000 02362nab a2200205 4500
005 20260520001752.0
008 260224s2010 xxu
245 0 0 _aOptimization of production performance in a Co2 flooding reservoir under uncertainty
260 _a
_b
_cfeb. 2010
270 _a14/06/2010 ; 10/06/2010
300 _a8 p. ; 71-78
520 _aTranscripción del resumen del autor. CO2 flooding has gained momentum in the oil and gas industry and might be suitable for approximately 80% of oil reservoirs worldwide based on the oil recovery criteria alone. In addition to miscibility, production performance needs to be optimized to achieve higher sweep efficiency and oil recovery. Although many techniques have been made available for production optimization in the upstream oil and gas industry, it is still a challenging task to optimize production performance in the presence of physical and/or financial uncertainties. In this paper, a new technique is developed to optimize production performance in a CO2 flooding reservoir under uncertainty. More specifically, potential uncertainties influencing production performance are analyzed and assessed by using the geostatistical technique. This enables us to integrate the available information within a unified and consistent framework and to generate multiple geological realizations accounting for uncertainty and spatial variability. Subsequently, the net present value (NPV) is selected as the objective function to be optimized by using the genetic algorithm, while well rates of the injectors and the flowing bottomhole pressure for the producers are chosen as the controlling variables. In addition, corresponding modifications have been made to accelerate the convergence speed of the genetic algorithm. A field case is used to demonstrate the procedures of the newly developed technique and the optimized results show that the oil recovery and the NPV can be increased by 6.4% and 9.2%, respectively. It is also found that the genetic algorithm is a powerful and reliable search method to optimize production performance of reservoirs with complex structures.
581 _a2
773 0 _tJournal of Canadian Petroleum Technology
_g49
942 _cARTICULO
100 1 _aChen, S.
_927439
100 1 _aLi, H.
_920271
100 1 _aYang, D.
_921331
999 _c170887
_d170887