Fractured Continuum Approach to Stochastic Permeability Modeling
S. A. McKenna, P. C. Reeves, 2006. "Fractured Continuum Approach to Stochastic Permeability Modeling", Stochastic Modeling and Geostatistics: Principles, Methods, and Case Studies, Volume II, T. C. Coburn, J. M. Yarus, R. L. Chambers
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A new kind of fracture-permeability model called the fractured continuum model (FCM) is presented that incorporates the advantages of discrete fracture network models and the processing speed of effective continuum representations of fracture permeability. Observations of fracture orientation, length, frequency, and transmissivity from boreholes and outcrops are used as input to the FCM approach. Geostatistical realizations of fracture connectivity, represented by the coordination number of a local percolation network, and fracture frequency are combined with object-based simulations of high- and low-permeability classes in the model domain. At each location, these three spatially variable properties are combined into an effective grid-block permeability using an approximation based on the effective medium theory. The resulting realizations of fracture permeability, containing greater than 106 elements, are used as input to a single-phase flow model. A parallel computer platform coupled with a unique groundwater flow code is used to efficiently solve steady-state pressure fields on multiple realizations. The ability to solve many realizations in a short amount of time allows for the evaluation of the effects of two different conceptual models of fracture permeability on particle traveltimes.
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Stochastic Modeling and Geostatistics: Principles, Methods, and Case Studies, Volume II
Since publication of the first volume of Stochastic Modeling and Geostatistics in 1994, there has been an explosion of interest and activity in geostatistical methods and spatial stochastic modeling techniques. Many of the computational algorithms and methodological approaches that were available then have greatly matured, and new, even better ones have come to the forefront. Advances in computing and increased focus on software commercialization have resulted in improved access to, and usability of, the available tools and techniques. Against this backdrop, Stochastic Modeling and Geostatistics Volume II provides a much-needed update on this important technology. As in the case of the first volume, it largely focuses on applications and case studies from the petroleum and related fields, but it also contains an appropriate mix of the theory and methods developed throughout the past decade. Geologists, petroleum engineers, and other individuals working in the earth and environmental sciences will find Stochastic Modeling and Geostatistics Volume II to be an important addition to their technical information resources.