Optimizing oil and gas equipment can be an impossible task when you cannot answer critical questions about health and performance: Is this well approaching the end of its life? Are we prepared to react to market changes? Why did this piece of equipment fail? When will we get it back up and running? How long until our next equipment failure?
The problem has become especially acute in recent years. The downturn in oil and gas prices has put pressure on producers to cut costs and get the absolute most from their assets. But it’s difficult to improve equipment availability and get ahead of failures when you don’t have real-time insights into performance, or when the data you do collect is confined to silos.
