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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
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Lightweight route adjustment strategy for mobile sink wireless sensor networks
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<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
Dependence on Media and the Formation of the Level of the Academic Elite's Knowledge concerning United Nations' Affairs (A research based on a doctoral thesis)
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The UN organization is considered one of the most important organizations at the international level. It has accomplished multiple tasks and roles of many different issues and events that hit the developing and advanced world countries. It has performed a series of procedures and laws that have had an impact on ending the wars and conflicts that plagued some countries and continued for a period of time in the past. Moreover, it has improved the level of the international relations between a number of countries due to the problems and incidents took place between them. It has relied on finding solutions and treatments for humanitarian problems such as the preservation of the environment, preventing the spread of epidemics and diseases Thi

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Publication Date
Sun Aug 30 2020
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Kernel estimation of returns of retirement funds of employers based on monetary earnings (subscriptions and compensation) via regression discontinuity in Iraq
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Regression Discontinuity (RD) means a study that exposes a definite group to the effect of a treatment. The uniqueness of this design lies in classifying the study population into two groups based on a specific threshold limit or regression point, and this point is determined in advance according to the terms of the study and its requirements. Thus , thinking was focused on finding a solution to the issue of workers retirement and trying to propose a scenario to attract the idea of granting an end-of-service reward to fill the gap ( discontinuity point) if it had not been granted. The regression discontinuity method has been used to study and to estimate the effect of the end -service reward on the cutoff of insured workers as well as t

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the Causal Relationship Long-and Short-term Between the Price of Crude Oil, the Global Price of Gold and the US. Dollar Exchange Rate
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This research aims to test the causal relationship long-and short-run between the price of gold the global crude oil price and the exchange rate of the dollar and how you can take advantage of the nature of this relationship, particularly in the Arab oil states that achieve huge surpluses, including Iraq and how to keep on the purchasing power of these surpluses or reduce the levels of risk.

The problem is that the Arab oil countries, adversely affected, as a result of that relationship, due to the fact that its role confined to the sale of crude oil only. They do not have control in the dollar, then they are not able to take advantage of its impact on the price of gold the fact that gold is effective pr

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Possible Options in Managing the Exchange Rate of the Iraqi Currency in light of Current Economic Conditions
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The management of the exchange rate of the most important tools of economic policy because of its wide area in achieving stability and economic growth through the provision of stability in the exchange rate of the currency of the country concerned , as well as the impact and influence of money supply and then treat the economic crisis monetary and reduce the risk of currency exchange rate .For the management of the exchange rate in Iraq has passed through several stages , from installation to link to a basket of currencies to float freely , and we are dealing with in this research regard to the achievements of monetary policy , especially after the enjoyment of independence on according to the Iraqi Central Bank Law No. 56 of 2004 and Ma

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Calculating Production Rate of each Branch of a Multilateral Well Using Multi-Segment Well Model: Field Example
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Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Stator Faults Diagnosis and Protection in 3-Phase Induction Motor Based on Wavelet Theory
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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Tue Jun 24 2025
Journal Name
Baghdad Science Journal
Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
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Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

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