“Identification and Optimal Control for Surge and Swab Pressure Reduction While Performing Offshore Drilling Operations”

Authors: Njål Tengesdal and Christian Holden,
Affiliation: NTNU
Reference: 2020, Vol 41, No 3, pp. 165-184.

Keywords: Offshore-drilling, Nonlinear Estimation, MPC, Nonlinear Control, Offset-free control

Abstract: In this paper, an unscented Kalman filter coupled with a nonlinear model-predictive controller for a hydraulic wellbore model with multi-variable control and tracking is presented. In a wellbore, high drill string velocities in operational sequences such as tripping might result in surge and swab pressures in the annular section of the wellbore. To overcome these challenges, a controller incorporating safety and actuator limits should be used. A second-order model is used to predict axial drill string velocity downhole. With a nonlinear model-predictive controller (NMPC) specifying the block position trajectory, choke flow reference, desired back-pressure pump flowrate and stand-pipe pressure, we can automatically supervise and control the pressure in the wellbore. To compensate for unmeasured states, an estimator is designed to predict the frictional pressure forces in the wellbore and filter noisy measurements. A stochastic approach for the hydraulic model is taken, including variance of the average fluctuations for the flow and pressure states. Comparing three NMPC configurations, the result of using an integration of the tracking error in the prediction model gave best offset-free tracking of the bottom-hole pressure. The controller compensates for the unknown fluctuations, and is shown to be robust towards model mismatch. Including the mechanical system in the NMPC prediction model, we can effectively constrain the predicted axial drill string velocity to reduce the pressure oscillations and achieve tracking of bottom hole pressure and choke differential pressure. The outcome is shown through extensive simulations to be an effective control strategy, reducing the pressure spikes while tripping.

