In petroleum reservoir engineering, history matching refers to the calibration process in which a reservoir simulation model is validated through matching simulation outputs with the measurement of observed data. A traditional history matching technique is performed manually by engineering in which the most uncertain observed parameters are changed until a satisfactory match is obtained between the generated model and historical information. This study focuses on step by step and trial and error history matching of the Mishrif reservoir to constrain the appropriate simulated model. Up to 1 January 2021, Buzurgan Oilfield, which has eighty-five producers and sixteen injectors and has been under production for 45 years when it started in 1976. Reservoir exhibits heterogeneity in porosity and permeability throughout the field, therefore it’s a big challenge to control all reservoir properties during matching process. The historical matching process includes matching field and wells oil and water production rates, water injection rates, water cut, and reservoir static pressure. Finally, the results show that the good matching between simulated model and observed data; oil and water production rates, water injection rates, water cut, and static reservoir pressure which allow for implementing perfect future production forecasting strategies.
Waste is one of the most important problems affecting the city’s environment and its urban landscape, which results from the activities and activities of man and the natural environment. Its sources have varied between residential, commercial, industrial, medical and hazardous, and its spread in cities, on roads and on abandoned open lands, has led to significant negative effects and risks to human health and the environment.
Therefore, there were serious attempts to deal with waste and follow sequential steps that formed a waste management system such as (collection, sorting, transport, then treatment and disposal). Preventing and reducing waste, then recycling and recovering by composting or burning, and ending with bu
... Show MoreA study of the Torymid collection of Iraq. resulted in undescribed species of the genus
Liodontonierus Gah. L. longicorpus sp. n. with 2 figures.
For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.
The present work introduces, external morphological study of the leafhopper Neoalitarus
fenestratus Herrich-Schäeffer (Deltocephalinae:Oposiini), particularly the male genitalia
which were dissected and illustrated.
IA Ali, FK Emran, DF Salloom, Annals of the Romanian Society for Cell Biology, 2021
Periodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.
The
In this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor 2201.34 (wt)-0.76636. min-1 and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which
... Show More