The CO2-Assisted Gravity Drainage process (GAGD) has been introduced to become one of the mostinfluential process to enhance oil recovery (EOR) methods in both secondary and tertiary recovery through immiscibleand miscible mode. Its advantages came from the ability of this process to provide gravity-stable oil displacement forenhancing oil recovery. Vertical injectors for CO2 gas have been placed at the crest of the pay zone to form a gas capwhich drain the oil towards the horizontal producing oil wells located above the oil-water-contact. The advantage ofhorizontal well is to provide big drainage area and small pressure drawdown due to the long penetration. Manysimulation and physical models of CO2-AGD process have been implemented at reservoir and ambient conditions tostudy the effect of this method to improve oil recovery and to examine the most parameters that control the CO2-AGDprocess. The CO2-AGD process has been developed and tested to increase oil recovery in reservoirs with bottom waterdrive and strong water coning tendencies. In this study, a scaled prototype 3D simulation model with bottom waterdrive was used for CO2-assisted gravity drainage. The CO2-AGD process performance was studied. Also the effects ofbottom water drive on the performance of immiscible CO2 assisted gravity drainage (enhanced oil recovery and watercut) was investigated. Four different statements scenarios through CO2-AGD process were implemented. Resultsrevealed that: ultimate oil recovery factor increases considerably when implemented CO2-AGD process (from 13.5%to 84.3%). Recovery factor rises with increasing the activity of bottom water drive (from 77.5% to 84.3%). Also,GAGD process provides better reservoir pressure maintenance to keep water cut near 0% limit until gas flood frontreaches the production well if the aquifer is active, and stays near 0% limit at all prediction period for limited waterdrive.
Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil
... Show MoreHydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif
... Show MoreThis study aims at recognizing Pesticides and how the process of pesticides biodegradation by microbiology took place, and the effect of environmental condition on this process. And how the research uncovered the efficiency of microbiology in the biodegradation process of pesticides, as the perfect temperature for the biodegradation process is 40 °C and humidity effect on pesticides efficiency, when high humidity reduces pesticide efficiency and the perfect acidity to increase bacteria efficiency is 7, for the incubation period, it was found during the previous studies that the best incubation period is 5-7 days, in this period the bacteria imprint on pesticides and increase biodegradation of it.
In this paper, we investigate and study quantum theoretical of quark-gluon interaction modeling in QGP matter formatted. In theoretical modeling, we can use a flavor number, strength coupling, critical energy Tc = 190 MeV, system energy (400-650)MeV, fugacity of quark and gluon, and photon energy in range of 1-10 GeV parameter to calculation and investigation spectrum of photon rate. We calculation and study the photon rate produced through bremsstrahlung processes from the stable QGP matter. The photon rate production from cg → dgy systems at bremsstrahlung processes are found to be increased with increased fugacity, decreased strength coupling, decreased the photons energy and temperature of system. The photons rate in cg → dgy is inc
... Show MoreThis work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r
... Show MoreThe objective of this paper was to study the laser spot welding process of low carbon steel sheet. The investigations were based on analytical and finite element analyses. The analytical analysis was focused on a consistent set of equations representing interaction of the laser beam with materials. The numerical analysis based on 3-D finite element analysis of heat flow during laser spot welding taken into account the temperature dependence of the physical properties and latent heat of transformations using ANSYS code V.10.0 to simulate the laser welding process. The effect of laser operating parameters on the results of the temperature profile were studied in addition to the effect on thermal stresses and dimensions of the laser w
... Show MoreINTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound sy
... Show MoreSemiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that
... Show MoreThis study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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