Scalable Intelligent Oilfield Streaming Data Analytics Platform

摘要：

　　Oilfield operations generate huge amounts of data from electronic sensors used to monitor well performance and reservoir characteristics.There is an immediate demand to have a scalable and intelligent oilfield data analytics framework in the data center to analyze these data in real-time to extract valuable insights,optimize both operation and safety,and make tactical decisions.We have designed a scalable intelligent oilfield streaming data analytics platform using modern big data technologies,which are capable of ingesting streaming sensor data from multiple wells,cleansing them to improve data quality,and conducting advanced analytics on them for statistical analysis,event detection,production forecasting,and visual analytics using machine/deep learning algorithms.

关键词： intelligent oilfield big data analytics machine learning

作者: D.M.Mistry Y.Zhu L.Huang

作者单位: Prairie View A&M University,Prairie View,Texas,USA

会议类型: 国内会议

会议名称: 2017年第五届数字油田国际学术会议(DOFIAC2017)

会议地点: 青岛

会议语种:英文

页码: 283-288

在线出版日期: 2017-10-15（万方平台首次上网日期，不代表论文的发表时间）