基于遗传算法的交联聚合物驱参数优化方法

xinmeng

基于遗传算法的交联聚合物驱参数优化方法 Advances in Geo-Energy Research, 2018, 2(4): 441-449 原文网址: http://www.astp-agr.com/index.php/Index/Index/detail?id=90             交联聚合物驱是在调剖堵水和聚合物驱的基础上发展起来的一项新型稳油控水技术，可进一步提高采收率，一般在聚合物驱的基础上可再提高5%～15%。在交联聚合物驱油过程中，若注入的聚合物和交联剂太少，起不到驱替的效果，反之会堵塞地层孔隙，并且导致生产成本增加。因此，注入聚合物和交联剂的浓度需要进行优化。近年来，随着计算机技术的快速发展，生物智能算法被越来越多的人所重视。这些算法具有简单易实现、鲁棒性强、易于和其它算法融合等优点,在解决复杂优化问题方面表现出优异的性能。本文以获得最大效益为目标函数，利用遗传算法全局寻优的特点，提出了一种交联聚合物驱注入参数优化设计方法。该方法通过遗传算法以随机方式获得给定范围内化学剂输入参数，自动调用交联聚合物驱数值模拟器计算原油产量，根据收支情况进一步计算目标函数的值。通过遗传算法迭代计算，自动优化出最优注入参数，对交联聚合物驱参数设计具有一定的指导意义。 Injection parameters optimization of crosslinked polymer flooding by genetic algorithm Peiqing Lian, Linlin Li, Taizhong Duan (Published: 2018-08-30) CorrespondingAuthor and Email: Peiqing Lian, lianpq.syky@sinopec.com Citation: Lian, P., Li, L., Duan, T. Injection parameters optimization of crosslinked polymer flooding by genetic algorithm. Advances in Geo-Energy Research, 2018, 2(4): 441-449, doi: 10.26804/ager.2018.04.08. ArticleType: Original article Abstract：     The crosslinked polymer flooding, which is developed on the basis of polymer flooding, is a new type of flooding technology. As an EOR method, cross-linked polymer flooding has become a research hotspot. In the process of cross-linked polymer flooding, if the concentrations of the polymer and the crosslinking agent are small, the viscosity of the solution is low, and it will not achieve the oil displacement effect. Meanwhile, if the concentrations of the polymer and crosslinking agent are large, the viscosity of the solution is high, it needs high pressure to drive it flowing in the formation. Further, with the increasing injection of chemical agents, the contradiction between reduced production and increased cost has presented. The performance of crosslinked polymer flooding depends on the interaction of these two factors. Therefore, the concentrations of polymer and crosslinking agent should be optimized. In this paper, an optimal design method is proposed by using genetic algorithm with global optimization characteristics algorithm, combining with the chemical flooding numerical simulation software UTCHEM, the concentrations of the chemical agents are optimized. Firstly, the cumulative oil production is calculated by numerical simulation software UTCHEM, then the concentrations of the chemical agents are randomly generated by the genetic algorithm in the encoding process, and the fitness function takes the profit of cross-linked polymer flooding. Given a set of initial values, through crossover and mutation of population, optimized injection concentrations of the polymer and cross-linking agent are obtained by the multi-generational calculation. Keywords: Enhanced oil recovery, crosslinked polymer flooding, genetic algorithm, fitness function.