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Earth Science

D-Index
55
Citations
22321
World Ranking
2505
National Ranking
1045

Overview

Tapan Mukerji is affiliated with Stanford University in the United States and is active in research spanning engineering and earth and planetary sciences. Their work includes contributions in geophysics, ocean engineering, mechanical engineering, mechanics of materials, and artificial intelligence.

The scientist has published extensively on topics related to seismic imaging and inversion techniques, hydraulic fracturing and reservoir analysis, drilling and well engineering, reservoir engineering and simulation methods, hydrocarbon exploration and reservoir analysis, model reduction and neural networks, as well as rock mechanics and modeling.

Frequent co-authors in their research include Nader C. Dutta, Ran Bachrach, Jack Dvorkin, Gary Mavko, and Ali Kashefi.

Main venues for their scholarly publications include:

  • arXiv (Cornell University)
  • Geophysics
  • Mathematical Geosciences
  • Journal of Geophysical Research Solid Earth
  • SSRN Electronic Journal

Representative recent papers authored by Mukerji include:

  • Physics-informed PointNet: A deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries, 2022, Journal of Computational Physics
  • Petrophysical properties prediction from prestack seismic data using convolutional neural networks, 2020, Geophysics
  • Probabilistic inversion of seismic data for reservoir petrophysical characterization: Review and examples, 2022, Geophysics
  • Applications of deep neural networks in exploration seismology: A technical survey, 2023, Geophysics
  • GANSim: Conditional Facies Simulation Using an Improved Progressive Growing of Generative Adversarial Networks (GANs), 2021, Mathematical Geosciences

Mukerji has contributed to book publications through Cambridge University Press, with titles including:

  • The Rock Physics Handbook, 2020
  • Quantitative Analysis of Geopressure for Geoscientists and Engineers, 2021

Best Publications

  • The Rock Physics Handbook: Tools for Seismic Analysis of Porous Media

    Gary Mavko;Tapan Mukerji;Jack Dvorkin

  • The Rock Physics Handbook

    Gary Mavko;Tapan Mukerji;Jack Dvorkin

  • The Rock Physics Handbook: Contents

    Unknown

  • Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk

    Per Avseth;Tapan Mukerji;Gary Mavko

  • Digital rock physics benchmarks-Part I: Imaging and segmentation

    Heiko Andrä;Nicolas Combaret;Jack Dvorkin;Erik Glatt

  • Digital rock physics benchmarks-part II: Computing effective properties

    Heiko Andrä;Nicolas Combaret;Jack Dvorkin;Erik Glatt

  • Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review

    Miguel Bosch;Tapan Mukerji;Ezequiel F. Gonzalez

  • Convolutional neural network for seismic impedance inversion

    Vishal Das;Ahinoam Pollack;Uri Wollner;Tapan Mukerji

  • Bounds on low‐frequency seismic velocities in partially saturated rocks

    Gary Mavko;Tapan Mukerji

  • Mapping lithofacies and pore‐fluid probabilities in a North Sea reservoir: Seismic inversions and statistical rock physics

    T. Mukerji;A. Jørstad;P. Avseth;G. Mavko

  • Quantitative Seismic Interpretation

    Per Avseth;Tapan Mukerji;Gary Mavko

  • Prestack and poststack inversion using a physics-guided convolutional neural network

    Reetam Biswas;Mrinal K. Sen;Vishal Das;Tapan Mukerji

  • Geological realism in hydrogeological and geophysical inverse modeling: A review

    Niklas Linde;Philippe Renard;Tapan Mukerji;Jef Caers

  • Stochastic reservoir characterization using prestack seismic data

    Jo Eidsvik;Per Avseth;Henning Omre;Tapan Mukerji

  • Rock-physics diagnostics of depositional texture, diagenetic alterations, and reservoir heterogeneity in high-porosity siliciclastic sediments and rocks — A review of selected models and suggested work flows

    Per Avseth;Tapan Mukerji;Gary Mavko;Jack Dvorkin

  • Permeability prediction from thin sections: 3D reconstruction and Lattice‐Boltzmann flow simulation

    Youngseuk Keehm;Tapan Mukerji;Amos Nur

  • Seismic inversion combining rock physics and multiple-point geostatistics

    Ezequiel F. González;Tapan Mukerji;Gary Mavko

  • Statistical rock physics: Combining rock physics, information theory, and geostatistics to reduce uncertainty in seismic reservoir characterization

    Tapan Mukerji;Per Avseth;Gary Mavko;Isao Takahashi

  • Seismic pore space compressibility and Gassmann’s relation

    Gary Mavko;Tapan Mukerji

  • Predicting stress-induced velocity anisotropy in rocks

    Gary Mavko;Tapan Mukerji;Nicola Godfrey

  • Quantitative Seismic Interpretation: References

    Per Avseth;Tapan Mukerji;Gary Mavko

Frequent Co-Authors

Gary Mavko
Gary Mavko Stanford University
Jack Dvorkin
Jack Dvorkin King Fahd University of Petroleum and Minerals
Jef Caers
Jef Caers Stanford University
Amos Nur
Amos Nur Stanford University
Stephan A. Graham
Stephan A. Graham Stanford University
Dario Grana
Dario Grana University of Wyoming
Manika Prasad
Manika Prasad Colorado School of Mines
S. Sen
S. Sen University of California, Davis
Martin Landrø
Martin Landrø Norwegian University of Science and Technology
Edmund Perfect
Edmund Perfect University of Tennessee at Knoxville

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