Real-Time Monitoring and Control of Crude Oil Export Pumps
Abstract
This paper is on the application of Model Reference Adaptive Control (MRAC) in optimizing the performance of crude oil export pumps with the goals of improving pump performance, enhancing system reliability, and increasing energy efficiency, by dynamically adjusting operational parameters in response to real-time changes in flow rates and crude oil properties. Manual control was compared to MRAC control, with a focus on error rate and accuracy rate evaluation. The MRAC method was implemented to reduce error rates and enhance control precision. The findings revealed significant improvements in both error and accuracy rates. The efficiency of the manual control is 84.5% while the efficiency of the MRAC is 90%. These results demonstrate the effectiveness of MRAC in optimizing pump operations, enhancing reliability, and reducing energy consumption. This work recommends the integration of MRAC in crude oil export pump systems to ensure sustained performance improvements, operational efficiency, efficient management of energy resources and the reduction of operational anomalies in oil export operations.
References
Ali, R., & Goble, W. (2004). Optimal near real-time control of water distribution system operations, The Instrumentation, Systems, and Automation Society, 22(40), 15-27.
Boccalatte, A., & Coccoli, M. (2020). Future directions of internet-based control systems. Journal of Computing and Information Technology, 10(2), 21-30.
Goldman, F. E., & Mays, L. W. (1999). The application of simulated annealing to the optimal operation of water systems. In Proceedings of the WRPMD’99 Preparing for the 21st Century, Tempe, AZ, USA, June 6–9.
Guruprakash, S., Rajendra, S., & Singh, P. (2020). Automation and supply of distributed control systems for crude oil field industries. International Research Journal of Engineering and Technology, 7(6), 6155. https://www.irjet.net
Ignatius, G. I., Nawawi, M. G. M., Mohd, Z. J., & Farah, B. S. (2023). Environmental effects from petroleum product transportation spillage in Nigeria: A critical review. Environmental Science and Pollution Research, 31(4), 1–29. https://doi.org/10.1007/s11356-023-31117-z
Mahmood, M., & Al-Naima, F. (2011). An internet-based distributed control systems: A case study of oil refineries. Energy and Power Engineering 3(3), 25-37. https://www.researchgate.net/publication/236018681
Mahmoud, A. A. B., & Piratla, K. R. (2019). Optimal operational control of water pipeline systems using real-time scheduling framework. In Pipelines 2019: Planning and Design, 15(3) 243-248.
Mfundo, N., Kapil, G., & Madindwa, M. (2020). Causes and impact of human error in maintenance of mechanical systems. MATEC Web of Conferences, 05001. https://www.matec-conferences.org/articles/matecconf/pdf/2020/08/matecconf_eppm2018_05001.pdf
Muqeet, M. A., Najeeb, M. A., Akbar, F., & Ali, S. (2015). PLC and SCADA-based control of continuous stirred tank reactor (CSTR). International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, 3(12), 45-54.
Nishad, A. D., Yadav, A. K., & Dwivedi, A. (2023). PLC & SCADA-based automation in boiler systems enhancing energy efficiency: A review. International Journal, 10(1), 13-22.
Odan, F. K., Reis, L. F. R., & Kapelan, Z. (2015). Real-time multiobjective optimization of operation of water supply systems. Journal of Water Resources Planning and Management, 141(1), 40-51.
Priyadarshy, S. (2016). IoT revolution in oil and gas industry. In H. Geng (Ed.), Internet of Things and Data Analytics Handbook (Ch. 31, pp. 513–520). Wiley. https://doi.org/10.1002/9781119173601.ch31
Aljohani, A. (2023). Risk mitigation and agility: Predictive analytics and machine learning for real-time supply chain. Sustainability, 15(20), 15088. https://doi.org/10.3390/su152015088
Copyright (c) 2025 Nkolika O. Nwazor, Justus N. Dike, Ezekiel O. Ashaka

This work is licensed under a Creative Commons Attribution 4.0 International License.