The petrophysical analysis is significant to determine the parameters controlling the production wells and the reservoir quality. In this study, Using Interactive petrophysics software to analyze the petrophysical parameters of five wells penetrated the Zubair reservoir in the Abu-Amood field to evaluate a reservoir and search for hydrocarbon zones. The available logs data such as density, sonic, gamma ray, SP, neutron, and resistivity logs for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5 were used to determine the reservoir properties in Zubair reservoir. The density-neutron and neutron-sonic cross plots, which appear as lines with porosity scale ticks, are used to distinguish between the three main lithologies of sandstone, limesto

Drag has long been identified as the main reason for the loss of energy in fluid transmission like pipelines and other similar transportation channels. The main contributor to this drag is the viscosity as well as friction against the pipe walls, which will results in more pumping power consumption.

   The aim in this study was first to understand the role of additives in the viscosity reduction and secondly to evaluate the drag reduction efficiency when blending with different solvents.

   This research investigated flow increase (%FI) in heavy oil at different flow rates (2 to 10 m3/hr) in two pipes (0.0381 m & 0.0508 m) ID By using different additives (toluene and naphtha) with different concent

This research was aimed to evaluate activity of Rosemary volatile oil and Nisin A in vivo and on B. cereus isolated from some canned meat products in vitro. The results showed that the activity of Rosemary volatile oil (2000 µg/ml) and Nisin A (350 µg\ml) attained to 27 and 19 mm inhibitory zone diameter respectively in well diffusion method. The viable plate count from samples of canned meat treated with effective concentration of Rosemary volatile oil and Nisin A were examined. The samples with Rosemary volatile oil was not showed any CFU/g after 9 days of preservation while sample with Nisin A and control observed 49 and 45 CFU/g respectively. In vivo experiment on mice, two weeks after oral dose of Rosemary volatile oil (2000

Abstract

Objective: the idea of this study to improve transdermal permeability of Methotrexate using eucalyptus oil, olive oil and peppermint oil as enhancers.
Method: eucalyptus oil (2% and 4%), peppermint oil (2% and 4%) and olive oil (2% and 4%) all used as natural enhancers to develop transdermal permeability of Methotrexate via gel formulation. The gel was subjected to many physiochemical properties tests. In-vitro release and permeability studies for the drug were done by Franz cell diffusion across synthetic membrane, kinetic model was studied via korsmeyer- peppas equation.
Result: the results demonstrate that safe, nonirritant or cause necrosis to rats' skin and stable till 60 days gel was successfully formulated.<

The ability of insurance companies to achieve goals depends on their ability to meet customers' requirements, and this requires them to identify target markets and respond to needs and wishes of the markets, the skill is to convince the company to operate what is in the interest of the customer if he is convinced the customer service provided to him, he would repeat to deal with, and where the cost of maintaining existing customers is less than the cost of attracting new customers, the insurance companies that is working hard to maintain their customers, the more customer satisfaction with the services provided has increased loyalty and weakened the ability of competitors lured.

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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

   History matching is a significant stage in reservoir modeling for evaluating past reservoir performance and predicting future behavior. This paper is primarily focused on the calibration of the dynamic reservoir model for the Meshrif formation, which is the main reservoir in the Garraf oilfield. A full-field reservoir model with 110 producing wells is constructed using a comprehensive dataset that includes geological, pressure-volume-temperature (PVT), and rock property information. The resulting 3D geologic model provides detailed information on water saturation, permeability, porosity, and net thickness to gross thickness for each grid cell, and forms the basis for constructing the dynamic reservoir model. The dynamic reservoir mo