Production teams are being asked to do more with less – managing larger well portfolios, responding to more alarms, and making faster decisions with the same headcount. The data is already flowing in from SCADA, but turning it into timely action is where traditional workflows fall short.
Traditional production optimization workflows often rely on manual surveillance, reactive troubleshooting, and static setpoints that struggle to keep pace with changing field conditions. With increasing operational complexity across wells, many producers are now looking to AI-powered optimization to help scale operations more efficiently.
In Ambyint’s recent webinar, Applying AI to Production Optimization, Kevin Anstrom, Solutions Engineering Manager and Sid Rothlisberger, Senior Solutions Manager, explore what production optimization actually means in the field – and how AI is enabling operators to move beyond reactive monitoring toward continuous, scalable optimization.
Ambyint’s Infinity platform integrates directly with existing SCADA and data acquisition systems, applying physics-informed AI to deliver continuous optimization across rod lift and plunger lift wells. By combining physics-based models, subject matter expert insights, and machine learning, the platform supports anomaly detection, autonomous setpoint management, and proactive failure prevention – reducing the manual workload on engineers and field staff and freeing teams to focus on higher-value activities.
The webinar explores:
- How AI can support continuous production optimization across large well portfolios
- The role of anomaly detection in identifying issues before failures occur
- How autonomous setpoint management reduces manual intervention
- Common optimization gaps in traditional workflows
- How physics-informed AI integrates with existing SCADA infrastructure
The session also highlights how production teams are shifting from reactive alarm management toward proactive, data-driven operations that enable engineers and field staff to focus on higher-value activities.
Watch the replay: Applying AI to Production Optimization
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