ガス集輸システムにおける精密炭素管理のためのデジタルデリバリーフレームワーク：階層的会計から削減最適化まで

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:デジタル炭素会計と階層的排出推計の統合手法、および実測校正による精度向上の実証例として参考になる。

🏢実務担当者:自社のメタン・GHG会計にTier3レベルの機器別管理とデータハブ設計を導入する際の具体的な実装モデルとして活用できる。

🏛政策担当者:メタン規制の執行・検証可能性を高めるため、事業者に求める会計精度やデジタル報告基盤の設計に示唆を与える。

With the tightening of global methane regulations (EU Methane Regulation 2024/1787, U.S. EPA GHG rules, OGMP 2.0) and China’s dual-carbon commitments, precise and traceable carbon accounting for natural gas gathering systems has become an urgent engineering imperative. To tackle manual workflows, data isolation, low precision, and poor traceability in carbon accounting for natural gas field surface systems, this study develops a four-tier digital delivery framework. The main goal is to establish an end-to-end engineering paradigm that transforms carbon management from passive post-hoc statistics into an active, traceable decision-support tool. By embedding carbon attributes into seed files and adopting a unified one-code-through equipment coding scheme, static design data, dynamic SCADA measurements, and emission factor databases are interoperably consolidated within a central data hub. The hub implements a three-stage progressive accounting workflow and closed-loop emission mitigation. Methodologically, a three-tier progressive accounting model (Tier 1: system-level, Tier 2: process-level, Tier 3: equipment-level) is constructed, with Tier 3 supported by OGMP 2.0 source-level emission factors locally calibrated against 386 field LDAR measurements. Deployed at Gas Field A, the framework realizes full diagram-model consistency and narrows systematic error from ±30% to ±3.5%. Tier-2 accounting quantifies gathering, compression, and dehydration emissions at 322,000, 504,300, and 162,500 tCO2e, while Tier-3 analysis pinpoints reciprocating compressors and heaters as the primary contributors (51.70% of total emissions). Optimizations including compressor energy conservation, enhanced LDAR, and waste heat recovery provide an estimated annual mitigation potential of 97,400 tCO2e (10.10%). In conclusion, this framework mitigates data fragmentation and accuracy defects, delivering a transferable technical route for oil and gas operators to advance methane abatement and dual-carbon targets.

• semanticscholar https://doi.org/10.3390/app16199516first seen 2026-09-29 05:45:35