Foam injection is an effective method for modifying gas mobility in subsurface flow applications making it ideal for environmental remediation applications. Remediation of contaminated soils/aquifers of nonaqueous phase liquids using foamed surfactant solutions is a viable option but a predictive foam model is needed that is flexible to the addition of more accurate physical descriptions. Such a model is essential to ensure successful operations in soil remediation applications. The objective of this paper is to develop a full-physics, mechanistic transient foam flow model and integrate it into the multiphysics, modular AD-GPRS framework (Automatic Differentiation–General Purpose Research Simulator). We chose AD-GPRS because it allows rapid prototyping and addition of complex physics and modeling strategies. We develop the model ground-up from pore-scale observations and implement a new flowing foam fraction constitutive relation that depends on the local pressure gradient, local permeability, and flowing bubble density. Our model predicts the two flow regimes commonly observed in steady-state pressure gradient measurements: the low-quality regime and the high-quality regime. Additionally, the model is used to match transient experimental results of homogeneous and slightly heterogeneous cores with a wide range of permeability values. The implementation of this model within AD-GPRS allows testing of ideas and modeling strategies as well as inclusion of more complex physics or foam generation kinetics.

泡沫喷射是一种改善地下流动应用中气体流动性的有效方法，使其非常适合于环境修复应用。使用泡沫表面活性剂溶液修复非水相液体的污染土壤/含水层是可行的选择，但需要一种预测性泡沫模型，该模型应灵活地添加更准确的物理描述。这样的模型对于确保在土壤修复应用中成功运行至关重要。本文的目的是开发一个全物理的，机械的瞬态泡沫流动模型，并将其集成到多物理的模块化AD-GPRS框架（自动微分–通用研究模拟器）中。我们之所以选择AD-GPRS，是因为它可以快速制作原型并添加复杂的物理和建模策略。我们从孔隙尺度的观测结果中建立模型，并实现了一种新的流动泡沫分数本构关系，该关系取决于局部压力梯度，局部渗透率和流动气泡密度。我们的模型预测了稳态压力梯度测量中通常会观察到的两种流动状态：低质量状态和高质量状态。此外，该模型用于匹配具有广泛渗透率值的均质岩心和略有异质岩心的瞬态实验结果。在AD-GPRS中实施此模型可以测试思想和建模策略，还可以包含更复杂的物理或泡沫生成动力学。和流动的气泡密度。我们的模型预测了稳态压力梯度测量中通常会观察到的两种流动状态：低质量状态和高质量状态。此外，该模型用于匹配具有广泛渗透率值的均质岩心和略有异质岩心的瞬态实验结果。在AD-GPRS中实施此模型可以测试思想和建模策略，还可以包含更复杂的物理或泡沫生成动力学。和流动的气泡密度。我们的模型预测了稳态压力梯度测量中通常会观察到的两种流动状态：低质量状态和高质量状态。此外，该模型用于匹配具有广泛渗透率值的均质岩心和略有异质岩心的瞬态实验结果。在AD-GPRS中实施此模型可以测试思想和建模策略，还可以包含更复杂的物理或泡沫生成动力学。该模型用于匹配具有广泛渗透率值的均质和微异质岩心的瞬态实验结果。在AD-GPRS中实施此模型可以测试思想和建模策略，还可以包含更复杂的物理或泡沫生成动力学。该模型用于匹配具有广泛渗透率值的均质和微异质岩心的瞬态实验结果。在AD-GPRS中实施此模型可以测试思想和建模策略，还可以包含更复杂的物理或泡沫生成动力学。