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