Mr Afshin Tatar
Higher Degree by Research Candidate
School of Chemical Engineering
College of Engineering and Information Technology
Afshin's research focuses on Machine Learning-Assisted Carbon Capture and Storage (CCS): Modelling and Optimisation. In this project, he addresses both the storage and capture components.In the storage phase, he investigates both geological (rock) and fluid (brine) properties. Deep learning methods are applied to identify and classify rock types suitable for CO₂ storage, while fluid modeling focuses on the behavior of brine when CO₂ is dissolved, assessing its characteristics through data-driven models.For the capture phase, he utilizes machine learning techniques to analyze and optimize the absorption capacities of various chemicals used in CO₂ capture. This includes studying both amine-based and ionic liquid absorbents, as well as investigating their efficiency in real-world applications.
Afshin's research focuses on Machine Learning-Assisted Carbon Capture and Storage (CCS): Modelling and Optimisation. In this project, he addresses both the storage and capture components.
In the storage phase, he investigates both geological (rock) and fluid (brine) properties. Deep learning methods are applied to identify and classify rock types suitable for CO₂ storage, while fluid modeling focuses on the behavior of brine when CO₂ is dissolved, assessing its characteristics through data-driven models.
For the capture phase, he utilizes machine learning techniques to analyze and optimize the absorption capacities of various chemicals used in CO₂ capture. This includes studying both amine-based and ionic liquid absorbents, as well as investigating their efficiency in real-world applications.
His research interests include:
- Carbon Capture and Storage (CCS)
- Artificial Intelligence (Machine Learning, Data Mining, Neural Networks, Deep Learning, Image Analysis, and Optimisation)
- Data-Driven and Physics-Informed Models
- Cheminformatics
- Ionic Liquids
| Date | Position | Institution name |
|---|---|---|
| 2023 - 2023 | Lecturer, Python Programming | Islamic Azad University of Bojnord, Faculty of Skill and Entrepreneurship · Contract |
| 2022 - 2023 | Research Assistant | Amol University of Special Modern Technologies, full time |
| 2021 - 2021 | Research Assistant | Nazarbayev University, full time |
| 2019 - 2021 | Chemical Engineer | SINOPEC, full time |
| 2016 - 2019 | Assistant Chemical Engineer | SINOPEC, full time |
| 2014 - 2016 | Production Operator | SINOPEC, full time |
| Date | Type | Title | Institution Name | Country | Amount |
|---|---|---|---|---|---|
| 2024 | Award | 2024 SPE-SA Scholarship | Society of Petroleum Engineering (SPE) | Australia | - |
| 2023 | Scholarship | University of Adelaide research scholarship for Ph.D. in Engineering | The University of Adelaide | Australia | - |
| 2017 | Recognition | Highly Cited Research in Journal of Natural Gas Science and Engineering | Journal of Natural Gas Science and Engineering, Elsevier | Netherlands | - |
| 2017 | Award | Most Cited Paper Award Certificate | journal of Greenhouse Gases: Science & Technology, Wiley. | United Kingdom | - |
| 2016 | Award | Most Outstanding Researcher Award | Young Researchers and Elite Club | Iran, Islamic Republic of | - |
| 2015 | Award | Most Cited Paper Award Certificate | journal of Petroleum (Online ISSN: 2405-5816), KeAi Publishing | China | - |
| 2007 | Scholarship | Full scholarship from National Iranian Oil Company (NIOC) for B.Sc. in Petroleum University of Technology | Petroleum University of Technology | Iran, Islamic Republic of | - |
