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AI as Game-Changer: NLNG Puts Intelligence to Work for Safer, Cleaner LNG

AI as Game-Changer: NLNG Puts Intelligence to Work for Safer, Cleaner LNG
Olakunle Osobu, NLNG’s Deputy MD (centre) speaking during a panel session on “Operational Excellence through the Application of Artificial Intelligence Technologies” at the 2025 Gastech Exhibition and Conference in Milan, Italy, on Wednesday.

Milan/Lagos — Nigeria LNG (NLNG) is hard-wiring artificial intelligence across its value chain, calling AI the game-changer for efficiency, reliability and sustainability in gas operations. On the “Operational Excellence through AI” panel at Gastech 2025, Milan, Olakunle Osobu, Deputy Managing Director, said the company’s “Goal Zero” HSE policy and core operations KPIs are already improving with AI-enabled workflows.

NLNG is embedding AI into existing control and maintenance platforms—not as a pilot but as a controls-grade capability that unlocks predictive, preventive and corrective maintenance. Outcomes: higher asset uptime, fewer unplanned outages, and tighter emissions monitoring that supports the company’s energy-transition commitments.

On the people/process side, NLNG is using virtual reality (VR) and AI agents to accelerate onboarding and boost knowledge retention, while smart cameras and satellite analytics enhance visual inspections, safety compliance and right-first-time interventions. Process automation and AI optimisation are stabilising production, anticipating equipment stress, and prioritising maintenance windows without sacrificing throughput.

Value-first, not hype-first: Through its Centre of Excellence, NLNG is upskilling staff and gating use cases by ROI and risk—aligning AI with business needs rather than experimentation.


Why It Matters (for LNG Ops & Nigeria’s Gas Ambition)

  • Reliability economics: In LNG, a trip on a compressor/refrigerant loop can move millions. Predictive models for bearing wear, exchanger fouling and surge risk protect cargo schedules and working capital.
  • HSE uplift: Computer vision + analytics cut exposure hours, enforce permit-to-work discipline, and compress incident response, central to Goal Zero.
  • Methane & CO₂: AI-assisted leak detection and continuous monitoring help quantify and cut intensity, now required in differentiated LNG and financier due diligence.
  • Talent velocity: VR training and AI copilots reduce time-to-competence as plants digitise and veteran technicians retire.

Where AI Lands in an LNG Plant (Practical Map)

  • Rotating equipment: Predictive maintenance for compressors, turbines, pumps; anomaly detection on vibration, temperature, lube oil.
  • Process optimisation: Model-predictive control to balance energy use, minimise flaring, maximise LNG yield.
  • Integrity & inspection: CV on drones/cameras for corrosion/insulation damage/hot spots; satellite cues for perimeter and flare efficiency.
  • Operations support: AI agents for shift handover, alarm rationalisation, and SOP retrieval; VR for emergency drills and hazardous-area familiarisation.
  • Environmental performance: AI-driven emissions baselining, root-cause analytics, and MRV (measurement, reporting, verification).

Execution Risks to Manage (and How)

  • Data quality: Invest in sensor health, calibrated tags, and clean historians; bad data kills good models.
  • Cybersecurity: Treat AI as part of OT; enforce zero-trust, patch discipline and model governance.
  • Change management: Pair every model with a clear operator action; measure adoption via control-room KPIs.
  • Vendor sprawl: Standardise on interoperable stacks and open APIs to avoid stranded pilots.

What to Watch (Next 12–18 Months)

  1. Predictive hit-rate (false positives/negatives) and unplanned downtime trend.
  2. Energy use per tonne LNG and flaring/emissions intensity verified by MRV.
  3. HSE leading indicators: near-miss reporting quality, permit breaches, response times.
  4. Workforce metrics: onboarding time, competency scores, VR utilisation.

BRANDECONOMY Take

NLNG’s AI push qualifies as an game-changer because it sits inside the control loop—where minutes equal money and models meet metal. Keep focus on predictive reliability, emissions integrity and operator adoption, and AI becomes ROI: lower unit costs, stronger marketability of Nigerian LNG, and a regional benchmark for digital operations.

Bottom line: In LNG, AI pays when it is embedded, governed, and acted upon—converting buzzwords into avoided downtime and avoided emissions. The NLNG AI game-changer move will be refreshing as the results unfold.

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