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Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Quality Index (RQI) versus normalized porosity (øz) are presented to identify optimal hydraulic flow units. Four HFUs were distinguished in this study area with good correlation coefficient for each HFU (R2=0.99), therefore permeability can be predicted from porosity accurately if rock type is known.

   Conventional core analysis and well log data were obtained in well 1 and 2 in one of carbonate Iraqi oil field. The relationship between core and well log data was determined by Artificial Neural Network (ANN) in cored wells to develop the predictive model and then was used to develop the flow units prediction to un-cored wells. Finally permeability can be calculated in each HFU using effective porosity and mean FZI in these HFUs. Validation of the models evaluated in a separate cored well (Blind-Test) which exists in the same formation. The results showed that permeability prediction from ANN and HFU matched well with the measured permeability from core data with R2 =0.94 and ARE= 1.04%.

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Vanadium and Nickel Ions from Iraqi Atmospheric Residue by Using Solvent Extraction Method
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Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal percent we

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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Radiological Assessment of Mandibular Retromolar Canal (MRMC) Using CBCT-Radiographs in a Sample of Iraqi Patients
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Background: Because of its clinical and surgical importance and lack of precise information about this rare and important anatomical landmark, this study was designed to detect the presence, configurations and length of Mandibular Retromolar Canal (MRMC) with aid of CBCT visualization. Materials and methods: In this retrospective study the data was obtained from Specialist Health Center in AL-Sadder city in Baghdad for (100) patients with 200 inferior dental canal, all of them referred to CBCT scan (Kodak 9500, French origin). The scanning was done with tube voltage 90 kVp, tube current with 10mA and exposure time was 10 s., the field of view was measured with 5cm x 3.7cmwith 0.03mm voxel size Results: In the present study the prevalence of

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Publication Date
Fri Jan 01 2021
Journal Name
Clinical Epidemiology And Global Health
Association of overweight/obesity with the severity of periodontitis using BPE code in an iraqi population
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Publication Date
Thu Oct 01 2020
Journal Name
International Communications In Heat And Mass Transfer
Thermal behaviour of the flow boiling of a complex nanofluid in a rectangular channel: An experimental and numerical study
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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
A Real-Coded Genetic Algorithm with System Reduction and Restoration for Rapid and Reliable Power Flow Solution of Power Systems
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The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Production of Load Bearing Concrete Masonry Units (blocks) From Green Concrete Containing Plastic Waste and Nano Silica Sand Powder
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil

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Publication Date
Thu Mar 16 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solvent -Free One -Pot Multicomponent, Synthesis, Characterization and Anti-bacterial activity, of some 2substituted-3-cyano-Pyridine Derivatives
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           Solvent- free thermal heating, one-pot condensation of acetophenone, ethyl cyanoacetate or malononitrle and substituted Aromatic aldehyde, ammonium acetate give, 2oxo-3-cyano-4-substituted Aryl-6-phenyl pyridine [I]a-h , or  2-amino-3-cyano-4-substituted Aryl-6-phenyl pyridine derivatives[II]a-f , respectively.              Treatment of compounds 2-oxo-3-cyano-4-substituted Aryl-6-phenyl pyridine with phosphorous penta sulphide (P2S5), give 2-thioxo-3-cyano-4-substituted Aryl-6-phenyl pyridine derivatives[III]a-c .             All prepared compounds

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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