A Methane Emission Estimation Tool (MEET) for predictions of emissions from upstream oil and gas well sites with fine scale temporal and spatial resolution: Model structure and applications

Estimation of natural methane emissions from the largest oil sand deposits on earth

Worldwide methane emission by various industrial sources is one of the important human concerns due to its serious climate and air-quality implications. This study investigates less-considered diffusive natural methane emissions from the world's largest oil sand deposits. An analytical model, considering the first-order methane degradation, in combination with Monte Carlo simulations, is used to quantitatively characterize diffusive methane emissions from Alberta's oil sands formations. The results show that the average diffusive methane emissions from Alberta's oil sands formations is 1.56 × 10-4 kg/m2/year at the 90th percentile of cumulative probability. The results also indicate an annual diffusive methane emissions rate of 0.857 ± 0.013 Million tons of CO2e/year (MtCO2e/year) from Alberta's oil sands formations. This finding suggests that natural diffusive leakages from the oil sands contribute an additional 1.659 ± 0.025 and 5.194 ± 0.079% to recent Canada's 2019 and Alberta's 2020 methane emission estimates from the upstream oil and gas sector, respectively. The developed model combined with Monte Carlo simulations can be used as a tool for assessing methane emissions and current inventories.

Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources

Distributions of methane emission rates originating from oil and gas production facilities are highly skewed and span 6-8 orders of magnitude. Traditional leak detection and repair programs have relied on surveys with handheld detectors at intervals of 2 to 4 times a year to find and fix emissions; however, this approach may lead unintended emissions to be active for the same interval independently of their magnitude. In addition, manual surveys are labor intensive. Novel methane detection technologies offer opportunities to further reduce emissions by quickly detecting the high-emitters, which account for a disproportionate fraction of total emissions. In this work, combinations of methane detection technologies with a focus of targeting high-emitting sources were simulated in a tiered approach for facilities representative of the Permian Basin, a region with skewed emission rates where emissions above 100 kg/h account for 40-80% of production site-wide total emissions, which include sensors on satellites, aircraft, continuous monitors, and optical gas imaging (OGI) cameras, with variations on survey frequency, detection thresholds, and repair times. Results show that strategies that quickly detect and fix high-emitting sources while decreasing the frequency of OGI inspections, which find the smaller emissions, achieve higher reductions than quarterly OGI and, in some cases, reduce emissions further than monthly OGI.

Reconciling Multiple Methane Detection and Quantification Systems at Oil and Gas Tank Battery Sites

Emission rates were estimated for >100 oil and gas production sites with significant liquid-handling equipment (tank battery sites) in the Permian Basin of west Texas. Emission estimates based on equipment counts and emission factors, but not accounting for large uninventoried emission events, led to ensemble average emission rates of 1.8-3.6 kg/h per site. None of the site-specific emission estimates for individual sites, based on equipment counts, exceeded 10 kg/h. On-site drone-based emission measurements led to similar emission estimates for inventoried sources. Multiple aircraft measurement platforms were deployed and reported emissions exceeding 10 kg/h at 14-27% of the sites, and these high-emission rate sites accounted for 80-90% of total emissions for the ensemble of sites. The aircraft measurement systems were deployed asynchronously but within a 5 day period. At least half of the sites with emission rates above 10 kg/h detected by aircraft had emissions that did not persist at a level above 10 kg/h for repeat measurements, suggesting typical high-emission rate durations of a few days or less for many events. The two aircraft systems differed in their estimates of total emissions from the ensembles of sites sampled by more than a factor of 2; however, the normalized distributions of emissions for sites with emission rates of >10 kg/h were comparable for the two aircraft-based methods. The differences between the two aircraft-based platforms are attributed to a combination of factors; however, both aircraft-based emission measurement systems attribute a large fraction of emissions to sites with an emission rate of >10 kg/h.

Multiscale Methane Measurements at Oil and Gas Facilities Reveal Necessary Frameworks for Improved Emissions Accounting

Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. Recent legislation in the United States requires updating current methane reporting programs for oil and gas facilities with empirical data. While technological advances have led to improvements in methane emissions measurements and monitoring, the overall effectiveness of mitigation strategies rests on quantifying spatially and temporally varying methane emissions more accurately than the current approaches. In this work, we demonstrate a quantification, monitoring, reporting, and verification framework that pairs snapshot measurements with continuous emissions monitoring systems (CEMS) to reconcile measurements with inventory estimates and account for intermittent emission events. We find that site-level emissions exhibit significant intraday and daily emission variations. Snapshot measurements of methane can span over 3 orders of magnitude and may have limited application in developing annualized inventory estimates at the site level. Consequently, while official inventories underestimate methane emissions on average, emissions at individual facilities can be higher or lower than inventory estimates. Using CEMS, we characterize distributions of frequency and duration of intermittent emission events. Technologies that allow high sampling frequency such as CEMS, paired with a mechanistic understanding of facility-level events, are key to an accurate accounting of short-duration, episodic, and high-volume events that are often missed in snapshot surveys and to scale snapshot measurements to annualized emissions estimates.