Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Iron , Cobalt , and Nickel powders with different particle sizes were subjected to sieving and He-Ne laser system to determine the particle size . 1wt% from each powders was blended carefully with 99wt% from Iraqi oil . Microscopic examination were carried for all samples to reveal the particle size distribution . A Siemens type SRS sequential wavelength dispersive(WDS) X-ray spectrometer was used to analyze all samples , and the XRF intensity were determined experimentally and theoretically for all suspended samples , Good agreement between theoretical and experimental results were found .

The present study aims to develop and apply the unrealistic optimism scale among high school students. The researcher has designed a scale of (38) paragraphs to measure the unrealistic optimism. A sample of (200) male and female students were chosen randomly to collect the needed data. The study found that the unrealistic scale of optimism has good psychometric characteristics. The research sample has a high level of التفاؤل غير الواقعي لدى عينة البحث unrealistic optimism. There is a statistically significant difference between male and female in the unrealistic optimism in favor of the male students. Finally, there is a statistically significant difference between students in the fourth and sixth gra

   A new nano-sized NiMo/TiO₂-γ-Al₂O₃ was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO₂- γ-Al₂O₃ nano catalyst support with 64% TiO_2, 32% Al₂O₃, Ni-Mo/TiO-γ-Al₂O₃ catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO₂- γ-Al₂O₃ nanocomposites and Ni-Mo /TiO₂

The antimicrobial activity of ginger extracts ( cold-water, hot-water, ethanolic and essential oil ) against some of pathogenic bacteria ( Escherichia coli , Salmonella sp , Klebsiella sp , Serratia marcescens, Vibrio cholerae , Staphylococcus aureus , Streptococcus sp) was investigated using Disc diffusion method , and the results were compared with the antimicrobial activity of 12 antibiotics on the same bacteria . The results showed that the ginger extracts were more effective on gram-positive bacteria than gram-negative . V. cholerae and S. marcescens,were the most resistant bacteria to the extracts used , while highest inhibition was noticed against Streptococcus sp (28 mm) . The ethanolic extract showed the broadest antibacterial ac

The purpose of this study was to investigate the effect of a Cognitive- Behavioral Training Program in reducing Problems Solving among a sample of education university  College Students, the study sample consisted of (50) students were randomly assigned to two groups: experimental, and control; (25) students per group, the results of (ANOVA) revealed that there were significant differences at (p < 0.05) between experimental and control group in Problems Solving level, while there were significant differences between both groups in achievement. The researchers recommended further studies on the other variables which after training students on the method of solving problems and techniques to reduce stress.<