Stochastic Methods for Flow in Porous Media

Stochastic Methods for Flow in Porous Media

Coping with Uncertainties

1st Edition - October 3, 2001

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  • Author: Dongxiao Zhang
  • Hardcover ISBN: 9780127796215
  • eBook ISBN: 9780080517773

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Stochastic Methods for Flow in Porous Media: Coping with Uncertainties explores fluid flow in complex geologic environments. The parameterization of uncertainty into flow models is important for managing water resources, preserving subsurface water quality, storing energy and wastes, and improving the safety and economics of extracting subsurface mineral and energy resources. This volume systematically introduces a number of stochastic methods used by researchers in the community in a tutorial way and presents methodologies for spatially and temporally stationary as well as nonstationary flows. The author compiles a number of well-known results and useful formulae and includes exercises at the end of each chapter.

Key Features

  • Balanced viewpoint of several stochastic methods, including Greens' function, perturbative expansion, spectral, Feynman diagram, adjoint state, Monte Carlo simulation, and renormalization group methods
  • Tutorial style of presentation will facilitate use by readers without a prior in-depth knowledge of Stochastic processes
  • Practical examples throughout the text
  • Exercises at the end of each chapter reinforce specific concepts and techniques
  • For the reader who is interested in hands-on experience, a number of computer codes are included and discussed


Upper level undergraduate, graduate students, scientists, and professionals in the fields of hydrology, petroleum engineering, soil physics, geological engineering, civil & environmental engineering, applied mathematics

Product details

  • No. of pages: 368
  • Language: English
  • Copyright: © Academic Press 2001
  • Published: October 3, 2001
  • Imprint: Academic Press
  • Hardcover ISBN: 9780127796215
  • eBook ISBN: 9780080517773

About the Author

Dongxiao Zhang

Affiliations and Expertise

Los Alamos National Laboratory, New Mexico, U.S.A.

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