S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Energy Systems Engineering (에너지시스템공학부) Theses (Ph.D. / Sc.D._에너지시스템공학부)
Stochastic Sequential Optimization for Full Field Development of Gas Condensate Reservoirs
가스컨덴세이트 필드 개발의 추계학적 순차 최적화
- 공과대학 에너지시스템공학부
- Issue Date
- 서울대학교 대학원
- stochastic sequential optimization ; field development optimization ; areal segmentation ; genetic algorithm ; gas condensate ; economic uncertainty
- 학위논문 (박사)-- 서울대학교 대학원 : 에너지시스템공학부, 2017. 2. 강주명.
- This study presents a new methodology for optimizing a full-field development plan using areal segmentation and stochastic sequential optimization. Previous works related to field development optimization have required a huge number of simulation runs to optimize well locations, and some of works with sequential optimization have shown unreliable results on the first step optimization.
The author introduced both areal segmentation and stochastic sequential optimization, and integrated them with a standard genetic algorithm. Areal segmentation utilizes the well locations defined before the optimization, and enhances the optimization efficiency by reducing number of required simulation runs while optimizing locations of individual wells. Stochastic sequential optimization helps to have higher credibility on the result of the first step optimization by incorporating Monte-Carlo simulation with the variables of the second step optimization.
The applicability of the methodology is verified by successfully optimizing full field development plan of a gas condensate field in offshore, Vietnam. Stochastic sequential optimization helps to make a reliable decision for the first step optimization under economic uncertainties, and areal segmentation plays a key role to accelerate the optimization procedure by reducing the number of simulation runs tremendously. Finally, the optimum plan achieves 10% higher cumulative oil recovery and 11-15% higher economic value than the base plan.
The proposed techniques in this study can be applied to optimize not only full field development plan but also reservoir management plan, and it would be helpful to improve economics of many kinds of oil and gas projects under economic and geological uncertainties.