| Language | Competency |
|---|---|
| English | Can read, write, speak, understand spoken and peer review |
| Persian | Can read, write, speak, understand spoken and peer review |
| Date | Institution name | Country | Title |
|---|---|---|---|
| 2023 | University of Adelaide | Australia | PhD |
| 2011 - 2014 | Sahand University of Technology | Iran | M.Sc. |
| 2007 - 2011 | Petroleum University of Technology | Iran | B.Sc. |
| Date | Title | Institution name | Country |
|---|---|---|---|
| 2024 | Convolutional Neural Networks | DeepLearning.AI, offered through Coursera | - |
| 2024 | Machine Learning Exploitability | Kaggle | - |
| 2024 | 16th IEAGHG International CCS Summer School | International Energy Agency Greenhouse Gas R&D Programme (IEAGHG) | Australia |
| 2023 | PYTHON203: Data Manipulation and Visualisation in Python | Intersect Research Faster | - |
| 2023 | Data Manipulation and Visualisation in Python | DeepLearning.AI, offered through Coursera | - |
| 2023 | Structuring Machine Learning Projects | DeepLearning.AI, offered through Coursera | - |
| 2023 | Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization | DeepLearning.AI, offered through Coursera | - |
| 2023 | Introduction to Deep Learning & Neural Networks with Keras | IBM, offered through Coursera | - |
| 2023 | Neural Networks and Deep Learning | DeepLearning.AI, offered through Coursera | - |
| Year | Citation |
|---|---|
| 2025 | Tatar, A., Haghighi, M., & Zeinijahromi, A. (2025). Experiments on image data augmentation techniques for geological rock type classification with convolutional neural networks. Journal of Rock Mechanics and Geotechnical Engineering, 17(1), 106-125. Scopus14 WoS12 |
| 2025 | Tatar, A., Zeinijahromi, A., & Haghighi, M. (2025). Explainable Artificial Intelligence in modelling hydrogen gas solubility in n-Alkanes. Separation and Purification Technology, 362, 131741. Scopus3 WoS4 |
| 2025 | Shokrollahi, A., Tatar, A., Atrbarmohammadi, S., & Zeinijahromi, A. (2025). Explainable Advanced Modelling of CO₂-Dissolved Brine Density: Applications for Geological CO₂ Storage in Aquifers. Inventions, 10(1), 15-1-15-24. Scopus1 WoS1 |
| 2024 | Esmaeili-Jaghdan, Z., Tatar, A., Shokrollahi, A., Bon, J., & Zeinijahromi, A. (2024). Machine learning modelling of dew point pressure in gas condensate reservoirs: application of decision tree-based models. Neural Computing and Applications, 36(4), 1973-1995. Scopus3 WoS3 |
| 2024 | Foroughizadeh, P., Shokrollahi, A., Tatar, A., & Zeinijahromi, A. (2024). Hydrogen solubility in different chemicals: A modelling approach and review of literature data. Engineering Applications of Artificial Intelligence, 136(Part B), 108978-1-108978-24. Scopus9 WoS9 |
| 2024 | Tatar, A., Shokrollahi, A., Zeinijahromi, A., & Haghighi, M. (2024). Deep Learning for Predicting Hydrogen Solubility in n-Alkanes: Enhancing Sustainable Energy Systems. Sustainability, 16(17), 7512-1-7512-24. |
| 2024 | Shokrollahi, A., Tatar, A., & Zeinijahromi, A. (2024). Advancing CO₂ Solubility Prediction in Brine Solutions with Explainable Artificial Intelligence for Sustainable Subsurface Storage. Sustainability, 16(17), 7273-1-7273-26. Scopus6 WoS6 |
| 2023 | Lashkenari, M. S., Bagheri, M., Tatar, A., Rezazadeh, H., & Inc, M. (2023). A further study in the prediction of viscosity for Iranian crude oil reservoirs by utilizing a robust radial basis function (RBF) neural network model. Neural Computing and Applications, 35(14), 10663-10676. Scopus12 WoS9 |
