Osprey Informatics featured at natural resources AI event in Calgary
Join Osprey, IBM and Ambyint on April 12 at IBM Calgary for the Calgary AI Meetup. Details below:
The April meetup will be held at IBM’s office on 11th Avenue. The focus of this month’s meetup is to share how developments in artificial intelligence impacts industries close to home: natural resources extraction and the service companies who support the energy business.
First, Giovane Cesar de Silva will discuss how IBM Watson can improve operations, safety, and efficiency at natural resources companies. Giovane is a leader in IBM’s Natural Resources practice and a senior data scientist with IBM’s Advanced Analytics team. He has more than 15 years of experience in machine learning, forecasting, and optimization, spanning industries like banking, oil & gas, rail transport, and aviation. Giovane’s talk should provide interesting insights about how Watson is deployed in industry today and a good look at future opportunities.
Next, Rosalee Gordon, Director of Product for Osprey Informatics, and Dave Woods, Director of Development, will discuss how Osprey has leveraged computer vision to launch a new alerting system. Osprey Informatics provides a visual monitoring solution for industrial companies who have remote and distributed sites. Rosalee & Dave’s talk will cover the impact of computer vision to the performance of the alerting system, the challenges encountered along the way, and Osprey’s vision for leveraging AI for industrial monitoring going forward. Today, twenty oil & gas companies use Osprey to reduce operational costs and mitigate environmental, safety, and security risks.
Our final presenter for the evening will be Ryan Benoit, CTO of Ambyint. Ambyint complements traditional physics-based analysis for artificial lift optimization with modern artificial intelligence trained and tuned using the industry’s largest labeled data set. Enabled by this massive data set, Ambyint can detect key production issues proactively, including detection, characterization, and prediction of well anomalies or prediction of wellhead leaks.