HR: 1340h
AN: H23A-1116 [Abstracts]
TI: Combining Core and Geophysical Data Using Spatial Statistics to Infer the Permeability Structure of
Glacial Sediments
AU: Kilner, M
EM: mkilner@fugro.co.uk
AF: formerly 1, now Fugro Engineering Services Limited, 18 Frogmore Road
, Hemel Hempstead, Her HP3 9RT
United Kingdom
AU: * West, J
EM: jared@earth.leeds.ac.uk
AF: Institute of Earth and Biosphere, School of Earth and Environment, University of Leeds, Woodhouse Lane,
Leeds, LS2 9JT
United Kingdom
AU: Murray, T
EM: tavi@geography.leeds.ac.uk
AF: School of Geography, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT
United Kingdom
AB:
Geophysical surveys, such as resistivity and electromagnetic surveys, are a valuable tool in characterization of the
permeability structure of aquifer confining layers for the purpose of pollution vulnerability assessment. However, these
geophysical techniques suffer from a range of limitations associated with sampling volume or data inversion process. For
example, when characterizing glacial sequences comprising sands and clays, resistivity inversions often mis-place the depths
of layer boundaries, and fail to relatively detect thin layers at depth, or those below conductive overburden. These
problems seriously compromise our ability to generate accurate permeability fields directly from geophysical data. We
present an approach aimed at overcoming these limitations by combining geophysical data with core data using co-kriging.
Normally, geophysical datasets are accompanied by relatively sparse direct geological data (e.g. borehole logs). These data
can be used to identify where geophysical datasets fail to adequately reflect geological structure; they can also identify
areas where the structure is more adequately reflected in the geophysical data. Here, we present an attempt to use the
spatial structure of areas of a glacial cover sequence where good geophysical data are available to interpolate geological
structure between sparse boreholes. The spatial structure of the geophysical data is first characterized using
semi-variograms; co-kriging of the spatially dense geophysical and sparse borehole data enables the interpolation of a more
complete geological cross section. The permeability fields produced by this approach are compared with those generated by
direct conversion of resistivity profiling data, in order to ascertain the significance of the proposed approach for
groundwater vulnerability assessment.
DE: 1827 Glaciology (1863)
DE: 1832 Groundwater transport
DE: 1875 Unsaturated zone
DE: 1894 Instruments and techniques
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting