Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations ranges between 12.5 to 15 ppg. The predicted safe mud weight value seems to be narrow with a well deviation higher than 350. Therefore, for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations, the wellbore appears unstable compared to other formations. The results of stability analyses indicate that the breakout mud weight wasn’t affected by wellbore azimuth because of low-stress contrast. Furthermore, shear failure can be prevented by drilling the well with an inclination of less than 350. As well as, to prevent breakdown the well should be drilled with an inclination between 25o to 65o in the direction of minimum horizontal stress. These outcomes could be used to prevent wellbore instability and determine a safe mud-weight window when planning to drill nearby wells in the future.
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
... Show MoreRecognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u
... Show MoreWhen images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona
... Show MoreSeventeen core samples were taken from Luhais and Tuba oil wells according to the presence of oil bearing formations. These wells were located in the province of Basra/southern Iraq. The formation that the samples are collected from Zubair and Mishrif formations. The core samples were taken from the wells at different depths. In the current study the ultrasonic technique was conducted to measure (Vp and Vs) as well as to determine some petrophysical properties for core samples and some elastic moduli such as (Young's modulus, Bulk modulus, Shear modulus, Poisson's ratio and Lame's constant) depending on the values of Vp and Vs as well as density. The relationships between seismic wave velocities with elastic moduli and petrophysical prop
... Show MoreThe dry weight of the liver of Rana ridibunda was expressed as percentage of the dry
weight of the body. The female liver weight always exceeds that of the male, except in July
and September. The difference between males and females for the whole year, regardless of
months, was not significant. Livers of both sexes were relatively large prior to hibernation
(December), decreased during hibernation (January and February) until a minimum weight in
March (post-hibernation).
The increase of liver weight during December is apparently simply to meet the metabolic
requirements for survival during hibernation. The percent reduction in liver weight during
hibernation was 1.081% in males and 1.356% in females. The decrease
This study investigated a novel application of forward osmosis (FO) for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). FO is a part of a zero liquid discharge system that consists of oil skimming, coagulation/flocculation, forward osmosis, and crystallization. Treatment of oilfield produced water requires systems that use a sustainable driving force to treat high-ionic-strength wastewater and have the ability to separate a wide range of contaminants. The laboratory-scale system was used to evaluate the performance of a cellulose triacetate hollow fiber CTA-HF membrane for the FO process. In this work, sodium chloride solution was used as a feed solution (FS) with a concentratio
... Show MoreIn this work, we have used the QCD dynamic scenario of the quark gluon interaction to investigate and study photon emission theoretically based on quantum theory. The QCD theory is implemented by deriving the photon emission rate equation of the state of ideal QGP at a chemical potential. The photon rate of the quark-gluon interaction has to be calculated for the anti up-gluon interaction in the g → γ system at the temperature of system with critical temperature ( 132.38, , and 198.57) MeV and photon energy ( GeV. We investigated a significant effect of critical temperature, strength coupling, and photon energy on the photon rate contribution. Here, the increased photon emission rate and decreased streng
... Show More