| 2023 | Ghasemi, M., Tatar, A., Shafiei, A., & Ivakhnenko, O. P. (2023). Prediction of asphaltene adsorption capacity of clay minerals using machine learning. Canadian Journal of Chemical Engineering, 101(5), 2579-2597. Scopus6 WoS5 |
| 2023 | Behvandi, R., Tatar, A., Shokrollahi, A., & Zeinijahromi, A. (2023). Evaluation of phase equilibrium conditions of clathrate hydrates in natural gas binary mixtures: Machine learning approach. Geoenergy Science and Engineering, 224, 211634-1-211634-26. Scopus4 WoS4 |
| 2023 | Rayhani, M., Tatar, A., Shokrollahi, A., & Zeinijahromi, A. (2023). Exploring the power of machine learning in analyzing the gas minimum miscibility pressure in hydrocarbons. Geoenergy Science and Engineering, 226, 211778-1-211778-20. Scopus14 WoS10 |
| 2023 | Tatar, A., & Shafiei, A. (2023). Connectionist Models for Asphaltene Precipitation Prediction by <i>n</i>-Alkane Titration─Pressure and Crude Oil Properties Considered. Industrial and Engineering Chemistry Research, 62(34), 13281-13302. Scopus1 WoS1 |
| 2022 | Shafiei, A., Tatar, A., Rayhani, M., Kairat, M., & Askarova, I. (2022). Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of low salinity water injection in carbonate oil reservoirs. Journal of Petroleum Science and Engineering, 219, 19 pages. Scopus45 WoS37 |
| 2022 | Mirzaie, M., Esfandyari, H., & Tatar, A. (2022). Dew point pressure of gas condensates, modeling and a comprehensive review on literature data. Journal of Petroleum Science and Engineering, 211, 17 pages. Scopus14 WoS12 |
| 2022 | Tatar, A., Esmaeili-Jaghdan, Z., Shokrollahi, A., & Zeinijahromi, A. (2022). Hydrogen solubility in n-alkanes: Data mining and modelling with machine learning approach. International Journal of Hydrogen Energy, 47(85), 35999-36021. Scopus25 WoS22 |
| 2022 | Yerkenov, T., Tazikeh, S., Tatar, A., & Shafiei, A. (2022). Asphaltene Precipitation Prediction during Bitumen Recovery: Experimental Approach versus Population Balance and Connectionist Models. ACS Omega, 7(37), 33123-33137. Scopus4 WoS4 Europe PMC2 |
| 2021 | Tatar, A., Askarova, I., Shafiei, A., & Rayhani, M. (2021). Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs. ACS Omega, 6(47), 32304-32326. Scopus18 WoS16 Europe PMC3 |
| 2021 | Sayahi, T., Tatar, A., Rostami, A., Anbaz, M. A., & Shahbazi, K. (2021). Determining solubility of CO2 in aqueous brine systems via hybrid smart strategies. International Journal of Computer Applications in Technology, 65(1), 1-13. Scopus17 WoS15 |
| 2021 | Ghorbani, H., Wood, D. A., Choubineh, A., Tatar, A., Abarghoyi, P. G., Madani, M., & Mohamadian, N. (2021). Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared (vol 6, pg 404, 2019). PETROLEUM, 7(2), 2 pages. |
| 2020 | Mirzaie, M., & Tatar, A. (2020). Modeling of interfacial tension in binary mixtures of CH4, CO2, and N2 - alkanes using gene expression programming and equation of state. Journal of Molecular Liquids, 320, 15 pages. Scopus34 WoS32 |
| 2020 | Ghorbani, H., Wood, D. A., Choubineh, A., Mohamadian, N., Tatar, A., Farhangian, H., & Nikooey, A. (2020). Performance comparison of bubble point pressure from oil PVT data: Several neurocomputing techniques compared. Experimental and Computational Multiphase Flow, 2(4), 225-246. Scopus55 WoS50 |
| 2020 | Tatar, A., Moghtadaei, G. M., Manafi, A., Cachadiña, I., & Mulero, Á. (2020). Determination of pure alcohols surface tension using Artificial Intelligence methods. Chemometrics and Intelligent Laboratory Systems, 201, 14 pages. Scopus11 WoS9 |
