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Prediction of Fracture Pressure Gradient in Halfaya Oilfield
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   Fracture pressure gradient prediction is complementary in well design and it is must be considered in selecting the safe mud weight, cement design, and determine the optimal casing seat to minimize the common drilling problems. The exact fracture pressure gradient value obtained from tests on the well while drilling such as leak-off test, formation integrity test, cement squeeze ... etc.; however, to minimize the total cost of drilling, there are several methods could be used to calculate fracture pressure gradient classified into two groups: the first one depend on Poisson’s ratio of the rocks and the second is fully empirical methods. In this research, the methods selected are Huubert and willis, Cesaroni I, Cesaroni II, Cesaroni III, Eaton, and Daines where Poisson’s ratio is considered essential here and the empirical methods selected are Matthews and Kelly and Christman. The results of these methods give an approximately match with the previous field study which has been relied upon in drilling the previous wells in the field and Cesaroni I is selected to be the equation that represents the field under study in general. In the shallower formations, Cesaroni I is the best method; while in deepest formations, Eaton, Christman, and Cesaroni I are given a good and approximately matching. The fracture pressure gradient of Halfaya oilfield range is (0.98 to 1.03) psi/ft.

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Stiffness Characteristics of Pile Models for Cement Improving Sandy Soil by Low-Pressure Injection Laboratory Setup
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Soil improvement has developed as a realistic solution for enhancing soil properties so that structures can be constructed to meet project engineering requirements due to the limited availability of construction land in urban centers. The jet grouting method for soil improvement is a novel geotechnical alternative for problematic soils for which conventional foundation designs cannot provide acceptable and lasting solutions. The paper's methodology was based on constructing pile models using a low-pressure injection laboratory setup built and made locally to simulate the operation of field equipment. The setup design was based on previous research that systematically conducted unconfined compression testing (U.C.Ts.). Th

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Publication Date
Mon Oct 04 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations
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Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

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Publication Date
Sat Mar 31 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Comparison between the Product-Refill and the Equalization Oxygen Pressure Swing Adsorption Processes
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This work presents a design for a pressure swing adsorption process (PSA) to separate oxygen from air with approximately 95% purity, suitable for different numbers of columns and arrangements. The product refill PSA process was found to perform 33% better (weight of zeolite required or productivity) than the pressure equalization process. The design is based on the adsorption equilibrium of a binary mixture of O2 and N2 for two of the most commonly used adsorbents, 5A & 13X, and extension from a single column approach. Zeolite 13X was found to perform 6% better than zeolite 5A. The most effective variables were determined to be the adsorption step time and the operational pressure. Increasing the adsorption step

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Publication Date
Tue Nov 08 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
The effect of background vacuum pressure on the length of gas discharge plasma by using Aluminum electrodes
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Length of plasma generated by dc gas discharge under different vacuum pressures was studied experimentally. The cylindrical discharge tube of length 2m was evacuated under vacuum pressure range (0.1-0.5) mbar at constant external working dc voltage 1500V. It was found that the plasma length (L) increased exponentially with increasing of background vacuum air pressure. Empirical equation has been obtained between plasma length and gas pressure by using Logistic model of curve fitting. As vacuum pressure increases the plasma length increases due to collisions, ionizations, and diffusions of electrons and ions.

Publication Date
Wed Jun 11 2025
Journal Name
Journal Of Baghdad College Of Dentistry
An evaluation of the influence of different finishing lines on the fracture strength of full contour zirconia CAD/CAM and heat press all-ceramic crowns
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ABSTRACT Background: One of the major problems of all ceramic restorations is their probable fracture against the occlusal forces. The objective of this in vitro study was to evaluate the effect of two gingival finishing lines (90°shoulder and deep chamfer) on the fracture resistance of full contour CAD/CAM and heat press all-ceramic crowns. Materials and Methods: Thirty two maxillary first premolars were prepared to receive full contour CAD/CAM (zolid) and heat press (Cergo Kiss) ceramic crowns using a special paralleling device (Parallel-A-Prep). The teeth were divided into four groups according to the type of finishing line prepared. Each crown was cemented to its corresponding tooth using self-etch, self-adhesive dual cure resin ceme

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
The Effect of Cyclic Bending Loads on Crack Growth in Pipes for Inclined and Transverse Cracks with or Without Internal Pulsing Pressure
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In the present research a new test rig has been proposed to be suitable for different cyclic loads such as cyclic bending, cyclic torsion, proportional and non proportional loads. In this work the efforts were concentrated on the cyclic bending loads concerning cracked pipes with or without internal pulsing pressure to study crack propagation in small bore pipes (up to 1'') for transverse or inclined cracks. The rig simulates the real service conditions under different stresses by means the least dangerous case will be suggested, so the experiments were considered for copper pipe, and the results have been tabulated and drawn to demonstrate the crack growth behavior as well as to justify the outcomes practically, consequently the durabil

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Publication Date
Mon Jun 05 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Association of Disease Duration and Duration of Olanzapine Use with Blood Sugar, Blood Pressure, BMI, and Lipid Profile among Schizophrenic Patients in Iraq
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Background: The association of olanzapine with hyperglycemia, an elevated lipid profile, and high blood pressure was early recognized after its approval and has become of increased concern. Objective: To determine the association of olanzapine use with blood sugar levels, lipid profiles, and blood pressure in hospitalized Iraqi patients with schizophrenia. Methods: A cross-sectional study involving 50 hospitalized patients with schizophrenia who met the Diagnostic and Statistical Manual of Mental Disorders (DSM)-V diagnostic criteria and had taken olanzapine for at least two years was carried out between November 2022 and February 2023 at two facilities in Baghdad, Iraq (Ibn Rushd Psychiatric Teaching Hospital and Al Rashad Hospital

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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