Cenovus is a Canadian integrated oil and natural gas company headquartered in Calgary. We’re committed to maximizing value by responsibly developing our assets in a safe, innovative and efficient way. Our operations include oil sands projects in northern Alberta, which use specialized methods to drill and pump the oil to the surface, and established natural gas and oil production in Alberta and British Columbia.

In certain areas of Asset Management, Cenovus’s data-driven decision-making philosophy has had analytics play a major role in certain asset management activities. This presentation reviews 2 initiatives: How Text Analytics improved the quality of data used in Asset Failure analysis and how Machine Learning algorithms were used to derive models for Asset Failure prediction. Based on ongoing initiatives, the presentation provides insight into real-world opportunity definitions, ML algorithms, technology, data gathering/cleansing techniques, user-acceptance roadblocks and other learnings from an organizational perspective.

Learning Objectives:

• Understanding ROI for Data Science initiatives
• Understanding Data cleansing techniques
• Overcoming roadblocks to adoption, show business value