The French firm implemented Azure IoT Edge and Azure machine learning to offer enhanced solutions for oil and gas companies
French company Schneider Electric, which focuses on the digital transformation of energy management and automation, selected Microsoft’s Azure machine learning and Azure IoT Edge to add predictive capabilities to its solutions.
With this technology, the French company aims to solve the challenges faced by companies in the oil and gas sector without easy access to the cloud based on location, and which may be reluctant to send data outside their own networks.
Schneider Electric has developed tools for monitoring and managing resource production and consumption. The firm uses EcoStruxure—its IoT-enabled, open-architecture platform—as a hub for collaborating across its ecosystem of partners to deliver real-time control and operational efficiency.
Schneider Electric solutions are implemented by oil and gas companies that may have thousands of pumps spread over a large geographic area. “With the volatility of oil prices, producers are under tremendous pressure to shrink production costs and increase efficiency,” said Fahd Saghir, industry solutions manager (Upstream O&G) for Schneider Electric. “We provide tools that help them do that.”
The firm’s Realift rod pump control allows companies to monitor and configure pump settings and operations remotely, only sending personnel onsite when necessary for repair or maintenance.
However, Schneider Electric was interested in enhancing Realift to provide additional capabilities including the ability to predict problems so they can be averted before a fault occurs. “If you look at most of the controllers that exist in the market today, they are reactive, looking at what is happening now and responding accordingly,” says Helenio Gilabert, Director for SCADA and Telemetry at Schneider Electric. “We want to be proactive and include predictive analytics at the edge.”
“Azure Machine Learning gave us the powerful intelligence we need, as well as flexible model management capabilities,” said Matt Boujonnier, analytics application architect for Schneider Electric. “And IoT Edge provided an easy way to package and deploy our machine learning applications. Traditionally, machine learning is something that has only run in the cloud, but for many IoT scenarios that isn’t good enough, because you want to run your application as close as possible to any events. Now we have the flexibility to run it in the cloud or at the edge—wherever we need it to be.”
Using machine learning tools gives Realift the ability to analyze readings from various elements of the rod pump mechanism and sense patterns that indicate a possible mechanical failure or a deviation from the pump’s optimal operating conditions. The solution can modify the operating parameters of the pump to avoid or mitigate the impact of the unexpected changes and it can also shut down the pump before any damage occurs and notify the company that repairs are necessary.
“One clear business benefit is operator efficiency,” says Saghir. “By proactively identifying pump problems through edge analytics, companies reduce unplanned downtime, which decreases costs, increases production, and increases the agility of maintenance services,” Saghir added.
