Water flooding is one of the most important methods used in enhanced production; it was a pioneer method in use, but the development of technology within the oil industry, takes this subject toward another form in the oil production and application in oil fields with all types of oils and oil reservoirs. Now days most of the injection wells directed from the vertical to re-entry of full horizontal wells in order to get full of horizontal wells advantages.
This paper describes the potential benefits for using of re-entry horizontal injection wells as well as combination of re –entry horizontal injection and production wells. Al Qurainat productive sector was selected for study, which is one of the four main productive sectors of Sout

Investigation of the adsorption of acid fuchsin dye (AFD) on Zeolite 5A is carried out using batch scale experiments according to statistical design. Adsorption isotherms, kinetics and thermodynamics were demonstrated.  Results showed that the maximum removal efficiency was using zeolite at a temperature of 93.68751 mg/g. Experimental data was found to fit the Langmuir isotherm and pseudo second order kinetics with maximum  removal of about 95%.  Thermodynamic analysis showed an endothermic adsorption. Optimization was made for the most affecting operating variables and a model equation for the predicted efficiency was suggested.

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

Carbides or nitrides thin films present materials with good mechanical properties for industrial applications as they can be coatings at low temperatures serve temperature sensitive surfaces. In this work the effect of the C percentage on the mechanical properties represented by the Young modulus (E) of combinatorial magnetron sputtered TiC_x (34%x˂65%) has been studied. The structure of the produced films is TiC independent on the C concentration. The mechanical properties are increased with increasing the C concentration up to 50%, and then decreasing with further C % increasing. These results can be explained by considering the resultant residual stresses.

Abstract This research investigates how activated carbon (AC) was synthesized from potato peel waste (PPW). Different ACs were synthesized under the atmosphere's conditions during carbonation via two activation methods: first, chemical activation, and second, carbon dioxide-physical activation. The influence of the drying period on the preparation of the precursor and the methods of activation were investigated. The specific surface area and pore volume of the activated carbon were estimated using the Brunauer–Emmett–Teller method. The AC produced using physical activation had a surface area as high as 1210 m2/g with a pore volume of 0.37 cm3/g, whereas the chemical activation had a surface area of 1210 m2/g with a pore volume of 0.34 c

The antioxidant and antibacterial activities of ethanolic extract and phenolic compounds extract of Lemon balm (Melissa officinalis) and Oregano (Oreganum vulgare) plants were studied; the phenolic content and the relationship between these compounds and the above activities were also investigated. The results showed that the Lemon balm had the highest phenolic content (56.5% mg g) and the phenolic content of Oregano was twice lower than Lemon balm. Lemon balm has the highest antioxidant activity which causes lipid peroxidation inhibition activity of linoleic acid (90.5%), this activity was more than ?-tocopherole antioxidant activity (79.3 %). It was found that the main source of antioxidant activity o

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

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