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A Data Size Reduction Approach Applicable in Process Control System of Oil and Gas Plants

Author

Listed:
  • Reza Abbasinejad

    (Technical Inspection Department, Sarkhoon and Qeshm Gas Treating Company, Bandarabbas 7915996489, Iran)

  • Farzad Hourfar

    (School of Electrical & Computer Engineering, University of Tehran, Tehran 1417466191, Iran)

  • Chandra Mouli R Madhuranthakam

    (Chemical Engineering Department, Abu Dhabi University, Abu Dhabi 59911, UAE)

  • Ali Elkamel

    (Department of Chemical Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
    Department of Chemical Engineering, Khalifa University, Abu Dhabi 127788, UAE)

Abstract

In oil and gas plants, the cost of devices applicable for supervising and controlling systems directly depends on the transmission and storage systems, which are related to the data size of process variables. In this paper, process variables frequency-domain and statistical analysis results have been studied to infer if there exists any possibility to reduce data size of the process variables without loss of any necessary information. Although automatic control is not applicable in a shutdown condition, for generalization of the obtained results, unscheduled shutdown data has also been analyzed and studied. The main goal of this paper is to develop an applicable algorithm for oil and gas plants to decrease the data size in controlling and monitoring systems, based on well-known and powerful mathematical techniques. The results show that it is possible to reduce the size of data dramatically (more than 99% for controlling, and more than 55% for monitoring purposes in comparison with existing methods), without loss of vital information and performance quality.

Suggested Citation

  • Reza Abbasinejad & Farzad Hourfar & Chandra Mouli R Madhuranthakam & Ali Elkamel, 2020. "A Data Size Reduction Approach Applicable in Process Control System of Oil and Gas Plants," Sustainability, MDPI, vol. 12(2), pages 1-22, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:639-:d:309049
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