The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and fluid saturation in carbonate rocks. A strong linear correlation between P-wave velocity and S-wave velocity and between P-wave velocity and density rock was found. The resulting linear equations can be used to estimate P-wave velocity from the S-wave velocity in the case of both. The results of multiple regression analysis indicated that the density, porosity, water-saturated, and shear wave velocity (VS) are strongly related to Vp.
Community participation is one of the basic pillars of the sustainable development process. It provides opportunities for different groups of society to contribute to the management, preparation and implementation of development plans commensurate with their needs and aspirations. In this context, the study presents a study of the concept of community participation and its importance in sustainable development, In terms of its conditions, requirements and principles, as well as its image, as well as addressing the most important challenges and obstacles facing the participation of citizens in development projects. The research also provides an analysis of a number of international and Arab experiences adopted In its polici
... Show MoreThe relationship between costs of environment and costs of product life – cycle. Boubtlessly when the economical unit exercise their productive works, they lead to pollution in water, air and soil as well as all stages of product life- cycle from Rans Dstage, production stage, packaging stage and finally abandonment stage- Pollution causes environmental costs. Lgnoring or hiding environmental costs and no taking them in consideration with product cost lead to a wrong account of preduot cost.
Therefore, environmental costs should be included and matched for all stages with in product costs to know which activities, processes
... Show MoreThis study aims to highlight the role of strategic leadership in adopting the intelligent organization model. The study was conducted on 7 economic organizations in Algeria. The study population consisted of 354 leaders, of whom a random sample of 176 leaders (managers, department heads, division heads, engineers) was selected. The researcher used a questionnaire as the main tool of the study. Statistical analysis and hypothesis testing were conducted using SEM (Structural Equation Modeling) with the aid of SPSS.v26 and AMOS.v24 software. The study concluded with a set of results, most notably: there is a statistically significant direct positive effect between strategic leadership and building intelligent organizations at a significance le
... Show MoreOne of the therapeutic effects of nicotine is used as a protective against developing ulcerative colitis . ulcerative colitis is an inflammatory disease of the bowel affecting the superficial lining mucosa in the rectum and large intestine. In this study nicotine tablets were formulated as modified release tablets targeted to the colon. All formulas were studied for drug release , effect of diluent, retardant concentration, avicel grade,and compression force, the selected formula was then further studied for drug release in 3 different pH ( coated tablets) .The kinetic study revealed acceptable shelf life . Finally the selected formula was given to 6 patients in a pre-liminary clinical study which showed that nicotine c
... Show MoreSeveral correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability
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