The optimization of artificial gas lift techniques plays a crucial role in the advancement of oil field development. This study focuses on investigating the impact of gas lift design and optimization on production outcomes within the Mishrif formation of the Halfaya oil field. A comprehensive production network nodal analysis model was formulated using a PIPESIM Optimizer-based Genetic Algorithm and meticulously calibrated utilizing field-collected data from a network comprising seven wells. This well group encompasses three directional wells currently employing gas lift and four naturally producing vertical wells. To augment productivity and optimize network performance, a novel gas lift design strategy was proposed. The optimization of gas allocation was executed to maximize oil production rates while minimizing the injected gas volume, thus achieving optimal oil production levels at the most effective gas injection volume for the designated network. The utilization of the PIPESIM Optimizer, founded on genetic algorithm principles, facilitated the attainment of these optimal parameters. The culmination of this study yielded an optimal oil production rate of 18,814 STB/d, accompanied by a gas lift injection rate of 7.56 MMscf/d. This research underscores the significance of strategic gas lift design and optimization in enhancing oil recovery and operational efficiency in complex reservoir systems like the Mishrif formation within the Halfaya oil field.
In this paper, the class of semi
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
... Show MoreThis research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f
... Show MoreThe objective of this research is to determine the relationship between the performance evaluation process and the training programs for the employees, to identify the extent of the organization's commitment to perform the performance evaluation process for its employees and to use the results of this process in determining the appropriate training programs. Performance evaluation, functional analysis, evaluation method used, dependent variable (training programs) and its dimensions, type of programs, program objectives, program curriculum, And the application of the field research methodology and the questionnaire, which included 146 individuals to know their views and analyz
... Show MoreThis experiment was performed to investigate the influence of different oils in the diets of laying quail on their egg quality characteristics. One hundred and twenty 7-wk old Japanese quails (Coturnix coturnix japonica) were allocated to four groups with three replicates containing 10 quail each (30 quail per each treatment group). They were fed for 13 weeks (including one week of adaptation period) on diets containing 3% oil from different sources, viz. either sunflower (T1), linseed (T2), maize (T3), or fish oil (T4). Inclusion the diet of laying quail with fish oil (T4) and maize oil (T2) resulted in significant increase with respect to egg weight, yolk weight, albumen weight, yolk diameter, yolk height, albumen diameter, albumen height
... Show MoreThis experiment was performed to investigate the influence of different oils in the diets of laying quail on their egg quality characteristics. One hundred and twenty 7-week-old Japanese quails (Coturnix coturnix japonica) were allocated to four groups with three replicates containing 10 quail each (30 quail per treatment group). They were fed for 13 weeks (including one week of adaptation period) on diets containing 3% oil from different sources, viz., sunflower (T1), linseed (T2), maize (T3), or fish oil (T4). Inclusion of the diet of laying quail with fish oil (T4) and maize oil (T2) resulted in a significant increase with respect to egg weight, yolk weight, albumen weight, yolk diameter, yolk height, albumen diameter, albumen height, sh
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