Framework for integrated oil pipeline monitoring and incident mitigation systems

Wireless Sensor Nodes (motes) have witnessed rapid development in the last two decades. Though the design considerations for Wireless Sensor Networks (WSNs) have been widely discussed in the literature, limited investigation has been done for their application in pipeline surveillance. Given the increasing number of pipeline incidents across the globe, there is an urgent need for innovative and effective solutions for deterring the incessant pipeline incidents and attacks. WSN pose as a suitable candidate for such solutions, since they can be used to measure, detect and provide actionable information on pipeline physical characteristics such as temperature, pressure, video, oil and gas motion and environmental parameters. This paper presents specifications of motes for pipeline surveillance based on integrated systems architecture. The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines. The requirements and components of motes, different threats to pipelines and ways of detecting such threats presented in this paper will enable better deployment of pipeline surveillance systems for incident mitigation. It was identified that the shortcomings of the existing wireless sensor nodes as regards their application to pipeline surveillance are not effective for surveillance systems. The resulting specifications provide a framework for designing a cost-effective system, cognizant of the design considerations for wireless sensor motes used in pipeline surveillance

Investigation and Implementation of IoT Based Oil & Gas Pipeline Monitoring System

Wireless Sensor Networks (WSNs) involve top potential technologies that will dramatically change the way of human living and working. Many scientific, industrial and environmental applications require real time information related to physical events like pressure, temperature or humidity. In the past the only way to transfer the sensed data to control center was through cumbersome and costly wires. But recent advancement in wireless networking enables WSNs to communicate the sensed real time event data wirelessly. WSNs have capabilities of sensing, processing and communicating which make them most suitable for monitoring different on and gas industries upstream, midstream and downstream operations which help to increase production, decrease the accidents, maintenance cost and malfunctioning

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

The role of wireless sensor networks (WSNs) in industrial oil and gas condition monitoring

Wireless sensor networks have a vast amount of applications including environmental monitoring, military, ecology, agriculture, inventory control, robotics and health care. This paper focuses on the area of monitoring and protection of oil and gas operations using wireless sensor networks that are optimized to decrease installation, and maintenance cost, energy requirements, increase reliability and improve communication efficiency. In addition, simulation experiments using the proposed model are presented. Such models could provide new tools for research in predictive maintenance and condition-based monitoring of factory machinery in general and for “open architecture machining systems” in particular. Wireless sensing no longer needs to be relegated to locations where access is difficult or where cabling is not practical. Wireless condition monitoring systems can be cost effectively implemented in extensive applications that were historically handled by running routes with data collectors.The result would be a lower cost program with more frequent data collection, increased safety, and lower spare parts inventories. Facilities would be able to run leaner because they will have more confidence in their ability to avoid downtime