This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water

    This research has tackled a scientific figure belongs to Koofi grammatical school. He is Abdullah Al-Tuaal who has occupied the fourth layer among the Koofi grammarians. There was a confusion between him and another Koofi grammarian from the same layer (Mohammed Bin Qaadim) in some old references. This research has clarified this confusion to affirm that they are two different grammarians.This research also tackles the scientific status of Al-Tuaal and the grammatical views that have been ascribed to him in addition to the analysis and discussion of these views. All this in the light of what has been mentioned in grammar books about the issues in which these views were stated.

The spectral characteristics and the nonlinear optical properties of the mixed donor (C-480) acceptor (Rh-6G) have been determined. The spectral characteristics are studied by recording their absorption and fluorescence spectra. The nonlinear optical properties were measured by z-scan technique, using Q-switched Nd: YAG laser with 1064 nm wavelength. The results showed that the optimum concentration of acceptor is responsible for increasing the absorption and the emission bandwidth of donor to full range and to 242 nm respectively by the energy transfer process, also the efficiency of the process was increased by increasing the donor and acceptor concentration. The obtained nonlinear properties results of the mixture C-480/ Rh-6G showed

Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately determi

Polyetheretherketone (PEEK) has favorable biomechanical properties to be used as an implant material. Unfortunately, it is hydrophobic and does not promote cellular adhesion, which could result in poor integration with bone tissue. Bio-functionalization of PEEK surface with osteogenic peptides derived from bone extracellular matrix proteins is an exciting approach to encourage bone formation around the implant. In the current study, bone-forming peptide-2 was immobilized on PEEK surface using two different methods, using dopamine and a diglycidyl ether as conjugate compounds, respectively. Peptide quantification test revealed that the two strategies resulted in the most amount of peptides were attached with 0.5 mM concentration and no furth

We manufactured the nanoparticles light emitting diode (NPs-LED) for organic and inorganic semiconductors to achieve electroluminescence (EL). The nanoparticles of Europium oxide(Eu₂O₃) were incorporated into the thin film layers of the organic compounds, poly(3,4,- ethylene dioxythiophene)/polystyrene sulfonic acid (PEDOT:PSS), N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’- diamine (poly TPD) and polymethyl methacrylate (PMMA), by the spin coating and with the help of the phase segregation method. The EL of NPs-LED, was study for the different bias voltages (20, 25, 30) V at the room temperature, from depending on the CIE 1931 color spaces and it was generated the white light at 20V, t

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Objectives: The study aimed to determine the effect of chemotherapy on the life style of patients who
receive chemotherapy.
Methodology: A descriptive study was conducted in Specialty Surgery Teaching Hospital, Al-yamok
Teaching Hospital, and Radiation and Nuclear Medicine Hospital in Baghdad for the period from May
2007 to October 2008. A purposive "non-probability" sample of (loo) patients with bladder cancer
who receive chemotherapy where concerned in this study.
A questionnaire fom was constnicted for the purpose of the study and it was comprised of
two parts. The questiormaire consists of (125) items. They include (1) demographic information (2)
assessment of lifestyle dimension. The content validity of the q

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.