| 2020 | Ghorbani, H., Wood, D. A., Choubineh, A., Tatar, A., Abarghoyi, P. G., Madani, M., & Mohamadian, N. (2020). Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared. Petroleum, 6(4), 404-414. Scopus71 |
| 2019 | Barati-Harooni, A., Najafi-Marghmaleki, A., Hoseinpour, S. A., Tatar, A., Karkevandi-Talkhooncheh, A., Hemmati-Sarapardeh, A., & Mohammadi, A. H. (2019). Estimation of minimum miscibility pressure (MMP) in enhanced oil recovery (EOR) process by N2 flooding using different computational schemes. Fuel, 235, 1455-1474. Scopus44 WoS33 |
| 2019 | Rashid, S., Ghamartale, A., Abbasi, J., Darvish, H., & Tatar, A. (2019). Prediction of Critical Multiphase Flow Through Chokes by Using A Rigorous Artificial Neural Network Method. Flow Measurement and Instrumentation, 69, 9 pages. Scopus29 WoS26 |
| 2019 | Ameli, F., Hemmati-Sarapardeh, A., Tatar, A., Zanganeh, A., & Ayatollahi, S. (2019). Modeling interfacial tension of normal alkane-supercritical CO2 systems: Application to gas injection processes. Fuel, 253, 1436-1445. Scopus16 WoS14 |
| 2019 | Tatar, A., Barati, A., Najafi, A., & Mohammadi, A. H. (2019). Radial basis function (RBF) network for modeling gasoline properties. Petroleum Science and Technology, 37(11), 1306-1313. Scopus9 WoS7 |
| 2019 | Moghadasi, R., Rostami, A., Tatar, A., & Hemmati-Sarapardeh, A. (2019). An experimental study of Nanosilica application in reducing calcium sulfate scale at high temperatures during high and low salinity water injection. Journal of Petroleum Science and Engineering, 179, 7-18. Scopus24 WoS20 |
| 2019 | Rahmati, A. S., & Tatar, A. (2019). Application of Radial Basis Function (RBF) neural networks to estimate oil field drilling fluid density at elevated pressures and temperatures. Oil and Gas Science and Technology, 74, 6 pages. Scopus21 WoS17 |
| 2018 | Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Arabloo, M., Rafiee-Taghanaki, S., & Mohammadi, A. H. (2018). Reliable modeling of constant volume depletion (CVD) behaviors in gas condensate reservoirs. Fuel, 231, 146-156. Scopus35 WoS30 |
| 2018 | Hemmat Esfe, M., Tatar, A., Ahangar, M. R. H., & Rostamian, H. (2018). A comparison of performance of several artificial intelligence methods for predicting the dynamic viscosity of TiO2/SAE 50 nano-lubricant. Physica E Low Dimensional Systems and Nanostructures, 96, 85-93. Scopus85 WoS76 |
| 2018 | Hoseinpour, S. A., Barati-Harooni, A., Nadali, P., Mohebbi, A., Najafi-Marghmaleki, A., Tatar, A., & Bahadori, A. (2018). Accurate model based on artificial intelligence for prediction of carbon dioxide solubility in aqueous tetra-n-butylammonium bromide solutions. Journal of Chemometrics, 32(2), 20 pages. Scopus7 WoS7 |
| 2018 | Ahmadi, M. H., Tatar, A., Seifaddini, P., Ghazvini, M., Ghasempour, R., & Sheremet, M. A. (2018). Thermal conductivity and dynamic viscosity modeling of Fe2O3/water nanofluid by applying various connectionist approaches. Numerical Heat Transfer Part A Applications, 74(6), 1301-1322. Scopus48 WoS47 |
| 2018 | Kahani, M., Ahmadi, M. H., Tatar, A., & Sadeghzadeh, M. (2018). Development of multilayer perceptron artificial neural network (MLP-ANN) and least square support vector machine (LSSVM) models to predict Nusselt number and pressure drop of TiO2/water nanofluid flows through non-straight pathways. Numerical Heat Transfer Part A Applications, 74(4), 1190-1206. Scopus64 WoS64 |
| 2018 | Rostami, A., Kalantari-Meybodi, M., Karimi, M., Tatar, A., & Mohammadi, A. H. (2018). Efficient estimation of hydrolyzed polyacrylamide (HPAM) solution viscosity for enhanced oil recovery process by polymer flooding. Oil and Gas Science and Technology, 73, 17 pages. Scopus52 WoS46 |
