Mohammadsadegh Momeni

 

Mr. Mohammadsadegh Momeni

PhD candidate, , MSc, BSc
Associate Lecturer 
Petroleum Engineering

Contact Details 
Telephone: +60 85 443939 Extn: 2432
Fax: +60 85 443837 
Location: Skylark 3.L2.341
Email: ms.momeni@curtin.edu.my

Background

Mohammadsadegh Momeni is an associate lecturer at the Department of Petroleum Engineering, Curtin University, Malaysia. He has extensive knowledge on the subject of drilling engineering having worked as a drilling engineer and as a research assistant in University Technology PETRONAS involved in several research and consulting projects in the area of drilling. His teaching experience has also extended to Islamic Azad university for two years as a lecturer.

Academic History

  • Doctor of Philosophy (PhD) in Petroleum Engineering, Universiti Teknologi PETRONAS (on going) 
  • Master of Engineering  (Petroleum Engineering), Islamic Azad University of Iran
  • Bachelor of Engineering  (Petroleum Engineering), Islamic Azad University of Iran

Research Interest

  • Drill bit selection
  • Rate of penetration prediction and optimization
  • Image processing techniques
  • Image feature extraction
  • Artificial intelligence

Journal Publications

[1]        M. Momeni, S. Ridha, S. Hosseini, X. Liu, A. Atashnezhad, and S. Ghaheri, “Optimum drill bit selection by using bit images and mathematical investigation,” International Journal of Engineering-Transactions B: Applications, vol. 30, p. 1807, 2017.

[2]        M. Momeni, S. J. Hosseini, S. Ridha, M. B. Laruccia, and X. Liu, “An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration,” Journal of Engineering Science and Technology, vol. 13, pp. 361-372, 2018.

[3]        M. Momeni, S. Ridha, S. Hosseini, B. Meyghani, and S. Emamian, “Bit selection using field drilling data and mathematical investigation,” in IOP Conference Series: Materials Science and Engineering, 2018, p. 012008.

[4]        P. Assefi, M. Ghaedi, A. Ansari, M. Habibi, and M. Momeni, “Artificial neural network optimization for removal of hazardous dye Eosin Y from aqueous solution using Co2O3-NP-AC: Isotherm and kinetics study,” Journal of Industrial and Engineering Chemistry, vol. 20, pp. 2905-2913, 2014.

[5]        M. Ghaedi, A. Daneshfar, A. Ahmadi, and M. Momeni, “Artificial neural network-genetic algorithm based optimization for the adsorption of phenol red (PR) onto gold and titanium dioxide nanoparticles loaded on activated carbon,” Journal of Industrial and Engineering Chemistry, vol. 21, pp. 587-598, 2015.

[6]        M. Gheshmi, S. Fatahiyan, N. Khanesary, C. Sia, and M. Momeni, “Investigating the effects of rock porosity and permeability on the performance of nitrogen injection into a southern Iranian oil reservoirs through neural network,” in IOP Conference Series: Materials Science and Engineering, 2018, p. 012021.

[7]        M. Moayedfar, H. Hanaei, A. M. Rani, M. A. B. Musa, and M. S. Momeni, “Early Shear Failure Prediction in Incremental Sheet Forming Process Using FEM and ANN,” in IOP Conference Series: Materials Science and Engineering, 2018, p. 012031.

[8]        S. Ghaheri, M. Suhaili, N. Sapari, and M. Momeni, “Sedimentary architecture and depositional environment of Kudat Formation, Sabah, Malaysia,” in IOP Conference Series: Materials Science and Engineering, 2017, p. 012025.

Share this