Influence of Well Control Parameters in the Development of Petroleum Fields Under Uncertainties
- Daniel Rodrigues dos Santos (University of Campinas) | Denis José Schiozer (University of Campinas)
- Document ID
- Society of Petroleum Engineers
- SPE Latin America and Caribbean Mature Fields Symposium, 15-16 March, Salvador, Bahia, Brazil
- Publication Date
- Document Type
- Conference Paper
- 2017. Society of Petroleum Engineers
- 1.6 Drilling Operations, 4.1.2 Separation and Treating, 1.7.5 Well Control, 4 Facilities Design, Construction and Operation, 3 Production and Well Operations, 1.7 Pressure Management, 4.1 Processing Systems and Design
- Development phase, Waterflooding, Production strategy selection, Uncertainties, Well control optimization
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In the development of oil fields, many parameters have to be selected in optimization procedures, demanding large computational effort, especially when uncertainties are considered. Therefore, it is common to separate design variables (G1) and well control variables (G2) optimization in a hierarchical process, but this may yield suboptimal results. We propose a well control analysis under uncertainties to verify whether G2 can be optimized separately in the development phase of petroleum fields. We also investigate the impact of G2 optimization on economic returns when platforms limit the production and for more pessimistic production costs. We perform reactive and proactive G2 optimization under uncertainties on a Benchmark Model (UNISIM-I-D, based on Namorado field) in three cases. In Case I, we use previously optimized strategies for G1, while G2 were controlled in a simplified way considering geological and economic uncertainties. In Case II we investigate the G2 optimization based on expected monetary value (EMV) for a restricted platform. Case III adopts the same restriction of Case II, but considers a pessimistic economic scenario. We consider five procedures for G2 optimization: (P1) longterm bottom-hole pressure control; (P2) short-term rates control; (P4) long-term rates control; (P4) well shut-in time control; and (P5) a combination of these procedures. In Case I, the EMV low percentage increase after G2 optimization indicates that a hierarchical process can be used in similar problems. Yet, G2 should be optimized during the lifetime of the field to increase EMV without additional cost. Depending on the representative model (RM) that best characterizes the field, there are potential further gains of almost 200 million USD for one of the scenarios studied. We achieved an increase of EMV around 8% for Case II. This suggests that G2 have a greater economic return when the platform restricts the production and injection for the field and G1 were not previously optimized. Case III showed even higher EMV gain (34%) indicating the importance of considering the economic scenario when defining the G2 strategy for the field. To reduce the search space in optimization problems, conventional techniques focus on optimizing design variables, underestimating the influence of well control management on G1. Moreover, some works do not include uncertainties and operational constraints. The results of this work indicate that G1 and G2 can be optimized hierarchically for a situation in which platforms do not constraint production or injection (Case I), since G2 variables have lower influence. This conclusion is not valid for restricted platforms and a pessimistic economic scenario (as in Case II and III) where G2 have higher influence in the results.
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Alhuthali, A. H. 2009. Optimal Waterflood Management Under Geologic Uncertainty Using Rate Control: Theory and Field Applications. Presented at SPE Technical Conference and Exhibition, New Orleans, 4-7 October. SPE-129511-STU. http://dx.doi.org/10.2118/129511-STU.
Alhuthali, A. H. H., Datta-Gupta, A., Yuen, B. B. W.. 2008. Optimal Rate Control Under Geologic Uncertainty. Presented at SPE/DOE Symposium on Improved Oil Recovery, Tulsa, 20-23 April. SPE-113628-MS. http://dx.doi.org/10.2118/113628-MS.
Artus, V., Durlofsky, L. J., Onwunalu, J. and Aziz, K. 2006. Optimization of nonconventional wells under uncertainty using statistical proxies. Comput. Geosci. 10 (04): 389–389. http://dx.doi.org/10.1007/s10596-006-9031-9.
Asadollahi, M. and Naevdal, G. 2009. Waterflooding Optimization Using Gradient Based Methods. Presented at SPE/EAGE Reservoir Characterization and Simulation Conference, Abu Dhabi, 19-21 October. SPE-125331-MS. http://dx.doi.org/10.2118/125331-MS.
Bellout, M. C., Ciaurri, E. D., Durlofsky, L. J.. 2012. Joint optimization of oil well placement and controls. Comput. Geosci. 16 (04): 1061–1061. http://dx.doi.org/10.1007/s10596-012-9303-5.
Chaudhri, M. M., Phale, H. A., Liu, N.. 2009. An Improved Approach for Ensemble-Based Production Optimization. Presented at SPE Western Regional Meeting, San Jose, 24-26 March. SPE-121305-MS. http://dx.doi.org/10.2118/121305-MS.
Cimic, M. 2006. Russian Mature Fields Redevelopment. Presented at SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, 3-6 October. SPE-102123-MS. http://dx.doi.org/10.2118/102123-MS.