| 2018 | Ahmadi, M. H., Tatar, A., Alhuyi Nazari, M., Ghasempour, R., Chamkha, A. J., & Yan, W. M. (2018). Applicability of connectionist methods to predict thermal resistance of pulsating heat pipes with ethanol by using neural networks. International Journal of Heat and Mass Transfer, 126, 1079-1086. Scopus48 WoS47 |
| 2017 | Zendehboudi, A., & Tatar, A. (2017). Oil flooded scroll compressors: Predicting the energy performance and evaluating the experimental data. Measurement Journal of the International Measurement Confederation, 112, 38-46. Scopus13 WoS12 |
| 2017 | Zendehboudi, A., Tatar, A., & Li, X. (2017). A comparative study and prediction of the liquid desiccant dehumidifiers using intelligent models. Renewable Energy, 114, 1023-1035. Scopus30 WoS28 |
| 2017 | Najafi-Marghmaleki, A., Barati-Harooni, A., Tatar, A., Mohebbi, A., & Mohammadi, A. H. (2017). On the prediction of Watson characterization factor of hydrocarbons. Journal of Molecular Liquids, 231, 419-429. Scopus26 WoS22 |
| 2017 | Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., & Bahadori, A. (2017). Accurate prediction of CO2 solubility in eutectic mixture of levulinic acid (or furfuryl alcohol) and choline chloride. International Journal of Greenhouse Gas Control, 58, 212-222. Scopus24 WoS23 |
| 2017 | Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., & Mohammadi, A. H. (2017). A GEP based model for prediction of densities of ionic liquids. Journal of Molecular Liquids, 227, 373-385. Scopus15 WoS15 |
| 2017 | Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., Mohebbi, A., Khaksar-Manshad, A., & Mohammadi, A. H. (2017). An accurate model for prediction of wax deposition in oil systems. Petroleum and Coal, 59(6), 797-807. |
| 2017 | Zendehboudi, A., & Tatar, A. (2017). Utilization of the RBF network to model the nucleate pool boiling heat transfer properties of refrigerant-oil mixtures with nanoparticles. Journal of Molecular Liquids, 247, 304-312. Scopus48 WoS44 |
| 2017 | Barati-Harooni, A., Nasery, S., Tatar, A., Najafi-Marghmaleki, A., Isafiade, A. J., & Bahadori, A. (2017). Prediction of H2S Solubility in Liquid Electrolytes by Multilayer Perceptron and Radial Basis Function Neural Networks. Chemical Engineering and Technology, 40(2), 367-375. Scopus10 WoS9 |
| 2017 | Dadkhah, M. R., Tatar, A., Mohebbi, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Ghiasi, M. M., . . . Pourfayaz, F. (2017). Prediction of solubility of solid compounds in supercritical CO2 using a connectionist smart technique. Journal of Supercritical Fluids, 120, 181-190. Scopus30 WoS27 |
| 2016 | Nasery, S., Barati-Harooni, A., Tatar, A., Najafi-Marghmaleki, A., & Mohammadi, A. H. (2016). Accurate prediction of solubility of hydrogen in heavy oil fractions. Journal of Molecular Liquids, 222, 933-943. Scopus41 WoS38 |
| 2016 | Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Mohebbi, A., Ghiasi, M. M., Mohammadi, A. H., & Hajinezhad, A. (2016). Comparison of two soft computing approaches for predicting CO2 solubility in aqueous solution of piperazine. International Journal of Greenhouse Gas Control, 53, 85-97. Scopus42 WoS39 |
| 2016 | Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., & Mohammadi, A. H. (2016). Experimental and modeling studies on adsorption of a nonionic surfactant on sandstone minerals in enhanced oil recovery process with surfactant flooding. Journal of Molecular Liquids, 220, 1022-1032. Scopus98 WoS87 |
