Internet of things and big data analytics for smart oil field malfunction diagnosis

With the rapid development of information technology and digital communication, the data types are more abundant by integration of various technologies. In this paper, based on the analysis of a large number of historical data of oil and water wells, the changes of some important parameters of the wells can be monitored and then used in the trend prediction and the early warning system. Subsequently, we use 6 Sigma algorithm to process the historical data, and by the big data trend analysis combining with various parameters, we can diagnose six operating conditions, such as sand production, abnormal of moisture content etc. Through experiments, the algorithm is stable and reliable in practical application, and it has great significance to ensure the normal production of oil field and improve the management ability for oil field.