Challenge

• Large oil producer was interested in understanding the ongoing effectiveness of their downhole pumps to lift fluid to the surface.
• Pumpjack failures proved difficult to detect using rule-based diagnostic methods and often led to expensive field failures and lost production

Solution

• Created a unified view for wells over time by combining dynamometer, operational, well maintenance, downtime, and performance failure data.
• Using Azure Machine Learning, Neal Analytics classified failure types to identify patterns of failure occurrences and allow for remote diagnostics of pre-failure conditions

Result

• Reduced cost of non-productive time and operations
• Increased Return on Assets by avoiding severe pump jack failures.
• Optimized maintenance schedules based on risk probabilities.