Ebadi, F. and Davies, D. R. 2006. Should "Proactive" or "Reactive" Control Be Chosen for Intelligent Well Management? Presented at Intelligent Energy Conference and Exhibition, Amsterdam, 11-13 April. SPE-99929-MS. http://dx.doi.org/doi:10.2118/99929-MS.
Gaspar, A. T. F. S., Barreto, C. E. A. G., Mazo, E. O. M.. 2014. Application of Assisted Optimization to Aid Oil Exploitation Strategy Selection for Offshore Fields. Presented at SPE Latin America and Caribbean Petroleum Engineering Conference, Maracaibo, 21-23 May. SPE-169464-MS. http://dx.doi.org/10.2118/169464-MS.
Gaspar, A. T. F. S., Barreto, C. E. A. G. and Schiozer, D. J. 2016. Assisted process for design optimization of oil exploitation strategy. Journal of Petroleum Science and Engineering. 146: 473–488. http://dx.doi.org/10.1016/j.petrol.2016.05.042.
Haldorsen, H. H. and Leach, P. 2015. Energy 360: Invited Perspective: The Outlook for Energy: A View to 2040. J. Pet. Technol. 67 (04): 14–14. SPE-0415-0014-JPT. http://dx.doi.org/10.2118/0415-0014-JPT.
Humphries, T. D., Haynes, R. D. and James, L. A. 2013. Simultaneous and sequential approaches to joint optimization of well placement and control. Comput. Geosci. 18 (03): 433–433. http://dx.doi.org/10.1007/s10596-013-9375-x.
Jansen, J. D., Brouwer, R. and Douma, S. G. 2009. Closed Loop Reservoir Management. Presented at SPE Reservoir Simulation Symposium, The Woodlands, 2-4 February. SPE-119098-MS. http://dx.doi.org/10.2118/119098-MS.
Jesmani, M., Bellout, M. C., Hanea, R.. 2015. Particle Swarm Optimization Algorithm for Optimum Well Placement Subject to Realistic Field Development Constraints. Presented at SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, 14-16 September. SPE-175590-MS. http://dx.doi.org/10.2118/175590-MS.
Lake, L. W., Liang, X., Edgar, T. F.. 2007. Optimization Of Oil Production Based On A Capacitance Model Of Production And Injection Rates. Presented at Hydrocarbon Economics and Evaluation Symposium, Dallas, 1-3 April. SPE-107713-MS. http://dx.doi.org/10.2118/107713-MS.
Li, L. and Jafarpour, B. 2012. A variable-control well placement optimization for improved reservoir development. Comput. Geosci. 16 (04): 871–871. http://dx.doi.org/10.1007/s10596-012-9292-4.
Litvak, M. and Angert, P. 2009. Field Development Optimization Applied to Giant Oil Fields. Presented at SPE Reservoir Simulation Symposium, The Woodlands, 2-4 February. SPE-118840-MS. http://dx.doi.org/10.2118/118840-MS.
Perrone, A. and Rossa, E. D. 2015. Optimizing Reservoir Life-Cycle Production Under Uncertainty: a Robust Ensemble-Based Methodology. Presented at SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, 14-16 September. SPE-175570-MS. http://dx.doi.org/10.2118/175570-MS.
Pinto, M. A. S., Gildin, E. and Schiozer, D. J. 2015. Short-Term and Long-Term Optimizations for Reservoir Management with Intelligent Wells. Presented at SPE Latin American and Caribbean Petroleum Engineering Conference, Quito, 18-20 November. SPE-177255- MS. http://dx.doi.org/doi:10.2118/177255-MS.
Schiozer, D. J., Santos, A. A. de S. and Drumond, P. S. 2015. Integrated Model Based Decision Analysis in Twelve Steps Applied to Petroleum Fields Development and Management. Presented at EUROPEC 2015, Madrid, 1-4 June. SPE-174370-MS. http://dx.doi.org/10.2118/174370-MS.
van Essen, G., Zandvliet, M., Van den Hof, P.. 2009. Robust Waterflooding Optimization of Multiple Geological Scenarios. SPE J. 14 (01): 24–24. SPE-102913-PA. http://dx.doi.org/10.2118/102913-PA.
Yang, C., Nghiem, L. X., Card, C.. 2007. Reservoir Model Uncertainty Quantification Through Computer-Assisted History Matching. Presented at SPE Annual Technical Conference and Exhibition, Anaheim, 11-14 November. SPE-109825-MS. http://dx.doi.org/10.2118/109825-MS.
Zandvliet, M., Handels, M., van Essen, G.. 2008. Adjoint-Based Well-Placement Optimization Under Production Constraints. SPE J. 13 (04): 392–392. SPE-105797-PA. http://dx.doi.org/10.2118/105797-PA.