The objective of this work is to develop and apply a numerical workflow for the simultaneous determinations of the effective porosity and the dispersion coefficient from core flood taking chemical reactions into account. This approach consists of modeling the species transport at the core scale coupled with the chemical reactions, as involved in alkali flooding core experiments. Then, the one-dimensional model is compared with experimental breakthrough curves of tracer and pH, and the optimization process based on a genetic algorithm permits to identify the optimal parameter combination of effective porosity and dispersion coefficient. This approach is validated for an artificial case, then investigated on two distinct experimental configurations of core flooding. The proposed workflow, which involves an additional experimental measurement for pH, provides both an estimate of the kinetic porosity that is lower than the measured porosity, as well as an estimate of the dispersion coefficient that is significantly different from the usual single signal approach. The tests performed in this work do not take the interactions of the fluid with the rock into account.

这项工作的目的是开发和应用数值工作流程，以同时确定有效孔隙度和岩心驱散系数，同时考虑化学反应。这种方法包括模拟岩心尺度上的物质传输以及化学反应，如碱驱岩心实验中所涉及的那样。然后，将一维模型与示踪剂和pH值的实验突破曲线进行比较，基于遗传算法的优化过程允许识别有效孔隙度和分散系数的最佳参数组合。这种方法在一个人工案例中得到验证，然后对两种不同的岩心驱油实验配置进行了研究。建议的工作流程包括额外的 pH 实验测量，提供低于测量孔隙度的动力学孔隙度估计值，以及与通常的单信号方法显着不同的色散系数估计值。在这项工作中进行的测试没有考虑流体与岩石的相互作用。