Abstract
Abstract This paper presents the Digital Methane Emissions Atlas, a confidentiality-safe geospatial decision framework that converts heterogeneous methane observations into defensible operational decisions. Methane mitigation in oil and gas now depends less on isolated detection and more on integrating evidence into a single auditable workflow. The Atlas addresses this need through an episode-centric analytical chain spanning fusion, reconciliation, evidence assessment, prioritization, lifecycle tracking, hotspot intelligence, benchmarking, and monitoring design. Using a synthetic but structurally realistic Kazakhstan portfolio, the framework consolidates satellite, aerial, drone, LDAR, and fixed-sensor detections into fused methane episodes with preserved source lineage; reconciles event-level rates through a precision-weighted posterior; and converts observational heterogeneity into interpretable evidence consistency and decision readiness scores. Operational extensions estimate breach-oriented risk, expected abatement, intervention utility, recurrence-oriented follow-up needs, and closure likelihood. Representative outputs trace a high-priority episode from multi-source detection through posterior reconciliation, lifecycle interpretation, field benchmarking, and staged monitoring expansion under budget constraints. The contribution is a unified, methodology-first architecture rather than a single predictive model. The current implementation remains a synthetic, pre-linked, heuristic prototype rather than a fully calibrated industrial MRV platform, but it demonstrates a credible foundation for multi-scale methane decision support at event, field, and portfolio levels.