title: A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production.
abstract: This paper addresses the need for surveillance of fugitive methane emissions over broad geographical regions. Most existing techniques suffer from being either extensive (but qualitative) or quantitative (but intensive with poor scalability). A total of two novel advancements are made here. First, a recursive Bayesian method is presented for probabilistically characterizing fugitive point-sources from mobile sensor data. This approach is made possible by a new cross-plume integrated dispersion formulation that overcomes much of the need for time-averaging concentration data. The method is tested here against a limited data set of controlled methane release and shown to perform well. We then present an information-theoretic approach to plan the paths of the sensor-equipped vehicle, where the path is chosen so as to maximize expected reduction in integrated target source rate uncertainty in the region, subject to given starting and ending positions and prevailing meteorological conditions. The information-driven sensor path planning algorithm is tested and shown to provide robust results across a wide range of conditions. An overall system concept is presented for optionally piggybacking of these techniques onto normal industry maintenance operations using sensor-equipped work trucks.
authors.forename: John D
authors.initials: JD
authors.lastname: Albertson
authors.forename: Tierney
authors.initials: T
authors.lastname: Harvey
authors.forename: Greg
authors.initials: G
authors.lastname: Foderaro
authors.forename: Pingping
authors.initials: P
authors.lastname: Zhu
authors.forename: Xiaochi
authors.initials: X
authors.lastname: Zhou
authors.forename: Silvia
authors.initials: S
authors.lastname: Ferrari
authors.affiliation: Arcadis-US Inc. , 4915 Prospectus Drive F, Durham, North Carolina 27713, United States.
authors.forename: M Shahrooz
authors.initials: MS
authors.lastname: Amin
authors.affiliation: Arcadis-US Inc. , 4915 Prospectus Drive F, Durham, North Carolina 27713, United States.
authors.forename: Mark
authors.initials: M
authors.lastname: Modrak
authors.affiliation: Office of Research and Development, National Risk Management Research Laboratory, United States Environmental Protection Agency , 109 TW Alexander Drive, E343-02, RTP, North Carolina 27711, United States.
authors.forename: Halley
authors.initials: H
authors.lastname: Brantley
authors.affiliation: Office of Research and Development, National Risk Management Research Laboratory, United States Environmental Protection Agency , 109 TW Alexander Drive, E343-02, RTP, North Carolina 27711, United States.
authors.forename: Eben D
authors.initials: ED
authors.lastname: Thoma
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D001499:Bayes Theorem; D004784:Environmental Monitoring / Q000379:methods*; D008697:Methane / Q000032:analysis*; D008962:Models, Theoretical; D018986:Motor Vehicles; D009657:North Carolina; D061329:Oil and Gas Fields; D000066388:Oil and Gas Industry / Q000379:methods*; D058998:Remote Sensing Technology / Q000379:methods*
chemical_list: D000393:Air Pollutants; D008697:Methane