This paper deals with studying the effect of hole inclination angle on computing slip velocity and consequently its effect on lifting capacity. The study concentrates on selected vertical wells in Rumaila field, Southern Iraq. Different methods were used to calculate lifting capacity. Lifting capacity is the most important factor for successful drilling and which reflex on preventing hole problems and reduces drilling costs. Many factors affect computing lifting capacity, so hence the effect of hole inclination angle on lifting capacity will be shown in this study. A statistical approach was used to study the lifting capacity values which deal with the effect of hole inclination angle and those values that do not put the effect of hole inclination angle under consideration. Results illustrated that low hole inclination angles had a slight effect on lifting capacity values , but this study could be used on high inclination angles like directional wells or horizontal wells , hence high hole inclinations angle will yields high effect on lifting capacity values.
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Background: Pregnancy is a physiological condition that affects the general and oral health.It is also associated with an increase in oxidative stress, which may presispose to oral diseases including dental caries. Aim of the study: This study aimed to measure salivary protein carbonyl, glutathione peroxidase and selenium levels of women who are pregnant and their association with dental caries in comparison to non-pregnant women, and to find out the mostly affected biomarker of oxidative stress during pregnancy. Subjects, materials and methods: A cross-sectional research was performed for a samples of 30 pregnant and 30 non-pregnant women who were chosen from city of Baghdad's Primary Healthcare Centers. Both groups aged 25-30 years. In
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
Exploitation of mature oil fields around the world has forced researchers to develop new ways to optimize reservoir performance from such reservoirs. To achieve that, drilling horizontal wells is an effective method. The effectiveness of this kind of wells is to increase oil withdrawal. The objective of this study is to optimize the location, design, and completion of a new horizontal well as an oil producer to improve oil recovery in a real field located in Iraq. “A” is an oil and gas condensate field located in the Northeast of Iraq. From field production history, it is realized the difficulty to control gas and water production in this kind of complex carbonate reservoir with vertical producer wells. In this study, a horizont
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Background: Gasoline constituents and its derivatives had many hazardous effects on the general health of humans. Thus, gasoline stations workers may be affected by different types of related diseases.This study was conducted to assess selected salivary elements and their relation with dental caries, oral hygiene status and periodontal diseases among gasoline stations workers in comparison with individuals have no regular exposure to gasoline. Materials and methods: The study group consists of thirty male subjects with an age range (33-39) years who worked in different gasoline stations in different areas of Baghdad city and thirty persons that matching in age and gender and not exposed to gasoline were selected as a control group. Dental c
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
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