Oscillatory Flow Testing in a Sandbox – Towards Oscillatory Hydraulic Tomography

Abstract:

Detailed knowledge of subsurface hydraulic properties is important for predicting

groundwater flow and contaminant transport. The spatial variation of hydraulic properties

in the shallow subsurface has been extensively studied in the past two decades. A

recent approach to characterize subsurface properties is hydraulic tomography, in which

pressure data from multiple constant-rate pumping tests is inverted using a numerical

model. Many laboratory sandbox studies have explored the performance of hydraulic

tomography under different controlled conditions and shown that detailed heterogeneity

information can be extracted (Liu et al., 2002, Illman et al., 2007, 2008, 2010a, 2010b,

Liu et al., 2007, 2008, Xiang et al., 2009, Yin and Illman, 2009, Liu and Kitanidis, 2011,

Berg and Illman, 2011a). Recently, Cardiff et al. (2013) proposed a modified approach

of Oscillatory Hydraulic Tomography (OHT) – in which periodic pumping signals of

different frequencies are used for aquifer stimulation – to characterize aquifer properties.

The potential advantages of OHT over traditional hydraulic tomography include: 1) no

net injection or extraction of water; 2) little movement of existing contamination; 3)

minimal impact of model boundary conditions; and 4) robust extraction of oscillatory

signals from noisy data.

To evaluate the premise of OHT, we built a highly-instrumented 2-D laboratory

sandbox and record pressure responses to periodic pumping tests. In our setup, the

laboratory sandbox is filled with sand of known hydraulic properties, and we measure

aquifer responses at a variety of testing frequencies. The signals recorded are processed

using Fourier-domain analysis, and compared against expected results under linear

(Darcian) theory. The responses are analyzed using analytical and numerical models,

which provide key insights as to: 1) how “effective” hydraulic properties estimated using

homogeneous models are associated with aquifer heterogeneity; and 2) how OHT is able

to detect and image aquifer heterogeneity.