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4D Finite element modeling of stress distribution in depleted reservoir of south Iraq oilfield
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Abstract<p>The harvest of hydrocarbon from the depleted reservoir is crucial during field development. Therefore, drilling operations in the depleted reservoir faced several problems like partial and total lost circulation. Continuing production without an active water drive or water injection to support reservoir pressure will decrease the pore and fracture pressure. Moreover, this depletion will affect the distribution of stress and change the mud weight window. This study focused on vertical stress, maximum and minimum horizontal stress redistributions in the depleted reservoirs due to decreases in pore pressure and, consequently, the effect on the mud weight window. 1D and 4D robust geomechanical models are built based on all available data in a mature oil field. The 1D model was used to estimate all mechanical rock properties, stress, and pore pressure. The minimum and maximum horizontal stress were determined using the poroelastic horizontal strain model. Furthermore, the mechanical properties were calibrated using drained triaxial and uniaxial compression tests. The pore pressure was tested using modular dynamic tester log MDT. The Mohr–Coulomb model was applied in the 4D model to calculate the stress distribution in the depleted reservoir. According to study wells, the target area has been classified into four main groups in Mishrif reservoir based on depletion: highly, moderately, slightly, and no depleted region. Also, the results showed that the units had been classified into three main categories based on depletion state (from above to low depleted): L1.1, L1.2, and M1. The mean average reduction in minimum horizontal stress magnitude was 322 psi for L1.1, 183.86 psi for L1.2, and 115.56 psi for M1. Thus, the lower limit of fracture pressure dropped to a high value in L1.1, which is considered a weak point. As a result of changing horizontal stress, the mud weight window became narrow.</p>
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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Physics: Conference Series
Theory and applications of Marshall Olkin Marshall Olkin Weibull distribution
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Abstract<p>In probability theory generalizing distribution is an important area. Several distributions are inappropriate for data modeling, either symmetrical, semi-symmetrical, or heavily skewed. In this paper, a new compound distribution with four parameters called Marshall Olkin Marshall Olkin Weibull (MOMOWe) is introduced. Several important statistical properties of new distribution were studied and examined. The estimation of unknown four parameters was carried out according to the maximum likelihood estimation method. The flexibility of MOMOWe distribution is demonstrated by the adoption of two real datasets (semi-symmetric and right-skewed) with different information fitting criteria. Su</p> ... Show More
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Modeling sequential preparation with rheumatoid tonsils in Nineveh for the period 2004-2009
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Abstract
             In this research will be treated with a healthy phenomenon has a significant impact on different age groups in the community, but a phenomenon tonsillitis where they will be first Tawfiq model slope self moving averages seasonal ARMA Seasonal through systematic Xbox Cengnzla counter with rheumatoid tonsils in the city of Mosul, and for the period 2004-2009 with prediction of these numbers coming twelve months, has found that the specimen is the best representation of the data model is the phenomenon SARMA (1,1) * (2,1) 12  from the other side and explanatory variables using a maximum temperature and minimum temperature, sol

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Publication Date
Sun Jan 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Proposed Algorithm for Gumbel Distribution Estimation
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Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Recovering Time-Dependent Coefficients in a Two-Dimensional Parabolic Equation Using Nonlocal Overspecified Conditions via ADE Finite Difference Schemes
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Publication Date
Wed Jan 01 2020
Journal Name
Archives Of Clinical Infectious Diseases
Toxoplasmosis and Risk of Endothelial Dysfunction: Role of Oxidative Stress and Pro-Inflammatory Mediators
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Background: Infection with Toxoplasma gondii (T. gondii) leads to activation of T-helper cells (Th-1 and Th-2) which are involved in the synthesis and release of different cytokines which may lead to endothelial dysfunction. Objectives: To evaluate the endothelial function in patients with acute toxoplasmosis. Methods: This case-control study involved 31 patients with toxoplasmosis aged 19 - 47 years matched with 20 healthy subjects. Anti-T. gondii antibody (IgG, IgM, IgA) was determined by direct antigen-antibody reaction. Interleukin-6(IL-6), endothelin-1 (ET-1) and human malondialdehyde (MDA) serum levels were measured. Results: IgM, IgG and IgA levels were high in the infected patients compared with controls (P < 0.01). Furthermore, IL-

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Publication Date
Sat Jul 01 2023
Journal Name
American Journal Of Economics And Business Innovation
The Effect of Workplace Stress on Employee Engagement, the Mediation Role of Leadership Style
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The aim of the current study was to investigate the impact of workplace stress on employee engagement within Iraqi universities through the mediator role of leadership style. Work-related stress and non-work-related stress were identified as representing workplace stress. Employee engagement has been measured through three types: social engagement, affective engagement, and intellectual engagement. Two types of leadership styles have been tested: directive and participative leadership. the structural equation Modeling was used to test the study model. A sample of 245 employees in Iraqi universities, including university professors, was targeted. Only 214 respondents participated in the survey. The results showed that non-work-relate

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Publication Date
Thu Nov 29 2018
Journal Name
Journal Of Electronic Materials
Numerical Modeling of 193-nm Excimer Laser Ablation on CR-39 Polymer
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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Petroleum Research And Studies
Modeling of Oil Viscosity for Southern Iraqi Reservoirs using Neural Network Method
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The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

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