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Optimized inspection of upstream oil and gas methane emissions using airborne LiDAR surveillance

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  • Rashid, Kashif
  • Speck, Andrew
  • Osedach, Timothy P.
  • Perroni, Dominic V.
  • Pomerantz, Andrew E.

Abstract

Methane is a short-lived climate pollutant responsible for approximately 20% of anthropogenic global warming, and reducing methane emissions from the oil and gas (O&G) industry is considered among the most urgent and actionable measures to mitigate climate change. Recent reports suggest a large fraction of upstream O&G methane emissions result from a small number of super-emitter facilities, emphasizing the value of novel methods that inspect O&G facilities with greater frequency than is practical using existing techniques. Here we describe an optimized method wherein O&G facilities are inspected for emissions at high frequency and high sensitivity using active laser (LiDAR) sensors mounted to aircraft. The method relies on a hierarchical clustering and routing procedure to establish optimal routes to be flown by aircraft departing from local airports and equipped with LiDAR methane sensors. Routes are optimized to inspect all well sites subject to emissions regulation in three O&G intensive regions: the Permian basin, the state of Colorado, and the state of Pennsylvania. While some cost estimates require additional field data, these modeling results suggest the optimized inspections can be performed with comparable effectiveness and up to a factor of six lower cost per inspection compared to current detection methods. The cost per inspection required to achieve equivalent emissions reduction depends on factors such as the weather conditions during inspection (which impacts the limit of detection and therefore the inspection frequency required to achieve equivalency) and the well density (which impacts the flying distance), and the advantage of this program over traditional inspection will be reduced under unfavorable conditions. These modeling results suggest that optimized routing may enable frequent inspection of upstream O&G facilities at large scale and potentially lead to a substantial decrease in both oilfield methane emissions and compliance costs borne by industry.

Suggested Citation

  • Rashid, Kashif & Speck, Andrew & Osedach, Timothy P. & Perroni, Dominic V. & Pomerantz, Andrew E., 2020. "Optimized inspection of upstream oil and gas methane emissions using airborne LiDAR surveillance," Applied Energy, Elsevier, vol. 275(C).
  • Handle: RePEc:eee:appene:v:275:y:2020:i:c:s0306261920308394
    DOI: 10.1016/j.apenergy.2020.115327
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    References listed on IDEAS

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    1. Daniel Zavala-Araiza & Ramón A Alvarez & David R. Lyon & David T. Allen & Anthony J. Marchese & Daniel J. Zimmerle & Steven P. Hamburg, 2017. "Super-emitters in natural gas infrastructure are caused by abnormal process conditions," Nature Communications, Nature, vol. 8(1), pages 1-10, April.
    2. Irnich, S. & Schneider, M. & Vigo, D., 2014. "Four Variants of the Vehicle Routing Problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63514, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Hausfather, Zeke, 2015. "Bounding the climate viability of natural gas as a bridge fuel to displace coal," Energy Policy, Elsevier, vol. 86(C), pages 286-294.
    4. Katsumasa Tanaka & Otávio Cavalett & William J. Collins & Francesco Cherubini, 2019. "Asserting the climate benefits of the coal-to-gas shift across temporal and spatial scales," Nature Climate Change, Nature, vol. 9(5), pages 389-396, May.
    5. Maria Battarra & Güneş Erdoğan & Daniele Vigo, 2014. "Exact Algorithms for the Clustered Vehicle Routing Problem," Operations Research, INFORMS, vol. 62(1), pages 58-71, February.
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    Cited by:

    1. Shuo Sun & Linwei Ma & Zheng Li, 2021. "Methane Emission Estimation of Oil and Gas Sector: A Review of Measurement Technologies, Data Analysis Methods and Uncertainty Estimation," Sustainability, MDPI, vol. 13(24), pages 1-29, December.
    2. Pengying Wang & Shuo Zhang & Limei Chen, 2023. "Research on the Integration of a Natural Gas-Distributed Energy System into the Oilfield Facility in China," Sustainability, MDPI, vol. 15(4), pages 1-15, February.

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