| 2016 | Barati-Harooni, A., Soleymanzadeh, A., Tatar, A., Najafi-Marghmaleki, A., Samadi, S. J., Yari, A., . . . Mohammadi, A. H. (2016). Experimental and modeling studies on the effects of temperature, pressure and brine salinity on interfacial tension in live oil-brine systems. Journal of Molecular Liquids, 219, 985-993. Scopus60 WoS54 |
| 2016 | Tatar, A., Barati-Harooni, A., Partovi, M., Najafi-Marghmaleki, A., & Mohammadi, A. H. (2016). An accurate model for predictions of vaporization enthalpies of hydrocarbons and petroleum fractions. Journal of Molecular Liquids, 220, 192-199. Scopus19 WoS18 |
| 2016 | Sayahi, T., Tatar, A., & Bahrami, M. (2016). A RBF model for predicting the pool boiling behavior of nanofluids over a horizontal rod heater. International Journal of Thermal Sciences, 99, 180-194. Scopus62 WoS58 |
| 2016 | Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., Arabloo, M., Phung, L. T. K., Lee, M., & Bahadori, A. (2016). Prediction of frictional pressure loss for multiphase flow in inclined annuli during Underbalanced Drilling operations. Natural Gas Industry B, 3(4), 275-282. Scopus12 |
| 2016 | Tatar, A., Barati-Harooni, A., Moradi, S., Nasery, S., Najafi-Marghmaleki, A., Lee, M., . . . Bahadori, A. (2016). Prediction of heavy oil viscosity using a radial basis function neural network. Petroleum Science and Technology, 34(21), 1742-1748. Scopus11 WoS7 |
| 2016 | Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Mohebbi, A., Kalantari-Meybodi, M., & Mohammadi, A. H. (2016). On the prediction of interfacial tension (IFT) for water-hydrocarbon gas system. Journal of Molecular Liquids, 224, 976-990. Scopus16 WoS16 |
| 2016 | Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Ahmadi-Pour, M., Nadali, P., & Mohammadi, A. H. (2016). Prediction of moisture content of natural gases using a GA-RBF model. Journal of Molecular Liquids, 223, 994-999. Scopus5 WoS4 |
| 2016 | Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Choobineh, M. J., & Mohammadi, A. H. (2016). GA-RBF model for prediction of dew point pressure in gas condensate reservoirs. Journal of Molecular Liquids, 223, 979-986. Scopus27 WoS20 |
| 2016 | Tatar, A., Nasery, S., Bahadori, A., Bahadori, M., Najafi-Marghmaleki, A., & Barati-Harooni, A. (2016). Implementing radial basis function neural network for prediction of surfactant retention in petroleum production and processing industries. Petroleum Science and Technology, 34(11-12), 992-999. Scopus11 WoS11 |
| 2016 | Tatar, A., Nasery, S., Bahadori, M., Bahadori, A., Bahadori, M., Barati-Harooni, A., & Najafi-Marghmaleki, A. (2016). Prediction of water removal rate in a natural gas dehydration system using radial basis function neural network. Petroleum Science and Technology, 34(10), 951-960. Scopus15 WoS13 |
| 2016 | Tatar, A., Najafi-Marghmaleki, A., Barati-Harooni, A., Gholami, A., Ansari, H. R., Bahadori, M., . . . Bahadori, A. (2016). Implementing radial basis function neural networks for prediction of saturation pressure of crude oils. Petroleum Science and Technology, 34(5), 454-463. Scopus23 WoS21 |
| 2016 | Tatar, A., Naseri, S., Bahadori, M., Hezave, A. Z., Kashiwao, T., Bahadori, A., & Darvish, H. (2016). Prediction of carbon dioxide solubility in ionic liquids using MLP and radial basis function (RBF) neural networks. Journal of the Taiwan Institute of Chemical Engineers, 60, 151-164. Scopus74 WoS67 |
| 2016 | Tatar, A., Barati, A., Yarahmadi, A., Najafi, A., Lee, M., & Bahadori, A. (2016). Prediction of carbon dioxide solubility in aqueous mixture of methyldiethanolamine and N-methylpyrrolidone using intelligent models. International Journal of Greenhouse Gas Control, 47, 122-136. Scopus62 WoS57 |
