Application Of Real-time Data Fast Algorithm For Oil And Gas Production Index

In recent years, the Internet of things(IOT) technology gets rapid development in all fields, in order to speed up the information construction in the business field, China Petrol sets about the construction of IOT of oil and gas production. In IOT of oil and gas production, real-time database system is the open structure between the application service layer and production data acquisition layer. It needs to retrieve the required real-time production data rapidly in a specified limited time. Index is an effective tool to realize the data to be rapidly retrieved. In the process of the IOT construction of oil and gas production, the study of establishing an indexing system suitable for real-time memory database is significant.First of all, the paper introduces several kinds of commonly used indexing technology in the database, and attaches importance on T tree and B+tree index system and the insert, query and delete method of the two systems. Then the paper gives a summary of the deficiency of these traditional indexing algorithms in the real-time database IOT. Based on the traditional indexing technology, a new tree structure:L+tree is introduced. The paper focuses on the study of the algorithm of L+tree structure, and summarizes its biggest improvements to the T tree:add a subsequent node pointer in each node, which is easy for the rapid range query data. The paper proves by theory that this improvement can make the system realize the rapid range query data, which can save a lot of time when making a query operation.Then, combined with the overall design of IOT system, the design realizes automatic production data collection, fast query, remote monitoring, warning, support for oil and gas production process management and further improvement of the timeliness and accuracy of oil and gas field production are needed in IOT through the establishment of real-time database platform. For the realization of the system to the specific requirements of the rapid retrieval of production data, the L-tree indexing algorithm is applied to the design of real-time database. Specific steps are as follows:first, to establish the L+tree index application model, mainly including the cached data module, L+tree index module, data acquisition module, integrated application module, data processing module and so on, five big modules, and the function of each module is introduced in detail. Then the function of the application process of L+tree index model is introduced in detail, and other processes.At last, the design simulates the data points that the experiment required through the matrikonOPC server, establishes the corresponding interface to the OPC server data in the real-time database system (real-time database created T+tree index tree index and L before the comparison experiment), simulates real-time accusation for the real-time database performance, namely the data query performance and insert performance were tested.the experiment proves that L+tree is better than T tree in the query performance, and can satisfy the specific requirements to improve memory space utilization as far as possible and to realize rapid query of the real-time data in the system.