The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting crude oil viscosity. However, these correlations are limited to predict the oil viscosity at specified conditions. In the present work, an extensive experimental data of oil viscosities collected from different samples of Iraqi oil reservoirs was applied to develop a new correlation to calculate the oil viscosity at various operating conditions either for dead, satura

In this research the specifications of Iraqi drinking bottled water brands are investigated throughout the comparison between local brands, Saudi Arabia and the World Health Organization (WHO) for bottled water standard specifications. These specifications were also compared to that of Iraqi Tap Water standards. To reveal variations in the specifications for Iraqi bottled water,  and above mentioned standards some quality control tools are conducted for more than 33% of different bottled water brands (of different origins such as spring, purified,..etc) in Iraq by investigating the  selected quality parameters registered on their marketing labels. Results employing Minitab software (ver. 16) to generate X bar,

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

A series of overbased magnesium fatty acids such as caprylate, caprate, laurate, myristate, palmitate, stearate and oleate) were synthesized by the reaction of the fatty acids with active – 60 magnesium oxide and carbon dioxide (CO2) gas at 60 oC in the presence of ammonia solution as catalyst, toluene / ethanol solvent mixture (9:1vol/vol) was added.
The prepared detergent additives were characterized by FTIR, 1HNMR and evaluated by blending each additive in various concentrations with medium lubricant oil fraction (60 stock) supplied by Iraqi Midland Refineries Company. The total base number (TBN, mg of KOH/g) was determined, and the results of TBN were treated by using two-way analysis of variance (ANOVA) test. It was found that

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 p