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Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy inference system and genetic algorithm. An offset field data was collected from mud logging and wire line log from East Baghdad oil field south region to build the AI models, including datasets of two wells: well 1 for AI modeling and well 2 for validation of the obtained results. The types of interesting formations are sandstone and shale (Nahr Umr and Zubair formations). Nahr Umr and Zubair formations are medium –harder. The prediction results obtained from this study showed that the ANN technique can predict the ROP with high efficiency as well as FIS technique could achieve reliable results in predicting ROP, but GA technique has shown a lower efficiency in predicting ROP. The correlation coefficient and RMSE were two criteria utilized to evaluate and estimate the performance ability of AI techniques in predicting ROP and comparing the obtained results. In the Nahr Umr and Zubair formations, the obtained correlation coefficient values for training processes of ANN, FIS and GA were 0.94, 0.93, and 0.76 respectively. Data sets from another well (well 2) in the same field of interest were utilized to validate of the developed models. Datasets of well 2 were conducted against sandstone and shale formations (Nahr Umr and Zubair formations). The results revealed a good matching between the actual rate of penetration values and the predicted ROP values using two artificial intelligence techniques (neural network, and fuzzy inference technique). In contrast, the genetic algorithm model showed overestimation/ underestimation of the rate of penetration against sandstone and shale formations. This means that the optimum prediction of rate of penetration can be obtained from neural network model rather than using genetic algorithm and genetic algorithm techniques. The developed model can be successfully used to predict the rate of penetration and optimize the drilling parameters, achieving reduce the cost and time of future wells that will be drilled in the East Baghdad Iraqi oil field.

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
The Calculation and Analysis of the Total Electron Content Over Different Latitudes and Seasons Using the Numerical Trapezoidal and Simpson Methods
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It has been shown in ionospheric research that calculation of the total electron content (TEC) is an important factor in global navigation system. In this study, TEC calculation was performed over Baghdad city, Iraq, using a combination of two numerical methods called composite Simpson and composite Trapezoidal methods. TEC was calculated using the line integral of the electron density derived from the International reference ionosphere IRI2012 and NeQuick2 models from 70 to 2000 km above the earth surface. The hour of the day and the day number of the year, R12, were chosen as inputs for the calculation techniques to take into account latitudinal, diurnal and seasonal variation of TEC. The results of latitudinal variation of TE

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Publication Date
Sat Mar 17 2012
Journal Name
Environmental Science And Pollution Research Volume
Equilibrium, kinetic, and thermodynamic biosorption of Pb(II), Cr(III), and Cd(II) ions by dead anaerobic biomass from synthetic wastewater
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Purpose Heavy metals are toxic pollutants released into the environment as a result of different industrial activities. Biosorption of heavy metals from aqueous solutions is a new technology for the treatment of industrial wastewater. The aim of the present research is to highlight the basic biosorption theory to heavy metal removal. Materials and methods Heterogeneous cultures mostly dried anaerobic bacteria, yeast (fungi), and protozoa were used as low-cost material to remove metallic cations Pb(II), Cr(III), and Cd(II) from synthetic wastewater. Competitive biosorption of these metals was studied. Results The main biosorption mechanisms were complexation and physical adsorption onto natural active functional groups. It is observed that

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Publication Date
Tue Jun 27 2023
Journal Name
Chemphyschem
Predicting a New Δ‐Proton Sponge‐Base of 4,12‐Dihydrogen‐4,8,12‐triazatriangulene through Proton Affinity, Aromatic Stabilization Energy, and Aromatic Magnetism
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Abstract<p>Herein, we report designing a new Δ (delta‐shaped) proton sponge base of 4,12‐dihydrogen‐4,8,12‐triazatriangulene (compound <bold>1</bold>) and calculating its proton affinity (<italic>PA</italic>), aromatic stabilization, natural bond orbital (NBO), electron density <italic>ρ</italic>(r), Laplacian of electron density ∇<sup>2</sup><italic>ρ</italic>(r), (2D‐3D) multidimensional <italic>off</italic>‐nucleus magnetic shielding (<italic>σ</italic><sub>zz</sub>(r) and <italic>σ</italic><sub>iso</sub>(r)), and scanning nucleus‐independent chemical shift (NICS<sub>zz</sub> and</p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
International Journal Of Pharmaceutical Research
Phytochemical investigation,anti-proliferative and antioxidant- activities of Iraqi Capparisspinosa L. (Family Capparidaceae) against MCF-7 human Breast cancer cell line
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Prioritized Text Detergent: Comparing Two Judgment Scales of Analytic Hierarchy Process on Prioritizing Pre-Processing Techniques on Social Media Sentiment Analysis
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Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

