S
Siyamak Moradi
Researcher at Petroleum University of Technology
Publications - 41
Citations - 612
Siyamak Moradi is an academic researcher from Petroleum University of Technology. The author has contributed to research in topics: Enhanced oil recovery & Asphaltene. The author has an hindex of 11, co-authored 39 publications receiving 394 citations. Previous affiliations of Siyamak Moradi include Islamic Azad University & Sharif University of Technology.
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Combination of a new natural surfactant and smart water injection for enhanced oil recovery in carbonate rock: Synergic impacts of active ions and natural surfactant concentration
TL;DR: In this paper, a new plant-base natural surfactant, named Tribulus Terrestris is introduced and combined with smart water samples (i.e., synthetic seawater with different concentrations of active Ca2+, Mg2+ and SO42− ions) to determine their individual and integrated effects on reduction in interfacial tension, wettability alteration and oil recovery in carbonate rock samples.
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Impact of a novel biosynthesized nanocomposite (SiO2@Montmorilant@Xanthan) on wettability shift and interfacial tension: Applications for enhanced oil recovery
Mohammad Javad Nazarahari,Abbas Khaksar Manshad,Muhammad Ali,Jagar A. Ali,Ali Shafiei,S. Mohammad Sajadi,Siyamak Moradi,Stefan Iglauer,Alireza Keshavarz +8 more
TL;DR: In this article, a novel nanocomposite (SiO2@Montmorilant@Xanthan) was used with various concentrations (100, 250, 500, 1000, 1500, and 2000) as dispersing agents in porous media.
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Investigation of asphaltene precipitation in miscible gas injection processes: experimental study and modeling
TL;DR: In this article, a scaling equation is presented to predict asphaltene precipitation under HPHT gas injection, and the scaling approach provides universal parameters for different fluid samples over a wide range of pressure and temperature that makes it novel for evaluation of future gas injection projects when simple PVT data are available.
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Estimation of asphaltene precipitation from titration data: a hybrid support vector regression with harmony search
TL;DR: This study concludes that optimization of SVR with HS produces a smart hybrid model, which is an appropriate solution for modeling of the asphaltene precipitation.
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Smart- and nano-hybrid chemical EOR flooding using Fe3O4/eggshell nanocomposites
Ali Omidi,Abbas Khaksar Manshad,Siyamak Moradi,Jagar A. Ali,S. Mohammad Sajadi,S. Mohammad Sajadi,Alireza Keshavarz +6 more
TL;DR: In this paper, the performance of CTAB (cetyltrimethylammonium bromide) and TR-880 surfactants was improved using a synthetic Fe3O4/eggshell nanocomposite (NC).