intrusion detection systems (IDS), intrusion prevention systems (IPS), and firewall security devices. By monitoring and analyzing the transmitted data in real time, abnormal behaviors are detected and blocked in a timely manner. Performing security detection processing on the data transmission connection instruction based on the oil well site data transmission security strategy, generating an oil well site data security connection instruction. The specific technical means of security detection include data encryption, authentication, and implementation of security protocols. Data encryption uses symmetric encryption algorithms (AES) and asymmetric encryption algorithms (RSA) to encrypt and transmit data, ensuring the confidentiality and integrity of data during transmission. Authentication ensures the credibility of the identities of both parties in the transmission through multi-factor authentication (MFA) and digital certificates (such as SSL / TLS certificates). Security protocols (such as TLS, IPsec) are used to establish a secure transmission channel to prevent data from being stolen or tampered with during transmission.

[0090] Preferably, step S23 includes the following steps:

[0091] Step S231: Generate an oil well site data transmission security policy by generating an oil well site data transmission strategy for the data transmission connection instruction, where the oil well site data transmission security policy includes a secure data passing policy and a security blocking policy; perform policy discrimination on the data transmission connection instruction based on a preset evaluation standard threshold to generate an oil well site policy discrimination result, where the oil well site policy discrimination result includes a secure data passing result and a security blocking result;

[0092] Step S232: When the oil well site policy discrimination result is a secure data passing result, apply the secure data passing policy to perform transmission path optimization processing on the data transmission connection instruction to generate path optimization data, and execute the oil well site data transmission security policy through the path optimization data;

[0093] Step S233: When the oil well site policy discrimination result is a security blocking result, apply the security blocking policy to perform risk control monitoring processing on the data transmission connection instruction to generate oil well site risk control data; perform dangerous data identification processing on the oil well site risk control data to generate oil well site identification data, and execute waste treatment.

[0094] In the embodiments of the present invention, a data transmission connection instruction is used to generate an oil well site data transmission strategy. The specific technical means include a strategy generation algorithm. An oil well site data transmission security strategy is generated, including a secure data passing strategy and a security blocking strategy. The secure data passing strategy is generated by a machine learning algorithm based on a preset evaluation standard threshold, combined with the factors of data transmission security, reliability, and efficiency. These algorithms can learn and predict based on historical data and real-time data, thereby dynamically adjusting the data transmission strategy. The security blocking strategy identifies potential security threats by setting anomaly detection and intrusion detection rules (based on Bayesian networks and neural network methods) and takes blocking measures. Based on the preset evaluation standard threshold, a strategy discrimination is performed on the data transmission connection instruction to generate an oil well site strategy discrimination result. The specific technical means include a threshold discrimination algorithm and decision logic. The threshold discrimination algorithm uses statistical methods and machine learning models to evaluate the data transmission connection instruction, and determines whether it conforms to the secure data passing strategy or the security blocking strategy according to the characteristics of the data and the transmission environment. The strategy discrimination result includes a secure data passing result and a security blocking result. When the oil well site strategy discrimination result is a secure data passing result, the secure data passing strategy is applied to perform transmission path optimization processing on the data transmission connection instruction. The specific technical means include a path optimization algorithm and the Dijkstra algorithm. The path optimization algorithm calculates the optimal transmission path, reduces transmission delay and network congestion, and improves the efficiency and reliability of data transmission. The generated path optimization data adjusts and optimizes the data transmission connection instruction to ensure that data can be transmitted safely and efficiently. When the oil well site strategy discrimination result is a security blocking result, the security blocking strategy is applied to perform risk control monitoring processing on the data transmission connection instruction. The specific technical means include a risk control mechanism and anomaly detection technology. The risk control mechanism monitors abnormal behaviors (such as packet loss, transmission delay, and data tampering) in the data transmission process in real time, and uses anomaly detection technology (based on statistical models) to identify and analyze potential security threats to generate oil well site risk control data. Hazardous data identification processing is performed on the oil well site risk control data. The specific technical means include a data identification algorithm and tagging processing. The data identification algorithm extracts and analyzes the characteristics of the risk control data, identifies it as hazardous data, and assigns corresponding tags (such as high risk, medium risk, and low risk). Finally, the data identified as hazardous is discarded to ensure the security and integrity of oil well site data transmission.

