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Probabilistic petrophysical reconstruction of Danta's Alpine peatland via electromagnetic induction data
  • +3
  • N Zaru,
  • S Silvestri,
  • M Assiri,
  • P Bai,
  • T M Hansen,
  • Giulio Vignoli
N Zaru
DICAAR, University of Cagliari
S Silvestri
Department of Biological, Geological, and Environmental Sciences, University of Bologna
M Assiri
TESAF, University of Padua
P Bai
SINOPEC Geophysical Research Institute Co. Ltd
T M Hansen
Department of Geoscience, Aarhus University
Giulio Vignoli
Near Surface Land and Marine Geology Department, GEUS, DICAAR, University of Cagliari

Corresponding Author:[email protected]

Author Profile


Peatlands are fundamental deposits of organic carbon. Thus, their protection is of crucial importance to avoid emissions from their degradation. Peat is a mixture of organic soil that originates from the accumulation of wetland plants under continuous or cyclical anaerobic conditions for long periods. Hence, a precise quantification of peat deposits is extremely important; for that, remote- and proximal-sensing techniques are excellent candidates. Unfortunately, remote-sensing can provide information only on the few shallowest centimeters, whereas peatlands often extend to several meters in depth. In addition, peatlands are usually characterized by difficult (flooded) terrains. So, frequency-domain electromagnetic instruments, as they are compact and contactless, seem to be the ideal solution for the quantitative assessment of the extension and geometry of peatlands. Generally, electromagnetic methods are used to infer the electrical resistivity of the subsurface. In turn, the resistivity distribution can, in principle, be interpreted to infer the morphology of the peatland. Here, to some extent, we show how to shortcut the process and include the expectation and uncertainty regarding the peat resistivity directly into a probabilistic inversion workflow. The present approach allows for retrieving what really matters: the spatial distribution of the probability of peat occurrence, rather than the mere electrical resistivity. To evaluate the efficiency and effectiveness of the proposed probabilistic approach, we compare the outcomes against the more traditional deterministic fully nonlinear (Occam's) inversion and against some boreholes available in the investigated area.  
02 Mar 2024Submitted to ESS Open Archive
04 Mar 2024Published in ESS Open Archive