RESUMEN
Carbon Capture, Utilization, and Storage (CCUS) offers a viable solution to reduce the carbon footprint in the petroleum industry, and foam injection presents a promising method to achieve this while simultaneously increasing oil recovery. In this work, we studied the feasibility of CO2 foam for co-optimizing enhanced oil recovery and CO2 storage in a high-salinity carbonate formation. The simulated hydrodynamic model is a depleted formation containing 30% residual oil, with three mechanisms for CO2 storage: solubility, residual, and mineralization trapping mechanisms. The results showed that after 20 years, oil recovery during foam injection was 2.7 times higher than CO2 injection, and the CO2 stored during foam flooding was 38% higher than CO2 injection. Notably, foam injection also increased CO2 storage capacity by 2.6 times, indicating the potential to store around 2 gigatons of CO2 in the simulated model. This was attributed to the ability of foam to significantly reduce gas mobility and thus form isolated bubbles through its Jamin effect. Residual trapping was the dominant trapping mechanism, contributing to over 70% of the total CO2 trapped, attributed to the reduction in the dissolution of CO2 in brine due to the high salinity of the aqueous medium. CO2 mineralization was also studied, showing the least trapping efficiency and the dissolution trend of all the carbonate minerals. This study illustrates a novel CO2 utilization and storage technique in which CO2 is concurrently sequestered while enhancing oil recovery in a depleted oil reservoir by injecting CO2 as foam. The relevance of this study lies in its potential to provide a dual benefit of reducing greenhouse gas emissions and boosting oil production, offering a sustainable approach for the petroleum industry.
RESUMEN
A key factor affecting foam stability is the interaction of foam with oil in the reservoir. This work investigates how different types of oil influence the stability of foams generated with binary surfactant systems under a high salinity condition. Foam was generated with binary surfactant systems, one composed of a zwitterionic and a nonionic surfactant, and the other composed of an anionic and a nonionic surfactant. Our results showed that the binary surfactant foams investigated are more tolerant under high salinity conditions and in the presence of oil. This was visually observed in our microscopic analysis and was further attributed to an increase in apparent viscosity achieved with binary surfactant systems, compared to single surfactant foams. To understand the influence of oil on foam stability, we performed a mechanistic study to investigate how these oils interact with foams generated with binary surfactants, focusing on their applicability under high salinity conditions. The generation and stability of foam are linked to the ability of the surfactant system to solubilize oil molecules. Oil droplets that solubilize in the micelles appear to destabilize the foam. However, oils with higher molecular weights are too large to be solubilized in the micelles, hence the molecules will have less ability to be transported out of the foam, so oil seems to stabilize the foam. Finally, we conducted a multivariate analysis to identify the parameters that influenced foam stability in different oil types, using the experimental data from our work. The results showed that the oil molecular weight, interfacial tension between the foaming liquid and the oil, and the spreading coefficient are the most important variables for explaining the variation in the data. By performing a partial least square regression, a linear model was developed based on these most important variables, which can be used to predict foam stability for subsequent experiments under the same conditions as our work.
RESUMEN
Oil reservoirs are nearing maturation, necessitating novel enhanced oil recovery (EOR) techniques to meet escalating global energy demands. This demand has spurred interest in reservoir production analysis and forecasting tools to enhance economic and technical efficiency. Accurate validation of these tools, known as simulators, using laboratory or field data is pivotal for precise reservoir productivity estimation. This study delves into the application of nanoparticles in foam flooding for mobility control to improve sweep efficiency. Foam generation can occur in-situ by simultaneous injection of surfactants and gas or through pre-generated foam injection into the reservoir. In this work, a series of systematic simulations were run to investigate how much injected fluids can reduce gas breakthrough while also increasing oil recovery. Subsequently, we analyzed the most effective optimization strategies, considering their economic limits. Our primary objective is to numerically model nanofoam flooding as an innovative EOR approach, synergizing foam flooding mechanisms with nanotechnology benefits. In this work, modeling of nanoparticles in foam liquid was represented by the interfacial properties provided to the injection fluid. Additionally, we simulated Water-Alternating-Gas (WAG) injection schemes across various cycles, comparing their outcomes. Our results showed that nanofoam injection achieved a higher recovery factor of at least 38% and 95% more than WAG and gas injections, respectively. The superior efficiency and productivity of foam injection compared to WAG and gas injection suggest an optimal EOR approach within the scope of our model. These simulated optimization techniques contribute to the future development of processes in this field.