[0095] Preferably, step S3 includes the following steps:

[0096] Step S31: Establish a data transmission channel using the Secure Sockets Layer protocol to generate an oil well site data transmission channel;

[0097] Step S32: Send the oil well site data to an external data source through the oil well site data transmission channel to generate a data set, and generate an oil well site sent data set;

[0098] Step S33: Perform invalid data filtering on the oil well site sent data set to generate an oil well site data filtered data set; perform security information processing on the oil well site data filtered data set to generate an oil well site preliminary security data set.

[0099] In the embodiment of the present invention, a data transmission channel is established by using the Secure Socket Layer (SSL) protocol to generate an oil well site data transmission channel. The specific technical means include the application of the SSL protocol. The SSL protocol constructs a secure data transmission environment by encrypting data, verifying the identities of the server and the client, and ensuring the integrity of data transmission. First, the client and the server perform an SSL handshake to exchange encryption algorithms and keys, and then transmit data in the encrypted channel. The SSL protocol combines asymmetric encryption (RSA) and symmetric encryption (AES) to ensure the confidentiality and security of data during transmission. The oil well site data is sent to an external data source through the oil well site data transmission channel to generate a data set, and an oil well site sent data set is generated. The specific technical means include data transmission protocols (such as HTTP / HTTPS) and data transmission control mechanisms. The established SSL / TLS channel is used to ensure the security of data transmission. Through the Transmission Control Protocol (such as TCP) and application layer protocols (such as HTTP / HTTPS, FTP), the oil well site data is sent from the local system to the external data source. These protocols ensure that the data is not lost, not repeated, and in the correct order during transmission through packet transmission, retransmission control, flow control, and congestion control mechanisms, and finally an oil well site sent data set is generated in the external data source. Perform invalid data filtering on the oil well site sent data set to generate an oil well site data filtered data set, and perform security information processing on the oil well site data filtered data set to generate an oil well site preliminary security data set. The specific technical means include data filtering algorithms and security processing technologies. Data filtering algorithms (rule-based filtering, machine learning filtering) identify and delete invalid data (null values, duplicate values, outliers) in the oil well site sent data set. Rule-based filtering screens and processes data based on predefined rules (regular expressions, thresholds); machine learning filtering automatically identifies and filters invalid data through a trained model. Security information processing technologies (such as data encryption, data masking) further process the oil well site data filtered data set. Data encryption technologies (AES, RSA) encrypt the data to ensure the confidentiality of the data during storage and transmission; data masking technologies (such as pseudonymization, generalization) protect data privacy by transforming sensitive data.

[0100] Preferably, step S32 includes the following steps:

[0101] Step S321: Package and encrypt the oil well site data through AES encryption to generate encrypted oil well site data and an oil well site decryption data packet, where the oil well site decryption data packet includes an oil well site timestamp and oil well site check code data;

[0102] Step S322: Send the encrypted oil well site data to an external data source through an oil well site data transmission channel to generate an external encrypted data set;

[0103] Step S323: Decrypt the external encrypted data set using the oil well site timestamp and oil well site check code data to generate an oil well site sending data set.

