【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
【机 构】
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Prairie View A&M University,Prairie View,Texas,USA
【出 处】
：
2017年第五届数字油田国际学术会议(DOFIAC2017)
论文部分内容阅读
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.
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