Team NOV - Anomaly Detection 

 

 

Project Title: Anomaly & Data Quality Detection for Oil & Gas operations using Deep Neural Networks 

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Description: In this project, we developed a fast, scalable, robust, and interpretable unsupervised anomaly detection algorithm for a historical drilling rig sensor dataset using machine learning and deep learning models. 

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Team Members: 

• Ye Tian (Professional Masters student, Statistics)

• Mengting Lei (Professional Masters student, Statistics) 

• Kyran Adams ('21 Computer Science)  

• Gayatri Sawant ('21 Computer Science)  

• Kyle Manning ('21 Statistics)

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Sponsor: NOV (National Oilwell Varco)

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Sponsor Mentors:

• Jon Walters - VP, Advanced Analytics, Controls, & Digital 

• Lance Staudacher - Senior Engineering Manager 

• Jae Yoon - Senior Data Scientist 

• Tim Williamson - Director, Data Governance 

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Faculty Mentor:

Dr. Arko Barman, Assistant Teaching Professor, D2K Lab