Use of Mechanistic Modeling to Improve Failure Mode Representation in Oil and Gas Emission Studies

Accurately quantifying methane emissions from oil and gas facilities remains challenging due to the influence of rare, short-duration, high-rate events that are often excluded from traditional inventories. We present the Mechanistic Air Emissions Simulator (MAES), a discrete-event, state-based modeling framework that integrates mechanistic equipment models with stochastic failure modes to estimate facility-level emissions over long time periods. MAES was applied to an example single-well production site with a closed vent system (CVS) and atmospheric storage tanks, simulating both nominal operation and failure scenarios such as stuck dump valves and overpressure events. Monte Carlo simulations generated distributions of emissions rather than single-point estimates, enabling direct comparison between inventory-equivalent outputs and realistic operational cases (including rare events). Results show that rare events─accounting for only ∼1% of simulated hours─substantially increase annualized emission rates by an order of magnitude. Sensitivity to CVS capacity was also evaluated: increasing gas handling capacity by 41.9% reduced annual average emissions by 14.3%, with diminishing returns for large events. These findings demonstrate the utility of MAES for bridging the gap between regulatory inventory methods and observed emissions, supporting improved facility design, targeted mitigation, and iterative calibration as new field and continuous monitoring data become available.