A simple, accurate and sensitive spectrophotometric method for the determinaion of epinephrine is described . The method is based on the coordination of Pr (III) with epinephrine at pH 6. Absorbance of the resulting orange yellow complex is measured at 482 nm . A graph of absorbance versus concentrations shows that beer 's low is obeyed over the concentration range (1-50)mg.ml-1 of epinephrine with molar absorpitivity of ( 2.180x103 L.mol-1.cm-1 ), a sandell sensitivity of (0.084 mg.cm-2 ), a relative error of (-2.83%) , a corrolation coffecient (r= 0.9989) and recovery % ( 97.03 ± 0.75 ) depending on the concentration.This method is applied to analyse EP in several commercially available pharmaceutical preparations

Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.

Acidizing is one of the most used stimulation techniques in the petroleum industry. Several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly in the development of the Mishrif reservoir, including the following: (1) high injection pressures make it difficult to inject acid into the reservoir formation, and (2) only a few acid jobs have been effective in Ahdeb oil wells, while the bulk of the others has been unsuccessful. The significant failure rate of oil well stimulation in this deposit necessitates more investigations. Thus, we carried out this experimental study to systematically investigate the influence of acid treatment on the geomechanical properties of Mi4

Protection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie

The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c

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 g

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F