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Poster communications

Periodic Hydraulic Testing for Discerning Fracture Network Connections

Abstract : Discrete fracture network (DFN) models often predict highly variable hydraulic connections between injection and pumping wells used for enhanced oil recovery, geothermal energy extraction, and groundwater remediation. Such connections can be difficult to verify in fractured rock systems because standard pumping or pulse interference tests interrogate too large a volume to pinpoint specific connections. Three field examples are presented in which periodic hydraulic tests were used to obtain information about hydraulic connectivity in fractured bedrock. The first site, a sandstone in New York State, involves only a single fracture at a scale of about 10 m. The second site, a granite in Brittany, France, involves a fracture network at about the same scale. The third site, a granite/schist in the U.S. State of New Hampshire, involves a complex network at scale of 30-60 m. In each case periodic testing provided an enhanced view of hydraulic connectivity over previous constant rate tests. Periodic testing is particularly adept at measuring hydraulic diffusivity, which is a more effective parameter than permeability for identify the complexity of flow pathways between measurement locations. Periodic tests were also conducted at multiple frequencies which provides a range in the radius of hydraulic penetration away from the oscillating well. By varying the radius of penetration, we attempt to interrogate the structure of the fracture network. Periodic tests, therefore, may be uniquely suited for verifying and/or calibrating DFN models.
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https://hal-insu.archives-ouvertes.fr/insu-01241975
Contributor : Isabelle Dubigeon <>
Submitted on : Friday, December 11, 2015 - 11:34:19 AM
Last modification on : Friday, April 5, 2019 - 8:17:40 PM

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  • HAL Id : insu-01241975, version 1

Citation

Matthew Becker, Tanguy Le Borgne, Olivier Bour, Nicolas Guihéneuf, Matthew Cole. Periodic Hydraulic Testing for Discerning Fracture Network Connections . AGU Fall Meeting 2015, Dec 2015, San Francisco, United States. pp.H51C-137. ⟨insu-01241975⟩

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