PDF PDF (2474 Kb)        DOI: 10.4173/mic.2020.3.3

DOI forward links to this article:
[1] Cancheng Sheng, Feifei Zhang, Yaoyao Tang, Yafeng Li and Xuesong Liu (2023), doi:10.3390/pr12010097
[1] Black, A.D., Walker, B.H., Tibbitts, G.A., and Sandstrom, J.L. (1986). PDC Bit Performance for Rotary, Mud Motor, and Turbine Drilling Applications, SPE Drilling Engineering. 1(06):409--416. doi:10.2118/13258-PA
[2] Borrelli, F. and Morari, M. (2007). Offset free model predictive control, Proceedings of the IEEE Conference on Decision and Control, 2007. pages 1245--1250. doi:10.1109/CDC.2007.4434770
[3] Breyholtz, O., Nygaard, G., Godhavn, J.-M., and Vefring, E.H. (2009). Evaluating control designs for co-ordinating pump rates and choke valve during managed pressure drilling operations, In 2009 IEEE Control Applications,(CCA) & Intelligent Control,(ISIC). IEEE, pages 731--738. doi:10.1109/CCA.2009.5281013
[4] Breyholtz, O., Nygaard, G., Siahaan, H., and Nikolaou, M. (2010). SPE 128151 Managed Pressure Drilling : A Multi-Level Control Approach, SPE Intelligent Energy Conference and Exhibition. doi:10.2118/128151-MS
[5] Breyholtz, O. and Nygaard, O. G.H. (2009). Deep Water Drilling: Full Pressure Profile Control in Open Hole Section Utilizing Model Predictive Control, International Petroleum Technology Conference. doi:10.2523/13256-MS
[6] Brown, R.G. and Hwang, P. Y.C. (2012). Introduction to Random signals and Applied Kalman Filtering with MATLAB exercises, Wiley, 4th edition.
[7] Cayeux, E., Daireaux, B., and Dvergsnes, E.W. (2010). Automation of Drawworks and Topdrive Management To Minimize Swab/Surge and Poor-Downhole-Condition Effects, IADC/SPE Drilling Conference and Exhibition. 26(4):557--568. doi:10.2118/128286-MS
[8] Cayeux, E., Daireaux, B., Dvergsnes, E.W., Florence, F., and Varco, N.O. (2014). Toward Drilling Automation : On the Necessity of Using Sensors That Relate to Physical Models, SPE Drilling & Completion. (March 2013):5--7. doi:10.2118/163440-PA
[9] Chen, C.-T. (2013). Linear System Theory and Design, Oxford University Press, Inc.
[10] Chirikjian, G.S. (2009). Stochastic Models Information Theory and Lie Groups, Volume 1: Classical Results and Geometric Methods, Springer Science & Business Media.
[11] Downton, G.C. (2012). Challenges of modeling drilling systems for the purposes of automation and control, IFAC Proceedings Volumes (IFAC-PapersOnline). 1(PART 1):201--210. doi:10.3182/20120531-2-NO-4020.00054
[12] Egeland, O. and Gravdahl, J.T. (2002). Modeling and Simulation for Automatic Control, volume76, Marine Cybernetics Trondheim, Norway.
[13] Findeisen, R. and Allgoewer, F. (2002). An Introduction to Nonlinear Model Predictive Control, Control, 21st Benelux Meeting on Systems and Control. (January 2002):1--23. doi:10.1167/iovs.06-0923
[14] Gjerstad, K., Time, R.W., and Bjorkevoll, K.S. (2013). A Medium-Order Flow Model for Dynamic Pressure Surges in Tripping Operations, SPE/IADC Drilling Conference. doi:10.2118/163465-MS
[15] Godhavn, J.-M. (2009). Control Requirements for High-End Automatic MPD Operations, SPE/IADC Drilling Conference and Exhibition. 25(March):336--345. doi:10.2118/119442-MS
[16] Gravdal, J., Lorentzen, R., Fjelde, K., and Vefring EH. (2010). Tuning of computer model parameters in managed pressure drilling applications using an unscented kalman filter technique, SPE Journal. 15(03):856--866. doi:10.2118/97028-MS
[17] Gravdal, J.E., Siahaan, H., and Bjorkevoll, K.S. (2018). Limiting Factors for the Ability to Achieve Accurate Pressure Control in Long Wells, Modeling, Identification and Control: A Norwegian Research Bulletin. 39(2):115--129. doi:10.4173/mic.2018.2.6
[18] Grune, L. and Pannek, J. (2011). Nonlinear Model Predictive Control: Theory and Algorithms, Springer.
[19] Haug, A.J. (2012). Bayesian estimation and tracking: a practical guide, John Wiley & Sons.
[20] Hermann, R. and Krener, A.J. (1977). Nonlinear Controllability and Observability, IEEE Transactions on Automatic Control. 22(5):728--740. doi:10.1109/TAC.1977.1101601
[21] Julier, S.J. and Uhlmann, J.K. (1997). New Extension of the Kalman Filter to Nonlinear Systems, In Proc. SPIE 3068, Signal Processing, Sensor Fusion, and Target Recognition VI, volume3. Orlando, FL, pages 182--193. doi:10.1117/12.280797
[22] Kaasa, G.-o., Stamnes, O.N., Aamo, O.M., and Imsland, L. (2012). Simplified hydraulics model used for intelligent estimation of downhole pressure for a managed-pressure-drilling control system, SPE Drilling & Completion. 27(01). doi:10.2118/143097-PA
