Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Shokor A. Rahaman"'
Autor:
Imtiaz Ahmed Shozib, Azlan Ahmad, Md Shokor A. Rahaman, Ahmad majdi Abdul-Rani, Mohammad Azad Alam, Mohammadali Beheshti, Iqbal Taufiqurrahman
Publikováno v:
Journal of Materials Research and Technology, Vol 12, Iss , Pp 1010-1025 (2021)
In this study, experimental investigations on the microhardness of the synthesized electroless Ni–P–TiO2 coated aluminium composite was carried out. The coated samples were characterized by scanning electron microscopy (SEM) for surface morpholog
Externí odkaz:
https://doaj.org/article/165d9a981ad741bbbd2bb88aa4df327b
Autor:
Abdus Samad Azad, Md Shokor A. Rahaman, Junzo Watada, Pandian Vasant, Jose Antonio Gamez Vintaned
Publikováno v:
Energy Reports, Vol 6, Iss , Pp 2230-2248 (2020)
Whatever the exact figures, world energy consumption, particularly electricity consumption, can increase significantly during couple of decades. It is not possible solely due to demographic pressure, but also due to expansion of living standards with
Externí odkaz:
https://doaj.org/article/d1038d4e1727436eaf5530965d26fb7d
Autor:
Jahedul Islam, Md Shokor A. Rahaman, Pandian M. Vasant, Berihun Mamo Negash, Ahshanul Hoqe, Hitmi Khalifa Alhitmi, Junzo Watada
Publikováno v:
Energies, Vol 14, Iss 4, p 857 (2021)
Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications ba
Externí odkaz:
https://doaj.org/article/3e128f2b10f64f9aa0d57a744e366f73
Comparison of Machine Learning Classifiers for Accurate Prediction of Real-Time Stuck Pipe Incidents
Autor:
Javed Akbar Khan, Muhammad Irfan, Sonny Irawan, Fong Kam Yao, Md Shokor Abdul Rahaman, Ahmad Radzi Shahari, Adam Glowacz, Nazia Zeb
Publikováno v:
Energies, Vol 13, Iss 14, p 3683 (2020)
Stuck pipe incidents are one of the contributors to non-productive time (NPT), where they can result in a higher well cost. This research investigates the feasibility of applying machine learning to predict events of stuck pipes during drilling opera
Externí odkaz:
https://doaj.org/article/b4c3cb94b549474cbc44815458cbdc09
Autor:
Iqbal Taufiqurrahman, Shokor A. Rahaman, Azlan Ahmad, Mohammadali Beheshti, Ahmad Majdi Abdul-Rani, Mohammad Azad Alam, Imtiaz Ahmed Shozib
Publikováno v:
Journal of Materials Research and Technology, Vol 12, Iss, Pp 1010-1025 (2021)
In this study, experimental investigations on the microhardness of the synthesized electroless Ni-P-TiO2 coated aluminium composite was carried out. The coated samples were characterized by scanning electron microscopy (SEM) for surface morphology an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebf31df2c2ec8d6fccbe365d09c9b535
http://www.sciencedirect.com/science/article/pii/S2238785421002908
http://www.sciencedirect.com/science/article/pii/S2238785421002908
Autor:
Berihun Mamo Negash, Ahshanul Hoqe, Jahedul Islam, Pandian Vasant, Hitmi Khalifa Alhitmi, Junzo Watada, Shokor A. Rahaman
Publikováno v:
Energies
Volume 14
Issue 4
Energies, Vol 14, Iss 857, p 857 (2021)
Volume 14
Issue 4
Energies, Vol 14, Iss 857, p 857 (2021)
Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a806e87e201eb0e102fe95407f8a259
Comparison of Machine Learning Classifiers for Accurate Prediction of Real-Time Stuck Pipe Incidents
Autor:
Adam Glowacz, Nazia Zeb, Muhammad Irfan, Fong Kam Yao, Javed Akbar Khan, Sonny Irawan, Ahmad Radzi Shahari, Shokor A. Rahaman
Publikováno v:
Energies; Volume 13; Issue 14; Pages: 3683
Energies, Vol 13, Iss 3683, p 3683 (2020)
Energies, Vol 13, Iss 3683, p 3683 (2020)
Stuck pipe incidents are one of the contributors to non-productive time (NPT), where they can result in a higher well cost. This research investigates the feasibility of applying machine learning to predict events of stuck pipes during drilling opera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d6d076308ffb2780ff5e88587b6a3cc
Autor:
Pandian Vasant, Md. Shokor A. Rahaman
Total organic carbon (TOC) is the most significant factor for shale oil and gas exploration and development which can be used to evaluate the hydrocarbon generation potential of source rock. However, estimating TOC is a challenge for the geological e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7aadb889df2c433d260d09447d7b6946
https://doi.org/10.4018/978-1-7998-1192-3.ch004
https://doi.org/10.4018/978-1-7998-1192-3.ch004
Publikováno v:
Journal of Physics: Conference Series. 1529:042084
For shale oil and gas exploration total organic carbon (TOC) is the significant factors where TOC estimation considered as a challenges for geological engineers because direct laboratory coring analysis is costly and time consuming. Passey method and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48463defba0ab15b67be91e339826704
https://doi.org/10.1088/1742-6596/1529/4/042084
https://doi.org/10.1088/1742-6596/1529/4/042084