[0104] In the embodiments of the present invention, the data of the oil well site is packaged and encrypted through AES encryption to generate encrypted data of the oil well site and a decryption data packet of the oil well site. The specific technical means include using the Advanced Encryption Standard (AES) to encrypt the data. AES is a symmetric encryption algorithm with high efficiency and security. Select a key length (128 bits, 192 bits, or 256 bits), and then perform block processing on the data of the oil well site, with each block of data having a length of 128 bits. Then, each block of data is encrypted through multiple rounds of encryption operations (including sub-key generation, byte substitution, row shift, column mixing, and round key addition) to finally generate an encrypted data block. To ensure the integrity of the data and prevent replay attacks, a timestamp and a checksum are also included in the encrypted data packet. The timestamp is used to record the generation time of the data, and the checksum is calculated through a hash function (such as SHA-256) and is used to verify the integrity of the data. The encrypted data of the oil well site is sent to an external data source through the data transmission channel of the oil well site to generate an external encrypted data set. The specific technical means include using a secure data transmission protocol (such as HTTPS) and a transmission control mechanism. The HTTPS protocol encrypts and authenticates the transmitted data through the SSL protocol to ensure the security of the data during transmission. During the transmission process, an SSL handshake is performed between the client and the server to establish a secure connection, and then the data is encrypted and transmitted through a symmetric encryption algorithm (such as AES). At the same time, the transmission control mechanism (such as TCP) ensures the reliability and integrity of the data transmission through means such as packet grouping, retransmission control, flow control, and congestion control. Finally, after the external data source receives the encrypted data, an external encrypted data set is generated. The external encrypted data set is decrypted using the timestamp and checksum data of the oil well site to generate a data set sent by the oil well site. The specific technical means include data decryption and integrity verification. The external encrypted data set is decrypted through the AES decryption algorithm. The decryption process is the opposite of the encryption process and includes multiple rounds of decryption operations (such as inverse sub-key generation, inverse byte substitution, inverse row shift, inverse column mixing, and round key addition). After decryption, the original data block is obtained. The generation time of the data is verified through the timestamp to ensure that the data is the latest and prevent replay attacks. Finally, the integrity of the data is verified through the checksum. The checksum calculated from the decrypted data block through the hash function is compared with the checksum in the decryption data packet. If they are the same, the data integrity is verified, and a data set sent by the oil well site is generated.

[0105] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes:

[0106] Step S41: Perform block processing on the preliminary secure data set of the oil well site to generate a block data set of the oil well site;

[0107] Step S42: Perform data cleaning on the oil well site block dataset to generate an oil well site cleaned dataset; perform data augmentation on the oil well site cleaned dataset to generate an oil well site augmented dataset;

[0108] Step S43: Perform dataset standardization on the oil well site augmented dataset to obtain an oil well site standardized safety dataset.

[0109] In the embodiment of the present invention, the preliminary safety dataset of the oil well site is subjected to data chunking to generate an oil well site block dataset. The specific technical means include data chunking technology, which aims to divide a large-scale dataset into smaller and manageable chunks. This is achieved by splitting the data according to a specific size or logical unit. The process of data chunking can be implemented programmatically, such as by using the partitioning function in a database management system (DBMS) or through the data sharding mechanism of a data processing framework (such as Apache Hadoop). Chunking helps improve data processing efficiency, optimize the storage structure, reduce memory occupancy, and facilitate subsequent data processing and analysis. The oil well site block dataset is subjected to data cleaning to generate an oil well site cleaned dataset, and then data augmentation is performed to generate an oil well site augmented dataset. Data cleaning techniques include data denoising, missing value handling, outlier detection and repair. Specific means include applying statistical methods (such as mean filling, median filling) to handle missing values and using machine learning algorithms (such as isolation forest) to detect and repair outliers. The purpose of data cleaning is to improve the accuracy and consistency of the data and ensure the reliability of subsequent analysis. Data augmentation expands the dataset through technical means to improve the diversity and richness of the data. Data augmentation can be achieved through generative adversarial networks (GANs), data interpolation, and synthetic data generation methods. These methods can generate data similar to the original data but with variations, thereby enhancing the generalization ability and robustness of the model. Dataset standardization is performed on the oil well site augmented dataset to obtain an oil well site standardized safety dataset. Data standardization is a key step in data preprocessing, aiming to convert data with different scales and distributions into a unified standard form. Specific technical means include data normalization and standardization. Data normalization is achieved by scaling the data to a specific interval (such as [0,1]), which can be accomplished through min-max scaling. Data standardization is achieved by subtracting the mean and dividing by the standard deviation to make the data conform to the standard normal distribution, which can be achieved through Z-score standardization. Standardization helps eliminate data scale differences, making the weights of different features more balanced in model training and improving the performance and stability of the algorithm.

