The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

The research is summarized in the construction of a mathematical model using the most common methods in the science of Operations Research, which are the models of transportation and linear programming to find the best solution to the problem of the high cost of hajj in Iraq, and this is done by reaching the optimum number of pilgrims traveling through both land ports and the number Ideal for passengers traveling through airports by Iraqi Airways, instead of relying on the personal experience of the decision-maker in Hajj and Umrah Authority by identifying the best port for pilgrim's travel, which can tolerate right or wrong, has been based on scientific methods of Operations Research, the researcher built two mathematical models

An investigation was conducted for dewaxing of lubricating oil fraction by urea to reduce the pour point.In this study mixture of 45 % methyl ethyl ketone (MEK) and 55 % toluene was used as a solvent. The studied variables are mixing time (10-70 min), solvent to oil volume ratio (0.5:1- 2:1), urea to wax weight ratio (2- 6) and constant mixing speed 1500 rpm. By analysis of the experimental results, the best operating conditions achieved are mixing time 40 min, solvent/oil 2:1 volume ratio, and urea/wax 4:1 weight ratio. At these conditions the pour point of the lubricating oil decreases from 24 ° C to -13 °C.

An experiment was carried out in the fields that belong to agiriculture college /Baghdad university (AL-Jadyria) according to randomized compeleted blocks design(R.C.B.D.) with three replications during the spring season of 2015 to Study impact of growing point pinching and foliar spraying of whey on some traits of vegetative growth and yield of okra(Abelmoschus esculentus L.Moench) AL-Batra local cultivar.The experiment was included six treatments which was pinching or no pinching of growthing point and foliar spraying of whey with three concentration (0%,50%and75%).The results showed that pinching was siginificant in all traits of vegetative growth except plant High where the highest values of branches number , diameter of stem and leafe

In Incremental sheet metal forming process, one important step is to produce tool path, an
accurate tool path is one of the main challenge of incremental sheet metal forming
process. Various factors should be considered prior to generation of the tool path i.e.
mechanical properties of sheet metal, the holding mechanism, tool speed, feed rate and
tool size. In this work investigation studies have been carried out to find the different tool
path strategies to control the twist effect in the final product manufactured by single point
incremental sheet metal forming (SPIF), an adaptive tool path strategy was proposed and
examined for several Aluminum conical models. The comparison of the proposed tool path with t

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It can be represented as a raster (a grid of squares) and it is commonly estimated by utilizing remote sensing techniques, or from land surveying. In this research a 3D building of Baghdad university campus have been performed using DEM, where the easting, northing, and elevation of 400 locations have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from QuickBird satellite sensor (with spatial resolution of 0.6 m). This image has been geo-referenced by selecting ground control points of the GPS. The rectification is running, using 1st order polynomial transformation.