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Development of 1D-Synthetic Geomechanical Well Logs for Applications Related to Reservoir Geomechanics in Buzurgan Oil Field
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Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechanical well logs for the production section of the Buzurgan oil field, located in the south of Iraq, using an artificial neural network. An issue with the area of study is that shear wave velocities and pore pressure measurements in some wells are missing or incomplete possibly for cost and time-saving purposes. The unavailability of these data can potentially create inaccuracies in reservoir characterization n and production management. To overcome these challenges, this study presents two developed models for estimating the shear wave velocity and pore pressure using ANN techniques. The input parameters are conventional well logs including compressional wave, bulk density, and gamma-ray. Also, this study presents a construction of 1-D mechanical earth model for the production section of Buzurgan oil field which can be used for optimizing the selected mud weights with less wellbore problems (less nonproductive time. The results showed that artificial neural network is a powerful tool in determining the shear wave velocity and formation pore pressure using conventional well logs. The constructed 1D MEM revealed a high matching between the predicted wellbore instabilities and the actual wellbore failures that were observed by the caliper log. The majority of borehole enlargements can be attributed to the formation shear failures due to an inadequate selection of mud weights while drilling. Hence, this study presents optimum mud weights (1.3 to 1.35 g/cc) that can be used to drill new wells in the Buzurgan oil field with less expected drilling problems.

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Publication Date
Tue Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Cutting Parameters on Temperature Distribution and Tool Life During Turning Stainless Steel 316L
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This paper is focused on studying the effect of cutting parameters (spindle speed, feed and depth of cut) on the response (temperature and tool life) during turning process. The inserts used in this study are carbide inserts coated with TiAlN (Titanum, Aluminium and Nitride) for machining a shaft of stainless steel 316L. Finite difference method was used to find the temperature distribution. The experimental results were done using infrared camera while the simulation process was performed using Matlab software package. The results showed that the  maximum difference between the experimental and simulation results was equal to 19.3 , so, a good agreement between the experimental and simulation results  was achieved. Tool life w

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Publication Date
Wed Dec 31 2025
Journal Name
Polymer-plastics Technology And Materials
Comprehensive Study on Structural, Optical, Electrical and Thermal Properties of HPMC/PEG-Li2SO4 Solid Polymer Blend Electrolytes
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In this study, high-performance solid polymer electrolytes (SPEs) with different compositions were investigated for next-generation lithium-based energy storage and flexible electronics technology applications. The SPE films were prepared by the solution casting method using hydroxypropyl methylcellulose (HPMC), polyethylene glycol (PEG), and lithium sulfate (Li2SO4 ). The obtained films were flexible and transparent, hence suitable for structural, optical, electrical, and thermal characterizations. The XRD pattern of HPMC indicated a broad peak at 2 theta approximate to 20 degrees, while the films HPMC/PEG- Li2SO4 showed sharp peaks assigned to the crystalline nature of Li2SO4 . Fourier-transform infrared (FTIR) spectra confirmed O-H vibra

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Publication Date
Fri Jan 01 2021
Journal Name
Desalination And Water Treatment
Removal of nitrates from water by Amberlite IR-400 and economic Duolite A-378 ion exchange resins
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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Treatment of petroleum refinery wastewater by an innovative electro-Fenton system: Performance and specific energy consumption evaluation
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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Evaluation of Volatile Organic Compounds from Broccoli Plants Infested with Myzus persicae and Parasitoids Aphidius colemani Attraction
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Abstract<p>Volatile organic compounds (VOCs) from uninfested and infested broccoli plant samples with green peach aphid <italic>Myzus persicae</italic> were investigated by headspace solid microextraction (HS-SPME) combined with gas chromatography mass spectrometry (GC-MS). Overall, 25 compounds were identified in uninfested and infested broccoli plants. The HS-SPME combined with GC-MS analysis of the volatiles described the differences between the infested and uninfested broccoli plant samples. Based on peak area from the GC-MS analysis, the VOCs from infested broccoli were significantly greater than that from uninfested broccoli, such as D-limonene, Undecane, 3,4-dimethyl-, Heptane, </p> ... Show More
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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Saudi Chemical Society
Synthesis, characterization and comparative study the microbial activity of some heterocyclic compounds containing oxazole and benzothiazole moieties
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Antibiotic Resistance of Staphylococcus Sp. Isolated from Air, Surface, Food and Clinical samples Collected from Baghdad Hospital
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Staphylococcus Sp.is the most common type of bacteria found in contamination place, we design this
study to compare the contamination accident between two hospitals in Baghdad.One of them isthe Burns
Specialist Hospital in the Medical CityinRusafa and another one is Al-Karama Hospital in Karkh. The
samples were collected fromOperativeWard No1 (OW1), Operative Ward No2 (OW2), Consulting Pharmacy
(CP), Emergency Room (ER), Reception Room (RR), Women's Ward (WW) and Men's Ward (MW).The
samples were taken from inside each clinical unit, surfaces, food, and air. The results showed that the
number of samples containing Staphylococcus sp. bacteria is 81, including 45 belonging to Al-Karama Burns
Ward Ho

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Publication Date
Thu Jul 04 2024
Journal Name
Journal Of Chemical Technology &amp; Biotechnology
Adsorption of bimetal from aqueous solution on plum seed activated carbon synthesized by pyrocarbonic acid microwave method
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Abstract<sec><title>BACKGROUND

This article presents the simultaneous adsorption of bimetal Cu2+ and Zn2+ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electr

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Fri Mar 01 2024
Journal Name
Journal Of Education And Health Promotion
Nurses' knowledge and protective health behaviors about prevention of COVID-19 pandemic complications at Baghdad Teaching Hospitals
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BACKGROUND:

Coronavirus disease (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus, SARS-CoV-2. Infection with SARS-CoV-2 primarily occurs through binding to angiotensin-converting enzyme-2 (ACE2), which is abundantly expressed in various anatomical sites, including the nasopharynx, lungs, cardiovascular system, and gastrointestinal and genitourinary tracts. This study aimed to nurses' knowledge and protective health behaviors about prevention of covid-19 pandemic complications.

MATERIALS AND METHODS:

A descriptive design stud

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