| 2016 | Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Norouzi-Farimani, B., & Mohammadi, A. H. (2016). Predictive model based on ANFIS for estimation of thermal conductivity of carbon dioxide. Journal of Molecular Liquids, 224, 1266-1274. Scopus33 WoS29 |
| 2016 | Rezaei, A., Abdi-Khangah, M., Mohebbi, A., Tatar, A., & Mohammadi, A. H. (2016). Using surface modified clay nanoparticles to improve rheological behavior of Hydrolized Polyacrylamid (HPAM) solution for enhanced oil recovery with polymer flooding. Journal of Molecular Liquids, 222, 1148-1156. Scopus120 WoS113 |
| 2016 | Naseri, S., Tatar, A., & Shokrollahi, A. (2016). Development of an accurate method to prognosticate choke flow coefficients for natural gas flow through nozzle and orifice type chokes. Flow Measurement and Instrumentation, 48, 1-7. Scopus37 WoS25 |
| 2016 | Afshin, T., Ali, B. H., Hossein, M., Saeid, N., Meysam, B., Moonyong, L., . . . Adel, N. M. (2016). Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks. Natural Gas Industry B, 3(2), 173-180. Scopus8 |
| 2015 | Tatar, A., Shokrollahi, A., Lee, M., Kashiwao, T., & Bahadori, A. (2015). Prediction of supercritical CO2/brine relative permeability in sedimentary basins during carbon dioxide sequestration. Greenhouse Gases Science and Technology, 5(6), 756-771. Scopus13 WoS12 |
| 2015 | Darvish, H., Nouri-Taleghani, M., Shokrollahi, A., & Tatar, A. (2015). Geo-mechanical modeling and selection of suitable layer for hydraulic fracturing operation in an oil reservoir (south west of Iran). Journal of African Earth Sciences, 111, 409-420. Scopus28 WoS22 |
| 2015 | Shokrollahi, A., Tatar, A., & Safari, H. (2015). On accurate determination of PVT properties in crude oil systems: Committee machine intelligent system modeling approach. Journal of the Taiwan Institute of Chemical Engineers, 55, 17-26. Scopus65 WoS60 |
| 2015 | Tatar, A., Shokrollahi, A., Halali, M. A., Azari, V., & Safari, H. (2015). A Hybrid Intelligent Computational Scheme for Determination of Refractive Index of Crude Oil Using SARA Fraction Analysis. Canadian Journal of Chemical Engineering, 93(9), 1547-1555. Scopus28 WoS26 |
| 2015 | Nouri-Taleghani, M., Mahmoudifar, M., Shokrollahi, A., Tatar, A., & Karimi-Khaledi, M. (2015). Fracture density determination using a novel hybrid computational scheme: A case study on an Iranian Marun oil field reservoir. Journal of Geophysics and Engineering, 12(2), 188-198. Scopus34 WoS26 |
| 2015 | Tatar, A., Naseri, S., Sirach, N., Lee, M., & Bahadori, A. (2015). Prediction of reservoir brine properties using radial basis function (RBF) neural network. Petroleum, 1(4), 349-357. Scopus33 |
| 2015 | Naseri, S., Tatar, A., Bahadori, M., Rozyn, J., Kashiwao, T., & Bahadori, A. (2015). Application of Radial Basis Function Neural Network for Prediction of Titration-Based Asphaltene Precipitation. Petroleum Science and Technology, 33(23-24), 1875-1882. Scopus10 WoS9 |
| 2015 | Tatar, A., Naseri, S., Bahadori, M., Rozyn, J., Lee, M., Kashiwao, T., & Bahadori, A. (2015). Evaluation of Different Artificial Intelligent Models to Predict Reservoir Formation Water Density. Petroleum Science and Technology, 33(20), 1749-1756. Scopus8 WoS6 |
| 2014 | Tatar, A., Yassin, M. R., Rezaee, M., Aghajafari, A. H., & Shokrollahi, A. (2014). Applying a robust solution based on expert systems and GA evolutionary algorithm for prognosticating residual gas saturation in water drive gas reservoirs. Journal of Natural Gas Science and Engineering, 21, 79-94. Scopus47 WoS43 |
