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Showing 2 results for Saadat

Mahdi Saadat, Majid Nabi Bidhendi,
Volume 3, Issue 1 (Spring & Summer 2017)
Abstract

It is essential to dtermine petrophysical properties of reservoir rock in exploration and poroduction processes.There are several methods in which predicts such properties  and these methode are evolving every day. BISQ model is a novel model that it’s accuracy in determination of seismic properties of reservoir rock is confirmed by different researchers. This model predicts seismic properties such as p-wave and s-wave velocity and quality factor using some petrophysical and elastic properties of reservoir rock. Because of a high order of non-linearity in the BISQ model, inversion of associated petrophysical properties using conventional linear methods is not feasible. So in this paper we used a global optimization method to detemine petrophysical properties of reservoir rock. Inversion process includes two major step. First one is a physical or petrophysical model in which predicts data. And second one is a mathmatical method in which estimate model parameter through an objective function. Selection of mathmatical method depend on physical or petrophysical modle that pridicts data. In this case the petrophysical model is non-linear so we should select a robust mathmatical method that has capibility of determination global optimum point in a highly non-linear space. We use a hybrid genetic algorithm(HGA) in which employs some self adaptive concepts to enhance search ability , diversity , and quality of answers in comparsion with conventional GAs. Here we first introduce inverse methode then the methode is applied on a synthtic and a real data and the results are analyzed.


Mahsa Saadat Gohari, Dr Afshin Qishlaqi,
Volume 8, Issue 1 (Spring & Summer 2022)
Abstract

The aim of this study is to determine the ambient concentration, content of heavy metals and morphology and mineralogy of PM2.5 samples collected from air pollution monitoring station in Haft-Tir square (central Tehran). For this purpose, PM2.5 samples were collected by means of low-volume sampling device during five months (April-August 2019). Based on the obtained results, there is more loading of PM2.5 on June higher that 10 μgm−3 and showed high to very high pollution level. Variations in metal concentration in the sampling months were relatively similar, showing order of Zn>Ni>Pb>Cr>Cu>Cd. Comparing the mean concentration of metals with international permissible limits the concentration of Pb and Cr in PM2.5 samples was lower than that of recommended by the WHO while the average concentration of Cd and Ni was higher than those of USEPA recommended limit. Calculations of enrichment factor and results of principal component analysis revealed that Cr is of geogenic origin, Cd and Zn are derived from anthropic sources and Pb, Cu and Ni are probably of mixed sources. Based on scanning electron microscopy images, PM2.5 are observed as a shapeless or irregular, rod-shaped, irregular spherical, completely spherical, sheeted, as well as long chain aggregates or single crystals. According to the results of X-ray diffraction analysis, clay minerals, quartz and calcite were found as major minerals, gypsum and dolomite minerals were identified as minor minerals and wüstite and halite minerals were identified as rare mineral phases.


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