Chevron, ConocoPhillips, ExxonMobil Deploy AI-Driven Automation

Major operators automate artificial lift operations

Chevron, ConocoPhillips and ExxonMobil are advancing their artificial lift and production optimization strategies by incorporating new automation technology and operational techniques, according to Hart Energy.

The companies are deploying systems that go beyond traditional pumping equipment to optimize well performance at scale. Among the technologies being implemented is GEORGE — an acronym for generative engineering orchestration and real-time ops guidance engine — which represents a new class of AI-powered tools designed to support field operations.

Why it matters

Artificial lift systems are critical infrastructure for maintaining production as wells mature and natural reservoir pressure declines. By automating lift optimization and integrating real-time operational guidance, operators can reduce downtime, extend equipment life, and improve recovery rates across large well portfolios. The shift toward AI-driven automation reflects broader industry efforts to extract more value from existing assets while managing operational costs in a capital-constrained environment.

Evolution beyond conventional lift management

The three supermajors are moving past conventional artificial lift management approaches by integrating automation platforms that can process real-time data and provide operational recommendations. This evolution allows field teams to respond more quickly to changing well conditions and optimize lift performance across multiple assets simultaneously.

While specific deployment details were limited in the report, the adoption of generative AI tools like GEORGE signals a broader trend toward autonomous operations in upstream oil and gas. These systems are designed to synthesize engineering data, operational history, and real-time sensor information to guide decision-making in the field.

Industry-wide automation push

The moves by Chevron, ConocoPhillips and ExxonMobil align with wider industry efforts to digitize operations and reduce the manual intervention required to maintain production. Artificial lift optimization has historically been labor-intensive, requiring frequent adjustments based on well performance and equipment condition.

Automation platforms promise to handle routine optimization tasks while flagging anomalies that require human expertise. This approach aims to improve both operational efficiency and safety by reducing the need for personnel to visit remote well sites for routine adjustments.

These details were first reported by Hart Energy in their Automation Watch coverage.