Artificial-lift optimization begins with data — not AI

Artificial-lift performance depends on more than equipment selection. As wells, reservoirs and production networks continuously change, fragmented data often leads to reactive operations, unnecessary downtime and missed production opportunities. This executive brief explores how a unified, contextualized data foundation enables operators to move beyond isolated optimization efforts toward predictive, coordinated performance management. By connecting operational data, analytics and control systems, organizations can improve production, lower costs, extend asset life and establish a scalable path toward more autonomous operations.

Artificial-lift performance is shaped by changing well conditions, shifting reservoir behavior and constraints across shared production infrastructure. Yet many operators still rely on disconnected data sources and manual workflows that make it difficult to see what's happening in real time. This challenge grows as wells mature and lift systems must adapt to changing inflow, pressure, fluid levels and operating conditions.

This executive brief examines why successful artificial-lift programs start with a strong data foundation. It outlines how operators can bring together field, control-system and operational data to improve visibility, support faster decisions and create a path toward predictive performance management. Additionally, the brief explores what's required to connect operational data and analytics in ways that support more informed, data-driven lift management.

What You'll Learn:

• Why fragmented operational data makes artificial-lift optimization harder than it needs to be
• How a unified, contextualized data foundation supports better production decisions
• The five-stage progression from reactive operations to autonomous performance management
• Key technology and architecture requirements for connecting data, analytics and control systems
• Where operators can realize value through improved uptime, energy efficiency, equipment reliability and workforce productivity

Download the executive brief Artificial-lift optimization begins with data – not AI to learn how upstream operators are building the data foundation needed to improve lift performance, reduce operational friction and support long-term digital transformation goals.