[23] Khalil, H.K. (1996). Nonlinear Systems, Prentice-Hall, New Jersey. 2(5):1--5.
[24] Kou, R.S., Elliott, L.D., and Tarn, J.T. (1973). Observability of Nonlinear System, Information and Control. 99:89--99.
[25] Kwakernaak, H. and Sivan, R. (1974). Linear Optimal Control Systems, IEEE Transactions on Automatic Control. 19(5):631--632. doi:10.1109/TAC.1974.1100628
[26] Landet, I.S., Mahdianfar, H., Aarsnes, U. J.F., Pavlov, A., and Aamo, O.M. (2012). Modeling for MPD Operations with Experimental Validation, IADC/SPE Drilling Conference and Exhibition. doi:10.2118/150461-MS
[27] Lyons, W., BS Plisga J, G., and Lorenz, M. (2015). Standard Handbook of Petroleum and Natural Gas Engineering, Gulf Professional Publishing, 3rd edition.
[28] Meglio, F.D. and Aarsnes, U. J.F. (2015). A distributed parameter systems view of control problems in drilling, IFAC-PapersOnLine. 48(6):272--278. doi:10.1016/j.ifacol.2015.08.043
[29] Mogster, J., Godhavn, J.M., and Imsland, L. (2013). Using MPC for managed pressure drilling, Modeling, Identification and Control. 34(3):131--138. doi:10.4173/mic.2013.3.3
[30] Nandan, A. and Imtiaz, S. (2017). Nonlinear model predictive control of managed pressure drilling, ISA Transactions. 69:307--314. doi:10.1016/j.isatra.2017.03.013
[31] Nygaard, G., Naevdal, G., and Mylvaganam, S. (2006). Evaluating nonlinear kalman filters for parameter estimation in reservoirs during petroleum well drilling, Proceedings of the IEEE International Conference on Control Applications. pages 1777--1782. doi:10.1109/CACSD-CCA-ISIC.2006.4776910
[32] Nygaard, G.H., Imsland, L.S., and Johannessen, E.A. (2007). Using NMPC based on a low-order model for controlling pressure during oil well drilling, IFAC Proceedings Volumes (IFAC-PapersOnline), 2007. 40(5):159--164. doi:10.3182/20070606-3-MX-2915.00025
[33] Nygaard, O. G.H., Johannessen, E.A., Gravdal, J.E., and Iversen, F. (2007). Automatic Coordinated Control of Pump Rates and Choke Valve for Compensating Pressure Fluctuations During Surge-and-Swab Operations, IADC/SPE Managed Pressure Drilling and Underbalanced Operations Conference & Exhibition, 2007. doi:10.2118/108344-MS
[34] Pannocchia, G., Gabiccini, M., and Artoni, A. (2015). Offset-free MPC explained: Novelties, subtleties, and applications, IFAC-PapersOnLine. 48(23):342--351. doi:10.1016/j.ifacol.2015.11.304
[35] Pedersen, T., Aarsnes, U. J.F., and Godhavn, J.-m. (2018). Flow and pressure control of underbalanced drilling operations using NMPC, Journal of Process Control. 68:73--85. doi:10.1016/j.jprocont.2018.05.001
[36] Qin, S.J. and Badgwell, T.A. (2003). A survey of industrial model predictive control technology, Control Engineering Practice. 11(7):733--764. doi:10.1016/S0967-0661(02)00186-7
[37] Rasmussen, O. and Sangesland, S. (2007). Evaluation of MPD Methods for Compensation of Surge-and-Swab Pressures inFloating Drilling Operations, 2007. doi:10.2523/108346-ms
[38] Rossler, A. (2006). Runge-Kutta methods for Ito stochastic differential equations with scalar noise, BIT Numerical Mathematics. 46(1):97--110. doi:10.1007/s10543-005-0039-7
[39] Slotine, J.-J.E. and Weiping, L. (1991). Applied Nonlinear Control, Prentice Hall International Inc., New Jersey.
[40] Stakvik, J.Aa., Berg, C., Kaasa, G.-O., Aamo, O.M., and Lehner, U. (2016). Adaptive Model Based Choke Control System for MPD Operations, SPE/IADC Managed Pressure Drilling and Underbalanced Operations Conference and Exhibition. pages 1--11. doi:10.2118/179714-MS
[41] Stamnes, O.N., Zhou, J., Kaasa, G.O., and Aamo, O.M. (2008). Adaptive Observer Design for the Bottomhole Pressure of a Managed Pressure Drilling System, Proceedings of the IEEE Conference on Decision and Control, 2008. pages 2961--2966. doi:10.1109/CDC.2008.4738845
[42] Whittaker, A. and EXLOG Staff. (1985). Theory and Application of Drilling Fluid Hydraulics, D. Reidel Publishing Company.
[43] Zhou, J. (2018). Control of of Bottom Bottom Hole Control of Pressure during Oil Well Drilling, IFAC-PapersOnLine. 51(4):166--171. doi:10.1016/j.ifacol.2018.06.060

  title={{Identification and Optimal Control for Surge and Swab Pressure Reduction While Performing Offshore Drilling Operations}},
  author={Tengesdal, Njål and Holden, Christian},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}