Shukla PK

About

Dr. Pradeep K. Shukla is an Assistant Professor (Research) at the Centre for Earth and Atmospheric Sciences, Sathyabama Institute of Science and Technology. He works across geomechanics, geotechnical analysis, petrophysics, and applied geophysics, focusing on stress–strain behaviour, pore-pressure prediction, wellbore stability, and subsurface risk assessment. He integrates well-log interpretation, rock physics, and seismic methods with AI/ML to enhance reservoir characterization and clean-energy studies, including natural hydrogen and gas hydrates.
He holds a PhD in Applied Geophysics from BHU Varanasi and completed postdoctoral research at IIT Bombay and IIT (ISM) Dhanbad. Dr. Shukla has published in SCIE-indexed journals, served as a reviewer, and received the 1st National Award at the India AI & GSI Hackathon 2025 for his AI-based mineral targeting solution supporting India’s net-zero vision.

Employment

• Sathyabama Institute of Science and Technology Assistant Professor (Research)
  2025 - Present
• Indian Institute of Technology (Indian School of Mines), Dhanbad Institute Postdoctoral Researcher
  2023 - 2025
• Indian Institute of Technology Bombay Postdoctoral Research Associate
  2022 - 2023

Education

• Banaras Hindu University PhD in Applied Geophysics
  2017 - 2022
• Indian Institute of Technology (Indian School of Mines), Dhanbad M.Sc. Tech
  2013 - 2016
• University of Allahabad B.Sc.
  2008 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• A novel statistical and soft computing technique for permeability prediction in the offshore Krishna–Godavari basin, NGHP-02, India
  Acta Geophysica 2026 0 citations DOI: 10.1007/s11600-025-01774-4
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• Salt rock creep deformation forecasting using deep neural networks and analytical models for subsurface energy storage applications
  Scientific Reports 2025 5 citations DOI: 10.1038/s41598-025-17940-z
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• A Hybrid Approach for Assessing Aquifer Health Using the SWAT Model, Tree-Based Classification, and Deep Learning Algorithms
  Water 2025 13 citations DOI: 10.3390/w17101546
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• A Robust Mechanistic Model for Pore Pressure Prediction from Petrophysical Logs Aided by Machine Learning in the Gas Hydrate-Bearing Sediments over the Offshore Krishna-Godavari Basin, India
  NATURAL RESOURCES RESEARCH 2023 8 citations DOI: 10.1007/S11053-023-10262-9
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• Petro-physics Analysis and Rock Physics Modeling for Estimation of Gas Hydrate Saturation: A Case Study in the Mahanadi Offshore Basin
  Journal of the Geological Society of India 2022 8 citations DOI: 10.1007/s12594-022-2091-1
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• Modeling of in-situ horizontal stresses and orientation of maximum horizhontal stress in the gas hydrate-bearing sediments of the Mahanadi offshore basin, India
  Geomechanics and Geophysics for Geo-Energy and Geo-Resources 2022 11 citations DOI: 10.1007/s40948-022-00401-6
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• Anisotropy analysis in shallow marine gas hydrate bearing sediments: a case study from the offshore Mahanadi basin, India
  Marine Geophysical Research 2022 8 citations DOI: 10.1007/s11001-021-09465-7
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• Delineation of discontinuity using multi-channel seismic attributes: An implication for identifying fractures in gas hydrate sediments in offshore Mahanadi basin
  Results in Geophysical Sciences 2020 12 citations DOI: 10.1016/j.ringps.2020.100007
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• Multi-channel 2D seismic constraints on pore pressure- and vertical stress-related gas hydrate in the deep offshore of the Mahanadi Basin, India
  Journal of Asian Earth Sciences 2019 18 citations DOI: 10.1016/j.jseaes.2019.103882
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• Multi-channel 2D seismic constraints on pore pressure- and vertical stress-related gas hydrate in the deep offshore of the Mahanadi Basin, India
  JOURNAL OF ASIAN EARTH SCIENCES 2019 18 citations DOI: 10.1016/J.JSEAES.2019.103882
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