Greenhouse Gases: Science and Technology最新文献

This study investigated the effects of absolute permeability on the performance of continuous CO₂ injection for a CO₂-enhanced oil recovery and storage process (CO₂-EOR and Storage) in a water-invaded zone. First, the CO₂ solubility in dead-oil and brine samples and the oil swelling factor were measured using a visual high-pressure–high-temperature cell. Following this, several continuous immiscible CO₂ injection core flooding tests at a constant rate of 0.5 cm³/min and in situ reservoir conditions were conducted. The core samples were taken from a carbonate depleted oil reservoir located in southern Iran. The results revealed that more than 30% of the injected CO₂ was trapped primarily by residual-phase and solubility-trapping mechanisms. In addition, it was found that the core samples with lower absolute permeability provided higher storage efficiency. In contrast, the ones with the highest absolute permeability showed the least potential for CO₂ storage. From the EOR point of view, on average, 18% of the residual oil was produced mechanistically through swelling as well as physical displacement. Although the results showed a declining trend in the amount of oil produced with increased absolute permeability, no clear relationship could be established.

Saline aquifers are considered among the most attractive porous media systems for underground hydrogen storage (UHS) because of their wide availability and the considerable capacity of storage. The successful implementation of UHS in saline aquifers depends on many vital factors and parameters. Among these factors, the solubility of hydrogen (H₂) in brine remains a relevant consideration, particularly due to its influence on potential bio-geochemical reactions that may occur within underground formations. Given the significant expense and time demands associated with experimental methods for determining hydrogen solubility in brine, there is a growing need for a reliable and low-cost alternative capable of delivering accurate predictions. In this research, a suite of robust machine learning (ML) schemes, including multilayer perceptron (MLP), genetic programming (GP), and the group method of data handling (GMDH), is employed to construct predictive models for hydrogen solubility in brine, specifically under challenging high-pressure and high-temperature scenarios. The obtained results demonstrated the promising performance of the newly suggested ML-based paradigms. MLP optimized with Levenberg–Marquardt (MLP-LMA) yielded the best statistical metrics, including an R² of 0.9991 and an average absolute relative error (AARE) of 0.9417%. The findings of this study are important because they demonstrate that ML-based approaches embodied in intelligent paradigms are accurate and efficient and therefore have potential for use in reservoir simulators to assess dissolution processes associated with UHS in porous media.

The amino groups and its substituents of organic amine absorbents have an important influence on the CO₂ absorption and desorption performance. In this study, four diamines with the same primary amino group and another different amino groups were selected as absorbents, including 1,3-propanediamine (1,3-PDA), 3-methylaminopropylamine (MAPA), 3-dimethylaminopropylamine (DMAPA), and 3-diethylaminopropylamine (DEAPA). The phase-change absorption system uses a mixture of polyether and H₂O as the solvent. The CO₂ absorption performance of flue gas was studied with the analysis on absorption and desorption rate, cycle capacity, and desorption ratio. The effect of diamine molecular structures on phase-change CO₂ capture was investigated by nuclear magnetic carbon spectroscopy. The results show that DEAPA exhibits highest absorption capacity of 1.21 mol CO₂/mol amine and recycling capacity of 1.09 mol CO₂/mol amine. The absorption rate of primary and secondary diamines in the phase-change system is significantly higher than that of primary and tertiary diamines. The diamine system with tertiary amino groups has significantly faster desorption rate, higher desorption ratio, and cycle capacity than the primary and secondary diamine systems. The intramolecular tertiary amino group is more conducive to promoting the absorption of CO₂ than the intermolecular tertiary amino group, which can increase the absorption rate of CO₂ by the primary amino group and enhance the CO₂ desorption.

Sedimentary geological formations are known to be great candidates for geological carbon sequestration. Published studies suggest the southeast of the United States contains many formations suitable for carbon storage. The Cassville 1 Stratigraphic Borehole well could act as a potential carbon reservoir for nearby energy resource facilities in Georgia, United States. Although studies have shown that porous formations are adequate for geological carbon sequestration, it is important to understand possible geochemical reactions between CO₂ and the targeted geological formation before injecting any fluids. In this study, a sandstone sample from the Cassville 1 well is being considered for geological carbon sequestration in the Conasauga Group in Northwest Georgia. The collected sandstone sample, consisting of quartz, K-feldspar, micas, kaolinite, and carbonate minerals such as calcite and dolomite, has a 6% porosity. Leveraging the formation composition and porosity, a one-dimensional continuum reactive transport model was built using CrunchFlow to assess possible geochemical reactions between injected CO₂ and the geological formation. Simulation results show that the carbonate minerals, calcite and dolomite, dissolve during the injection period of 10,000 days, increasing formation porosity from 6% to as much as 30%. The rate and extent of carbonate mineral dissolution and resulting porosity increase are highly sensitive to mineral reactive surface area values. No evidence of mineral precipitation was observed, suggesting that dissolution reactions will control porosity evolution during the CO₂ injection period.

Pollutant emissions such as carbon monoxide (CO), hydrocarbons (HCs), nitrogen oxides (NO_x), and particulate matter (PM) from diesel engines have serious adverse effects on both human health and the environment. Advanced post-engine emission control systems, such as the diesel oxidation catalyst (DOC) and selective catalytic reduction (SCR), have proven effective in substantially reducing or minimizing emissions of CO, HC, and NO_x. Additionally, the use of metal-based fuel additives in diesel fuel has been widely studied and applied in practice to improve engine performance and optimize emission outcomes. The interaction between metal-based fuel additives and the performance of DOC and SCR systems has become a key area of research focus. This study investigates the impact of metal-based fuel additives—including cerium (IV) oxide, copper (II) oxide, magnesium oxide, nickel (II) oxide, and titanium (IV) oxide—on the performance of DOC and SCR catalysts under various engine load conditions. In the experiments, conventional DOC and SCR catalysts were used, specifically Pt/Al₂O₃ for the DOC and V₂O₅-WO₃/TiO₂ versus Ag/Al₂O₃ for the SCR. The variations in CO, NO, and NO_x levels in the exhaust gas were monitored, and the efficiency of the catalysts in converting these emissions was calculated and analyzed. The results indicate that the combination of metal-based fuel additives with post-engine emission control technologies can effectively reduce pollutant emissions from diesel engines. Among the metal-based additives tested, cerium (IV) oxide and nickel (II) oxide were found to be particularly effective in enhancing the conversion efficiencies of DOC and SCR systems.