| Literature DB >> 27849603 |
Mary Kang1, Shanna Christian2, Michael A Celia3, Denise L Mauzerall3,4, Markus Bill5, Alana R Miller3, Yuheng Chen2, Mark E Conrad5, Thomas H Darrah6, Robert B Jackson7,8.
Abstract
Recent measurements of methane emissions from abandoned oil/gas wells show that these wells can be a substantial source of methane to the atmosphere, particularly from a small proportion of high-emitting wells. However, identifying high emitters remains a challenge. We couple 163 well measurements of methane flow rates; ethane, propane, and n-butane concentrations; isotopes of methane; and noble gas concentrations from 88 wells in Pennsylvania with synthesized data from historical documents, field investigations, and state databases. Using our databases, we (i) improve estimates of the number of abandoned wells in Pennsylvania; (ii) characterize key attributes that accompany high emitters, including depth, type, plugging status, and coal area designation; and (iii) estimate attribute-specific and overall methane emissions from abandoned wells. High emitters are best predicted as unplugged gas wells and plugged/vented gas wells in coal areas and appear to be unrelated to the presence of underground natural gas storage areas or unconventional oil/gas production. Repeat measurements over 2 years show that flow rates of high emitters are sustained through time. Our attribute-based methane emission data and our comprehensive estimate of 470,000-750,000 abandoned wells in Pennsylvania result in estimated state-wide emissions of 0.04-0.07 Mt (1012 g) CH4 per year. This estimate represents 5-8% of annual anthropogenic methane emissions in Pennsylvania. Our methodology combining new field measurements with data mining of previously unavailable well attributes and numbers of wells can be used to improve methane emission estimates and prioritize cost-effective mitigation strategies for Pennsylvania and beyond.Entities:
Keywords: abandoned wells; climate change; high emitters; methane emissions; oil and gas development
Year: 2016 PMID: 27849603 PMCID: PMC5137730 DOI: 10.1073/pnas.1605913113
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205