[0110] As an example of the present invention, refer to Figure 4 As shown, in this example, step S5 includes:

[0111] Step S51: Construct a relational database for the oil well site; store the standardized safety data set in a preset cache database for load balancing caching processing to generate hot data and cold data for the oil well site;

[0112] Step S52: Perform performance test optimization on the relational database for the oil well site to generate a performance test optimization result; optimize the relational database for the oil well site based on the performance test optimization result to generate a storage database for the oil well site; use database security reinforcement measures to reinforce the storage database for the oil well site to generate an encrypted database for the oil well site;

[0113] Step S53: Store the hot data and cold data of the oil well site in the encrypted database of the oil well site for data storage processing to generate secure data storage data, and complete the data storage operation of the oil well site.

[0114] In the embodiments of the present invention, constructing a relational database for an oil well site involves designing and implementing a structured data management system, usually using a relational database management system (RDBMS) such as MySQL. This process includes defining data tables, creating indexes, setting data constraints, and performing normalization to eliminate data redundancy and improve consistency. Storing the standardized security data set into a preset cache database and performing load balancing cache processing involves using in-memory cache technologies (such as Redis, Memcached) to handle frequently accessed data. The load balancing technology distributes requests to multiple cache instances through algorithms (such as round-robin, least connections) to ensure the stability and scalability of system performance, thereby generating hot data and cold data for the oil well site. This technical means optimizes the data access speed and improves the response time of user queries. Optimizing the performance of the relational database for the oil well site is to evaluate the processing ability, response time, and load-bearing capacity of the database through performance benchmark testing tools (such as SysBench, JMeter). The results of the performance test are used to identify performance bottlenecks and guide the optimization of the database, which includes query optimization (such as creating indexes, optimizing SQL query statements), resource configuration adjustment (such as increasing memory, adjusting cache settings), and database parameter adjustment (such as adjusting the connection pool size). Through these optimization measures, an efficient storage database for the oil well site is generated. Subsequently, the storage database is fortified using database security reinforcement measures, including implementing data encryption (such as using AES or RSA algorithms), configuring access control (such as role-based permission management, two-factor authentication), and enabling the audit log function. These measures generate an encrypted database for the oil well site, ensuring the confidentiality and integrity of data during storage and access. Storing the hot data and cold data of the oil well site into the encrypted database for the oil well site for data storage processing, this stage involves encrypting and storing the data through encryption technologies (such as symmetric encryption, asymmetric encryption). The encryption process ensures that the data cannot be accessed without authorization during static storage, while protecting the confidentiality and integrity of the data. Finally, secure data storage data is generated, completing the data storage operation for the oil well site.

[0115] Preferably, step S51 includes the following steps:

[0116] Step S511: Design the storage table structure using the entity-relationship model, and perform normal form specification processing on the storage table structure to generate a normalized database; use MySQL commands to perform index constraint processing on the normalized database to generate a relational database for the oil well site; perform a relational test on the relational database for the oil well site to generate a relational database for the oil well site.

[0117] Step S512: Store the standardized security data set in a preset cache database for load balancing cache processing to generate oil well site cache data; perform frequency data partitioning on the oil well site cache data based on the data update status and data access frequency to generate oil well site hot data and oil well site cold data;

[0118] Step S513: Perform hot data sharding processing on the oil well site hot data to generate hot concurrent data; perform multi-point cache processing on the hot concurrent data to complete the oil well site hot data caching operation; perform cold data compression processing on the oil well site cold data to generate oil well site cold compressed data; perform data migration processing on the oil well site cold compressed data to complete the oil well site cold data caching operation.

