ABSTRACT
Quantifying and controlling fugitive methane emissions from oil and gas facilities remains essential for addressing climate goals, but the costs associated with monitoring millions of production sites remain prohibitively expensive. Current thinking, supported by measurement and simple dispersion modelling, assumes single-digit parts-per-million instrumentation is required. To investigate instrument response, the inlets of three trace-methane (sub-ppm) analyzers were collocated on a facility designed to release gas of known composition at known flow rates between 0.4 and 5.2 kg CH4 h-1 from simulated oil and gas infrastructure. Methane mixing ratios were measured by each instrument at 1 Hertz resolution over nine hours. While mixing ratios reported by a cavity ring-down spectrometer (CRDS)-based instrument were on average 10.0 ppm (range 1.8 to 83 ppm), a mid-infrared laser absorption spectroscopy (MIRA)-based instrument reported short-lived mixing ratios far larger than expected (range 1.8 to 779 ppm) with a similar nine-hour average to the CRDS (10.1 ppm). We suggest the peaks detected by the MIRA are likely caused by a micrometeorological phenomenon, where vortex shedding has resulted in heterogeneous methane plumes which only the MIRA can observe. Further analysis suggests an instrument like the MIRA (an optical-cavity-based instrument with cavity size ≤10 cm3 measuring at ≥2 Hz with air flow rates in the order of ≤0.3 slpm at distances of ≤20 m from the source) but with a higher detection limit (25 ppm) could detect enough of the high-concentration events to generate representative 20 min-average methane mixing ratios. Even though development of a lower-cost, high-precision, high-accuracy instrument with a 25 ppm detection threshold remains a significant problem, this has implications for the use of instrumentation with higher detection thresholds, resulting in the reduction in cost to measure methane emissions and providing a mechanism for the widespread deployment of effective leak detection and repair programs for all oil and gas infrastructure.
ABSTRACT
Detecting and quantifying subsurface leaks remains a challenge due to the complex nature and extent of belowground leak scenarios. To address these scenarios, monitoring and evaluating changes in gas leakage behavior over space and time are crucial for ensuring safe and efficient responses to known or potential gas leaks. This study demonstrates the capability of linking environmental and gas concentration data obtained using a low-cost, near real-time methane (CH4) detector network and an inverse gas migration model to capture and quantify non-steady state belowground natural gas (NG) leaks. The Estimating Surface Concentration Above Pipeline Emission (ESCAPE) model was modified to incorporate the impact of soil properties on gas migration. Field-scale controlled NG experiments with leakage rates ranging from 37 to 121 g/h indicate that elevated belowground near-surface (BNS) gas concentrations persist long before elevated surface concentrations are observed. On average, BNS CH4 concentrations were 20%-486% higher than surface CH4 concentrations within the monitoring radius of 4 m from the leak location. An increase in the BNS CH4 concentration was observed within 3 h as the leak rate increased from 37 to 89 g/h. However, due to the atmospheric fluctuations, any changes in surface CH4 concentrations could not be confirmed within this period. The plume area of the BNS CH4 extended approximately two times farther than that of the surface CH4 as the gas leak rate increased from 37 to 121 g/h. The estimated NG leak rates by the modified ESCAPE model agreed well with the experimental NG leak rates (m = 0.99 and R2 = 0.77), demonstrating that including soil characteristics and BNS CH4 measurements can advance estimations of non-steady NG leak rates in low and moderate NG leak rate scenarios. The CH4 detector network and model show potential as an innovative tool to improve operators' risk assessment and NG leakage response.
