卤水
相对渗透率
石油工程
磁导率
地质学
环境科学
岩土工程
化学
多孔性
膜
生物化学
有机化学
作者
Matthieu Mascle,Ameline Oisel,P. K. Munkerud,Einar Ebeltoft,Olivier Lopez,Colin Pryme,S. Youssef
出处
期刊:Petrophysics
[Society of Petrophysicists and Well Log Analysts (SPWLA)]
日期:2025-02-01
卷期号:66 (1): 26-43
标识
DOI:10.30632/pjv66n1-2025a2
摘要
The injection of CO2 into deep saline aquifers for geological carbon sequestration is being developed worldwide as a large-scale technology to reduce the greenhouse effect. Successful management of such industrial-scale projects requires accurate characterization of reservoir dynamic properties. However, a literature review shows a lack of CO2-brine relative permeability (kr) measurements under reservoir conditions for most storage cases, as well as a non-consensus on the measurement methods that partially explain the discrepancies observed in published results. The objectives of the work presented here are to reconciliate these methods and to suggest “best practices” when measuring kr curves with CO2. CO2/brine kr curves have been measured using two protocols (steady-state (SS) and unsteady-state (USS) methods) on a homogenous Grès-de-Fontainebleau sandstone. Experiments were conducted at reservoir conditions (54°C, 90 bars) using the mini-coreflood injection platform CAL-X™ (Youssef et al., 2018). This setup limits the plug size to a typical core length of 20 mm but provides qualitative access to the local saturations. We found that the combination of the different methods (SS and USS) allows us to derive the most reliable curves. As experiments on small samples are an order of magnitude faster than those measured on standard samples, the combination of these methods is made possible in a reasonable time (a few days). Finally, using two-dimensional (2D) radiography to monitor local saturation has been demonstrated to be a key element for the kr curves or the capillary pressure (Pc) curves interpretations. It provides the possibility to quality check the displacement homogeneity, in both radial and vertical directions.
科研通智能强力驱动
Strongly Powered by AbleSci AI