Literature DB >> 31997723

Development of a low-cost UAV-based system for CH4 monitoring over oil fields.

Siwen Liu1, Xufei Yang1, Xiaobing Zhou2.   

Abstract

The recent booming of oil and gas production in the U.S. sparks a growing concern about greenhouse gas emissions from the petroleum industry. This study aimed to develop a low-cost UAV-based system for CH4 monitoring over oil fields. The system consisted of an airborne sensor node, a ground station, and a laptop. The sensor node was comprised of low-cost gas sensors, a microcontroller, a LoRa wireless transceiver, a GPS module, and an SD card reader. The ground station included a microcontroller and a LoRa transceiver. Both the sensor node and the ground station were programmed using Arduino. A graphic user interface was created using LabVIEW for data logging and visualization on the laptop. A preliminary test showed that the system was capable of measuring CH4 concentrations, along with temperature, humidity, and GPS location; while sending the real-time data to the ground station up to ∼1 km away without any loss. The system was further tested at two oil production sites in North Dakota. The results revealed a heterogeneous distribution of CH4 over the sites due to flares and road traffic, demonstrating a potential application of the system for air quality survey and gas leakage detection. The advantage of this system lies in its light weight (∼540 g), low cost (∼$300), expandability, ease of deployment and operation. Data quality collected by the system depended on the gas sensors chosen. With advancement in sensor technologies, it is expected that the quality of monitoring data can be considerably improved in the near future.

Entities:  

Keywords:  Air quality monitoring; LoRa; methane; oil fields; unmanned aerial vehicle

Year:  2020        PMID: 31997723     DOI: 10.1080/09593330.2020.1724199

Source DB:  PubMed          Journal:  Environ Technol        ISSN: 0959-3330            Impact factor:   3.247


  1 in total

1.  Powering UAV with Deep Q-Network for Air Quality Tracking.

Authors:  Alaelddin F Y Mohammed; Salman Md Sultan; Seokheon Cho; Jae-Young Pyun
Journal:  Sensors (Basel)       Date:  2022-08-16       Impact factor: 3.847

  1 in total

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