Wettability Alteration by Carbonated Brine Injection and Its Impact on Pore-Scale Multiphase Flow for Carbon Capture and Storage and Enhanced Oil Recovery in a Carbonate Reservoir

Interfacial tension and wettability alteration during hydrogen and carbon dioxide storage in depleted gas reservoirs

The storage of CO2 and hydrogen within depleted gas and oil reservoirs holds immense potential for mitigating greenhouse gas emissions and advancing renewable energy initiatives. However, achieving effective storage necessitates a thorough comprehension of the dynamic interplay between interfacial tension and wettability alteration under varying conditions. This comprehensive review investigates the multifaceted influence of several critical parameters on the alterations of IFT and wettability during the injection and storage of CO2 and hydrogen. Through a meticulous analysis of pressure, temperature, treatment duration, pH levels, the presence of nanoparticles, organic acids, anionic surfactants, and rock characteristics, this review elucidates the intricate mechanisms governing the changes in IFT and wettability within reservoir environments. By synthesizing recent experimental and theoretical advancements, this review aims to provide a holistic understanding of the processes underlying IFT and wettability alteration, thereby facilitating the optimization of storage efficiency and the long-term viability of depleted reservoirs as carbon capture and storage or hydrogen storage solutions. The insights gleaned from this analysis offer invaluable guidance for researchers, engineers, and policymakers engaged in harnessing the potential of depleted reservoirs for sustainable energy solutions and environmental conservation. This synthesis of knowledge serves as a foundational resource for future research endeavors aimed at enhancing the efficacy and reliability of CO2 and hydrogen storage in depleted reservoirs.

Machine learning approaches for estimating interfacial tension between oil/gas and oil/water systems: a performance analysis

Interfacial tension (IFT) is a key physical property that affects various processes in the oil and gas industry, such as enhanced oil recovery, multiphase flow, and emulsion stability. Accurate prediction of IFT is essential for optimizing these processes and increasing their efficiency. This article compares the performance of six machine learning models, namely Support Vector Regression (SVR), Random Forests (RF), Decision Tree (DT), Gradient Boosting (GB), Catboosting (CB), and XGBoosting (XGB), in predicting IFT between oil/gas and oil/water systems. The models are trained and tested on a dataset that contains various input parameters that influence IFT, such as gas-oil ratio, gas formation volume factor, oil density, etc. The results show that SVR and Catboost models achieve the highest accuracy for oil/gas IFT prediction, with an R-squared value of 0.99, while SVR outperforms Catboost for Oil/Water IFT prediction, with an R-squared value of 0.99. The study demonstrates the potential of machine learning models as a reliable and resilient tool for predicting IFT in the oil and gas industry. The findings of this study can help improve the understanding and optimization of IFT forecasting and facilitate the development of more efficient reservoir management strategies.

Experimental determination of wetting behavior under non-atmospheric conditions relevant to reservoirs: a practical guide

The wetting behavior in subsurface reservoirs plays a crucial role in storage, migration and liberation of fluid phases that are especially relevant to the energy sector. Further, the three-phase contact angle is important for implementing safe and successful subsurface storage of hydrogen and carbon dioxide. For reliable statements on the in situ wetting, it is important to be aware of the decisive factors of influence in order to design and perform the respective experiments in an appropriate way. This paper discusses the most important effects that shall be considered when determining contact angles experimentally, like drop size, surface roughness, aging process, dynamic behavior, and the pH, giving some valuable guidance to guarantee significant results. A drop base diameter of no less than 5 mm is found to be appropriate to minimize the impact of gravity on the contact angle under reservoir conditions. It is further confirmed that surface roughness contributes to better water wetting when the contact angles are below 90°. The versatility of contact angle measurements is shown through the dual-drop dual-crystal method that can be applied to estimate the adhesion forces present at the rock-brine interface and that need to be overcome by the flooding liquid to effectively displace hydrocarbons from the pores.

Impact of Chelating Agent Salt Type on the Enhanced Oil Recovery from Carbonate and Sandstone Reservoirs

In this paper, chelating agents were introduced as standalone fluids for enhancing the oil recovery from carbonate and sandstone reservoirs. Chelating agents such as glutamic acid di-acetic acid (GLDA), ethylene-diamine-tetra acetic acid (EDTA), and hydroxyl-ethylethylene-diamine-tri-acetic acid (HEDTA) were used. Chelating agents can be found in different forms such as sodium, potassium, or calcium salts. There is a significant gap in the literature about the influence of salt type on the hydrocarbon recovery from carbonate and sandstone reservoirs. In this study, the impact of the salt type of GLDA chelating agent on the oil recovery was investigated. Potassium-, sodium-, and calcium-based high-pH GLDA solutions were used. Coreflooding experiments were conducted at high-pressure high-temperature (HPHT) conditions using carbonate and sandstone cores. The used samples had porosity values of 15–18%, and permeability values were between 10 and 75 mD. Seawater was injected as a secondary recovery process. Thereafter, a GLDA solution was injected in tertiary mode, until no more oil was recovered. In addition to the recovery experiments, the collected effluent was analyzed for cations concentrations such as calcium, magnesium, and iron. Moreover, dynamic adsorption, interfacial tension, and contact angle measurements were conducted for the different forms of GLDA chelating agent solutions. The results of this study showed that incremental oil recovery between 19% and 32% of the Original Oil in Place (OOIP) can be achieved, based on the salt type and the rock lithology. Flooding carbonate rocks with the calcium-based GLDA chelating agent yielded the highest oil recovery (32% of OOIP), followed by that with potassium-based GLDA chelating agent, and the sodium-based GLDA chelating agent yielded the lowest oil recovery. The reason behind that was the adsorption of the calcium-based GLDA on the rock surface was the highest without reducing the rock permeability, which was indicated by the contact angle, dynamic adsorption, and flooding experiments. The outcome of this study will help in maximizing the oil recovery from carbonate and sandstone reservoirs by suggesting the most suitable salt type of chelating agents.