A comprehensive study on CO2/brine/hydrocarbon IFT for CO2 storage

CO2 capturing and storing it in geological sites or its usage for enhancing oil recovery (EOR) through gas flooding technique mitigates atmospheric CO2 emissions [1-3]. Reducing interfacial tension in CO2/brine and CO2/oil systems is one of the most effective methods for optimizing the CO2 sequestration process. In such a case, this gas easily penetrates into the porous environment and is stored, and as a result, CO2 is buried in subsurface formations. Also, this gas can increase the recovery factor by penetrating the oil formations based on different mechanisms. The effective mechanisms are oil phase swelling, oil viscosity reduction and wettability alteration [4, 5]. CO2 flooding lowers the interfacial tension (IFT) between oil and gas, and alters the wettability. This research intends to investigate the effect of different parameters on IFT in CO2/brine and CO2/oil systems. These parameters include: temperature, pressure, formation brine salinity and chemistry, CO2 purity, oil composition, and the effect of reservoir rock. The results obtained from this research can be used in the screening stage and selection of suitable formations for CO2 sequestration or CO2 flooding. For this purpose, different rock and oil samples will be collected from the studied fields. As noted in previous studies, the total acid number (TAN) of oil is a crucial factor affecting CO2/oil interfacial tension (IFT). Therefore, in our study, we will select and collect oil samples with varying TAN to analyze the impact of oil composition on CO2/oil IFT. Additionally, the objective of our study is to investigate the fluid/fluid interaction, and to eliminate the effect of rock chemical composition on the results, we will select an inactive and non-reactive rock type as a part of our experimental design. By using this approach, we aim to obtain more accurate and reliable results that are representative of the fluid/fluid interaction between CO2 and oil. Also, formation water with different compositions will be also synthesized in the laboratory. The effect of these parameters at different temperatures and pressures will be investigated experimentally by the IFT measuring apparatus. After conducting sufficient amount of experiments, there will be an important need to develop a comprehensive and reliable CO2/brine and CO2/oil IFT estimation model that can simultaneously consider impurity in CO2 phase, formation brine chemistry, live oil composition, and reservoir conditions. ANNs (Artificial neural networks) are powerful mathematical tools which are capable of providing a reliable model of a complex and nonlinear system between inputs and outputs through mimicking the biological neural network behavior. To date, ANNs have seen enormous applications in various engineering fields. At the end of this research the use of an ANN to accurately estimate CO2/brine, and CO2/brine IFT based on experimental data.