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Jassem Abbasi
Jassem Abbasi
PhD Research Fellow, University of Stavanger (UiS)
Bestätigte E-Mail-Adresse bei uis.no - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Modified shape factor incorporating gravity effects for scaling countercurrent imbibition
J Abbasi, M Riazi, M Ghaedi, A Mirzaei-Paiaman
Journal of Petroleum Science and Engineering 150, 108-114, 2017
462017
A new numerical approach for investigation of the effects of dynamic capillary pressure in imbibition process
J Abbasi, M Ghaedi, M Riazi
Journal of Petroleum Science and Engineering 162, 44-54, 2018
422018
Prediction of critical multiphase flow through chokes by using a rigorous artificial neural network method
S Rashid, A Ghamartale, J Abbasi, H Darvish, A Tatar
Flow Measurement and Instrumentation 69, 101579, 2019
32*2019
Physical activation functions (PAFs): An approach for more efficient induction of physics into physics-informed neural networks (PINNs)
J Abbasi, PØ Andersen
Neurocomputing 608, 128352, 2024
222024
Discussion on similarity of recovery curves in scaling of imbibition process in fractured porous media
J Abbasi, M Ghaedi, M Riazi
Journal of Natural Gas Science and Engineering 36, 617-629, 2016
172016
Impact of solutal Marangoni convection on oil recovery during chemical flooding
S Palizdan, J Abbasi, M Riazi, MR Malayeri
Petroleum Science, 1-20, 2020
132020
Theoretical comparison of two setups for capillary pressure measurement by centrifuge
J Abbasi, PØ Andersen
Heliyon 8 (9), 1-18, 2022
102022
Improvements in scaling of counter-current imbibition recovery curves using a shape factor including permeability anisotropy
J Abbasi, S Sarafrazi, M Riazi, M Ghaedi
Journal of Geophysics and Engineering 15 (1), 135, 2018
82018
A simulation investigation of performance of polymer injection in hydraulically fractured heterogeneous reservoirs
J Abbasi, B Raji, M Riazi, A Kalantariasl
Journal of Petroleum Exploration and Production Technology 7, 813-820, 2017
82017
Application of Physics-Informed Neural Networks for Estimation of Saturation Functions from Countercurrent Spontaneous Imbibition Tests
J Abbasi, P Østebø Andersen
SPE Journal, 1-20, 2024
72024
Simulation and Prediction of Countercurrent Spontaneous Imbibition at Early and Late Time Using Physics-Informed Neural Networks
J Abbasi, PØ Andersen
Energy & Fuels 37 (18), 13721–13733, 2023
72023
Prediction of permeability of tight sandstones from mercury injection capillary pressure tests assisted by a machine-learning approach
J Abbasi, J Zhao, S Ahmed, L Jiao, PØ Andersen, J Cai
Yandi Scientific Press, 2022
32022
A multiscale study on the effects of dynamic capillary pressure in two-phase flow in porous media
J Abbasi, M Ghaedi, M Riazi
Korean Journal of Chemical Engineering 37, 2124-2135, 2020
32020
History-Matching of imbibition flow in fractured porous media Using Physics-Informed Neural Networks (PINNs)
J Abbasi, B Moseley, T Kurotori, AD Jagtap, AR Kovscek, A Hiorth, ...
Computer Methods in Applied Mechanics and Engineering 437, 117784, 2025
1*2025
Improved Initialization of Non-Linear Solvers in Numerical Simulation of Flow in Porous Media With a Deep Learning Approach
J Abbasi, PØ Andersen
SPE Europec featured at EAGE Conference and Exhibition?, D031S008R005, 2022
12022
Modelling The Spread of COVID-19 Using The Fundamental Principles of Fluid Dynamics
HS Rabbani, K Osei-Bonsu, J Abbasi, PK Osei-Bonsu, TD Seers
medRxiv, 2020.06. 24.20139071, 2020
12020
A Discussion about the effect of considering the dynamic capillary forces on dissimilarity of imbibition recovery curves
J Abbasi, M Ghaedi, M Riazi
Saint Petersburg 2018 2018 (1), 1-5, 2018
12018
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