首页> 外文会议>Congreso y Exposición Internacional del Petróleo en México (Memorias Técnicas 2006) >Application of an Evolutionary Algorithm in Well Test Characterization of Naturally Fractured Vuggy Reservoirs
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Application of an Evolutionary Algorithm in Well Test Characterization of Naturally Fractured Vuggy Reservoirs

机译:演化算法在天然裂缝性松散油藏试井表征中的应用

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During the last years, several efforts have been done focused on developing the automatic computer-aided well test analysis. Traditionally, conventional gradient-based algorithms such as Levenberg-Marquardt have been used for parameters estimations. However, recently the use of new approaches based on global optimization methods has been introduced in the literature, mainly attempting to eliminate the influence of the initial guess on the overall regression, and overcoming the uniqueness problems. The aim of this work is to study the characterization of naturally fractured vuggy reservoirs via the automatic well test analysis by using a triple porosity model recently developed. Thus, an Evolutionary Algorithm (EA) was designed, taking into account the important fact that the triple porosity case may yield multiple solutions. Therefore, several aspects such as the parameters estimations with high precision and the necessity of developing analysis techniques computationally efficient are taken into account in the design of algorithms. According to the above, it is demonstrated that the algorithm developed in this work allows finding the multiple optimal solutions, with the desired precision. Advantages of the EA over the classical Levenberg-Marquardt method for this specific well test analysis problem are also discussed.
机译:在过去的几年中,在开发自动计算机辅助的试井分析方面进行了一些努力。传统上,常规的基于梯度的算法(例如Levenberg-Marquardt)已用于参数估计。但是,最近在文献中引入了基于全局优化方法的新方法的使用,主要是试图消除初始猜测对整体回归的影响,并克服唯一性问题。这项工作的目的是通过使用最近开发的三重孔隙度模型,通过自动试井分析,研究天然裂缝性松散储层的特征。因此,考虑到三重孔隙情况可能产生多种解决方案这一重要事实,设计了一种进化算法(EA)。因此,在算法的设计中考虑了诸如高精度的参数估计和开发具有计算效率的分析技术的必要性等多个方面。根据以上内容,证明了在这项工作中开发的算法可以找到具有所需精度的多个最优解。还讨论了针对该特定的试井分析问题,EA相对于经典Levenberg-Marquardt方法的优势。

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