In many oil-recovery systems, relative permeabilities (kr) are essential flow factors that affect fluid dispersion and output from petroleum resources. Traditionally, taking rock samples from the reservoir and performing suitable laboratory studies is required to get these crucial reservoir properties. Despite the fact that kr is a function of fluid saturation, it is now well established that pore shape and distribution, absolute permeability, wettability, interfacial tension (IFT), and saturation history all influence kr values. These rock/fluid characteristics vary greatly from one reservoir region to the next, and it would be impossible to make kr measurements in all of them. The unsteady-state approach was used to calculate the relative permeability of five carbonate for core plugs from the Mishrif formation of WQ1. The relative permeability calculated by using Johnson, Bossler and Naumann (JBN) Correlation, which is, consider one of the unsteady-state approach where it found that the core plugs are water wet. A normalizing approach has been used to remove the effect of irreducible water and residual saturations, which would vary according on the environment. Based on their own irreducible water and trapped saturations, the relative permeabilities can subsequently be de-normalized and assigned to distinct sections (rock types) of the reservoir. The goal of this research is to normalize the relative permeability that was determined through water flooding.
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreLongitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
... Show MoreThe advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con
... Show MoreA two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was
... Show MoreA total of 72 specimens of the wild jungle cat Felis chaus furax De Winton, 1898 were
examined for the purpose of this study. The results show that 55.6% of the sample harbored
either single or mixed infections with ecto- and/ or endoparasites. The mode of infection
shows that only four specimens( 5.6% of the total sample) acquire single infections, the
double infections comprise 15.3%, the triple infections comprised 33.3%, while the
quadruplicate infections comprised 1.4%.
The systematic list of the parasites included six ectoparasites: Ctenocephalides felis (insect),
Sarcoptes scabiei (mite), Haemaphysalis adleri, Rhipicephalus leporis, Rhipicephalus
turanicus and Hyalomma anatolicum excavatum (ticks) and seven
This study reports on natural convection heat transfer in a square enclosure of length (L=20 cm) with a saturated porous medium (solid glass beads) having same fluid (air) at lower horizontal layer and free air fill in the rest of the cavity's space. The experimental work has been performed under the effects of heating from bottom by constant heat flux q=150,300,450,600 W/m2 for four porous layers thickness Hp (2.5,5,7.5,1) cm and three heaters length δ(20,14,7) cm. The top enclosure wall was good insulated and the two side walls were symmetrically cooled at constant temperature. Four layers of porous media with small porosity, Rayleigh number range (60.354 - 241.41) and (Da) 3.025x10-8 has been investigated. The obtained data of temperatu
... Show MoreThe aim of this study is to investigate the sedimentation environments and diagenetic processes of the Ibrahim Formation (Oligocene-early Miocene) in Zurbatiya, eastern Iraq. The Ibrahim Formation is comprised mostly of clayey micrite and skeletal grains composed of planktonic foraminifera, calcispheres, radiolaria, and benthic foraminifera. Glauconite and pyrite were documented in some restricted zones of this formation; they reflect quiet and reducing conditions. Radiolaria were identified in Late-Oligocene which was not known previously at this age regionally in carbonate formations of the Arabian Plate (AP). Mudstone, wackestone, and planktonic foraminiferal wackepackstone are the main microfacies that are affected by dissolutio
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