Rock Physics for Quantitative Seismic Reservoir Characterization

Course Description

The purpose of the course is to give an overview of rock physics observations and models relating reservoir properties such as saturation, lithology, clay content, and pore pressure and their seismic signatures. Understanding this relation can help to improve quantitative seismic interpretation. The course covers fundamentals of Rock Physics ranging from basic laboratory and theoretical results to practical “recipes” that can be immediately applied in the field. Application of quantitative tools for understanding and predicting the effects of lithology, pore fluid types and saturation, saturation scales, stress, pore pressure and temperature, and fractures on seismic velocity. Use of rock physics models requires understanding the assumptions and pitfalls of each model and the uncertainties associated with the interpretations using these models. Analysis of case studies and strategies for quantitative seismic interpretation using statistical rock physics work flows, and suggestions for more effectively employing seismic-to-rock properties transforms in Bayesian machine learning for reservoir characterization and monitoring, with emphasis on seismic interpretation and uncertainty quantification for lithology and subsurface fluid detection.

Course Objectives

On completion of the course, participants will be able to:

  • Use rock physics models with a better understanding of assumptions and pitfalls;
  • Combine statistical rock physics in quantitative seismic interpretation workflows;
  • Select appropriate rock physics models for reservoir characterization;
  • Use rock physics models to build appropriate training sets for Bayesian machine learning applications in quantitative seismic interpretation.

Course Outline

  • Introduction to Rock Physics, motivation, introductory examples
  • Parameters that influence seismic velocities - conceptual overview
  • Effects of fluids, stress, pore pressure, temperature, porosity, fractures
  • Bounding methods for robust modeling of seismic velocities
  • Effective media models for elastic properties of rocks
  • Gassmann Fluid substitution – uses, abuses, and pitfalls
  • Derivation, recipe and examples, useful approximations
  • Partial saturation and the relation of velocities to reservoir processes
  • The importance of saturation scales and their effect on seismic velocity
  • Shaly sands and their seismic signatures
  • Granular media models, unconsolidated sand model, cemented sand model
  • Velocity dispersion and attenuation; Velocity Upscaling
  • Rock Physics of AVO interpretation and Vp/Vs relations
  • Quantitative seismic interpretation and rock physics templates
  • Statistical rock physics, Bayesian machine learning and uncertainty quantification
  • Rock physics modeling to augment deep learning training data
  • Example case studies using AVO and seismic impedance for quantitative reservoir characterization

Participants’ Profile

The course is recommended for all geophysicists, reservoir geologists, seismic interpreters, and engineers concerned with reservoir characterization, reservoir delineation, hydrocarbon detection, reservoir development and recovery monitoring.


No specific prerequisites needed.

Recommended Reading

Participants are recommended to preferably read:

  • Avseth, P., Mukerji, T., and Mavko, G., 2005, Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk, Cambridge University Press
  • Mavko, G., Mukerji, T., and Dvorkin, J., 2009, The Rock Physics Handbook, 2nd Edition, Cambridge University Press
  • Dvorkin, J., Gutierrez, M, and Grana, D., Seismic reflections of rock properties, Cambridge
  • Offset-dependent reflectivity, Castagna & Backus, SEG
  • Physical properties of rocks, Schoen, Elsevier

About the Instructor

Tapan Mukerji is a Professor (Research) at Stanford University where he got his Ph.D. (1995) in Geophysics. Tapan co-directs the Stanford Center for Earth Resources Forecasting (SCERF), Stanford Rock Physics and Borehole Geophysics (SRB) and the Basin and Petroleum System Modeling (BPSM) projects at Stanford University. His research interests include rock physics, spatial statistics, wave propagation, and stochastic methods for quantitative reservoir characterization and time-lapse reservoir monitoring. Tapan combines experience in conducting leading edge research, teaching, and directing graduate student research. He was awarded the Karcher Award in 2000 by the Society of Exploration Geophysicists, and received the ENI award in 2014. He is an associate editor for Geophysics, journal of the Society of Exploration Geophysicists, and Computers and Geosciences. In addition to numerous journal publications, Tapan has co-authored The Rock Physics Handbook, Quantitative Seismic Interpretation, and The Value of Information in the Earth Sciences, all published by Cambridge University Press. He has been an invited keynote speaker and instructor for numerous short courses on rock physics and geostatistics, in North and South America, Europe, Africa, Australia and Asia.