首页> 外文会议>International Symposium of the Society of Core Analysts >DEVELOPMENT OF AUTOMATED HISTORYMATCHING PROGRAM BASE ON GENETIC ALGORITHM FOR X-RAY CT CORE FLOODING EXPERIMENT
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DEVELOPMENT OF AUTOMATED HISTORYMATCHING PROGRAM BASE ON GENETIC ALGORITHM FOR X-RAY CT CORE FLOODING EXPERIMENT

机译:X射线CT核心泛洪实验遗传算法自动历史算法的开发

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Recently it has become a common practice to construct 3D coreflooding simulation model to interpret water displacement experiments conducted under X-ray CT scanning.The unknown grid block parameters i.e.kro/krw and Pc curves are required to be optimized to get reasonable matching with experimental data such as changes of grid block water saturation.In order to evaluate the matching process efficiently a new automated history-matching program has been developed.This program applies Genetic Algorithm to optimize several coefficients for normalized kro/krw and Pc curves for each litho-facies.Several blind tests were carried out on hypothetical coreflooding models by changing the conditions of velocity and wettability to investigate the degree of accuracy and limitation of the program.The result of the reproducibility of the relative permeabilities was excellent for both water-wet and oil-wet cases regardless the velocity of coreflooding.On the other hand,the degree of reproducibility was not necessarily satisfactory for capillary pressure curves especially in high velocity case.Sensitivity of the controlling parameter in Genetic Algorithm such as crossover rate and mutation ratio was also investigated.The suitable values are estimated,though no simple trend was found.The program was finally applied to the interpretation of actual water displacement tests on oil-wet carbonate cores.The program successfully gave a reasonable set of kro/krw and Pc curves for each litho-facies and demonstrated its capability of grid block parameter optimization.
机译:最近,它已成为构建在X射线CT扫描下进行的3D CorePooding仿真模型来解释在X射线CT扫描下进行的水位移实验的常见做法。需要优化未知的网格块参数IEKRO / KRW和PC曲线以获得合理匹配的实验数据如网格块水饱和度的变化。为了有效地评估匹配过程,已经开发了一种新的自动化历史匹配程序。该程序应用遗传算法来优化用于每个光学相对的归一化KRO / KRW和PC曲线的若干系数。盲目的盲目测试通过改变速度和润湿性的条件来调查程序的准确性和限制程度来进行假设的核心全面模型。相对渗透率的再现性的结果对于水湿和油来说是优异的湿式案例无论核心般的速度如何。另一方面,再现性程度是对于毛细管压力曲线不一定令人满意,特别是在高速案例中。还研究了遗传算法中的控制参数的敏感性,例如交叉速率和突变比率。估计合适的值,尽管没有发现简单的趋势。终于应用了程序对油湿碳酸核实际水位试验的解释。该计划成功地为每个光谱相结合了一套合理的KRO / KRW和PC曲线,并证明了其电网块参数优化能力。

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