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dc.contributor.authorDong, Yanhui
dc.contributor.authorFu, Yunmei
dc.contributor.authorYeh, Tian‐Chyi Jim
dc.contributor.authorWang, Yu‐Li
dc.contributor.authorZha, Yuanyuan
dc.contributor.authorWang, Liheng
dc.contributor.authorHao, Yonghong
dc.date.accessioned2019-08-27T18:13:04Z
dc.date.available2019-08-27T18:13:04Z
dc.date.issued2019-04-23
dc.identifier.citationDong, Y., Fu, Y., Yeh, T.‐C. J., Wang, Y.‐L., Zha, Y., Wang, L., & Hao, Y. (2019). Equivalence of discrete fracture network and porous media models by hydraulic tomography. Water Resources Research, 55, 3234–3247. https://doi.org/10.1029/2018WR024290en_US
dc.identifier.issn0043-1397
dc.identifier.doi10.1029/2018wr024290
dc.identifier.urihttp://hdl.handle.net/10150/634009
dc.description.abstractHydraulic tomography (HT) has emerged as a potentially viable method for mapping fractures in geologic media as demonstrated by recent studies. However, most of the studies adopted equivalent porous media (EPM) models to generate and invert hydraulic interference test data for HT. While these models assign significant different hydraulic properties to fractures and matrix, they may not fully capture the discrete nature of the fractures in the rocks. As a result, HT performance may have been overrated. To explore this issue, this study employed a discrete fracture network (DFN) model to simulate hydraulic interference tests. HT with the EPM model was then applied to estimate the distributions of hydraulic conductivity (K) and specific storage (S-s) of the DFN. Afterward, the estimated fields were used to predict the observed heads from DFN models, not used in the HT analysis (i.e., validation). Additionally, this study defined the spatial representative elementary volume (REV) of the fracture connectivity probability for the entire DFN dominant. The study showed that if this spatial REV exists, the DFN is deemed equivalent to EPM and vice versa. The hydraulic properties estimated by HT with an EPM model can then predict head fields satisfactorily over the entire DFN domain with limited monitoring wells. For a sparse DFN without this spatial REV, a dense observation network is needed. Nevertheless, HT is able to capture the dominant fractures.en_US
dc.description.sponsorshipNational Science and Technology Major Project of China [2017ZX05008-003-021]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB10030601]; Youth Innovation Promotion Association of the Chinese Academy of Sciences [2016063]; US Civilain Research and Development Foundation (CRDF) under the award: Hydraulic tomography in shallow alluvial sediments: Nile River Valley, Egypt [DAA2-15-61224-1]; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin Cityen_US
dc.language.isoenen_US
dc.publisherAMER GEOPHYSICAL UNIONen_US
dc.rightsCopyright © 2019. American Geophysical Union. All Rights Reserved.en_US
dc.titleEquivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomographyen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Dept Hydrol & Atmospher Scien_US
dc.identifier.journalWATER RESOURCES RESEARCHen_US
dc.description.note6 month embargo; published online: 23 April 2019en_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.volume55
dc.source.issue4
dc.source.beginpage3234-3247


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