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Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assumptions involved in these models have limited their applications to very specific scenarios. In this study, an analytical solution for determination of the volume of collapse during drilling is presented based on changes in the geometry of boreholes. The approach can be used in conjunction with different failure criteria to estimate the collapse onset in the presence of formation strengths and principal stresses. The study highlighted how the integration of information from different sources and disciplines were able to estimate the shear failure induced on the borehole wall during drilling.

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The effectiveness of the electronic public relations of Al- Shuhadaa Establishment: an analytical study of the website contents, the official social networking sites of Al- Shuhadaa Establishment
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public relations at Al-Shuhadaa Establishment: an analytical study of social networking sites and the website) came to know and monitor the contents of social networking sites for Al-Shuhadaa Establishment, the research problem was represented by the main question: (What is the effectiveness of social networking sites and the website of Al-Shuhadaa Establishment) ,This research was classified within the descriptive research, and the two researchers adopted the survey method in order to achieve the objectives of the research, and they used the tool: content analysis as a research tool, the analysis of the contents included the official website of the establishment (Instagram page), and other social networking sites that Al-Shuhadaa Establish

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Publication Date
Sun Sep 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Study in to the Dynamic Behavior of Packed Distillation Column
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The study of the dynamic behavior of packed distillation column was studied by frequency response analysis using Matlab program. A packed distillation column (80 mm diameter) (2000 mm height) filled with glass packing (Raschig Rings 10mm), packing height (1500 mm) has been modified for separation of methanol-water mixture (60 vol%). The column dynamic behavior was studied experimentally under different step changes in, feed rate (±30%), reflux rate (±22%), and reboiler heat duty (±150%), the top and bottom concentration of methanol were measured. A frequency response analysis for the above step response was carried out using Bode diagram, the log modulus and the phase angle were  used to analyze the process model. A Matlab progra

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Publication Date
Wed Apr 01 2015
Journal Name
Mathematical Methods In The Applied Sciences
An inverse problem of finding the time-dependent diffusion coefficient from an integral condition
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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between Bayesian Method and Full Maximum Likelihood to estimate Poisson regression model hierarchy and its application to the maternal deaths in Baghdad
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Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

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Publication Date
Tue Jun 16 2020
Journal Name
Baghdad Science Journal
Using Diatom Indices to Evaluate Water quality In Abu-Zirig Marsh Thi-Qar Province /south of Iraq
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The study attempts to assess water quality in Abu-Zirig Marsh which used epiphytic Diatom community for assessing water quality. Many of Diatom indices {Trophic diatom index (TDI), Diatom index (DI), Generic diatom index (GDI) have been used to give qualitative information about the status of the freshwater ecosystem(good, moderate, high pollution). In this study, the epiphytic diatoms on both host aquatic plants Phragmites australis and Typha domengensis were collected from Abu-Zirig Marsh within Thi-Qar Province at three sites in Autumn, 2018 and winter, 2019. Epiphytic diatoms were Identified by the preparation of permanent slides method, some species of epiphytic diatom showed dominance such as Cyclotella menegh

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancing the Lifting Capacity of Drilling Fluids in Vertical Oil Wells
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Of the many functions that are performed by the drilling fluid, the most important is to transport cuttings from the bit up the annulus to the surface. Various drilling fluid have been widely used in the oil industry to improve lifting capacity. In this study, three mud type have been used which they are, oil base mud, X-anthan polymer and a mixture of CMC and bentonite ,by using Carrying Capacity Index  calculation (CCI) , the Xanthan  gave good values of CCI than other studied drilling fluid. By using Sifferman chart and field data from well in south of Iraq and API equation to find cutting concentration in the annulus, The results showed that the used of thick mud increase the lifting capacity and decrease volumetric drill c

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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