Using Measurement-Informed Inventory to Assess Emissions in the Denver-Julesburg Basin

Aerial surveys, while effective in detecting emissions from upset conditions, face challenges in fully capturing CH4 emissions due to their temporal limitations, variability in measurements, and detection thresholds. Conversely, annual inventories submitted by operators likely don’t include emissions from failure events. This study introduces a novel methodology that utilizes the Mechanistic Air Emissions Simulator (MAES) to integrate two highly variable estimation methods: inventory and aerial methods. The proposed methodology identifies and characterizes failure events with site-specific information, thereby enhancing the accuracy of inventory programs through the so-called measurement-informed inventories (MIIs). Furthermore, it emphasizes the importance of carefully comparing instantaneous emission measurements from aerial surveys with annual average emissions reported in inventories, as they have distinct timeframes. Colorado State University (CSU) collaborated with the Colorado Department of Public Health and Environment (CDPHE) to utilize this approach to enhance reported emissions from the upstream sector in Colorado Denver-Julesburg (DJ) basin. This initiative is part of the state’s efforts to reduce emissions under the Upstream greenhouse gas (GHG) Intensity Program. The goal was to incorporate measured emissions from failure events conducted by Carbon Mapper (CM) in the simulations to derive a multiplier that rectifies for potential omissions of emissions from abnormal conditions within the oil and gas (O&G) sector. To simplify the simulation process, prototypical sites were defined in conjunction with operators and are used to represent groups of O&G facilities in the basin with similar configuration. The outcomes of this work indicate that inventories are likely underestimating total emissions, as an additional 16.4% of total emissions from abnormal events is estimated for the basin.