TY - JOUR

T1 - IoT infrastructures for well control

AU - Elmgerbi, Asad

PY - 2025/1/15

Y1 - 2025/1/15

N2 - The Industrial Internet of Things (IIoT or IoT) uses intelligent sensors and actuators to analyze data to optimize industrial company operations. Due to data analysis features, IoT has advantages such as real-time data analysis, fast processing of big data, intelligent analysis, and others.The purpose of this chapter is to reveal the possible application of Industrial Internet of Things in the oil industry with a focus on the drilling industry and well control. For this purpose, a comparison was made between the data system without IoT and with IoT edge data system on drilling rigs. Then, an example was given for using IoT edge computer vision systems (IoT-ECVS) in the drilling industry for a well control space-out system (WC-SOS). Deep learning models for object detection and rig deployment were described, where deep learning models include three steps: Training, testing, and production. Future implementations of IoT in the drilling industry, such as drill-string dynamics analysis, shale shaker analysis, and rig safety, have been proposed.The literature shows the advantages of applying IoT in the drilling industry including in well control. Real-time data analysis with minimal human involvement can prevent or reduce likelihood of incidents and enhance employees’ safety monitoring.

AB - The Industrial Internet of Things (IIoT or IoT) uses intelligent sensors and actuators to analyze data to optimize industrial company operations. Due to data analysis features, IoT has advantages such as real-time data analysis, fast processing of big data, intelligent analysis, and others.The purpose of this chapter is to reveal the possible application of Industrial Internet of Things in the oil industry with a focus on the drilling industry and well control. For this purpose, a comparison was made between the data system without IoT and with IoT edge data system on drilling rigs. Then, an example was given for using IoT edge computer vision systems (IoT-ECVS) in the drilling industry for a well control space-out system (WC-SOS). Deep learning models for object detection and rig deployment were described, where deep learning models include three steps: Training, testing, and production. Future implementations of IoT in the drilling industry, such as drill-string dynamics analysis, shale shaker analysis, and rig safety, have been proposed.The literature shows the advantages of applying IoT in the drilling industry including in well control. Real-time data analysis with minimal human involvement can prevent or reduce likelihood of incidents and enhance employees’ safety monitoring.

M3 - Article

JO - Taylor & Francis

JF - Taylor & Francis

ER -