An intelligent oil and gas well monitoring system based on Internet of Things
Title
An intelligent oil and gas well monitoring system based on Internet of Things
Subject
Corrosion Detection
Flow and Pressure Monitoring
Issue and Challenges
Leak Detection
Monitoring
Natural gas industry
Oil and Gas Industry Requirements
Oil and Gas Pipeline Monitoring
Oils
Production
Reliability
Temperature
Temperature sensors
Wireless sensor networks
Wireless Sensor Networks
Description
The oil and gas industrial sector is nowadays inclined towards utilizing smart field technologies for optimizing various operations of upstream, midstream and downstream sectors. The recent advances in Internet of things (IoTs) have promising benefits and advantages over manual wired/wireless systems. Oil and gas wells form an important element of upstream sector. After identifying potential viable fields and drilling of exploratory oil and gas wells, wellhead monitoring is another essential and crucial activity not only for safe operation and productivity but also for extending the production life of these wells. In this paper we propose an intelligent IoT based monitoring system which involves smart objects for reliable and efficient monitoring of oil and gas wells. The smart IoT objects are capable of sensing important parameters like pressure temperature, vibration etc. and reliably, efficiently and timely deliver the sensed data to the control center. The proposed system proactively reports about the anomalous events for predictive maintenance of the well equipment. The detection and reporting catastrophic failures and destructive events on time will increase production downtime and also oil theft can be easily prevented.
124-127
Creator
M. Y. Aalsalem
W. Z. Khan
W. Gharibi
N. Armi
Publisher
2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
Date
2017
Type
conferencePaper
Collection
Citation
M. Y. Aalsalem et al., “An intelligent oil and gas well monitoring system based on Internet of Things,” Lamar University Midstream Center Research, accessed May 13, 2024, https://lumc.omeka.net/items/show/27493.