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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
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Calculation of Pressure Loss of Two Drilling Muds in Noor Oil Field
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In this work, calculation of pressure losses in circulating system for two drilling muds is evaluated in Noor oil field. Two types of drilling muds that were used for drilling section 12 1/4" and 8 3/4" which are Salt saturated mud and Ferro Chrome Lignosulfonate-Chrome Lignite mud. These calculations are based on field data that were gathered from the drilling site of well Noor-15, which are included, rheological data, flow data and specification of drill string. Based on the obtained results, the best rheological model that fit their data is the Herschel-Bulkley model according to correlation coefficient value for their two drilling mud. Also, the difference between the calculated pressure lo

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Publication Date
Thu Feb 13 2020
Journal Name
Thesis
IMPLICATION OF GEOMECHANICAL EVALUATION ON TIGHT RESERVOIR DEVELOPMENT / SADI RESERVOIR HALFAYA OIL FIELD
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IMPLICATION OF GEOMECHANICAL EVALUATION ON TIGHT RESERVOIR DEVELOPMENT / SADI RESERVOIR HALFAYA OIL FIELD

Publication Date
Tue Jan 01 2019
Journal Name
1st Conference Of The Arabian Journal Of Geoscienses
Potentiometric salinity mapping of Mishrif oilfield waters in (Iraq's) southern oil fields
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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Science, Technology & Innovation
Potentiometric Salinity Mapping of Mishrif Oilfield Waters in (Iraq’s) Southern Oil Fields
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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
Diagnostic Value Of Post Exercise Systolic Blood Pressure Response In Ischemic Heart Disease
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 Background: The normal decline in systolic blood pressure during recovery phase of treadmill exercise dose not occur in most patients with coronary artery disease, in others recovery values systolic blood pressure may even exceed the peak exercise value. Objectives: Treadmill exercise test parameters indicating the presence and extent of coronary artery disease have traditionally included such as exercise duration, blood pressure and ST-segment response to exercise. The three –minute systolic blood pressure ratio is another important indicator of presence and significance of coronary artery disease is useful and obtainable measure that can be applied in all patients who are undergoing stress testing for evaluation of suspected is

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Craniofacial Surgery
Pros and Cons of the Transconjunctival Retroseptal Approach to the Isolated Orbital Floor Fracture
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To get access into the orbital floor 3 paths are commonly used which are transconjunctival, subciliary and subtarsal approaches. Each one of these approaches has its advantages and disadvantages. The study assessed the outcomes of the transconjunctival retroseptal approach, which reflects our experience in this type of surgery. Along 8 years, 26 patients received in the emergency room diagnosed with pure isolated orbital floor fractures, all of them admitted to the maxillofacial surgery department and approached by transconjunctival incision without lateral canthotomy. Three types of complications occurred: laceration of the lower eyelid, injury to the lacrimal system and entropion. All of these complications were managed accordingly with n

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation evaluation for Mauddud Formation in Bai Hassan oilfield, Northern Iraq
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   Formation evaluation is a critical process in the petroleum industry that involves assessing the petrophysical properties and hydrocarbon potential of subsurface rock formations. This study focuses on evaluating the Mauddad Formation in the Bai Hassan oil field by analyzing data obtained from well logs and core samples. Four wells were specifically chosen for this study (BH-102, BH-16, BH-86, and BH-93). The main objectives of this study were to identify the lithology of the Mauddud Formation and estimate key petrophysical properties such as shale volume, porosity, water saturation, and permeability. The Mauddud Formation primarily consists of limestone and dolomite, with some anhydrites present. It is classified as a clean for

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Effect of Pressure on the Properties of HgBa2Ca2Cu3O8+δ HTSC System
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High temperature superconductors with a nominal composition HgBa2Ca2Cu3O8+δ
for different values of pressure (0.2,0.3, 0.5, 0.6, 0.9, 1.0 & 1.1)GPa were prepared by
a solid state reaction method. It has been found that the samples were semiconductor
P=0.2GPa.while the behavior of the other samples are superconductor in the rang
(80-300) K. Also the transition temperature Tc=143K is the maximum at P is equal to
0.5GPa. X-ray diffraction showed a tetragonal structure with the decreasing of the
lattice constant c with the increasing of the pressure. Also we found an increasing of
the density with the pressure.

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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