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Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation pore pressure, and in-situ stresses of the studied area were included as inputs. The second step was by optimizing the process using a genetic algorithm (GA), as a class of optimizing methods for complex functions, to obtain the maximum ROP along with the related wellbore trajectory (AZI and INC). Finally, the suggested azimuth (AZI) and inclination (INC) are premeditated by considering the results of wellbore stability analysis using wireline logging measurements, core and drilling data from the offset wells.

The results showed that the optimized wellbore trajectory based on wellbore stability analysis was compatible with the results of the genetic algorithm (GA) that used to reach higher ROP. The recommended orientation that leads to maximum ROP and maintains the stability of drilling deviated wells (i.e., inclination ranged between 40°—50°) is parallel to (140°—150°) direction. The present study emphasizes that the proposed methodology can be applied as a cost-effective tool to optimize the wellbore trajectory and to calculate approximately the drilling time for future highly deviated wells.

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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Mon Oct 01 2018
Journal Name
International Journal Of Civil Engineering And Technology
NUMERICAL ANALYSIS OF PILES FOUNDATION TO REDUCE THE ZONE OF LIQUEFACTION OF SANDY SOIL UNDER DYNAMIC LOADS
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The major cause of destruction during vertical vibration is the failure of the soil structure. The soil may fail due to loss of strength during continues vibration. The saturated sandy soil losses strength due to an increase in pore pressure, this phenomenon is called "liquefaction". Piled foundations are usually adopted as a foundation solution in potentially liquefiable soil under dynamic loading. In this research, 3D finite element model using PLAXIS Software was employed for pile foundation in saturated sandy soil. The results show the acceleration mobilization and velocity on the footing increases with increasing the intensity of dynamic loads and it becomes zero at maximum value of vertical settlement which indicates the end of the ti

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Scopus
Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Comparison of the Cyclic Fatigue of Protaper Next, 2Shape and Hyflex EDM Using Glyde
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Publication Date
Wed Mar 20 2019
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE WATER ECOSYSTEM OF THE MARSHES OF MAYSAN GOVERNORATE USING REMOTE SENSING AND GIS
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The study addressed the water ecosystems of the marshes of Maysan Governorate as one of the important areas in Iraq in terms of the environmental, economic and tourism aspects. This area was exposed to great environmental changes due to natural and human factors which greatly affected the water ecosystem and made the area susceptible to many problems that affected the biological life of living organisms. The marshes of Maysan Governorate was affected by vital factors and non-vital factors. The marshes of Maysan Governorate was characterized by the UN Organization as one of the most important centers of biodiversity in the world because of the abundance of different and rare living organisms such as birds, fish, and reptiles as well as the e

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Publication Date
Wed Dec 25 2024
Journal Name
Jurnal Kimia Valensi
Green Synthesis, Characterization, and Applications of Aluminum Oxide Nanoparticles Using Aqueous Extract of Clove
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In this work, γ-Al2O3NPs were successfully biosynthesized, mediated aluminum nitrate nona hydrate Al(NO3)3.9H2O, sodium hydroxide, and aqueous clove extract in alkali media. The γ-Al2O3NPs were characterized by different techniques like Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy–dispersive x-ray spectroscopy, transmission electron microscope (TEM), Energy-dispersive X-ray spectroscopy (EDX), and atomic force microscopy (AFM). The final results indicated the γ-Al2O3NPs nanoparticle size, bonds nature, element phase, crystallinity, morphology, surface image, particle analysis – threshold detection, and the topography parameter. The id

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Improvement of the Rheological and Filtration Properties of Drilling Mud Using the Syrian Clay
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Drilling fluid properties and formulation play a fundamental role in drilling operations. The Classical water-based muds prepared from only the Syrian clay and water without any additives((Organic and industrial polymers) are generally poor in performance. Moreover, The high quantity of Syrian clay (120 gr / l) used in preparing drilling fluids. It leads to a decrease in the drilling speed and thus an increase in the time required to complete the drilling of the well. As a result, the total cost of drilling the well increased, as a result of an increase in the concentration of the solid part in the drilling fluid. In this context, our study focuses on the investigation of the improvement in drilling mud   Prepa

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Publication Date
Wed Jul 01 2026
Journal Name
South African Journal Of Chemical Engineering
Enhancement of water-based drilling fluid using novel composite of silica and alumina nanoparticles
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One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

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Publication Date
Tue Mar 29 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Prediction of bearing capacity of driven piles for Basrah governatore using SPT and MATLAB
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Based on the results of standard penetration tests (SPTs) conducted in Al-Basrah governorate, this research aims to present thematic maps and equations for estimating the bearing capacity of driven piles having several lengths. The work includes drilling 135 boreholes to a depth of 10 m below the existing ground level and three standard penetration tests (SPT) at depths of 1.5, 6, and 9.5 m were conducted in each borehole. MATLAB software and corrected SPT values were used to determine the bearing capacity of driven piles in Al-Basrah. Several-order interpolation polynomials are suggested to estimate the bearing capacity of driven piles, but the first-order polynomial is considered the most straightforward. Furthermore, the root means squar

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Scopus (35)
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Publication Date
Tue Jan 01 2019
Journal Name
Biochem. Cell. Arch
BIOSYNTHESIS OF SILVER NANOPARTICLES USING MINTS LEAF EXTRACT AND EVALUATION OF THEIR ANTIMICROBIAL ACTIVITY
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The aim of this study is to synthesize an easy, non-toxic and eco-friendly method. Silver nanoparticles which were synthesized by leaf extract of mint were characterized by UV-Visible Spectroscopy which appears UVVisible spectrum of demonstrated a peak 448 nm corresponding to surface Plasmon resonance of silver nanoparticles, Fourier Transform Infrared Spectroscopy (FTIR); functional groups involved in the silver nanoparticles synthesis were identified, the presence of silver nanoparticles was confirmed by X-ray diffraction (XRD) and Atomic Force Microscope (AFM) analysis clearly illustrated that the shape of silver nanoparticles was spherical and the size of the silver nanoparticles has been measured as 55- 85 nm. Evaluation of its antimic

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Scopus (3)
Scopus