HR: 13:30h
AN: NS33A-01 INVITED [Abstracts]
TI: Imaging 4-D hydrogeologic processes with geophysics: an example using crosswell electrical measurements to characterize a tracer plume
AU: * Singha, K
EM: ksingha@pangea.stanford.edu
AF: Stanford University, Building 320, Geology Corner, Stanford, CA 94305-2115 United States
AU: Gorelick, S M
EM: gorelick@ pangea.stanford.edu
AF: Stanford University, Building 320, Geology Corner, Stanford, CA 94305-2115 United States
AB:
Geophysical methods provide an inexpensive way to collect spatially exhaustive data about hydrogeologic, mechanical or
geochemical parameters. In the presence of heterogeneity over multiple scales of these parameters at most field sites,
geophysical data can contribute greatly to our understanding about the subsurface by providing important data we would
otherwise lack without extensive, and often expensive, direct sampling. Recent work has highlighted the use of time-lapse
geophysical data to help characterize hydrogeologic processes. We investigate the potential for making quantitative
assessments of sodium-chloride tracer transport using 4-D crosswell electrical resistivity tomography (ERT) in a sand and
gravel aquifer at the Massachusetts Military Reservation on Cape Cod. Given information about the relation between
electrical conductivity and tracer concentration, we can estimate spatial moments from the 3-D ERT inversions, which give us
information about tracer mass, center of mass, and dispersivity through time. The accuracy of these integrated measurements
of tracer plume behavior is dependent on spatially variable resolution. The ERT inversions display greater apparent
dispersion than tracer plumes estimated by 3D advective-dispersive simulation. This behavior is attributed to reduced
measurement sensitivity to electrical conductivity values with distance from the electrodes and differential smoothing from
tomographic inversion. The latter is a problem common to overparameterized inverse problems, which often occur when
real-world budget limitations preclude extensive well-drilling or additional data collection. These results prompt future
work on intelligent methods for reparameterizing the inverse problem and coupling additional disparate data sets.
DE: 0694 Instrumentation and techniques
DE: 1832 Groundwater transport
DE: 3260 Inverse theory
DE: 5109 Magnetic and electrical properties
SC: Near-Surface Geophysics [NS]
MN: 2005 Joint Assembly