[0119] In the embodiments of the present invention, designing a storage table structure using an entity-relationship model involves applying database modeling techniques to determine the logical structure of data. The entity-relationship model (ER model) is used to define entities and their relationships in a database, and the structure and relevance of data are visualized through an ER diagram. Normalization processing (such as the first normal form, the second normal form, and the third normal form) is to ensure the standardization of database design, reduce data redundancy, and improve data consistency. This process is usually completed by analyzing data dependency relationships. The generated normalized database can better support data integrity and query efficiency. Then, MySQL commands are used to perform index constraint processing on the normalized database, which involves creating indexes to optimize query performance and setting data constraints (such as primary key constraints and foreign key constraints) to ensure data integrity and consistency. Relational testing is performed on the normalized database, including data consistency testing, transaction processing testing, etc., to verify the design and function of the database. Finally, a relational database for oil well sites is generated, which has efficient data management capabilities and stable performance. The standardized security data set is stored in a preset cache database, and a cache system (such as Redis or Memcached) is used for load balancing processing. Load balancing technology evenly distributes data requests to multiple cache nodes through algorithms (such as hash distribution and round-robin), thereby improving the concurrent processing ability and response speed of the system. Frequency data partitioning is performed on the cached data based on the data update status and data access frequency, and the data is divided into hot data and cold data. This process involves using access statistics and analysis tools to monitor the access patterns of data to ensure that frequently accessed data (hot data) is processed first, while infrequently accessed data (cold data) is appropriately managed to optimize the use of system resources. Hot data sharding processing is performed on the hot data of the oil well site. Through data sharding technology, large-scale hot data is split into multiple data segments and stored on different nodes, thereby enabling concurrent access and processing of data. The generation of hot concurrent data involves using a distributed database system (such as Cassandra or MongoDB) to support concurrent access and improve the scalability and fault tolerance of the system. Multi-point caching processing is performed on the hot concurrent data, and a multi-node cache system is used to store and manage the hot data, thereby completing the hot data caching operation for the oil well site. For cold data, cold data compression processing is performed. Through compression algorithms (such as Gzip or LZ4), the data storage occupancy is reduced to generate cold compressed data for the oil well site. Subsequently, data migration processing is performed on the cold compressed data to transfer the data to a long-term storage solution (HDFS) to complete the cold data caching operation for the oil well site and ensure the efficient storage and management of cold data.

[0120] Preferably, step S52 includes the following steps:

[0121] Step S521: Perform performance test optimization on the relational database of the oil well site to generate the performance test optimization result; based on the performance test optimization result, perform optimization processing on the relational database of the oil well site to generate the storage database of the oil well site; perform database data segmentation processing on the storage database of the oil well site to generate the segmented data of the oil well site;

[0122] Step S522: Encrypt the segmented data of the oil well site using the AES encryption algorithm to generate the encrypted data of the oil well site and the AES key;

[0123] Step S523: Protect and manage the encrypted data of the oil well site and the AES key to generate the encrypted database of the oil well site.

[0124] In the embodiments of the present invention, performance testing and optimization are carried out on the relational database of the oil well site. This process uses a performance testing tool (MySQL Benchmark) to evaluate the performance of the database under different loads. The performance testing includes key metrics such as query response time, data throughput, and transaction processing speed. According to the test results, the generated performance testing optimization results will provide data support for the further optimization of the database. The optimization process includes adjusting database configuration parameters (such as cache size, connection pool settings), rebuilding indexes, optimizing query statements, partitioning table structures, and adjusting database design to improve the response speed and processing capacity of the database. The optimized database is called the oil well site storage database. Data segmentation processing is to improve the management efficiency and performance of the database by splitting large-scale data tables into multiple smaller parts, which are split according to data ranges (such as time intervals) or data partitions (such as regions). The segmented data is called oil well site segmented data, aiming to reduce the scanning range during query, improve data retrieval efficiency, and improve the performance of backup and recovery operations. The oil well site segmented data is encrypted through the AES encryption algorithm. The Advanced Encryption Standard (AES) is a symmetric encryption algorithm widely used for data protection. The AES encryption algorithm encrypts data through a key, converting the original data into ciphertext, thereby ensuring the confidentiality of data during storage and transmission. This step generates oil well site encrypted data and an AES key. The AES key is necessary for decrypting the ciphertext and needs to be properly managed and protected to prevent unauthorized access. Data encryption is a key step in data protection, ensuring that data cannot be interpreted by unauthorized users even if the storage medium is leaked or accessed improperly. The protection management of encrypted data and keys includes the secure storage of keys, access control, and key lifecycle management. The secure storage of keys utilizes a Hardware Security Module (HSM) to prevent key leakage or theft. Strict access control measures need to be implemented to ensure that only authorized users can access the keys. It also includes the regular replacement and update of keys to enhance the continuity and security of data protection. This process generates an oil well site encrypted database, which, as a database system integrating encryption and protection measures, ensures the security and confidentiality of oil well site data during storage and processing.

