Several researchers have studied the Sleipner model to understand the inherent flow physics better, to find a satisfactory match of the CO₂ plume migration. Various sources of uncertainty in the geological model and the fluid have been investigated. Most of the work undertaken on the Sleipner model employed the one factor at a time (OFAT) method and analysed the impact of uncertain parameters on plume match individually. In this study, we have investigated the impact of some of the most cited sources of uncertainties including porosity, permeability, caprock elevation, reservoir temperature, reservoir pressure and injection rate on CO₂ plume migration and structural tapping in the Sleipner. We tried to fully span the uncertainty space on Sleipner 2019 Benchmark (Layer 9) using a vertical-equilibrium based simulator. To the best of our knowledge, this is the first time that a study has focused on the joint effect of six uncertain parameters using data-driven models. This work would raise our scientific understanding of the complexity of the impact of the reservoir uncertainty on CO₂ plume migration in a real field model. The caprock elevation was shown to be the most important parameter in controlling the plume migration (overall importance of 26 %) followed by injection rate (24 %), temperature (22 %), heterogeneity in permeability (13 %), pressure (9 %) and porosity (6 %).

一些研究人员研究了Sleipner模型，以更好地了解固有的流动物理原理，以找到与CO ₂羽流迁移令人满意的匹配。已经研究了地质模型和流体的各种不确定性来源。在Sleipner模型上进行的大多数工作都采用了一个因素一次（OFAT）的方法，并分别分析了不确定参数对羽流匹配的影响。在这项研究中，我们调查了一些最引证的不确定性来源，包括孔隙度，渗透率，盖层高程，储层温度，储层压力和注入速率对CO _{2的影响。}Sleipner中的羽状迁移和结构攻丝。我们试图使用基于垂直平衡的模拟器来充分挖掘Sleipner 2019 Benchmark（第9层）的不确定性空间。据我们所知，这是首次使用数据驱动模型研究六个不确定参数的联合效应。这项工作将提高我们对实际模型中储层不确定性对CO ₂羽流迁移影响的复杂性的科学理解。在控制羽流迁移中（最重要的是26％），紧随其后的是注入率（24％），温度（22％），渗透率的非均质性（13％），压力（9％），盖层高程是最重要的参数。 ）和孔隙率（6％）。