A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited grids and used in the training and testing of the used network. A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so
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Carbonate-clastic succession which includes the Shu'aiba, Nahr Umr and Mauddud formations are representing a part of the Barremian-Aptian Sequence (Wasi'a Group). The present study includes three boreholes (Ba-1, 4 and 8) within the Balad Oil Field. The study area is located in central Iraq. This field represents a subsurface anticline with a northwest to southeast direction axis within the Mesopotamian Zone. Eight types of microfacies were recognized in the succession of the Mauddud and Shu’aiba formations. These microfacies represent shallow open marine, restricted and semi-restricted, reef - back reef, deep open marine and basinal depositional environments. While Nahr Umr Formation includes two successions, the first is the upp
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha
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High frequencies of multidrug resistant organisms were observed worldwide in intensive care units which is a warning as to use the only few effective antimicrobials wisely to reduce selective pressure on sensitive strains.
The aim of the current study is to asses the compliance of the currently followed antibiotic prescribing pattern in the intensive care unit in an Iraqi hospital with the international guidelines.A cross-sectional study was done in the intensive care unit (ICU) of the Surgical Specialties Hospital, Medical City in Bagdad from the 30th of November 2011 to the 5th of May 2012.Patients were followed until they were discharged or died to see any change in condition, response to drugs, devices u
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In recent decades, breeding deer populations in Iraq have expanded significantly in size and distribution. Owing to their role in pathogen transmission, these deer populations pose a risk to the livestock industry. However, little is known about the parasitic infection status of the breeding deer and the surrounding environment in Iraq. Atotal of 150 deer faecal samples were collected from male and female deer of various ages from four regions of Iraq and examined microscopically for intestinal parasites. Microscopic analysis revealed the presence of seven intestinal parasite species: Entamoeba spp. (48%), Giardia duodenalis (17%), Toxocara spp. (12%), Balantidium coli(9%), Taenia spp. (9%), Strongyloides spp. (3%) and Trichostrongy
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Abstract
The research aims to identify the mediator role of workplace spirituality in the relationship between psychological capital and entrepreneurial behavior: field research to a sample opinions from employees at the center of the Iraqi ministry of Oil . The importance of the current research emerged from paucity of studies that have attempted to identify and know the nature of the relationship between the variables as well as trying to find the current address and realistic problem directly affects the performance of employees in the Iraqi oil sector.
In order to achieve the goal of research the use of the analytical method (quantitative)
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
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