[0125] Preferably, step S53 includes the following steps:

[0126] Step S531: Preset the data integrity threshold of the oil well site; store the hot data and cold data of the oil well site in the oil well site encrypted database to generate the oil well site storage data;

[0127] Step S532: Compare and process the stored data of the oil well site with the data integrity threshold of the oil well site. When the stored safety data is less than the data integrity threshold of the oil well site, the standardized safety data set is determined as missing stored data, and data cleaning processing is performed on the missing stored data; when the stored safety data is greater than or equal to the data integrity threshold of the oil well site, the standardized safety data set is determined as stored information data;

[0128] Step S533: Perform supervised learning processing on the stored information data to generate secure stored data;

[0129] Step S534: Securely store the secure stored data in the database to complete the data storage operation of the oil well site.

[0130] In the embodiment of the present invention, a data integrity threshold of the oil well site is set, which is a reference value for measuring whether the data meets the integrity standard. The data integrity threshold is based on data quality standards and business requirements, including data accuracy, integrity, and non-redundancy. After the hot data and cold data of the oil well site are stored in the encrypted database of the oil well site, the stored data of the oil well site is generated. This data storage process includes writing the standardized data set into the encrypted database to ensure the confidentiality and security of the data during storage. The generation of the stored data of the oil well site is a key link in the entire data storage management process, providing basic data for subsequent data verification and processing. By comparing and processing the stored data of the oil well site with the preset data integrity threshold, data integrity verification is performed. The purpose of this comparison process is to confirm whether the stored data meets the predetermined integrity standard. When the stored data is less than the integrity threshold, the data is determined as missing stored data, indicating that there are problems such as data missing or damage in the data set. For this, data cleaning processing is implemented, aiming to delete or repair the missing stored data to prevent incomplete or incorrect data from having a negative impact on subsequent analysis. In contrast, when the stored data is greater than or equal to the integrity threshold, the data is determined as stored information data, indicating that it meets the integrity requirements and can be used for subsequent processing and analysis. By using the labeled data set to train the model, it can identify and predict the patterns of the data. In this process, supervised learning algorithms are applied to the stored information data to identify potential patterns and anomalies in the data, thereby generating secure stored data. This processing step helps to further improve the data quality, identifying and correcting potential data problems through learning algorithms to ensure the reliability and effectiveness of the data. Finally, the generated secure stored data is securely stored in the database. This process involves storing the processed data in the database and applying secure storage measures to protect the data from unauthorized access and potential security threats.

[0131] The beneficial effects of the present invention are as follows: By obtaining oil well site data, real-time monitoring of key on-site data is achieved, providing basic data support for subsequent analysis and decision-making. Establishing an external data source and obtaining data collection instructions through a preset data management system realizes an effective connection between the well site data and the external data source, generates a transmission connection instruction, and performs security detection and processing on it to ensure the security of data during transmission, thereby generating a data security connection instruction. This process not only ensures the accuracy of data transmission but also prevents potential security threats through security detection. Sending the oil well site data to the external data source according to the data security connection instruction and performing data filtering processing to generate a preliminary secure data set. This step effectively eliminates unnecessary or redundant data through data filtering, improving the quality and usability of the data. Performing data preprocessing on the preliminary secure data set to generate a standardized secure data set. The data preprocessing steps include operations such as data cleaning, missing value filling, and format unification, further improving the integrity and consistency of the data and laying a solid foundation for subsequent data analysis and applications. Establishing an oil well site data storage database and performing reinforcement processing to generate an encrypted database, and storing the standardized secure data set in the encrypted database to ensure the security of data storage. The encryption process protects the data through encryption algorithms, preventing unauthorized access and data leakage, and ensuring the privacy and security of the data. The acquisition of the finally securely stored data not only realizes the secure storage operation of the oil well site data but also provides high-quality and highly secure basic data for subsequent data analysis, mining, and decision support. Therefore, through the full life cycle management of the oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption and other links, the present invention realizes the high-quality, integrity, and security management of data, improving the reliability and analysis value of the data. Through the full life cycle management of the oil well site data, from data collection, transmission, security detection, preprocessing to storage encryption and other links, the present invention realizes the high-quality, integrity, and security management of data, improving the reliability and analysis value of the data.

