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structural geology, propagation mechanics and - Stanford School of ...

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1. Abstract<br />

Chapter 6<br />

Permeability effects <strong>of</strong> deformation b<strong>and</strong> arrays in s<strong>and</strong>stone<br />

We apply established numerical modeling techniques to the calculation <strong>of</strong> effective<br />

permeability for porous s<strong>and</strong>stone containing systematic arrays <strong>of</strong> low permeability<br />

deformation b<strong>and</strong>s (DBs). The numerical method, derived from homogenization theory,<br />

can produce effective permeability results for characteristic DB geometries, <strong>and</strong> provides<br />

a quantitative framework with which to exp<strong>and</strong> these effects to the reservoir-simulation<br />

scale from spatially limited data. The method is demonstrated in two dimensions for each<br />

<strong>of</strong> three characteristic DB patterns—parallel, cross-hatch <strong>and</strong> anastomosing—exposed in<br />

the Aztec s<strong>and</strong>stone at the Valley <strong>of</strong> Fire, Nevada, which provides an excellent exhumed<br />

analog for active s<strong>and</strong>stone reservoirs. Our analysis indicates that these extensive,<br />

systematic DB patterns can reduce effective permeability by as much as two orders <strong>of</strong><br />

magnitude at scales relevant to reservoir production, while inducing similar magnitudes<br />

<strong>of</strong> permeability anisotropy. The potential permeability impacts <strong>of</strong> DB arrays on reservoir<br />

production thus rival those routinely attributed to depositional heterogeneity—e.g.<br />

bedding <strong>and</strong> shale streaks. We suggest therefore that properly accounting for the<br />

aggregate effects <strong>of</strong> DBs where they occur could be as important to optimal reservoir<br />

simulation <strong>and</strong> production management in s<strong>and</strong>stone as accounting for sedimentary<br />

architecture.<br />

2. Introduction<br />

Sedimentary <strong>and</strong> <strong>structural</strong> heterogeneities both large (e.g. shale lenses, seismically<br />

detectable faults) <strong>and</strong> small (e.g. bedding, fractures) have been shown to pr<strong>of</strong>oundly<br />

influence effective permeability in s<strong>and</strong>stone. Small features, however, cannot explicitly<br />

be modeled in st<strong>and</strong>ard flow simulations using coarse (10 to 100 m) grid blocks. For<br />

porous, granular materials like s<strong>and</strong>stone, the simplifying assumption <strong>of</strong> isotropic<br />

background permeability is commonly assumed, with perhaps an anisotropy related to<br />

bedding. To more realistically account for the aggregate influence <strong>of</strong> small-scale features,<br />

an effective permeability must be calculated <strong>and</strong> assigned to each simulation block. This<br />

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