Wireless Sensor Networks for Fugitive Methane Emissions Monitoring in Oil and Gas Industry

Klein, Levente J.; Ramachandran, Muralindar; Kessel, Ted van; Nair, Dhruv; Hinds, Nigel; Hamann, Hendrik F.; Sosa, Norma

doi:10.1109/iciot.2018.00013

Cited by 10 publications

(4 citation statements)

References 18 publications

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“…The advanced healthcare functionality helps to minimize the violation of workplace health and safety codes as well as improve the safety and wellness of the field personnel. Some environmental sensors measure toxic gas, radiation level, noise, and temperature benefit asset management [58], [62]- [64]. Some measuring instruments, such as Drager Xam 2500 and Honeywell BW Ultra, can detect multi-gas, such as O 2 , CO, NO 2 , and H 2 S. The FLIR GF77 thermal camera has the functionality for visualizing methane emissions in realtime, which improves the efficiency of gas leak surveillance [65].…”

Section: A Personnel Health Safety and Location Trackingmentioning

confidence: 99%

“…In addition, the smart sensor enables personnel location tracking in the O&G workplace [64], [66]. This could be an offshore platform with tightly-packed multi-level architecture or an onshore facility spread over a large area.…”

Section: A Personnel Health Safety and Location Trackingmentioning

confidence: 99%

“…For example, in the case of RFID used on offshore platforms, each field worker on the rig wears an ID badge (i.e. active RFID tag) [58], [64], [66], [67]. At defined intervals, the tag transmits its ID number and essential information to the software management system.…”

Section: A Personnel Health Safety and Location Trackingmentioning

confidence: 99%

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Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

et al. 2021

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Working at an oil and gas facility, such as a drilling rig, production facility, processing facility, or storage facility, involves various challenges, including health and safety risks. It is possible to leverage emerging digital technologies such as smart sensors, wearable or mobile devices, big data analytics, cloud computing, extended reality technologies, robotic systems, and drones to mitigate the challenges faced by oil and gas workers. While these technologies are not new to the oil and gas industry, most of its existing digital transformation initiatives follow business or process-centric approaches, in which the critical driver of the technology adoption is the enhancement of production, efficiency, and revenue. As a result, they may not address the challenges faced by the workers. As oil and gas workers are among the essential assets in the oil and gas industry, it is vital to address the challenges faced by these workers. This paper proposes a human-centric digital transformational framework for the oil and gas industry to deploy existing digital technologies to enhance their workers' health, safety, and working conditions. The paper outlines the critical challenges faced by oilfield workers, introduces a system architecture to implements a human-centric digital transformation, discusses the opportunities of the proposed framework, and summarizes the key impediment for the proposed framework.

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Section: A Personnel Health Safety and Location Trackingmentioning

confidence: 99%

Section: A Personnel Health Safety and Location Trackingmentioning

confidence: 99%

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Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

et al. 2021

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“…Through the literature, there are several successful tries to utilize energy harvesting in the oil and gas industry, however, still lacking in power source reliability [12], limited to external damages (sabotage activities), and unable to detect leakages and corrosions (self-destruction) [11]. Thus, in this paper, dual source hybrid harvesters will be presented to circumvent the single harvester drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Development of an Energy-Aware Algorithm for Low Power Wireless Sensor Node Powered by Dual Energy Harvesting Sources

2019

IJRTE

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A novel self-powered wireless sensor node is proposed and prototyped to overcome the ambient energy lacking in the dual energy harvesting sources by including a secondary energy storage. Moreover, an energy-aware Event-Priority-Driven Dissemination (EPDD) management algorithm has been developed and implemented to control the WSN integrity and reducing the sensor node power consumption as well. EPDD was developed to manage the sensor node operation and to make the sink station able to detect a missing wireless node within the network, which will guarantee the nodes integrity detection. The evaluations revealed that the EPDD shows a good performance in reducing the node power consumption compared to the data push algorithm, whereby, EPDD node was operating 4 hours more than the data push node on the same power source. Regarding the WSN integrity, the EPDD algorithm outpaced the event trigger algorithm, whereby, the EPDD was easily able to detect a node down within the WSN at the contrary of the event trigger. -Kadhim received his M.Eng. degree in electronic and computer engineering from the UTeM, Malaysia in 2015, exploring embedded system design and robotics. He is currently pursuing the Ph.D. degree at the same university. His research interest includes embedded system and WSN design for IoT applications based hybrid energy harvesting. He has involved in several projects related to WSN based energy harvesting for telemetry monitoring also authored few papers related to WSNs and energy harvesting.Kok Swee Leong was awarded Ph.D in Electronics and Electrical Engineering from the Southampton University, UK in 2010, exploring thick-film technologies for fabricating piezoelectric energy harvesting devices. Dr. Kok has been a lecturer in UTeM since 2003 after completing his MSc degree in Electrical, Electronic and System Engineering from UKM, researching on optical planar waveguide fabrication and characterization. He is currently an Associate Professor and also research leader of Advanced Sensors and Embedded Control Systems (ASECs) Research Group under the Center of Telecommunication and Innovation (CeTRI), UTeM. He have been author and co-author for more than 50 publications and reviewing IEEE, IOP, Elsevier and other Scopus indexed journals. His research interest is related to energy harvesting system and applications, MEMS, and thick-film devices fabrication technologies for the application of sensing, actuating and self-powering for wireless sensor network.

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Energy Transition: Challenges and Opportunities for the Oil & Gas Industry

Saraji

Akindipe

2023

Lecture Notes in Energy

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Wireless Sensor Networks for Fugitive Methane Emissions Monitoring in Oil and Gas Industry

Cited by 10 publications

References 18 publications

Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

Development of an Energy-Aware Algorithm for Low Power Wireless Sensor Node Powered by Dual Energy Harvesting Sources

Energy Transition: Challenges and Opportunities for the Oil & Gas Industry

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