[0132] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be encompassed within the present invention.

[0133] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A method for storing oil well site data based on a database, characterized in that: The following steps are involved: Step S1: Acquire oil well site data; Step S2: Establishing an external data source; Obtain data collection instructions for oil well sites; Based on the preset data management system, the oil well site data acquisition instruction is connected with the external data source for data transmission, a transmission connection instruction is generated, and the transmission connection instruction is processed for data security detection, thereby generating the oil well site data security connection instruction. Step S2 includes the following steps: Step S21: Establish an external data source through the cloud platform; obtain oil well site data collection instructions; Step S22: using a preset data management system to perform data transmission connection processing according to the oil well site data collection instruction and the establishment of an external data source, thereby generating a data transmission connection instruction; Step S23: generating a data transmission strategy for the oil well site for the data transmission connection instruction, generating a data transmission safety strategy for the oil well site, wherein the data transmission safety strategy for the oil well site includes a safety data passing strategy and a safety blocking strategy; performing transmission path optimization processing on the data transmission connection instruction based on the safety data passing strategy to execute the data transmission safety strategy for the oil well site; performing risk control monitoring processing on the data transmission connection instruction based on the safety blocking strategy to execute abandonment processing; Step S24: Performing security detection processing on the data transmission connection instruction based on the oil well site data transmission security policy, and generating the oil well site data security connection instruction; Step S3: sending the oil well field data to an external data source according to the oil well field data security connection instruction, and performing data filtering processing on the oil well field data to generate a preliminary oil well field security data set; Step S4: preprocessing the preliminary safety data set of the oil well site to generate a standardized safety data set of the oil well site; Step S5: Establish an oil well site data storage database, and reinforce the oil well site data storage database to generate an oil well site encrypted database; store the standardized security data set in a preset cache database for load balancing cache processing to generate oil well site hot data and oil well site cold data; store the oil well site hot data and oil well site cold data in the oil well site encrypted database for data storage processing to obtain secure storage data, so as to realize the oil well site data storage operation.

2. The method for storing oil well site data based on a database according to claim 1, characterized in that: Step S23 includes the following steps: Step S231: generating a data transmission strategy for the oil well site for the data transmission connection instruction, generating a data transmission security strategy for the oil well site, wherein the data transmission security strategy for the oil well site includes a security data passing strategy and a security blocking strategy; performing a strategy discrimination on the data transmission connection instruction based on a preset evaluation standard threshold, generating an oil well site strategy discrimination result, wherein the oil well site strategy discrimination result includes a security data passing result and a security blocking result; Step S232: When the oil well site strategy identification result is a safety data passing result, the safety data passing strategy is applied to perform transmission path optimization processing on the data transmission connection instruction to generate path optimization data, and the oil well site data transmission safety strategy is executed through the path optimization data; Step S233: When the oil well site strategy judgment result is a safety blocking result, the safety blocking strategy is applied to perform risk control monitoring processing on the data transmission connection instruction to generate oil well site risk control data; the oil well site risk control data is subjected to dangerous data identification processing to generate oil well site identification data, and discard processing is performed.

3. The method for storing oil well site data based on a database according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: using the secure socket layer protocol to establish a data transmission channel to generate an oil well site data transmission channel; Step S32: sending the oil well site data to an external data source through an oil well site data transmission channel to generate a data set, thereby generating an oil well site sending data set; Step S33: performing invalid data filtering processing on the data set sent by the oil well site to generate an oil well site data filtering data set; performing safety information processing on the oil well site data filtering data set to generate an oil well site preliminary safety data set.

