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Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
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Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporating reservoir properties and production data of previous wells.</p><p>This study used the Artificial Neural Network (ANN) that has been programmed in a manner to predict the cumulative oil produced for a certain grid by providing the corresponding properties of the grid. The network has been validated with real data collected from a number of drilled hypothetical wells. Furthermore; the validated network used to simulate the field parts that have not been drilled yet, to predict the corresponding cumulative oil for each grid. Field-scale simulation has been carried out and new horizontal wells have been allocated using the validated prepared data by the Artificial Neural Network Algorithm and an approved Iraqi reservoir model. Finally, different optimization scenarios have been investigated on the overall field recovery performance.</p>
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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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Publication Date
Fri Feb 14 2014
Journal Name
International Journal Of Computer Applications
Parallelizing RSA Algorithm on Multicore CPU and GPU
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Publication Date
Fri Sep 03 2021
Journal Name
Entropy
Reliable Recurrence Algorithm for High-Order Krawtchouk Polynomials
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Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

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Publication Date
Mon Mar 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Speech Enhancement Algorithm Based on a Hybrid Estimator
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Abstract<p>Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra</p> ... Show More
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Publication Date
Mon Aug 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Solid waste recycling and management cost optimization algorithm
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Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

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Publication Date
Thu Jun 06 2024
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
Lightweight Block and Stream Cipher Algorithm: A Review
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Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable.  Fortunately, various lightweight encryption algorithms could be used to increase defense against various at

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Publication Date
Fri Apr 01 2022
Journal Name
Symmetry
Fast Overlapping Block Processing Algorithm for Feature Extraction
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In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods of Estimating the Parameters and Survival Function of a Log-logistic Distribution with a Practical Application
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The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

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Publication Date
Fri Jan 01 2021
Journal Name
Bionatura
STUDY THE TIGRIS RIVER IN SOUTH OF BAGHDAD CITY AND MAY USE IT AS IRRIGATION WATER
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