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

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Nonetheless, DBs are commonly ignored in the practice <strong>of</strong> s<strong>and</strong>stone reservoir<br />

management, even though their potential order-<strong>of</strong>-magnitude permeability effects rival<br />

those routinely attributed to depositional heterogeneities—e.g. bedding <strong>and</strong> shale<br />

fraction. We suggest therefore that recognizing <strong>and</strong> characterizing systematic DB patterns<br />

in the subsurface, <strong>and</strong> then accounting accurately for their aggregate influence on bulk<br />

permeability with an upscaling process such as presented here, should become a regular<br />

component <strong>of</strong> reservoir simulation <strong>and</strong> production management in s<strong>and</strong>stone. Finally, we<br />

observe that, even with only limited DB data gleaned from scattered core studies,<br />

valuable adjustments to the underlying permeability structure <strong>of</strong> s<strong>and</strong>stone reservoirs can<br />

be approximated based on the results presented here for the characteristic DB patterns <strong>of</strong><br />

the Aztec s<strong>and</strong>stone.<br />

9. Acknowledgements<br />

The authors would like to thank Eric Flodin <strong>and</strong> Nick Davatzes for their assistance in<br />

the field, <strong>and</strong> Herve Jourde for his help in the field <strong>and</strong> with the numerical modeling. This<br />

work was supported by the U.S. Department <strong>of</strong> Energy, Office <strong>of</strong> Basic Energy Science,<br />

Geosciences Research Program under grant DE-FG03-94ER14462, awarded to David<br />

Pollard <strong>and</strong> Atilla Aydin.<br />

167

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