Real-time Monitoring Method Of Steam Dryness For The Steam Boiler

The steam injection is the most effective method in heavy oilproduction. This method is through put the steam that is hightemperature and high pressure injected the oil well to reduce theviscosity of heavy oil, which is convenient for its exploitation. Thedryness of wet steam in heavy oil thermal recovery technology is one ofmain index, which is not only relates to the quality of produced heavyoil, but also plays an indispensable role on the oilfield equipment’ssafety operation. In order to ensure the quality of produced heavy oiland high efficiency operation of thermal recovery device, monitoringsteam dryness in real-time and accurate has become a universalconcerned hot issue at home and abroad. This thesis is based on a seriesof parameters of having effect for the steam dryness, through the neuralnetwork, combined the soft measurement technology and wet steamphysical properties to research the measurement method of steamdryness.First of all, for the problem of oilfield steam injection boiler‘srunning safety and heavy oil‘s exploitation, put forward to theimportance of studying steam dryness measurement method, andanalyzed the work flow and system function of steam injection boiler.Obvious the dryness measurement problem and lays a theoreticalfoundation for researching the steam dryness measuring method.Secondly, based on analyzing of existing steam drynessmeasurement methods at home and abroad, investigate and study a series of affecting the steam dryness parameters to find out twoparameters which are the temperature and pressure. They have a greatinfluence on the steam dryness. And analyze the physical properties forthe whole process of the water from liquid to gas. The analysis showsthat: as the temperature increases the volume will become large in theprocess of water turns into gas. Also steam dryness increases as thetemperature rises. Thereby an idea is that between the steam drynessand volume change exist some inherent contact. Therefore the neuralnetwork was chosen to establish this function relationship. Using thetemperature, pressure and volume flow rate as input parameters andsteam dryness as output parameter created a RBF neural network steamdryness measurement model. Thus the volume change type steamdryness measuring method is put forward. And through the MATLABsoftware simulation test and verify the effectiveness of thismeasurement method.Finally, put the volume change type steam dryness measurementmethod used in the real-time monitoring system to measure the steamdryness. The host computer of this system has function of monitoringsteam dryness, alarming, data query and so on. Combination of the tworealizes the on-line monitoring function of the steam dryness measuringmethod.