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Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the modeling part, a one-dimension mechanical earth model (1D MEM) parameters, drilling fluid properties, and rig- and bit-related parameters, were included as inputs. The optimizing process was then performed to propose the optimum drilling parameters to select the drilling bit that provides the maximum possible ROP. To achieve this, the corresponding mathematical function of the ANNs model was implemented in a procedure using the genetic algorithm (GA) to obtain operating parameters that lead to maximum ROP. The output will propose an optimal bit selection that provides the maximum ROP along with the best drilling parameters. The statistical analysis of the predicted bit types and optimum drilling parameters comparing the actual flied measured values showed a low root mean square error (RMSE), low average absolute percentage error (AAPE), and high correction coefficient (R2). The proposed methodology provides drilling engineers with more choices to determine the best-case scenario for planning and/or drilling future wells. Meanwhile, the newly developed model can be used in optimizing the drilling parameters, maximizing ROP, estimating the drilling time, and eventually reducing the total field development expenses.</p>
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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Selection of highly ethanol productive yeast
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Seventy five isolates of Saccharomyces cerevisiae were identified, they were isolated from different local sources which included decayed fruits and vegetables, vinegar, fermented pasta, baker yeast and an alcohol factory. Identification of isolates was carried out by cultural microscopical and biochemical tests. Ethanol sensitivity of the isolates showed that the minimal inhibitory concentration of the isolate (Sy18) was 16% and Lethal concentration was 17%. The isolate (Sy18) was most efficient as ethanol producer 9.36% (v/w). The ideal conditions to produce ethanol from Date syrup by yeast isolate, were evaluated, various temperatures, pH, Brix, incubation period and different levels of (NH4)2HP04. Maximum ethanol produced was 10

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Penetration of charged particles in ZnO using energy loss function model
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In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed
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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Impact of Artificial Intelligence on English Language Learning Challenges and Opportunities
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
EFFECT OF COOLING RATE ON MECHANICAL PROPERTIES OF EUTECTIC AND HYPOEUTECTIC Al-Si ALLOYS
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In this research the effect of cooling rate and mold type on mechanical properties of the eutectic
and hypoeutectic (Al-Si) alloys has been studied. The alloys used in this research work were (Al- 12.6%Si
alloy) and (Al- 7%Si alloy).The two alloys have been melted and poured in two types of molds with
different cooling rates. One of them was a sand mold and the other was metal mold. Mechanical tests
(hardness, tensile test and impact test) were carried out on the specimens. Also the metallographic
examination was performed.
It has been found that the values of hardness for the alloys(Al-12.6%Si and Al-7%Si) which poured in
metal mold is greater than the values of hardness for the same alloy when it poured in a heated

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Publication Date
Mon Apr 13 2026
Journal Name
Innovative Infrastructure Solutions
Beyond empiricism: a unified physics-based framework for resonance avoidance and carbon-efficient mass optimization of machine foundations
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Dynamic machine foundations can be considered as a necessary component of the industrial infrastructure. Design of the dynamic equipment foundations has, however, traditionally been grounded on a rule of thumb that is inaccurate and rigid to use at the discretion of the engineers. The conventional rule of thumb, which includes minimum weight ratios and resonance avoidance criteria, has been used singularly with two poles, which can be either conservatively designed systems that are too heavy, or systems that are going to experience too much vibration and fatigue. This paper presents a novel, analytical framework for the reinterpretation of traditional design practices, using a physics-based approach, and results in a single, unified overall

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