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Vertical Stress Prediction for Zubair Oil Field/ Case Study
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Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods show that extrapolated density measurement used an average for the real density. The gradient of an extrapolated method is much better in shallow depth into the vertical stress calculations. The Miller density method had an excellent fit with the real density in deep depth. It has been crucial to calculate vertical stress for the past 40 years because calculating pore pressure and geomechanical building models have employed vertical stress as input. The strongest predictor of vertical stress may have been bulk density. According to these results, the miller and extrapolated techniques may be the best two methods for determining vertical stress. Still, the gradient of an extrapolated method is much more excellent in shallow depth than the miller method. Extrapolated density approach may produce satisfactory results for vertical stress, while miller values are lower than those obtained by extrapolating. This may be due to the poor gradient of this method at shallow depths. Gardner's approach incorrectly displays minimum values of about 4000 psi at great depths. While other methods provide numbers that are similar because these methods use constant bulk density values that start at the surface and continue to the desired depth, this is incorrect.

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Composition and Temperature Dependence of Excess Volume of Heavy Oil-Stocks Mixtures + (Gas oil or Toluene or Reformate)
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Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Effects of Aloe vera Gel, Sesame Oil and Camphor Oil on Pseudomonas aeruginosa Isolated from Burnt Patients
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Three isolates of  P. aeruginosa were isolated from burnt patients. The ability of these isolates for adhesion and formation of slime layer were tested, the result showed that all isolates were able to adherence on the smooth surface. The sensitivity of  P. aeruginosa isolates for antibiotics were tested , all isolates were sensitive  to Gentamycin, Piperacillin and Amikacin Ciprofloxacin, and  resist to Tetracyclin, Amoxicillin, Cephalexine , Ceftriaxone. Ciprofloxacin and Amikacin were found effective against P. aeruginosa isolates with MIC values of 3.8 μg/ ml for  Ciprofloxacin  and 0.244 μg/ ml for Amikacin The antibacterial effect of Different concentrations of Aloe

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Analysis of Fatty Acid Composition in the Seed and flower oil of Syrian Ligustrun Lucidum and olive oil
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The fatty acid composition in the seed and flower of Ligustrun lucidum and olive oil was studied by Gas Chromatography. Results showed that the main components of seed oil were Palmitic (C16:0) 5,893% ,Palmitolic acid (C16:1)0,398%, Steaeic (C18:0)2,911% ,Oleic (C18:1)74,984%,Linoleic (C18:2) 12,959%,and Linolenic (C18:3) 0,997%. The proportion of unsaturated fatty acid was above 89,338%, so the seed oil of L. lucidum ait belonged to unsaturated oil which possessed promising application. The components of flower oil were Palmitic (C16:0) 65,674% ,Palmitolic acid (C16:1)6,516%, Steaeic (C18:0)2,641% ,Oleic (C18:1)14,707%,Linoleic (C18:2) 3,113%,and Linolenic (C18:3) 2,70%. The proportion of unsaturated fatty acid and saturated fatty acid wa

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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
The Position of the Oil Press about the World Oil Industry / OAPEC Bulletin 2011-2012 as a Model
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This research deals with the attitude of oil press towards oil industry in the world and the extent of their concerns with the stages of oil industry relating to the abundance of oil and natural gas, as it is an international strategic and complementary industry. The researcher uses the survey method for content analysis of the initial article and the press news for two: years (2011-2012). The results if the study are as follows
1- Oil press is concerned with developing and the stages of the Arabic oil industry in the interest of OAPEC in the first place.
2- It is concerned with exploring, extracting, and marketing oil in the first place, then with refining operations in refineries and petrochemical plants in the second place, an

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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Publication Date
Thu Sep 19 2024
Journal Name
Turkish Computational And Theoretical Chemistry
In-silico design, molecular docking, molecular dynamic simulations, Molecular mechanics with generalised Born and surface area solvation study, and pharmacokinetic prediction of novel diclofenac as anti-inflammatory compounds
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The prostaglandins inside inflamed tissues are produced by cyclooxygenase-2 (COX-2), making it an important target for improving anti-inflammatory medications over a long period. Adverse effects have been related to the traditional usage of non-steroidal anti-inflammatory drugs (NSAIDs) for the treatment of inflammation, mainly centered around gastrointestinal (GI) complications. The current research involves the creation of a virtual library of innovative molecules showing similar drug properties via a structure-based drug design. A library that includes five novel derivatives of Diclofenac was designed. Subsequently, molecular docking through the Glide module and determining the binding free energy implementing the P

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Reaction Kinetic of Al- Doura Heavy Naphtha Reforming Process Using Genetic Algorithm
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In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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