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Data as the New Oil: Producing Value in the Oil and Gas Industry
Oil and gas exploration and production activities generate large amounts of data from sensors, logistics, business operations and more. Given the data volume, variety and velocity, gaining actionable and relevant insights from this data is challenging. Learn about these challenges and how to address them by leveraging Big Data technologies in this webinar.
We will dive deep into a use case on predicting drilling equipment failure, a key step towards zero unplanned downtime. In the process of drilling wells, non-productive time due to drilling motor failure can be expensive. We will highlight how the Pivotal Data Labs team created a drilling motor failure prediction model from drill rig sensor data and drill operator data using Big Data technologies. Models such as these can be used to build essential early warning systems, reduce costs and minimize unplanned downtime.
Rashmi Raghu has extensive experience in executing complex analytics projects in multiple verticals. She is currently a Principal Data Scientist in the Pivotal Data Labs team at Pivotal with a focus on applications in the Internet-of-Things and the Energy sector. She holds a Ph.D. in Mechanical Engineering with a minor in Management Science & Engineering from Stanford University. Her doctoral research focused on the development of novel computational models of the cardiovascular system to aid disease research. Prior to that she obtained Master’s and Bachelor’s degrees in Engineering Science from the University of Auckland, New Zealand. Her professional interests include mathematical modeling and computational techniques for applications ranging from modeling physical systems to decision analysis.