Numerical models are a critical tool for forecasting subsurface multiphase flow associated with geologic carbon storage. The uncertainty of model results stems from many factors, including uncertainty in multiphase flow parameters. Specifically, relative permeability and capillary pressure relationships depend on both the rock properties and fluid properties, and the latter may be highly nonlinear as fluid temperature, and pressure conditions change. Forecasts of trapping mechanisms, phase behavior, and plume movement are impacted by choice of relative permeability and capillary pressure functions and how those functions are calibrated and constrained. In particular, one of the most neglected aspects of such simulations is meaningful capillary pressure processes. A primary goal of this study is to quantify the difference in forecasts for models that utilize capillary pressure functions calibrated with measured data from the results of models without such. Additionally, the relative permeability models developed here were derived from measured capillary pressure data. Those data were used to constrain saturation endpoints in the relative permeability curves and dictate how that relative permeability was distributed spatially. The main conclusions drawn from this analysis include (1) heterogeneity in relative permeability plays a significant role in simulated forecasts of CO₂ migration, trapping mechanisms and storage capacity, as well as oil and water production, and (2) capillary pressure, and in particular, the magnitude of capillarity also plays a significant role in these processes. Conversely, if the magnitude of capillarity is small relative to in situ fluid pressures, it imparts insignificant effects on these processes.

数值模型是预测与地质碳储存相关的地下多相流的关键工具。模型结果的不确定性源于多种因素，包括多相流参数的不确定性。具体而言，相对渗透率和毛细管压力关系取决于岩石性质和流体性质，后者可能随着流体温度和压力条件的变化而高度非线性。捕获机制、相行为和羽流运动的预测受相对渗透率和毛细管压力函数的选择以及这些函数的校准和约束方式的影响。特别是，此类模拟中最被忽视的方面之一是有意义的毛细管压力过程。本研究的一个主要目标是量化模型的预测差异，这些模型利用毛细管压力函数，并根据没有毛细管压力函数的模型结果的测量数据进行校准。此外，这里开发的相对渗透率模型来自测量的毛细管压力数据。这些数据用于限制相对渗透率曲线中的饱和度终点，并说明相对渗透率在空间上的分布方式。该分析得出的主要结论包括：（1）相对渗透率的非均质性在 CO2 的模拟预测中起着重要作用 这些数据用于限制相对渗透率曲线中的饱和度终点，并说明相对渗透率在空间上的分布方式。该分析得出的主要结论包括：（1）相对渗透率的非均质性在 CO2 的模拟预测中起着重要作用 这些数据用于限制相对渗透率曲线中的饱和度终点，并说明相对渗透率在空间上的分布方式。该分析得出的主要结论包括：（1）相对渗透率的非均质性在 CO2 的模拟预测中起着重要作用₂迁移、捕集机制和储存能力，以及油和水的生产，以及 (2) 毛细管压力，特别是毛细管作用的大小也在这些过程中起着重要作用。相反，如果毛细作用的大小相对于原位流体压力较小，则对这些过程的影响微不足道。