The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injection flows in the structure of the network of Zubair, oil field with 10 gas-lift injected wells. This will be done through numerical simulation and modeling studies. The overall enhancement of the filed production rate is found to have increased from 15767 STB/day to 19847 STB/day. The well's reservoir pressure and water cut sensitivity studies are carried out to study the possible impacts of these elements upon the well and its efficiency through the course of the field. Our understanding of the potential benefits of utilizing gas lift techniques in a field from a technical and economical point of view is deepened by the use of examples from economic analysis. Furthermore, even though the idea of employing GA in this manner is not new, this work discusses GA-based optimization methodologies for increasing the oil production rate by using gas lifting in a Zubair oilfield. In order to assign gas injection rates to specific wells in a network throughout the field using limited gas injection rates, the model for optimization will be laid out step-by-step making it simple to understand and employ as a guide, especially for the front-line production technicians involved in the development and design of gas-lift systems.
Genetic variation was studied in 22 local and imported samples collected from local Iraqi market by using Single sequence repeat (SSR-PCR). Six primers set were used in this study. These primers produced 33 bands. Molecular weights of these bands ranged between 100 bp to 1500 bp. The number of polymorphic bands is 24, whereas the number of monomorphic bands is 9. The results of Dendrogram of the studied samples depended on SSR-PCR results by using Jaccard coefficient for genetic similarity was distributed the samples into 10 groups. This Dendrogram revealed a higher similarity between Iraqi/Balad green bell pepper and Iraqi/Yousifia green bell pepper with 1 value. This value is the highest between samples in comparison with lowest values (0
... Show MoreThis research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for
... Show MoreThis paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p
... Show MoreIn the present work, it had been measured the concentration of radon gas (CRn) for (10) samples of cement used in constructions before and after painting them using enamel paint, purchased from the local markets, to see the extent of its ability to reduce emissions of Rn-222 in the air. These samples were obtained from different sources available in the local markets in Baghdad and other provinces. The measurements were done by the American-made detector (RAD7). The results showed that the highest CRn in the air emitted from cement samples after coating was in the cement sample (Iranian origin) where the concentration was (58.27 Bq/m3) while the lowest CRn was found in building material samples
... Show MoreThe present study addressed "Performance Appraisal of Human Resource Management and Its Effect on Achieving the Organizational Success", for the topics of performance appraisal of human resource management and the organizational success gained an increasing interest being relatively important and modern topics which had a great effect on the future of organizations.
The study aimed at revealing the pattern of appraising the performance of human resource management for the study sample, and whether it was qualified to lead the ministry towards the organizational success, for this purpose two main hypotheses were formulated: 1) there is a positive significant correlation between both variables: performanc
... Show MoreThis work studied the facilitation of the transportation of Sharqi Baghdad heavy crude oil characterized with high viscosity 51.6 cSt at 40 °C, low API 18.8, and high asphaltenes content 7.1 wt.%, by reducing its viscosity from break down asphaltene agglomerates using different types of hydrocarbon and oxygenated polar solvents such as toluene, methanol, mix xylenes, and reformate. The best results are obtained by using methanol because it owns a high efficiency to reduce viscosity of crude oil to 21.1 cSt at 40 °C. Toluene, xylenes and reformate decreased viscosity to 25.3, 27.5 and 28,4 cSt at 40 °C, respectively. Asphaltenes content decreased to 4.2 wt. % by using toluene at 110 °C. And best improvement in API of the heavy crude o
... Show MoreThe majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution
... Show MoreA spectrophotometric determination of azithromycin was optimized using the simplex model. The approach has been proven to be accurate and sensitive. The analyte has been reacted with bromothymol blue (BTB) to form a colored ion pair which has been extracted in chloroform in a buffer medium of pH=4 of potassium phthalate. The extracted colored product was assayed at 415 nm and exhibited a linear quantification range over (1 - 20) g/ml. The excipients did not exhibit any interferences with the proposed approach for assaying azithromycin in pharmaceutical formulations.
The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
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