Implementation Of Meta Heuristic Algorithm And Pressure Match Method To Observe Aquifer Constant In Retrograde Gas Condensate Reservoirs

M. Ahmadi, Z. Chen
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Abstract

Summary The motivation of doing this research was applying the hybrid of pressure match method and genetic algorithm (GA) to optimize the general material balance equation (GMBE) for a condensate gas reservoir with an almost strong aquifer to Figure out its 3 coefficients which are Nfoi, Gfgi and C. The advantage of implementing genetic algorithm (GA) is that the number of parameters which are supposed to be determined is not a concern. There is no doubt that calculating the aquifer constant without taking the reservoir parameters such as viscosity, porosity, net thickness and absolute permeability through making the observer wells much deeper is the most important, beneficial and technical vantage of the mentioned method. The comparison between obtained results from running the method and acquired outputs from the simulator unmask this fact that the pressure match-GA method has highly been successful of determining the coefficients by generating well matched pressures. As a demerit, the method has some problems with lower pressures based on the nature of general material balance equation (GMBE), being rooted in uncertainty, which defeating this obstacle can be considered as a topic for future studies as well as examining the compatibility of the suggested methodology for the heterogeneous reservoirs.
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元启发式算法与压力匹配法在逆行凝析气藏含水层常数观测中的实现
本研究的目的是将压力匹配法与遗传算法(GA)相结合,对具有强含水层的凝析气藏的一般物质平衡方程(GMBE)进行优化,求出其3个系数Nfoi、Gfgi和c。采用遗传算法(GA)的优点是不需要考虑需要确定的参数数量。毫无疑问,在不考虑黏度、孔隙度、净厚度、绝对渗透率等储层参数的情况下,通过加深观察井来计算含水层常数是该方法最重要、最有利的技术优势。将该方法的运行结果与模拟器获得的输出结果进行比较,揭示了压力匹配-遗传算法通过产生匹配良好的压力来确定系数的高度成功的事实。缺点是,基于一般物质平衡方程(GMBE)的性质,该方法在压力较低时存在一些问题,这些问题植根于不确定性,克服这一障碍可以作为未来研究的一个主题,并检查所建议的方法对非均质储层的兼容性。
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