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 resistivity for the formation (Rw = 0.021), the average resistivity of the mud filtration (Rmf = 0.57), and the Archie parameters determined by the picket plot method, where m value equal to 1.94, n value equal to 2 and a value equal to 1. Porosity values and water saturation Sw were calculated along with the depth of the composition using IP V3.5 software. The interpretation of the computer process (CPI) showed that the better porous zone holds the highest amount of hydrocarbons in the second zone. From the flow zone indicator method, there are four rock types in the studied reservoir.
The pioneer contributions included a sign for Iraqi Bryoflora were those of (Juratzka &
Milde) and Schiffner published at the end of the 19th century i.e. (1870 & 1897) respectively.
However, throughout the whole next century, the 20th, only few papers, by different authors,
have been published separately. They are Schiffner (1913); Handel-Mazzetti (1914); Froelich
(1959); Vondracek (1962 & 1965); Agnew &Townsend (1970); Agnew ( 1973 ) ; Agnew&
Vondracek (1975); Long (1979); Al-Ni’ma (1994). The most comprehensive work among
them was the “Moss Flora of Iraq” by Agnew & Vondracek (1975). It included a description
of 54 genera and 145 species with an identification key in addition to notes
Solutions of dyes Rhodamine 6G (Rh6G) and Coumarin480(C480) were prepared at five concentrations (1x10-3, 5x10-4, 1x10-4, 5x10-5 and1x10-5) mol/l, the mixing was stirred to obtain on a homogenous solution, the(poly methyl-methacrylate) (PMMA) was solved by chloroform solvent with certain ratio, afterward (PMMA+Rh6G) and (PMMA+C480) thin films were prepared by casting method on glass block which has substrate with dimensions (7.5 x2.5)cm2, the prepared samples were left in dark place at room temperature for 24 hours to obtain uniform and homogenous thin films. UV-VIS absorption spectra, transmission spectra and fluorescence spectra were done to measure linear refractive index and linear absorption coefficient. The nonlinear optical proper
... Show MoreThe present work studies the mechanical properties of SiO2 μPs, and NPs in St/PVA blends. The samples were prepared by casting method as PVA, St/PVA blends at different concentrations (30, 40, 50, and 60 %). DSC and TGA tests were carried out to the samples evolved. The result showed a single glass transition temperature (Tg) for all St /PVA blends that was attributed to the good miscibility of the blends involved. It was found that (Tg) decrease with starch ratio increase. It was seen that (PVA) of (Tg=105 oC); The glass transition temperature which was decrease with starch ratio that was attributed to glass transition relaxation process due to micro-Brownian motion of the main chain back bond. The endothermic peak at 200 oC was attrib
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreIn this paper, a construction microwave induced plasma jet(MIPJ) system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate using flow meter regulator. The influence of the MIPJ parameters such as applied voltage and argon gas flow rate on macroscopic microwave plasma parameters were studied. The macroscopic parameters results show increasing of microwave plasma jet length with increasing of applied voltage, argon gas flow rate where the plasma jet length exceed 12 cm as maximum value. While the increasing of argon gas flow rate will cause increasing into the ar
... Show MoreTransparent thin films of CdO:Ce has been deposited on to glass and silicon substrates by spray pyrolysis technique for various concentrations of cerium (2, 4, and 6 Vol.%). CdO:Ce films were characterized using different techniques such as X-ray diffraction (XRD), atomic force microscopy(AFM) and optical properties. XRD analysis show that CdO films exhibit cubic crystal structure with (1 1 1) preferred orientation and the intensity of the peak increases with increasing's of Ce contain when deposited films on glass substrate, while for silicon substrate, the intensity of peaks decreases, the results reveal that the grain size of the prepared thin film is approximately (73.75-109.88) nm various with increased of cerium content. With a sur
... Show MoreHepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth. In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre
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