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Aquifer Imaging with Oscillatory Hydraulic Tomography: Application at the Field Scale
Author(s) -
Cardiff Michael,
Zhou YaoQuan,
Barrash Warren,
Kitanidis Peter K.
Publication year - 2019
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/gwat.12960
Subject(s) - aquifer , tomography , signal (programming language) , geology , oscillation (cell signaling) , soil science , groundwater flow , groundwater , geotechnical engineering , optics , physics , computer science , biology , genetics , programming language
Modeling and laboratory experiments have demonstrated the ability of oscillatory hydraulic tomography (OHT) to characterize heterogeneity in aquifer hydraulic properties. In OHT, a location is stressed via periodic pumping/injection at a set frequency, and the resulting head signal is measured at a number of monitoring locations. The source of oscillations is repeatedly moved, allowing tomographic imaging of aquifer properties. Changing the period of oscillation also results in observations with additional information. In theory, OHT is comparable to other hydraulic tomography methods in that distributed pressure change measurements provide characterization information. In practice, OHT has several benefits including: (1) little to no water injected into or extracted from the aquifer; and (2) an observational signal at a set period that can be easily extracted in the presence of noise. We report the first field application of OHT, carried out at the Boise Hydrogeophysical Research Site (BHRS) using an oscillating signal generator with a very small cycling volume of <2 L, and a period range of 5 to 70 s. For these tests, signals were detected at distances of over 15 m. After processing to extract periodic signal properties, we perform tomography using a frequency‐domain numerical model for groundwater flow. In comparing results against prior characterization results from the BHRS, we find moderate to strong positive correlations between K profiles estimated via different methods at multiple wells, with moderate overall correlation between estimated three‐dimensional (3D) K volumes.