DOI: 10.3390/app16199516 ISSN: 2076-3417

A Digital Delivery Framework for Precision Carbon Management in Gas Gathering Systems: From Tiered Accounting to Reduction Optimization

Xin Wu, Liuyi Tang, Zhixiang Dai, Mo Chen, Yao Liu, Jimao Dai, Libing Du, Xiayi Zhou

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.