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 kilometerscale- 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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/624351 |
| Date | 04 1900 |
| Creators | Zha, Yuanyuan, Yeh, Tian-Chyi J., Illman, Walter A., Onoe, Hironori, Mok, Chin Man W., Wen, Jet-Chau, Huang, Shao-Yang, Wang, Wenke |
| Contributors | Univ Arizona, Dept Hydrol & Atmospher Sci, State Key Laboratory of Water Resources and Hydropower Engineering Science; Wuhan University; Wuhan China, Department of Hydrology and Atmospheric Sciences; University of Arizona; Tucson Arizona USA, Department of Earth and Environmental Sciences; University of Waterloo; Waterloo Ontario Canada, Japan Atomic Energy Agency; Mizunami Japan, GSI Environmental Inc.; Oakland California USA, Department of Safety, Health and Environmental Engineering; National Yunlin University of Science and Technology; Douliu Taiwan, Graduate School of Engineering Science and Technology; National Yunlin University of Science and Technology; Douliu Taiwan, Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region; Chang'an University; Xi'an China |
| Publisher | AMER GEOPHYSICAL UNION |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | © 2017. American Geophysical Union. All Rights Reserved. |
| Relation | http://doi.wiley.com/10.1002/2016WR019185 |
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