Goal:
Help upstream oil and gas operators minimize methane emissions, cut losses, and meet OGMP 2.0 and ESG compliance standards — automatically.
Impact Keywords:
- Methane Abatement
- ESG Compliance
- Emission Intelligence
- RegTech Automation
Approach:
LunarTech Lab built a unified AI platform that ingests multi-source sensor data and converts it into actionable emission insights.
- Multi-Source Data Fusion:
- Combined satellite, drone, and on-site sensor data to detect leaks and correlate them to specific equipment or sites.
- AI-Based Quantification:
- Used deep-learning and physics-based regression to estimate emission volumes, even under varying atmospheric conditions.
- Automated Prioritization:
- Ranked leaks by repair urgency, lost-gas value, and compliance risk, automatically triggering maintenance tickets.
- ESG Reporting Automation:
- Generated standardized, regulator-ready reports aligned with OGMP 2.0 and regional carbon-reporting templates.
- Continuous Learning:
- Models retrained monthly with new satellite imagery and field feedback, improving detection accuracy over time.
Summary:
This project gave operators real-time methane visibility, enabling them to capture lost product and avoid ESG penalties. The system automated 80% of manual reporting and reduced methane intensity by up to 35%.
