# F&G Safety Opportunity MOC AI opportunity in fire & gas safety for O&G. GCC Fire Safety market: $1.9B → $3.2B by 2034. Qatar NFE alone is $30B+, scaling from 77→142 mtpa LNG by 2030. ## The Problem Stack Three high-value problems, ranked by $ impact: ### 1. [[False Alarm Problem in F&G]] - O&G downtime: $149M/year per site (76% increase since 2019) - Offshore: $220K/hour, avg 32 hrs/month unplanned = $84M/facility/year - 1% downtime (3.65 days) = $5M+ annual loss - AI reduces false alarms by 80% vs threshold systems ### 2. [[Predictive Maintenance in O&G]] - 30-40% of O&G budgets go to maintenance - Detecting bearing anomaly 18 days early prevents $700K loss - Shell: AI found 65 control valves traditional methods missed - BP: $10M annual savings from predictive systems ### 3. [[Compliance Automation in F&G]] - Manual tracking across thousands of devices - Fines, litigation, reputation damage from violations - 15% insurance cost savings via AI risk assessments - Qatar NFE needs largest CCS compliance in LNG industry ## The Moat [[Multi-Modal Anomaly Detection]] is the defensible play: - Computer vision + IoT sensor fusion - Learns facility-specific "normal" signatures (steam vs smoke, flaring vs fire) - Time-series anomaly detection on vibration, temperature, pressure, flow - Auto-generates compliance reports for NFPA/OSHA/ISO audits Revenue model: SaaS per facility + % of downtime prevented. Outcome-based pricing aligns with the $84M/year problem. ## Why Qatar/GCC - **Scale**: NFE = 6 mega LNG trains, world's largest non-associated gas field - **Greenfield**: New facilities adopt AI-native vs retrofit - **Capex intensity**: F&G safety is non-negotiable CAPEX - **Regulatory push**: GCC governments mandating advanced systems - **Density**: Ras Laffan = concentrated facility cluster ## Links **Fundamentals:** - [[Fire and Gas Detection MOC]] - [[F&G Control Systems]] - [[Safety Integrity Level - SIL]] **Defense:** - [[Defensibility Principles MOC]] --- #moc #opportunity #fire-and-gas #ai #qatar