| 2014 | Hemmati-Sarapardeh, A., Shokrollahi, A., Tatar, A., Gharagheizi, F., Mohammadi, A. H., & Naseri, A. (2014). Reservoir oil viscosity determination using a rigorous approach. Fuel, 116, 39-48. Scopus128 WoS114 |
| 2013 | Kamari, A., Khaksar-Manshad, A., Gharagheizi, F., Mohammadi, A. H., & Ashoori, S. (2013). Robust Model for the Determination of Wax Deposition in Oil Systems. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 52(44), 15664-15672. WoS62 |
| 2013 | Tatar, A., Shokrollahi, A., Mesbah, M., Rashid, S., Arabloo, M., & Bahadori, A. (2013). Implementing Radial Basis Function Networks for modeling CO2-reservoir oil minimum miscibility pressure. Journal of Natural Gas Science and Engineering, 15, 82-92. Scopus152 WoS136 |
| - | A, T., & MA, H. (2016). On the Estimation of the Density of Brine with an Extensive Range of Different Salts Compositions and Concentrations. Journal of Thermodynamics & Catalysis, 7(2). |
| Year | Citation |
|---|---|
| 2018 | Tatar, A. (2018). Microbial Enhanced Oil Recovery: Microbiology and Fundamentals. In Fundamentals of Enhanced Oil and Gas Recovery from Conventional and Unconventional Reservoirs (pp. 291-508). Elsevier. DOI Scopus16 |
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Teaching Assistant, Data analytics in oil and gas industry, University of Adelaide, September 2025 – present.
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Teaching Assistant Tutor, Unconventional Resources & Recovery, University of Adelaide, March 2025 – July 2025.
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Teaching Assistant, Well Testing & Pressure Transient Analysis, University of Adelaide, March 2025 – June 2025.
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Teaching Assistant, Data analytics in oil and gas industry, University of Adelaide, July 2024-November 2024.
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Teaching Assistant Tutor, Formation Evaluation, Petrophysics & Rock Properties, University of Adelaide, July 2024-November 2024.
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Teaching Assistant, Unconventional Resources & Recovery, University of Adelaide, March 2024-May 2024.
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Teaching Assistant, Formation Evaluation, Petrophysics & Rock Properties, University of Adelaide, July 2023-December 2023.
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Lecturer, Python Programming, Faculty of Skill and Entrepreneurship of Islamic Azad University, Bojnord branch, 2023.
| Date | Role | Committee | Institution | Country |
|---|---|---|---|---|
| 2025 - ongoing | Representative | SPE South Australia Section | University of Adelaide | Australia |
| Date | Role | Membership | Country |
|---|---|---|---|
| 2025 - ongoing | Member | American Chemical Society (ACS) | United States |
| 2025 - ongoing | Member | European Association of Geoscientists and Engineers (EAGE) | Australia |
| 2024 - ongoing | Member | Petroleum Exploration Society of Australia (PESA) | Australia |
| 2023 - ongoing | Member | Society of Petroleum Engineering (SPE) | Australia |
| Date | Role | Editorial Board Name | Institution | Country |
|---|---|---|---|---|
| 2024 - ongoing | Editor | International Journal of Energy Research | Wiely | United States |
| 2024 - ongoing | Editor | Frontiers in Energy Research | Frontiers | Switzerland |
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