PROFILE DETAILS
ashiqulshuvo@cuet.ac.bd
Md. Ashiqul Islam Shuvo is working as a lecturer at the
Department of Petroleum and Mining Engineering (PME), CUET. He worked as a Research Assistant on a research project titled “Hybrid
connectionist model to predict rock permeability using core/log data”. In this research, he has developed data-driven machine-learning models to predict rock permeability from well-log data. The project was funded by the Directorate of
Research and Extension (DRE), CUET. He is also interested in the area of
Drilling fluid, Fluid flow through porous media, and Enhanced gas recovery
techniques. He strongly desires to explore and develop himself as a
qualified and skilled researcher in the petroleum and energy sector.
Drilling Fluid, Fluid flow through
porous media, Well Logging, Enhanced Gas Recovery, Machine Learning
B.Sc in Petroleum and Mining Engineering,
CUET
Serial No | Title | Authors | Informations | Year |
---|---|---|---|---|
1 | Applicability of sawdust as a green additive to improve the rheological and filtration properties of water-based drilling fluid: an experimental investigation | Shuvo, M.A.I., Sultan, M.Z.B. & Ferdous, A.R.R | Journal of Petroleum Exploration and Production Technology (https://doi.org/10.1007/s13202-023-01706-2) | 2023 |
2 | Performance Analysis of Enhanced Gas Recovery Approach | Shuvo, M.A.I., Sultan, M.Z.B. & Sabuz, S.H | Journal of Petroleum Science and Technology 12(2) (DOI:10.22078/JPST.2022.4775.1795) | 2022 |
3 | A data driven approach to assess the petrophysical parametric sensitivity for lithology identification based on ensemble learning | Md.A.I. Shuvo and S.M.H. Joy | Journal of Applied Geophysics (https://doi.org/10.1016/j.jappgeo.2024.105330) | 2024 |