THE CHALLENGE
In pursuit of achieving near-zero upstream methane intensity emissions by 2035, SOCAR faced a key challenge: effective processing and aligning methane emissions data coming from diverse measurement sources across its assets. While each asset provided relevant emissions data on a timely basis, variations in measurement techniques and formats created difficulties in consolidating and analyzing the information efficiently. This complexity led to delays in analysis and made it challenging to establish a consistent emissions baseline. The situation underscored the need for an integrated platform capable of automatically consolidating and analyzing methane emissions data across all assets, enabling faster, more consistent, and data-driven decision-making.
THE SOLUTION
To address this challenge, SOCAR, in collaboration with Boston Consulting Group (BCG), developed the Methane AI platform within the Caspian AI Institute—a centralized solution designed to streamline all methane-related activities. The platform consolidates data from multiple detection sources, including ground measurements, bottom-up measurement campaigns, and aerial observations from satellites and drones—to establish a reliable baseline and precisely track methane emissions in both space and time. It supports both SOCAR’s internal reporting processes and OGMP 2.0 annual submissions through automated quantification engines, enabling visualization, tracking and analysis of emissions.
Operators use heatmaps to identify critical leak points, while dashboards and abatement curves support decision-making and help optimize resource allocation. The system also automates data ingestion, flags inconsistencies, and facilitates emissions reconciliation, empowering asset teams to take timely action. As a result, SOCAR significantly improved data transparency, quick processing, and established a foundation for consistent emissions tracking and targeted reductions—accelerating progress toward its methane targets.
Expanding impact
The implementation of Methane AI at SOCAR demonstrated that scalable, accurate methane management requires both technological innovation and strong cross-functional collaboration. One key lesson was the importance of integrating data from diverse sources—static infrastructure, operational metrics, and field-based measurements—into a single, standardized platform to enable effective quantification and reconciliation.
A key success factor was designing the platform to support both internal reporting needs and the requirements set by OGMP 2.0, enabling emissions data to be consistently structured, verified, and ready for submission. By embedding abatement tracking and aligning with reporting requirements, the platform supported both compliance and measurable progress toward SOCAR’s methane reduction targets.
For other signatories, an actionable recommendation is to leverage existing systems used by OGDC Signatory members, such as Methane AI platforms that automate data flows and incorporate verification steps early in the process to ensure accuracy and completeness. Finally, building technical capacity and organizational structure to operate and maintain these platforms is essential for achieving methane reduction goals.