A consistent approach toward reservoir simulation at different time scales

2006 SPE Intelligent Energy Conference and Exhibition

Volumn 1, Issue , 2006, Pages 126-134

  Nikolapu, M ^a   Cullick, A S ^b   Saputelli, L ^b   Mijares, G ^b   Sankaran, S ^b   Reis, L ^c  

^a UNIVERSITY OF HOUSTON   (United States)

^b HALLIBURTON   (United States)

^c Petrobras ^*  (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED RECOVERY MECHANISMS; FLOW NETWORKS; OIL AND GAS ASSETS; RESERVOIR SIMULATION;

COMPUTER SIMULATION; ENHANCED RECOVERY; OIL FIELD DEVELOPMENT; OIL WELL DRILLING; OPTIMIZATION; PRODUCTION CONTROL;

PETROLEUM RESERVOIRS;

EID: 33745447599     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. Saputelli, L.A., M. Nikolaou, and M.J. Economides. Self-Learning Reservoir Management, in paper SPE 84064, Annual Technical Conference and Exhibition. 2003. Denver, CO.
2. Mochizuki, S., L. Saputelli, C.S. Kabir, R. Cramer, M.J. Lochmann, R.D. Reese, L.K. Harms, C.D. Sisk, J.R. Hite, and A. Escorcia. Real Time Optimization: Classification and Assessment, in SPE 90213. 2004.
3. Saputelli, L., H. Malki, J. Canelon, and M. Nikolaou, A critical overview of artificial neural network applications in the context of continuous oil field optimization. SPE-77703, 2002.
4. Saputelli, L., S. Mochizuki, L. Hutchins, R. Cramer, M.B. Anderson, J.B. Mueller, A. Escorcia, A.L. Harms, C.D. Sisk, S. Pennebaker, J.T. Han, A. Brown, C.S. Kabir, R.D. Reese, G.J. Nunez, K.M. Landgren, C.J. McKie, and C. Airlie, Promoting Real-Time Optimization of Hydrocarbon Producing Systems. SPE 83978, 2003.
5. Saputelli, L., M. Nikolaou, and M.J. Economides, Real-Time Reservoir Management: A Multi-Scale Adaptive Optimization and Control Approach. Computational Geosciences, Special Issue on Modeling, 2005: p. to appear.
6. Nikolaou, M., A.S. Cullick, and L. Saputelli. Production Optimization - A Moving-Horizon Approach, in SPE 99358, Intelligent Energy 2006.2006. Amsterdam.
7. Brouwer, D.R., G. Nævdal, J.D. Jansen, E.H. Vefring, and C.P.J.W. van Kruijsdijk. Improved Reservoir Management Through Optimal Control and Continuous Model Updating, in SPE 90149. 2004.
8. Heijn, T., R. Markovinovid, and J.D. Jansen, Generation of Low-Order Reservoir Models Using System-Theoretical Concepts. SPE Journal, paper 88361, 2004.9(2): p. 202-218.
9. Ternyik, J., H. Bilgesu, S. Mohaghegh, and D. Rose. Virtual Measurement in Pipes, Part 1: Flowing Bottom Hole Pressure under Multi-phase flow and inclined wellbore conditions, in SPE Paper 30975. 1995.
10. Zhu, X., Y.C. Soh, and L. Xie, Design and analysis of discretetime robust Kaiman Filters. Automatica, 2002. 38: p. 1069-1077.
11. Jansen, P.E. and M.G. Kelkar. Application of Wavelets to production data in describing inter-well relationships, in SPE 38876. 1997.
12. Ramirez, W.F., Application of Optimal Control Theory to Enhanced Oil Recovery. 1987: Elsevier.
13. Brouwer, D.R. and J.D. Jansen, Dynamic Optimization of Waterflooding With Smart Wells Using Optimal Control Theory. SPE Journal, paper 78278, 2004.9(4): p. 391-402.
14. Renard, G., D. Dembele, J. Lessi, and J.L. Mari. System Identification Approach Applied to Watercut Analysis in Waterflooded Layered Reservoirs, in SPE 39606. 1998.
15. Brouwer, D.R., Dynamic water flood optimization with smart wells using optimal control theory. 2004: Ph.D. Thesis, Technische Universiteit Delft.
16. Aziz, K. and A. Settari, Petroleum Reservoir Simulation. 1979: Elsevier.
17. Brogan, W.L., Modern control theory. 3rd ed. 1991: Prentice Hall.
18. Chen, C.-T., Linear system theory and design. 3rd ed. 1999: Oxford University Press.
19. Kailath, T., Linear systems. 1980: Prentice-Hall.
20. Ljung, L., System Identification: Theory for the User. 2nd ed. 1999: Prentice Hall.
21. Söderstrom, T. and P. Stoica, System Identification. Series in Systems and Control Engineering. 1989: Prentice Hall International.
22. van Overschee, P. and B. DeMoor, Subspace Identification of Lin'ear Systems: Theory, Implementation, Applications. 1996: Kluwer.
23. Verhaegen, M., Identification of the deterministic part of MIMO state space models. Automatica, 1994. 30: p. 61-74.
24. Larimore, W.E. Canonical vartate analysis in identification, filtering and adaptive control, in 29th IEEE Conference on Decision and Control. 1990. Honolulu, HI.
25. Jolliffe, I.T., Principal Component Analysis. 1986: Springer-Verlag.