4. The method for storing oil well site data based on a database according to claim 3, characterized in that: Step S32 includes the following steps: Step S321: Packaging and encrypting the oil well site data through AES encryption to generate oil well site encrypted data and oil well site decrypted data packets, wherein the oil well site decrypted data packets include oil well site timestamp and oil well site check code data; Step S322: sending the oil well site encrypted data to an external data source through an oil well site data transmission channel to generate a data set, thereby generating an external encrypted data set; Step S323: decrypt the external encrypted data set using the oil well site timestamp and the oil well site verification code data to generate an oil well site sending data set.

5. The method for storing oil well site data based on a database according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing data block processing on the preliminary safety data set of the oil well site to generate a block data set of the oil well site; Step S42: performing data cleaning processing on the oil well site block data set to generate an oil well site cleaning data set; performing data enhancement processing on the oil well site cleaning data set to generate an oil well site enhanced data set; Step S43: performing data set standardization processing on the oil well site enhanced data set, thereby obtaining a standardized safety data set of the oil well site.

6. The method for storing oil well site data based on a database according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: constructing an oil well site relational database; storing the standardized security data set in a preset cache database for load balancing cache processing, and generating oil well site hot data and oil well site cold data; Step S52: optimizing the performance test of the oil well site relational database and generating a performance test optimization result; optimizing the oil well site relational database based on the performance test optimization result and generating an oil well site storage database; reinforcing the oil well site storage database using database security reinforcement measures and generating an oil well site encrypted database; Step S53: storing the hot data and cold data of the oil well field in the oil well field encryption database for data storage processing, generating secure data storage data, and completing the oil well field data storage operation.

7. The method for storing oil well site data based on a database according to claim 6, characterized in that: Step S51 includes the following steps: Step S511: Design a storage table structure using an entity-relationship model, and perform paradigm standardization processing on the storage table structure to generate a standard database; perform index constraint processing on the standard database using MySQL commands to generate an oil well field standard database; perform relational testing on the oil well field standard database to generate an oil well field relational database; Step S512: storing the standardized security data set in a preset cache database for load balancing cache processing to generate oil well field cache data; dividing the oil well field cache data into frequency data based on data update status and data access frequency to generate oil well field hot data and oil well field cold data; Step S513: perform hot data sharding processing on the hot data of the oil well site to generate hot concurrent data; perform multi-point cache processing on the hot concurrent data to complete the hot data cache operation of the oil well site; perform cold data compression processing on the cold data of the oil well site to generate cold compressed data of the oil well site; perform data migration processing on the cold compressed data of the oil well site to complete the cold data cache operation of the oil well site.

8. The method for storing oil well site data based on a database according to claim 6, characterized in that: Step S52 includes the following steps: Step S521: Perform performance test optimization on the oil well site relational database to generate performance test optimization results; optimize the oil well site relational database based on the performance test optimization results to generate an oil well site storage database; perform database data segmentation on the oil well site storage database to generate oil well site segmentation data; Step S522: encrypt the oil well site segmented data using the AES encryption algorithm to generate oil well site encrypted data and an AES key; Step S523: Protect and manage the oil well site encrypted data and AES keys to generate an oil well site encrypted database.

9. The method for storing oil well site data based on a database according to claim 6, characterized in that: Step S53 includes the following steps: Step S531: Preset the oil well site data integrity threshold; store the oil well site hot data and the oil well site cold data in the oil well site encryption database to generate oil well site storage data; Step S532: Compare the oil well site storage data with the oil well site data integrity threshold. When the safety data storage data is less than the oil well site data integrity threshold, the standardized safety data set is determined as missing storage data, and the missing storage data is cleared; when the safety data storage data is greater than or equal to the oil well site data integrity threshold, the standardized safety data set is determined as storage information data. Step S533: Perform supervised learning processing on the storage information data to generate secure storage data; Step S534: securely store the securely stored data in a database to complete the oil well site data storage operation.

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