In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss is a gathering of numerous issues for example rheology of mud), flow regime and the well geometry. An artificial neural network (ANN) that used in this effort is an accurate or computational model stimulated by using JMP software. The aim of this study is to find out the effect of rheological models on the hydraulic system and to use the artificial neural network to simulate the parameters that were used as emotional parameters and then find an equation containing the parameters μp, Yp and P Yp/ μp to calculate the pressure losses in a hydraulic system. Data for 7 intermediate casing wells with 12.25" hole size and 95/8" intermediate casing size are taken from the southern Iraq field used for the above purpose. Then compare the result with common equations used to calculate pressure losses in a hydraulic system. Also, we calculate the optimum flow by the maximum impact force method and then offset in Equation obtained by (Joint Marketing Program) JMP software. Finally, the equation that was found to calculate pressure losses instead of using common hydraulic equations with long calculations gave very close results with less calculation.
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreGranulation Technique for Gamma Alumina Catalyst Support was employed in inclined disk granulator (IDG), rotary drum granulator (RD) and extrusion – spheronization equipments .Product with wide size range can be produced with only few parameters like rpm of equipment, ratio of binder and angle of inclination. The investigation was conducted for determination the optimum operating conditions in the three above different granulation equipments.
Results reveal that the optimum operating conditions to get maximum granulation occurred at ( speed: 31rpm , Inclination:420 , binder ratio:225,300% ) for the IDG,( speed: 68rpm , Inclination: 12.50 , binder ratio: 300% ) for the RD and ( speed:1200rpm , time of rotation: 1-2min )for the Caleva
Post-structural critical studies highlighted the importance of studying the texts surrounding the text as an important part in the process of receiving and understanding texts, and although this topic was dealt with by the ancient Arabs and Europeans, interest in it appeared clearly after the appearance of Gerard Genet's book (SEUILS), which separated it Text Thresholds. Or what he called paratexte, and dealt with them with interest as he reads them on books. With the development of semiotic studies, interest in paratexte studies began in a broader way and in various literary and non-literary texts, including journalistic texts. And since specialized magazines are one of the press releases that enjoy their privacy in terms of topics and
... Show MoreFace recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.
The bit record is a part from the daily drilling report which is contain information about the type and the number of the bit that is used to drill the well, also contain data about the used weight on bit WOB ,revolution per minute RPM , rate of penetration ROP, pump pressure ,footage drilled and bit dull grade. Generally we can say that the bit record is a rich brief about the bit life in the hole. The main purpose of this research is to select the suitable bit to drill the next oil wells because the right bit selection avoid us more than one problems, on the other hand, the wrong bit selection cause more than one problem. Many methods are related to bit selection, this research is familiar with four of thos
... Show MoreRegression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh
... Show MoreAlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).
AlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).
The aim of this study was extraction of jojoba oil using different solvents. A mixture of waterhexane and water-ethanol are used as solvents to extract jojoba oil in a batch extraction process and compared with a pure solvent extraction process. The effects of particle size of crushed seeds, solvent-to-water ratio and time on jojoba oil extraction were investigated. The best recovery of oil was obtained at the boiling temperature of the solvent and four hour of extraction time. When seed particle size was 0.45 mm and a pure ethanol was used (45% yield of oil extraction), whereas, it was 40% yield of oil at 25% water-hexane mixture. It was revealed that the water-ethanol and water-hexane mixtures have an effect on the oil extraction yield. T
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