TY - GEN
T1 - Better drilling through sensor analytics
T2 - 5th International Workshop on Knowledge Discovery from Sensor Data, SensorKDD'11 - Held in Conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD-2011
AU - Gupta, Chetan
AU - Viswanathan, Krishnamurthy
AU - Choudur, Lakshminarayan
AU - Hao, Ming
AU - Dayal, Umeshwar
AU - Vennelakanti, Ravigopal
AU - Helm, Paul
AU - Dev, Anil
AU - Manjunath, Sunil
AU - Dhulipala, Sastry
AU - Bellad, Sangamesh
PY - 2011
Y1 - 2011
N2 - In this paper, we present our Live Operational Intelligence (LOI) framework for developing, deploying, and executing applications that mine and analyze large amounts of data collected from multiple data sources to help operations staff take more informed decisions during management of operations in various industry verticals. We illustrate the use of the LOI framework with a case study from oil and gas drilling operations. The application involves characterizing and profiling on-shore wells being tapped for natural gas, and using this knowledge to construct a real-time operational intelligence engine for monitoring oil and gas drilling operations.
AB - In this paper, we present our Live Operational Intelligence (LOI) framework for developing, deploying, and executing applications that mine and analyze large amounts of data collected from multiple data sources to help operations staff take more informed decisions during management of operations in various industry verticals. We illustrate the use of the LOI framework with a case study from oil and gas drilling operations. The application involves characterizing and profiling on-shore wells being tapped for natural gas, and using this knowledge to construct a real-time operational intelligence engine for monitoring oil and gas drilling operations.
KW - Case study
KW - Operational intelligence
KW - Sensor data analytics
UR - http://www.scopus.com/inward/record.url?scp=80051691537&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80051691537&partnerID=8YFLogxK
U2 - 10.1145/2003653.2003654
DO - 10.1145/2003653.2003654
M3 - Conference contribution
AN - SCOPUS:80051691537
SN - 9781450308328
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 8
EP - 15
BT - Proc. of the 5th International Workshop on Knowledge Discovery from Sensor Data, SensorKDD'11 - Held in Conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD-2011
Y2 - 21 August 2011 through 24 August 2011
ER -