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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
Mon Jan 01 2024
Journal Name
International Journal Of Research In Science And Technology
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

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Publication Date
Fri Sep 01 2017
Journal Name
Food Research International
Effect and mechanism of cellulose nanofibrils on the active functions of biopolymer-based nanocomposite films
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
The Effect of Electrospinning Parameters on Morphological and Mechanical Properties of PAN-based Nanofibers Membrane
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The electrospun nanofibers membranes (ENMs) have gained great attention due to their superior performance. However, the low mechanical strength of ENMs, such as the rigidity and low strength, limits their applications in many aspects which need adequate strength, such as water filtration. This work investigates the impact of electrospinning parameters on the properties of ENMs fabricated from polyacrylonitrile (PAN) solved in N, N-Dimethylformamide (DMF). The studied electrospinning parameters were polymer concentration, solution flow rate, collector rotating speed, and the distance between the needle and collector. The fabricated ENMs were characterized using scanning electron microscopy (SEM) to understand the surface morphology and es

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Reduction of the error in the hardware neural network
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Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

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Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Detection System of Varicose Disease using Probabilistic Neural Network
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Tue Jun 18 2024
Journal Name
2023 Asee Annual Conference &amp; Exposition Proceedings
Study of Artificial Intelligence Computing Devices for Undergraduate Computer Science and Engineering Labs
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Publication Date
Mon Jun 30 2025
Journal Name
Modern Sport
The Contribution Rate of Certain Cognitive and Visual Abilities to the Performance of Forehand and Backhand Skills in Tennis
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The significance of the study lies in identifying a scientific and objective indicator that clarifies the extent to which key cognitive and visual abilities contribute to skill performance in tennis. This enables coaches and instructors to design scientifically based educational and training units that incorporate these abilities according to their level of contribution, thereby positively impacting technical performance. The abundance of stimuli in tennis and the difficulty of controlling performance, due to the sport's ongoing developments, require a high level of cognitive and visual abilities. The researchers aimed to examine the problem of inadequate organization in educational content, where one aspect is emphasized over other

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Publication Date
Mon Jun 30 2025
Journal Name
Modern Sport
The Contribution Rate of Certain Cognitive and Visual Abilities to the Performance of Forehand and Backhand Skills in Tennis
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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Impact of non-current assets impairment reporting on certain financial indicators application on Al-Mansour Pharmaceuticals- a private corporation
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   This research deals with the financial reporting for non-current assets impairment from the viewpoint of international accounting standards, particularly IAS 36 "Impairment of non-current assets." The research problems focus on the presence of internal and external indicators on impairment of non-current assets in many of companies listed in Iraqi stock exchange. So it is required to apply IAS 36 to reporting for the impairment loss of assets since this impairment impact certain financial indicators. These indicators help users in their decision-making and forecasting future financial situation and the ability of the company to achieve future profits or maintain current profits. The research aims to shedding lig

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