Dr. Mohatsim mahetaji | Decision-making and Problem-solving | Best Researcher Award Published on 13/10/202513/10/2025 by Leadership and Management D. Mohatsim mahetaji | Decision-making and Problem-solving | Best Researcher Award Parul University | India Dr. Mohatsim A. Mahetaji is an emerging scholar in petroleum engineering and geomechanics who completed his PhD (2024) at the Department of Petroleum Engineering, School of Energy Technology, Pandit Deendayal Energy University, following an MTech in Petroleum and a BE in Mechanical Engineering. He has held roles as Teaching Assistant, Research & Teaching Assistant (2019-2023) and Research Associate (Oct–Dec 2023) before becoming an Assistant Professor in January 2025 at Parul Institute of Technology. His research spans computational analysis, artificial intelligence / machine learning, data science in drilling and well-bore stability, geomechanics and carbon capture & storage, with several peer-reviewed publications in high-impact journals. He has developed new 3D failure criteria for in-situ rock, and applied machine learning in pore-pressure prediction and wellbore mud weight optimisation. His work reflects a strong modelling and simulation orientation aimed at cost-effective, sustainable hydrocarbon exploration and production. While detailed citation counts and h-index are not publicly available, his trajectory and output indicate rising academic impact. Dr. Mahetaji continues to innovate at the intersection of AI/ML and geosciences, contributing to both theory (failure criteria) and applied drilling design, positioning him as a promising contributor in energy technology and subsurface engineering. Profiles: Google Scholar | ORCID Featured Publications Mahetaji, M., & Brahma, J. (2024). A critical review of rock failure criteria: A scope of machine learning approach. Engineering Failure Analysis, 159, 107998. Mahetaji, M., Brahma, J., & Sircar, A. (2020). Pre-drill pore pressure prediction and safe well design on the top of Tulamura anticline, Tripura, India: A comparative study. Journal of Petroleum Exploration and Production Technology, 10(3), 1021–1049. Mahetaji, M., & Brahma, J. (2024). Prediction of minimum mud weight for prevention of breakout using new 3D failure criterion to maintain wellbore stability. Rock Mechanics and Rock Engineering, 57(3), 2231–2252. Mahetaji, M., Brahma, J., & Vij, R. K. (2023). A new extended Mohr-Coulomb criterion in the space of three-dimensional stresses on the in-situ rock. Geomechanics and Engineering, 32(1), 49–68. Mahetaji, M., Brahma, J., & Vij, R. K. (2023). Multivariable regression 3D failure criteria for in-situ rock. Earth Sciences Research Journal, 27(3), 273–287.
Dr. Mohatsim A. Mahetaji is an emerging scholar in petroleum engineering and geomechanics who completed his PhD (2024) at the Department of Petroleum Engineering, School of Energy Technology, Pandit Deendayal Energy University, following an MTech in Petroleum and a BE in Mechanical Engineering. He has held roles as Teaching Assistant, Research & Teaching Assistant (2019-2023) and Research Associate (Oct–Dec 2023) before becoming an Assistant Professor in January 2025 at Parul Institute of Technology. His research spans computational analysis, artificial intelligence / machine learning, data science in drilling and well-bore stability, geomechanics and carbon capture & storage, with several peer-reviewed publications in high-impact journals. He has developed new 3D failure criteria for in-situ rock, and applied machine learning in pore-pressure prediction and wellbore mud weight optimisation. His work reflects a strong modelling and simulation orientation aimed at cost-effective, sustainable hydrocarbon exploration and production. While detailed citation counts and h-index are not publicly available, his trajectory and output indicate rising academic impact. Dr. Mahetaji continues to innovate at the intersection of AI/ML and geosciences, contributing to both theory (failure criteria) and applied drilling design, positioning him as a promising contributor in energy technology and subsurface engineering.
Mahetaji, M., & Brahma, J. (2024). A critical review of rock failure criteria: A scope of machine learning approach. Engineering Failure Analysis, 159, 107998. Mahetaji, M., Brahma, J., & Sircar, A. (2020). Pre-drill pore pressure prediction and safe well design on the top of Tulamura anticline, Tripura, India: A comparative study. Journal of Petroleum Exploration and Production Technology, 10(3), 1021–1049. Mahetaji, M., & Brahma, J. (2024). Prediction of minimum mud weight for prevention of breakout using new 3D failure criterion to maintain wellbore stability. Rock Mechanics and Rock Engineering, 57(3), 2231–2252. Mahetaji, M., Brahma, J., & Vij, R. K. (2023). A new extended Mohr-Coulomb criterion in the space of three-dimensional stresses on the in-situ rock. Geomechanics and Engineering, 32(1), 49–68. Mahetaji, M., Brahma, J., & Vij, R. K. (2023). Multivariable regression 3D failure criteria for in-situ rock. Earth Sciences Research Journal, 27(3), 273–287.