A geological model was built for the Sadi reservoir, located at the Halfaya oil field. It is regarded as one of the most significant oilfields in Iraq. The study includes several steps, the most essential of which was importing well logs from six oil wells to the Interactive Petrophysics software for conducting interpretation and analysis to calculate the petrophysical properties such as permeability, porosity, shale volume, water saturation, and NTG and then importing maps and the well tops to the Petrel software to build the 3D-Geological model and to calculate the value of the original oil in place. Three geological surfaces were produced for all Sadi units based on well-top data and the top Sadi structural map. The reservoir has been divided into 85 sublayers in the vertical direction and 170*143 grid cells in the x-y direction, totalling 2,066,350 grid cells. The Sequential Gaussian Simulation technique is used to fill 3D grid cells with property values in locations far from wells after upscaling the well log data, then distributed across all reservoir zones. The standard original oil in place has been calculated, uncertainty evaluation was used to obtain more accurate results. Model Risk Analysis employs Monte Carlo Simulation to generate the pessimistic, most likely, and optimistic reserve values (P90, P50, and P10). The uncertainty was affected by the oil formation volume factor, oil depth, petrophysical model (porosity, water saturation, and NTG), and reservoir geometric structure (horizons and zones).
A simple method was used to create a graphene oxide/chitosan (GO/CS) nanocomposite, which was then used in batch experiments to remove copper ions from industrial wastewater under various conditions of initial concentration, adsorbent weight, pH, and contact time. Maximum removal percentage equal to 99.4 % for initial copper ion concentration of 5x10-2 mol/L at pH 6, time 75 min, temperature 25 °C, and adsorbing dose 0.1 g. The pseudo-second order kinetic model and the Freundlich isotherm adequately fit the experimental results. The process was spontaneous and endothermic, according to thermodynamic studies.
Background. “Polyetheretherketone (PEEK)” is a biocompatible, high-strength polymer that is well-suited for use in dental applications due to its unique properties. However, achieving good adhesion between PEEK and hydrophilic materials such as dental adhesives or cement can be challenging. Also, this hydrophobicity may affect the use of PEEK as an implant material. Surface treatment or conditioning is often necessary to improve surface properties. The piranha solution is the treatment of choice to be explored for this purpose. Methods. PEEK disks of 10 mm diameter and 2 mm thickness were used in this study. Those samples were divided into five groups (each group has five samples). The first is the control group, in which no
... Show MoreIn the present work, the possibility of treating many types of radioactive sources was examined practically. Six types of sealed radioactive sources were selected: 137Cs, 133Ba, 90Sr, 152Eu, 226Ra, and 241Am. The sources were exposed to a neutron flux emitted from 241Am/Be source for 33 days. The results showed a measurable reduction of activity for 226Ra, 241Am, and 152Eu, while the other radionuclides, 137Cs, 133Ba, and 90Sr, showed less response to neutron incineration.
Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
In this paper, we have extracted Silica from rice husk ash (RHA) by sodium hydroxide to produce sodium silicate. 3-(chloropropyl)triethoxysilane (CPTES) functionalized with sodium silicate via a sol-gel method in one pot synthesis to prepare RHACCl. Chloro group in compound RHACCl replacement in iodo group to prepere RHACI. The FT-IR clearly showed absorption band of C-I at 580 cm-1. Functionalized silica RHACI has high surface area (410 m2/g) and average pore diameter (3.8 nm) within mesoporous range. X-ray diffraction pattern showed that functionalized silica RHACI has amorphous phase .Thermogravemitric analysis (TGA) showed two decomposition stages and SEM morphology of RHACI showed that the particles have irregu
... Show MoreThe preparation of the title compound, C26H25N, was achieved by the condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 molar ratio. There are two crystallographically independent molecules in the asymmetric unit. The two cyclohexyl rings adopt an
Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.
Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishmanial acti
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