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Title: Distributed wireless sensing for fugitive methane leak detection

Abstract

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It is demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. IBM, Yorktown Heights, NY (United States). Thomas J. Watson Research Center
Publication Date:
Research Org.:
IBM, Yorktown Heights, NY (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
Contributing Org.:
METEC, Colorado State University
OSTI Identifier:
1409489
Grant/Contract Number:
AR0000540
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Proceedings for IEEE Big Data 2017
Additional Journal Information:
Conference: IEEE Big Data, 2017 , Boston, MA (United States), 11 Dec 2017
Country of Publication:
United States
Language:
English
Subject:
04 OIL SHALES AND TAR SANDS; wireless sensor network; fugitive methane gas; cloud analytics; computation at edge; data fusion

Citation Formats

Klein, Levente J., van Kessel, Theodore, Nair, Dhruv, Muralindar, Ramachandran, Hinds, Nigel, Hamann, Hendrik, and Sosa, Norma. Distributed wireless sensing for fugitive methane leak detection. United States: N. p., 2017. Web. doi:10.1109/BigData.2017.8258502.
Klein, Levente J., van Kessel, Theodore, Nair, Dhruv, Muralindar, Ramachandran, Hinds, Nigel, Hamann, Hendrik, & Sosa, Norma. Distributed wireless sensing for fugitive methane leak detection. United States. doi:10.1109/BigData.2017.8258502.
Klein, Levente J., van Kessel, Theodore, Nair, Dhruv, Muralindar, Ramachandran, Hinds, Nigel, Hamann, Hendrik, and Sosa, Norma. Mon . "Distributed wireless sensing for fugitive methane leak detection". United States. doi:10.1109/BigData.2017.8258502.
@article{osti_1409489,
title = {Distributed wireless sensing for fugitive methane leak detection},
author = {Klein, Levente J. and van Kessel, Theodore and Nair, Dhruv and Muralindar, Ramachandran and Hinds, Nigel and Hamann, Hendrik and Sosa, Norma},
abstractNote = {Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It is demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.},
doi = {10.1109/BigData.2017.8258502},
journal = {IEEE Proceedings for IEEE Big Data 2017},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 11 00:00:00 EST 2017},
month = {Mon Dec 11 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on December 11, 2018
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  • Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less
  • This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH 4) sensor system (DMSS) for continuous monitoring, detection, and localization of CH 4 leaks in natural gas infrastructure, such as transmission and distribution pipelines, wells, and production pads. The CH 4 sensing element, a key component of the DMSS, consists of a metal oxide nanocrystal (MONC) functionalized multi-walled carbon nanotube (MWCNT) mesh which, in comparison to existing literature, shows stronger relative resistance change while interacting with lower parts per million (ppm) concentration of CH 4. A Gaussian plume triangulation algorithm has been developed for the DMSS. Givenmore » a geometric model of the surrounding environment the algorithm can precisely detect and localize a CH 4 leak as well as estimate its mass emission rate. A UV-based surface recovery technique making the sensor recover 10 times faster than the reported ones is presented for the DMSS. In conclusion, a control algorithm based on the UV-accelerated recovery is developed which facilitates faster leak detection.« less
  • Integration of the exciting coil and the pick-up coil array for the wireless magnetic motion sensing system has been investigated to clear the limitation of the system arrangement. From the comparison of the integrated-type and the sandwich-type, which was proposed by our previous study, regardless of the lower signal-to-noise ratio of the integrated-type than that of the sandwich-type a repeatable detection accuracy of around 1 mm is obtained at the distance of 120 mm from the pick-up coil array (sandwich-type: up to 140 mm). A different tendency of the detection errors in detection was also observed. In spite of differentmore » tendency, the cause of the errors has been clarified. The impedance change of the exciting coil due to a resonance of the LC marker perturbs strength of the magnetic field which is used for marker excitation. However, the errors are able to compensate to the actual positions and orientations of the marker by using compensatory method which was already established.« less
  • Ophir Corporation was awarded a contract by the U. S. Department of Energy, National Energy Technology Laboratory under the Project Title ''Airborne, Optical Remote Sensing of Methane and Ethane for Natural Gas Pipeline Leak Detection'' on October 14, 2002. This six-month technical report summarizes the progress for each of the proposed tasks, discusses project concerns, and outlines near-term goals. Ophir has completed a data survey of two major natural gas pipeline companies on the design requirements for an airborne, optical remote sensor. The results of this survey are disclosed in this report. A substantial amount of time was spent onmore » modeling the expected optical signal at the receiver at different absorption wavelengths, and determining the impact of noise sources such as solar background, signal shot noise, and electronic noise on methane and ethane gas detection. Based upon the signal to noise modeling and industry input, Ophir finalized the design requirements for the airborne sensor, and released the critical sensor light source design requirements to qualified vendors. Responses from the vendors indicated that the light source was not commercially available, and will require a research and development effort to produce. Three vendors have responded positively with proposed design solutions. Ophir has decided to conduct short path optical laboratory experiments to verify the existence of methane and absorption at the specified wavelength, prior to proceeding with the light source selection. Techniques to eliminate common mode noise were also evaluated during the laboratory tests. Finally, Ophir has included a summary of the potential concerns for project success and has established future goals.« less