4.7 Article

Hydraulic conductivity imaging from 3-D transient hydraulic tomography at several pumping/observation densities

期刊

WATER RESOURCES RESEARCH
卷 49, 期 11, 页码 7311-7326

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/wrcr.20519

关键词

hydraulic tomography; resolution; field study; hydrogeophysics; inversion

资金

  1. NSF [0710949, 934680, 0934596]
  2. US Army RDE-COM ARL Army Research Office [W911NF-09-1-0534]
  3. Directorate For Geosciences
  4. Division Of Earth Sciences [0710949] Funding Source: National Science Foundation
  5. Division Of Mathematical Sciences
  6. Direct For Mathematical & Physical Scien [0934596] Funding Source: National Science Foundation

向作者/读者索取更多资源

3-D Hydraulic tomography (3-D HT) is a method for aquifer characterization whereby the 3-D spatial distribution of aquifer flow parameters (primarily hydraulic conductivity, K) is estimated by joint inversion of head change data from multiple partially penetrating pumping tests. While performance of 3-D HT has been studied extensively in numerical experiments, few field studies have demonstrated the real-world performance of 3-D HT. Here we report on a 3-D transient hydraulic tomography (3-D THT) field experiment at the Boise Hydrogeophysical Research Site which is different from prior approaches in that it represents a baseline analysis of 3-D THT performance using only a single arrangement of a central pumping well and five observation wells with nearly complete pumping and observation coverage at 1 m intervals. We jointly analyze all pumping tests using a geostatistical approach based on the quasi-linear estimator of Kitanidis (1995). We reanalyze the system after progressively removing pumping and/or observation intervals; significant progressive loss of information about heterogeneity is quantified as reduced variance of the K field overall, reduced correlation with slug test K estimates at wells, and reduced ability to accurately predict independent pumping tests. We verify that imaging accuracy is strongly improved by pumping and observational densities comparable to the aquifer heterogeneity geostatistical correlation lengths. Discrepancies between K profiles at wells, as obtained from HT and slug tests, are greatest at the tops and bottoms of wells where HT observation coverage was lacking.

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