GSTDTAP  > 资源环境科学
DOI10.1002/2016WR019185
Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach
Zha, Yuanyuan1,2; Yeh, Tian-Chyi J.2; Illman, Walter A.3; Onoe, Hironori4; Mok, Chin Man W.5; Wen, Jet-Chau6,7; Huang, Shao-Yang8; Wang, Wenke9
2017-04-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2017
卷号53期号:4
文章类型Article
语种英语
国家Peoples R China; USA; Canada; Japan; Taiwan
英文摘要

Hydraulic tomography (HT) has become a mature aquifer test technology over the last two decades. It collects nonredundant information of aquifer heterogeneity by sequentially stressing the aquifer at different wells and collecting aquifer responses at other wells during each stress. The collected information is then interpreted by inverse models. Among these models, the geostatistical approaches, built upon the Bayesian framework, first conceptualize hydraulic properties to be estimated as random fields, which are characterized by means and covariance functions. They then use the spatial statistics as prior information with the aquifer response data to estimate the spatial distribution of the hydraulic properties at a site. Since the spatial statistics describe the generic spatial structures of the geologic media at the site rather than site-specific ones (e.g., known spatial distributions of facies, faults, or paleochannels), the estimates are often not optimal. To improve the estimates, we introduce a general statistical framework, which allows the inclusion of site-specific spatial patterns of geologic features. Subsequently, we test this approach with synthetic numerical experiments. Results show that this approach, using conditional mean and covariance that reflect site-specific large-scale geologic features, indeed improves the HT estimates. Afterward, this approach is applied to HT surveys at a kilometer-scale-fractured granite field site with a distinct fault zone. We find that by including fault information from outcrops and boreholes for HT analysis, the estimated hydraulic properties are improved. The improved estimates subsequently lead to better prediction of flow during a different pumping test at the site.


领域资源环境
收录类别SCI-E
WOS记录号WOS:000403682600020
WOS关键词INVERSE PROBLEM ; GROUNDWATER-FLOW ; TRANSMISSIVITY ; HETEROGENEITY ; HYDROGEOLOGY ; TRANSPORT ; SANDBOX ; MODELS ; MEDIA ; ZONE
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/21782
专题资源环境科学
作者单位1.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan, Peoples R China;
2.Univ Arizona, Dept Hydrol & Atmospher Sci, Tucson, AZ USA;
3.Univ Waterloo, Dept Earth & Environm Sci, Waterloo, ON, Canada;
4.Japan Atom Energy Agcy, Mizunami, Japan;
5.GSI Environm Inc, Oakland, CA USA;
6.Natl Yunlin Univ Sci & Technol, Dept Safety Hlth & Environm Engn, Touliu, Yunlin, Taiwan;
7.Natl Yunlin Univ Sci & Technol, Res Ctr Soil & Water Resources & Nat Disaster Pre, Touliu, Yunlin, Taiwan;
8.Natl Yunlin Univ Sci & Technol, Grad Sch Engn Sci & Technol, Touliu, Yunlin, Taiwan;
9.Changan Univ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Xian, Peoples R China
推荐引用方式
GB/T 7714
Zha, Yuanyuan,Yeh, Tian-Chyi J.,Illman, Walter A.,et al. Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach[J]. WATER RESOURCES RESEARCH,2017,53(4).
APA Zha, Yuanyuan.,Yeh, Tian-Chyi J..,Illman, Walter A..,Onoe, Hironori.,Mok, Chin Man W..,...&Wang, Wenke.(2017).Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach.WATER RESOURCES RESEARCH,53(4).
MLA Zha, Yuanyuan,et al."Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach".WATER RESOURCES RESEARCH 53.4(2017).
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