https://scholars.lib.ntu.edu.tw/handle/123456789/614747
標題: | Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography | 作者: | Dong Y. Fu Y. Yeh T.-C.J. YU-LI WANG Zha Y. Wang L. Hao Y. |
關鍵字: | Digital storage; Porous materials; Tomography; Discrete fracture network; Discrete fracture network models; Equivalent porous medias; Fracture connectivity; Hydraulic properties; Hydraulic tomographies; Observation networks; Representative elementary volume; Fracture; fracture network; hydraulic conductivity; hydraulic property; hydrological modeling; observational method; porous medium; probability; tomography | 公開日期: | 2019 | 出版社: | Blackwell Publishing Ltd | 卷: | 55 | 期: | 4 | 起(迄)頁: | 3234-3247 | 來源出版物: | Water Resources Research | 摘要: | Hydraulic 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 (Ss) 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. ©2019. American Geophysical Union. All Rights Reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064638738&doi=10.1029%2f2018WR024290&partnerID=40&md5=98f4a94e3272ee914b823aa6eddf8e4d https://scholars.lib.ntu.edu.tw/handle/123456789/614747 |
ISSN: | 00431397 | 其他識別: | WRERA | DOI: | 10.1029/2018WR024290 |
顯示於: | 生物環境系統工程學系 |
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