This paper covers a case study demonstrating how automating greenhouse gas (GHG) calculations can improve accuracy, transparency, and efficiency across natural gas operations. This US case study from the Appalachian Basin shows how operational activity data and measurement inputs can be mapped directly into emissions estimation models, producing comprehensive inventories for carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). The automated methodology reduces human error common in spreadsheet-based reporting, integrates source-level emissions factors, and enables near real-time identification of emission-intensive processes. Beyond inventory generation, the framework supports emissions forecasting, allowing operators to model the impacts of operational changes, reduction technologies, and production planning on future carbon and methane intensities. The paper also discusses the potential of how requirements from Australian reporting frameworks, including the National Greenhouse and Energy Reporting Scheme, can be incorporated into automated workflows. Overall, the approach positions automated GHG quantification as both a compliance and operational intelligence capability supporting methane mitigation across upstream and midstream assets.
Solano et al. (Thu,) studied this question.
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