Prediction of Riser Base Pressure in a Multiphase Pipeline-Riser System Using Artificial Neural Networks
Abstract
In the multiphase flow of oil and gas in pipeline-riser systems, reliable pressure measurements and monitoring is of
utmost importance for flow assurance. These measurements are usually obtained using remote pressure
measuring gauges and other devices. They are employed in the automatic slug flow control technique. However,
these devices are quite expensive and often require calibration at intervals to guarantee accuracy and precision.
There is therefore, the need for suitable alternatives. In this study, a feed-forward back propagation artificial
neural network (ANN) for predicting riser base pressure in offshore pipeline riser systems is presented. A total of
16,870 experimental data sets were used to develop the ANN model. The results show near perfect predictions
with an average mean square error of 0.00207197 and regression correlation coefficient, R values as high as
0.99919. The models obtained from this work can be pivotal to the development of data driven control of slug in
pipeline-riser systems.
References
intelligence. Proceeding of SPE/DGS Saudi Arabia Section Technical Symposium and Exhibition, AlKhobar, Saudi Arabia, May 15 - 18, 2011. doi: 10.2118/149035-MS
Awadalla, M., Yousef, H., Al-Hinai, A. and Al-Shidani, A. (2016). Prediction of oil well flowing bottom-hole pressure
in petroleum fields. Proceedings of the International Conference on Industrial Engineering and
Operations Management, Kuala Lumpur, Malaysia, March 8 – 10, 2016.
Cao, Y., Lao, L., and Yeung, H. (2013). Method, controller and system for controlling the slug flow of a multiphase
fluid. UK Patent Application GB2468973
Di Meglio, F., Petit, N., Alstad, V., and Kaasa, G. O. (2012). Stabilization of slugging in oil production facilities with
or without upstream pressure sensors. Journal of Process Control, 22, 809 - 822.
Ehinmowo, A. B. (2015). Stabilising slug flow at large valve opening using an intermittent absorber (PhD thesis),
Cranfield University, Bedfordshire, United Kingdom.
Ehinmowo, A. B., Ogunleye, O. O., and Orodu, O. D. (2016). Experimental investigation of hydrodynamic slug
mitigation potential of an intermittent absorber. Chemical Engineering Research and Design, 113, 50 –
60.
Kumar, A. (2012). Artificial neural network as a tool for reservoir characterization and its application in the
petroleum engineering. Proceedings of the Offshore Technology Conference, Houston, Texas, USA, April
30 – May 3, 2012. doi: 10.4043/22967-MS
Li, X., Miskimins, J. L. and Hoffman, B. T. (2014). A combined bottom-hole pressure calculation procedure using
multiphase correlations and artificial neural network models. Proceeding of SPE Annual Technical
Conference and Exhibition, Amsterdam, Netherlands, October 27 – 29, 2014.
Mohaghegh, S., Reeves, S. and Hill, G. (1999). Development of an intelligent systems approach for restimulation
candidate selection. Proceeding of SPE Gas Technology Sysmposium, Calgary, AB, Canada, April 3 – 5,
2000.
Mohammadpoor, M., Shabazi, K., Torabi, F. and Qazvini, A. R. (2010). A new methodology for prediction of
bottomhole flowing pressure in vertical multiphase flow in Iranian oil fields using artificial neural
networks (ANNs). Proceeding of SPE Latin American and Caribbean Petroleum Engineering Conference,
Lima, Peru, December 1 – 3, 2010. doi: 10.2118/139147-MS.
Ogazi, A. I., Cao, Y., Yeung, H., and Lao, L. (2010). Slug control with large valve openings to maximize oil
production. SPE Journal, 15(3): 812–821.
Osman, E. A., Ayoub, M. A. and Aggour, M. A. (2005). An artificial neural network model for predicting bottomhole
flowing pressure in vertical multiphase flow. Proceeding of SPE Middle East Oil and Gas Show and
Conference, Kingdom of Bahrain, March 12 – 15, 2005. doi: 10.2118/93632-MS.
Storkaas, E. (2005). Stabilizing control and controllability: control solutions to avoid slug flow in pipeline-riser
systems (PhD Thesis). Norwegian University of Science and Technology, NTNU, Norway.
Ternyik, J., Bilgesu, H. I., Mohaghegh, S. and Rose, D. M. (1995). Virtual measurement in pipes: part 1-flowing
bottom hole pressure under multi-phase flow and inclined wellbore conditions. Proceeding of SPE
Eastern Regional Meeting, Morgantown, WV, September 17 – 21, 1995. doi: 10.2118/30975-MS
