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Abstract


 
Chapter from: CA 3: Stochastic Modeling and Geostatistics 
Edited by 
Jeffrey M. Yarus and Richard L. Chambers

Authors:
Y. Anguy, R. Erlich, C. M. Prince, V. L. Riggert, and D. Bernard

Methodology and Concepts


Published 1994 as part of Computer Applications 3
Copyright © 1994 The American Association of Petroleum Geologists.  All Rights Reserved.
 

Chapter 5

*
The Sample Support Problem 
for Permeability Assessment 
in Sandstone Reservoirs

Y. Anguy
Laboratoire Energétique et Phénomènes de Transfert
L.E.P.T.-ENSAM
Esplanade des Arts et Métiers
Cedex, France
R. Ehrlich
C. M. Prince
V. L. Riggert
Department of Geological Sciences
University of South Carolina
Columbia, South Carolina, U.S.A.
D. Bernard
Laboratoire Energétique et Phénomènes de Transfert
L.E.P.T.-ENSAM
Esplanade des Arts et Métiers
Cedex, France

*
ABSTRACT

All sandstone fabrics contain a characteristic complex of microstructures of a scale that is large with respect to the size of sample plugs conventionally used to measure permeability. A fundamental element of this microstructure consists of circuits composed of oversized pores and throats representing the sites of loose or flawed packing, and largely controlling permeability at the permeability-plug scale. Very small changes in the location of a permeability plug with respect to these circuits can result in significant variation in measured permeability. In the terminology of geostatistics, this is a classic problem of insufficient sample support, producing artificially heightened variance over small spatial scales as a result of a sampling volume that is too small. The varying pattern of the spatial variability of the microstructure dictates that permeability plugs must vary in size to contain enough of the microstructure to ensure adequate sample support. This is impossible in practice, but a combination of physical data and image analysis can yield permeability values representing rock volumes of the requisite size. A minimum sample size can be determined by measuring the scales of structural complexity using Fourier transforms of the image of the porous microstructure

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