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The Development And Application Of Oil Well Production Monitoring System

Posted on:2014-06-10Degree:MasterType:Thesis
Country:ChinaCandidate:C ZhaoFull Text:PDF
GTID:2271330503455672Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the release of "four modernizations" management model and promotion of deeply integration of two modernizations(industrialization and informatization) in Shengli Oilfield, more and more information technologies are applied in oil field production. In order to better grasp the production parameters of oil wells, some remote monitoring and control systems have been successively applied in oil fied since 2003, but due to various reasons, these systems failed to provide technical support for production. There is a lack of effective monitoring and management mothod for working status of oil well system.In view of the above situation, this paper proposes to establish a set of perfect monitoring and control system for oil production with the application of information technology.The technology is based on independently-developed oil well site control centre, it combines protection, control, acquisition and transmission in one, in the premise of cost reduction, improving a variety of functions and the application becomes more stable. With geographic information system and oil production engineering database, the software of background management establishs a real-time intelligent diagnose and early warning system. The technology greatly upgrade and improve the site application function and stability, the background management system monitors the operation rate and status of oil well, pre-diagnoses the balance rate, mechanical efficiency and downhole conditions, provides energy consumption prediction for power management and energy saving management. It changes the oil well management model, from post-processing to early warning, improves the efficiency and increases the benefit.
Keywords/Search Tags:production parameter, remote monitor and control, intelligent diaganose, Energy consumption prediction
PDF Full Text Request
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