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    Quantitative imaging of water, ice and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data
    (Oxford : Oxford Univ. Press, 2019) Wagner, F.M.; Mollaret, C.; Günther, T.; Kemna, A.; Hauck, C.
    Quantitative estimation of pore fractions filled with liquid water, ice and air is crucial for a process-based understanding of permafrost and its hazard potential upon climate-induced degradation. Geophysical methods offer opportunities to image distributions of permafrost constituents in a non-invasive manner. We present a method to jointly estimate the volumetric fractions of liquid water, ice, air and the rock matrix from seismic refraction and electrical resistivity data. Existing approaches rely on conventional inversions of both data sets and a suitable a priori estimate of the porosity distribution to transform velocity and resistivity models into estimates for the four-phase system, often leading to non-physical results. Based on two synthetic experiments and a field data set from an Alpine permafrost site (Schilthorn, Bernese Alps and Switzerland), it is demonstrated that the developed petrophysical joint inversion provides physically plausible solutions, even in the absence of prior porosity estimates. An assessment of the model covariance matrix for the coupled inverse problem reveals remaining petrophysical ambiguities, in particular between ice and rock matrix. Incorporation of petrophysical a priori information is demonstrated by penalizing ice occurrence within the first two meters of the subsurface where the measured borehole temperatures are positive. Joint inversion of the field data set reveals a shallow air-rich layer with high porosity on top of a lower-porosity subsurface with laterally varying ice and liquid water contents. Non-physical values (e.g. negative saturations) do not occur and estimated ice saturations of 0–50 per cent as well as liquid water saturations of 15–75 per cent are in agreement with the relatively warm borehole temperatures between −0.5  and 3 ° C. The presented method helps to improve quantification of water, ice and air from geophysical observations.
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    Hydraulic properties at the North Sea island of Borkum derived from joint inversion of magnetic resonance and electrical resistivity soundings
    (Munich : EGU, 2012) Günther, T.; Müller-Petke, M.
    For reliably predicting the impact of climate changes on salt/freshwater systems below barrier islands, a long-term hydraulic modelling is inevitable. As input we need the parameters porosity, salinity and hydraulic conductivity at the catchment scale, preferably non-invasively acquired with geophysical methods. We present a methodology to retrieve the searched parameters and a lithological interpretation by the joint analysis of magnetic resonance soundings (MRS) and vertical electric soundings (VES). Both data sets are jointly inverted for resistivity, water content and decay time using a joint inversion scheme. Coupling is accomplished by common layer thicknesses. We show the results of three soundings measured on the eastern part of the North Sea island of Borkum. Pumping test data is used to calibrate the petrophysical relationship for the local conditions in order to estimate permeability from nuclear magnetic resonance (NMR) data. Salinity is retrieved from water content and resistivity using a modified Archie equation calibrated by local samples. As a result we are able to predict porosity, salinity and hydraulic conductivities of the aquifers, including their uncertainties. The joint inversion significantly improves the reliability of the results. Verification is given by comparison with a borehole. A sounding in the flooding area demonstrates that only the combined inversion provides a correct subsurface model. Thanks to the joint application, we are able to distinguish fluid conductivity from lithology and provide reliable hydraulic parameters as shown by uncertainty analysis. These findings can finally be used to build groundwater flow models for simulating climate changes. This includes the improved geometry and lithological attribution, and also the parameters and their uncertainties. © Author(s) 2012.