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.
This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).
This research presents a statistical study of radiation generated from communication towers in the Nineveh Plain region Baghdeda. The intensity of radiation energy was measured at 10 meters away from the communication tower in different locations, using a (1PC XH-901 Dosimeter/ Personal Dose Alarm / Radiation Detector, dosage rate: 0.01 μSv/h to 150μSv/h) to measure the amount of radiation at various times. Energy densities were measured and compared with standard limits provided by other authorities, such as the International Committee for Radiation Protection. Results were analyzed using SPSS version 26 to implement the data. The results show that the means of the radiation levels measured at all the zones do not statistically differ
... Show MoreThe current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition
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This research aims to know the effect of job burnout in the worker’s performance. The researcher presented a theoretical basis for job burnout and the worker's performance. In order to achieve the objectives of the research, a hypothesis was drawn up that determines the nature of the relationship between the independent variable of job burnout and its dimensions (reduced personal accomplishment, depersonalization, Emotional Exhaustion) and variable dependent performance of workers dimensions (productivity, job satisfaction, organizational commitment, creativity), And to represent the volume of this community according to (de Morgan, D. Morgan) glo
... Show MorePrecise 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
... Show MoreOil pollution of the soil due to a leakage in oil tubes, transportation of products, or during oil excavations can change the soil physical and mechanical, chemical, and biological properties. Consequently, the soil may or may not be eligible for engineering construction projects and it may need a significant treatment. Therefore, it is required to have a better understanding of the general behavior and the corresponding geotechnical properties upon pollution particularly for those areas associated with oil explorations and industry like Thi-Qar Governorate. Fine and coarse soils from two sites at the University of Thi-Qar are artificially contaminated with oil products ranging from 0% to 10% of their dry weight. Testing programs have been
... Show MoreThe study includes building a 3-D geological model, which involves get the Petrophysical properties as (porosity, permeability and water saturation). Effective Porosity, water saturation results from log interpretation process and permeability from special correlation using core data and log data. Clay volume can be calculated by six ways using IP software v3.5 the best way was by using gamma Ray. Also, Water Resistivity, flushed zone saturation and bulk volume analysis determined through geological study. Lithology determined in several ways using M-N matrix Identification, Density-Neutron and Sonic-Neutron cross plots. The cut off values are determined by Using EHC (Equivalent Hydra