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.
The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
... Show MoreBackground: Periodontal diseases are bacterial infections of the gingiva, bone and attachment fibers that support the teeth and hold them in the jaw. α-amylase is an enzyme, produced mainly by parotid gland and it seems to play a role in maintaining mucosal immunity. Aims of the study: Determine the salivary levels of α-Amylase and flow rate and their correlations with clinical periodontal parameters(Plaque Index , Gingival Index , Bleeding on Probing , Probing Pocket Depth , and Clinical Attachment Level ) and the correlation between α-Amylase with flow rate of study groups that consist of ( patients had gingivitis and patients had chronic periodontitis with different severities(mild ,moderate ,severe) and control group . Ma
... Show MoreIn this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad. One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.
The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a
... Show MoreHuman beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
The Evolution Of Information Technology And The Use Of Computer Systems Led To Increase Attention To The Use Of Modern Techniques In The Auditing Process , As It Will Overcome Some Of The Human Shortcomings In The Exercise Of Professional Judgment, Then It Can Improve The Efficiency And Effectiveness Of The Audit Process, Where The New Audit Methodologies Espouse The Concept Of Risk Which Includes Strategic Dimension With Regard To The Capacity Of The Entity To Achieve Its Goals, Which Requires Auditors To Rely On Advanced Technology That Can Identify The Factors Which Prevent The Entity From Achieving Its Objectives. The Idea Of Research Is To Preparing An Electronic Program Fer All Audit Work From Planning Through Sampling And Document
... Show MoreABSTRACT Background: Color changes that are detectable to human eye can affect the esthetic appearance of ceramic veneers. The purpose of this study was to evaluate and compare the effect of artificial accelerated aging on the color of ceramic veneers cemented with different resin cements. Materials and Methods: Sixty discs were prepared with 0.5 mm thickness, 30 discs made from IPS e.max press (Ivoclar Vivadent) and 30 discs were made from VITA Enamic (VITA Zahnfabrik). The discs were cemented with three resin cements: Variolink Veneer MV 0 shade (Ivoclar Vivadent), Rely X veneer Translucent shade (3M ESPE) and NX3 Nexus Clear shade (Kerr Corporation) with 0.1 mm thickness. The spectrophotometer Easyshade Advance was used to measure the co
... Show MoreIn this paper, first we refom1Ulated the finite element model
(FEM) into a neural network structure using a simple two - dimensional problem. The structure of this neural network is described
, followed by its application to solving the forward and inverse problems. This model is then extended to the general case and the advantages and di sadvantages of this approach are descri bed along with an analysis of the sensi tivity of
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.
So, this study aimed at testing the system performance at poor s
... Show MoreThis study was designed to stand on the most important causes of contamination in sesarean section in women by the aerobic bacteria species the bacteria isolates were diagnosed in the Maternity and Children Hospital in the Qadsiya province and in the special clinics. Sixty five persent of women having cesarean operation were contaminated with different bacteria in different ratios. Staphylococcus aureus showed the higher percentage (62.4) , Pseudomonas.aerogenosa 18% , E.coli 9.5% and Proteus.spp (6,4%).While Streptococcus pyogens showed lowest percentage 3.6% . The results of antibiotic sensitivity test for all bacteria isolates showed Chloramphenicol and Ami
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