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Publication Date
Sun Jan 01 2017
Journal Name
Food And Nutrition Sciences
Optimization of Culture Conditions to Produce Phytase from &amp;lt;i&amp;gt;Aspergillus tubingensis SKA&amp;lt;/i&amp;gt;
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The effects of nutrients and physical conditions on phytase production were investigated with a recently isolated strain of Aspergillus tubingensis SKA under solid state fermentation on wheat bran. The nutrient factors investigated included carbon source, nitrogen source, phosphate source and concentration, metal ions (salts) and the physical parameters investigated included inoculum size, pH, temperature and fermentation duration. Our investigations revealed that optimal productivity of phytase was achieved using wheat bran supplemented with: 1.5% glucose. 0.5% (NH4)2SO4, 0.1% sodium phytate. Additionally, optimal physical conditions were 1 × 105 spore/g substrate, initial pH of 5.0, temperature of fermentation 30˚C and fermentation dura

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
The Utilization of Remote Sensing Imagery and Inverse Distance Weighted Scheme to Simulate the White Oil Effects on Soil Geotechnical Properties
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     This research aims to utilize a complementarity of field excavations and laboratory works with spatial analyses techniques for a highly accurate modeling of soil geotechniques properties (i.e. having lower root mean square error value for the spatial interpolation). This was conducted, for a specified area of interest, firstly by adopting spatially sufficient and  well distributed samples (cores). Then, in the second step, a simulation is performed for the variations in properties when soil is contaminated with commonly used industrial material, which is white oil in our case. Cohesive (disturbed and undisturbed) soil samples were obtained from three various locations inside Baghdad University campus in AL-J

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Publication Date
Wed Jan 05 2022
Journal Name
Iraqi Journal Of Science
The Inhibition Activity of Silver Nanoparticles Compared with D-Glycin and Imipenem Effect on the Biofilm Formation by Food-origin Salmonella
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Since decades silver was depended worldwide as a treatment to a lot of diseases
ranging from burn infections, anthrax, and typhoid fever to bacterial conjunctivitis
in stillbirth, but its effectiveness against biofilms is still undetermined. Salmonella is
a major cause of food poisoning outbreaks especially in the third world countries.
Thus, in the present study; the antimicrobial activity of silver nanoparticles (Ag-
NPs) against Salmonella enterica biofilm was examined; their activity was
compared with amino acid; D-Glycin and imipenem antibiotic. The result of the
study revealed that Ag-NPs exhibited considerable antimicrobial property against
Salmonella enterica biofilm where the minimum inhibitory concentrat

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Preparation, Characterization and Spectroscopic Study of New Tridentate Schiff Base and its Cu(II), Ni(II) and Zn(II) Metal Complexes
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A new tridentate ligand has been synthesized derived from phenyl(pyridin-3-yl)methanone. Three coordinated metal complexes were prepared by complexation of the new ligand with Cu(II), Ni(II) and Zn(II) metal salts. The new Schiff base “benzyl -2-[phenyl(pyridin-3-yl)methylidene]hydrazinecarbodithioate” and the new metal complexes were characterized using various physico-chemical and spectroscopic techniques. From the analysis results, the expected structure to the metal complexes are octahedral in geometry for Cu(II) complex, square planner for Ni(II) and tetrahedral for Zn(II) complex. The new compounds are expected to show strong bioactivity against bacteria and cancer cells.

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Publication Date
Fri Jan 24 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The validity of salivary microRNAs (hsa-miR-200a, hsa-miR-125a and hsa- miR-93) as oral squamous cell carcinoma biomarker
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Background: Oral squamous cell carcinoma represents the vast majority of oral cancer it is a common malignant tumor with an increasing incidence. Around the world, the 5 year mortality rate of oral cancer is about 50%. Thus novel biomarkers for early detection oral squamous cell carcinoma are needed. The level of three salivary microRNAs namely hsa-miR-200a, hsa-miR-125a and hsa- miR-93 were measured in saliva of patients with oral squamous cell carcinoma and compared their levels in saliva of healthy control subjects to determine their potential as oral cancer biomarker. Materials and methods: The level of these three microRNAs was measured by using revers transcription, preamplification and quantitative PCR. Results: Only miR-200a presen

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