Minou Rabiei

  • Assistant Professor, Petroleum Engineering

Contact Info

  • Email: minou.rabiei@UND.edu
  • Office: 701.777.5927
  • Dept: 701.777.2533

Office Address

Collaborative Energy Complex Room 113E
243 Centennial Dr Stop 8154
Grand Forks, ND 58202-8155


Introduction to Petroleum Engineering

Petroleum Geostatistics

Petroleum Economics and Law

Data Mining in Petroleum Engineering


Minou Rabiei is an Assistant Professor at University of North Dakota, Petroleum Engineering Department. Prior to joining UND, Minou served as an Associate Lecturer at Curtin University, Western Australia. Minou holds a PhD in Applied Statistics focused in Reservoir Engineering, MSc in Advanced Information Technology and BSc in Mining Engineering. Her research involves novel applications of data-driven analytics in petroleum engineering. 

Research Areas of Interest

  • Application of data mining, machine learning and big data analytics in petroleum engineering
  • Reservoir characterization using modern applied statistics 
  • Decision support systems for optimized reservoir management
  • Petroleum geostatistics

Funded Research Projects

  • A Case-Based Reasoning Approach for Harnessing Big Data in Unconventional Petroleum Projects, UND Early Career Research Award, Principal Investigator.  
  • Enhancing Regulatory Compliance by Capitalizing on Big Data Analytics and Artificial Intelligence: A Mutually Beneficial Regulators-Industry Collaboration, UND Energy & Environmental Sustainability White Papers, Principal Investigator.
  • An Integrated Software Package for Data Processing, Modelling and Simulation of Unconventional Reservoirs, Research North Dakota-Venture Grant, Principal Investigator.
  • A New Approach to Quantifying Adsorption/Diffusion Characteristics of Shale Formations through 3D Printing Technology, ACS (American Chemical Society), Co-Investigator.
  • Simulation of Hydraulic Fracturing and Re-fracturing Operations to Enhance Oil Production from Bakken and Three Forks Formations, Research North Dakota, Co-Investigator.
  • Tokhmechi, B., Rabiei, M., Rasouli, V., Azizi, H., (2018). A New 2D Block Ordering System for Wavelet-Based Multi Resolution Up-Scaling. Journal of Mining and Environment. Under Review
  • Hongsheng, W., Rabiei, M., Wang, S., Cui, G., (2018). Fracture Quantification Method with 3D X-ray Image - Entropy-assisted Indicator Kriging Method. SPE Western Regional Meeting to be held in California April, 2018. SPE-190045
  • Hongsheng, W., Rabiei, M., Wang, S., (2018). Microcrack Segmentation of Middle Bakken Shale Rock Sample with High-resolution SEM – The Application of Self-adaptive Image Enhancement Technique. 52nd US Rock Mechanics/Geomechanics Symposium, to be held in Washington, June 17-20, 2018.
  • Balaji, K., Rabiei, M., Temizel, C., et al. (2018) Status of Data-Driven Methods and their Applications in Oil and Gas Industry. SPE Europec featured at 80th EAGE Conference and Exhibition to be held in Denmark, June 11-14, 2018.
  • Tokhmechi, B., Rasouli, V., Azizi, H., Rabiei, M., (2018). A Hybrid Clustering-Classification Based Estimator for Characterization of Thin Bed Heterogeneous Reservoirs. Journal of Carbonates and Evaporites. https://doi.org/10.1007/s13146-018-0435-0
  • Jabbari, j., Afsari, K., Rabiei, M., Monk, A., (2017). Thermally-induced wettability alteration from hot-water imbibition in naturally fractured reservoirs—Part 1: Numerical model development & 1D models. FUEL. Vol. 208, 15 November 2017, pp. 682–691, https://doi.org/10.1016/j.fuel.2017.07.016
  • Jabbari, j., Afsari, K., Rabiei, M., Monk, A., (2017). Thermally-induced wettability alteration from hot-water imbibition in naturally fractured reservoirs—Part 2: 2D models, sensitivity study & heavy oil. FUEL. Vol. 208, 15 November 2017, pp. 692–700, https://doi.org/10.1016/j.fuel.2017.07.031
  • Hongsheng, W., Rabiei, M., Lei, G., Wang, S., (2017). A Novel Granular Profile Control Agent for Steam Flooding: Synthesis and Evaluation, Society of Petroleum Engineers. https://doi.org/10.2118/185650-MS
  • Liew, C. X., Gholami, R., Rabiei, M., Rasouli, V., Iglauer, S., Elochukwu, H., (2017). A New Mud Design to Improve Drilling Efficiency Across Fault Zones. Water Resources Research Journal, Under Review
  • Tokhmechi B., Nasiri J., Azizi H., Rabiei M., and Rasouli V., (2017); Wavelet Neural Network: A Hybrid Method in Modeling Heterogeneous Reservoirs, Submitted to the International Journal of Wavelets, Multiresolution and Information Processing
  • Gholami, R., Rabiei, M., Rasouli, V., Aadnoy, B., Fakhari, N. (2015). Application of quantitative risk assessment in wellbore stability analysis. Journal of Petroleum Science and Engineering, 135, 185-200. http://dx.doi.org/10.1016/j.petrol.2015.09.013
  • Jabbari, H., Ostadhassan, m., Rabiei, M. (2015). Study of Geomechanical Effects in CO2-EOR for Bakken Formation. SPE/CSUR Unconventional Resources Conference. Society of Petroleum Engineers (SPE). http://dx.doi.org/10.2118/175908-ms
  • Rabiei, M., Gupta, R. (2012). Intelligent knowledge management for identifying excess water production in oil wells. International Conference on Petroleum and Mineral Resources.
  • Rabiei, M., Gupta, R. (2011). Evolution from Water-Oil Ratio to Tree Based Classifier - A Novel Methodology for Effective Diagnosis of Water Production Mechanism in Oil Wells. Proceedings of the International Conference on SocProS, AISC 131, pp. 921–930.
  • Gupta, R., Rabiei, M. (2011). Wheedle out knowledge from data using ensemble classifiers - An effective diagnosis of water production mechanism in oil wells. Second International Conference on Computing (ICC).
  • Rabiei, M., Gupta, R., Cheong, Y.P. and Sanchez, G. (2010). Transforming data into knowledge using data mining techniques: application in excess water production problem diagnosis in oil wells. SPE Asia Pacific Oil and Gas Conference & Exhibition (APOGCE), Australia, SPE 133929.
  • Rabiei, M., Gupta, R., Cheong, Y.P. and Sanchez, G. (2010). A novel approach in extracting predictive information from water-oil ratio for enhanced water production mechanism diagnosis. APPEA Journal, pp. 567-579.
  • Rabiei, M., Gupta, R., Cheong, Y.P. and Sanchez, G. (2009), Excess water production diagnosis in oil fields using ensemble classifiers. International Conference on Computational Intelligence and Software Engineering, IEEE 10.1109/CISE.2009, pp. 1-4.

PhD, Curtin University, 2012