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Environmental control of the oil industry extractive
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The research aims to prepare a report by the external auditor (Federal Office of Financial Supervision) for the control environment it is includes financial control, commitment and performance of the North Oil Company (extractive) according to the causes of pollution. The research problem it is not the Federal Office of Financial Supervision preparation a report on the things the environment include the prevent or reduction failure the administration of the causes of the pollution caused by oil mining industry by both bad planning or operational or related to efficient human resources as well as of technology to use and resulting from non-compliance local laws and instructions, as well as the inefficiency of spending on environmental issues by The research Hypothec is that environmental control for  all kinds (financial Audying  ,control of commitment and control performance)By the external auditor contributes to reducing or minimizing the negative environmental effects through verifying compliance with local laws and regulations as well as the efficiency of spending on environmental matters by extractive companies It is the most important conclusions the company had not preparation programs (Plan) for the repair of environmental assets so as an increase quantity of leaky oil from pipeline ,So does not have an official landfills and industrial waste, unlike of the laws as well as the lack of precision in determining the need (planned) of the necessary supplies of cars , machinery and industrial security requirements as well as  lack of  the     staff  in the environmental issues professionals .

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Intelligent EMG Pattern Recognition Control Method for Upper-Limb Multifunctional Prostheses: Advances, Current Challenges, and Future Prospects
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Publication Date
Mon Dec 07 2020
Journal Name
Iranian Journal Of Parasitology
Serum levels of il-12 and il-23 in breast cancer patients infected with toxoplasma gondii: A case-control study
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Publication Date
Mon Oct 06 2025
Journal Name
Journal Of Sport Biomechanics
Effects of an Integrated Balance and Muscle Tension Control Training Program on Kinematic Variables and Defensive Accuracy in Volleyball Players
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Objective This study aims to investigate the impact of integrated training on kinematics variables and defensive accuracy in volleyball, focusing on enhancing balance and muscle tension control through proprioceptive neuromuscular facilitation (PNF) exercises. Methods The sample consisted of 14 male volleyball athletes from the first volleyball league of Al-Jaish Sports Club were divided into experimental (n=7) and control group (n=7). In the pre- and post-intervention periods, dynamic balance, muscle tension control and kinematic variables (during a lateral reaching task) as well as defensive performance accuracy upon fatigue onset of recoil laser strikes were assessed. Exposure the intervention program was carried out for six weeks, and t

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Publication Date
Thu Jul 31 2025
Journal Name
Lecture Notes In Networks And Systems
Integration Between Network Analysis and Business Process Reengineering and Their Role in Reduce Project Costs/Applied Research in the Oil Projects Company
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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

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Publication Date
Wed Oct 28 2015
Journal Name
Al-khwarizmi Engineering Journal
Effect of Bearing Compliance on Thermo-hydrodynamic Lubrication of High Speed Misaligned Journal Bearing Lubricated with Bubbly Oil
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Abstract

In the present work  the effect of bearing compliance on the performance of high speed misaligned journal bearing lined with a compliant PTFE liner lubricated with bubbly oil at high speeds has been studied. The effect of induced oil film temperature due to shearing effect has been implemented. Hydrodynamic effect of the complaint bearing and the influence of aerated oil have been examined by the classical thermohydrodynamic lubrication theory modified to include the effect of oil film turbulence and oil film temperature with suitable models for bubbly oil viscosity and density. The effect of liner elastic deformation has been implemented by using Winkler model. The effects of variable density and s

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing current and future direction of non-oil primary balance: Case Study of Iraq Using Exponential Smoothing model
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In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
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Abstract<p>This study is concerned with making comparison in using different geostatistical methods for porosity distribution of upper shale member - Zubair formation in Luhais oil field which was chosen to study.</p><p>Kriging, Gaussian random function simulation and sequential Gaussian simulation geostatistical methods were adopted in this study. After preparing all needed data which are contour map, well heads of 12 wells, well tops and porosity from CPI log. Petrel software 2009 was used for porosity distribution of mentioned formation in methods that are showed above. Comparisons were made among these three methods in order to choose the best one, the comparing cri</p> ... Show More
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Publication Date
Mon Jan 13 2020
Journal Name
Day 3 Wed, January 15, 2020
Numerical Simulation of Gas Lift Optimization Using Genetic Algorithm for a Middle East Oil Field: Feasibility Study
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<p>Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t</p> ... Show More
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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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