Abstract

As energy systems transition towards decarbonization, natural gas is expected to play an important role as a cleaner hydrocarbon fuel source to bridge the gap between renewable energy production and increasing energy demand. Regulations aim to reduce methane emissions from natural gas systems to ensure the total environmental impacts of natural gas production and consumption are indeed lesser than for other fossil fuels. GHGSat Inc., has developed a tiered top-down remote sensing approach utilizing satellite and airborne instruments to monitor methane emissions from industrial sites globally. This satellite-aircraft hybrid system was demonstrated in the Permian basin for detecting and quantifying methane emissions from oil and gas (O&G) facilities. A heavy-tail distribution of methane emissions was observed, with 12% of emitting targets (total sample size of 106) accounting for over 50% of total detected methane emissions. Traditional leak detection and repair (LDAR) programs often incorporate multiple annual screening campaigns with ground-based optical gas imaging (OGI) technologies to detect methane leaks from O&G infrastructure. Three alternative LDAR programs incorporating GHGSat's satellite and airborne monitoring technologies were modelled using the Arolytics AroFEMP methane model. Model parameters were derived from GHGSat's 2021 Permian basin data to evaluate their equivalency and costs against traditional LDAR monitoring. When compared to the required practice of performing OGI surveys four times per year, the proposed alternative LDAR programs were modelled to have at least equivalent methane reduction performance while being substantially more cost-effective.

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