Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

In this work, chemical oxidation was used to polymerize conjugated polymer "Polypyrrole" at room temperature Graphene nanoparticles were added by in situ-polymerization to get (PPY-GN) nano. Optical and Electrical properties were studied for the nanocomposites. optical properties of the nanocomposites were studied by UV-Vis spectroscopy at wavelength range (200 -800 nm). The result showed optical absorption spectra were normally determined and the result showed that the maximum absorbance wave length at 280nm and 590nm. The optical energy gap has been evaluated by direct transition and the value has decreased from (2.1 eV for pure PPy) to (1.3 eV for 5 %wt. of GN). The optical constants such as the band tail width ΔE was evaluated, the

Comparative Analysis of Economic Policy Stability between Monarchical and Republican Systems: A Theoretical Fundamental Research

The current paper aims to identify potential factors associated with employees’ intentions to leave information and communication technology companies in Iraq. There is evident variability in the literature regarding these factors; hence, a factor analysis approach was employed to identify these factors within the surveyed environment. Due to the difficulty in precisely delineating the size of the research population, a purposive sampling method was employed to reach an appropriate number of respondents within the aforementioned companies. A total of 288 employees responded to the survey conducted via Google Forms. The test results revealed the presence of five primary factors associated with employees’ intentions to leave, name

Abstract Exotoxin A is the most lethal virulence factor produced by Pseudomonas aeruginosa. It inhibits elongation factor-2 by ADP-ribosylation of EF2. This causes stop of the elongation of polypeptides. In recent study, the effect of low concentration of exotoxin A on some important internal organs of mice was studied. Four groups white mice were injected intraperitonialy with pure exotoxin A in the following manner 0.1, 0.2, 0.3, 0.4 ng\ animals. One mouse receives normal saline inrtaperitonialy as a control. After 72 hours the mice were killed and four organs were taken, liver, spleen, lung and heart from each killed mice. Histological sections were made from each organ and stained with hematoxylin and eosin stain then examined under mic

The objective of this work is to investigate the performance of a conventional three phase induction motor supplied by unbalanced voltages. An effort to study the motor steady state performance under this disturbance is introduced. Using per phase equivalent circuit analysis with the concept of symmetrical components approach, the steady state performance is theoretically calculated. Also, a model for the induction motor with the MATLAB/Simulink SPS tools has been implemented and steady state results were obtained. Both results are compared and show good correlation as well. The simulation model is introduced to support and enhance electrical engineers with a complete understanding for the steady state performance of a fully loaded induc

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve