Reactive fluid/rock interactions during carbon dioxide (CO₂) injection into saline aquifers would trigger injectivity issues, particularly due to the presence of salt precipitation and fines migration. Previous CO₂ injectivity change models, on the other hand, are ascribed by permeability change caused by salt precipitation without taking into account the alteration caused by fines migration. Therefore, this research aims to develop a correlation to predict the CO₂ injectivity in which the permeability change is described as a function of brine salinity, CO₂ injection flow rate, particle size and particle concentration parameters. The impacts of individual and combined interactions between these parameters were investigated using core flooding experiments. The experiments were performed using Berea sandstone saturated with different brine salinities between 0 and 100,000 ppm. Then, CO₂ saturated brine which contains various concentrations of different-sized particles was injected followed by several supercritical CO₂ (scCO₂) injection from 2 to 10 cm³/min. The percentage difference between the initial and final permeabilities was used to calculate the permeability change. Lastly, the statistical response surface methodology (RSM) was applied to model and predict the permeability changes. The relationship between permeability change and the interaction effects of four design parameters were explained with the help of 2D response surface using analysis of variance (ANOVA). The experimental results showed that brine salinity has a greater influence on permeability reduction as compared to the particles and CO₂ injection flow rates. The presence of both salt precipitation and fines migration during scCO₂ injection was found to intensify the permeability reduction up to threefold with increasing brine salinity and particle size. The newly developed model fit well with the experimental data and was statistically validated with reported data from different case studies.

将二氧化碳 (CO ₂ ) 注入咸水层期间的反应性流体/岩石相互作用会引发注入问题，特别是由于盐沉淀和细粒迁移的存在。 另一方面，以前的 CO ₂注入变化模型归因于盐析引起的渗透率变化，而没有考虑细粒迁移引起的变化。因此，本研究旨在开发相关性来预测 CO ₂注入量，其中渗透率变化被描述为盐水盐度 CO ₂的函数注射流速、粒径和颗粒浓度参数。使用岩心驱油实验研究了这些参数之间单独和组合相互作用的影响。实验是使用被 0 到 100,000 ppm 的不同盐水盐度饱和的 Berea 砂岩进行的。然后，注入含有不同浓度不同尺寸颗粒的CO ₂饱和盐水，然后从 2 到 10 cm ³注入几次超临界 CO ₂ (scCO ₂ )/分钟。初始渗透率和最终渗透率之间的百分比差异用于计算渗透率变化。最后，应用统计响应面方法 (RSM) 对渗透率变化进行建模和预测。借助方差分析 (ANOVA) 的二维响应面，解释了渗透率变化与四个设计参数相互作用效应之间的关系。实验结果表明，与颗粒和 CO ₂ 注入流速相比，盐水盐度对渗透率降低的影响更大。scCO ₂过程中存在盐析和细粒迁移 发现随着盐水盐度和粒度的增加，注入使渗透率降低了三倍。新开发的模型与实验数据非常吻合，并通过来自不同案例研究的报告数据进行了统计验证。