
TY  - JOUR
A1  - Skurdal, G. H. 
A1  - Pfaffhuber, A. A. 
A1  - Davis, A. 
A1  - Bazin, S. 
A1  - Ansch&#xfc;tz, H. 
A1  - Nyboe, N. S. 
A1  - Foged, N. 
A1  - Thomassen, T. 
A1  - Wiig, T. 
T1  - Stretching AEM near-surface resolution limits related to low- and very high resistivity contrasts
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2018
VL  - 2018
IS  - 1
SP  - 1
EP  - 5
KW  - 
UR  - https://doi.org/10.1071/ASEG2018ABW8_4G 
N2  - Data from AEM surveys carried out in Norway, to support ground investigations for infrastructure projects, were used in this study. In large infrastructure projects, knowledge of sediment thickness is vital, along with information about sediment type as possible occurrence of highly sensitive clay. The acquisition systems, calibration and data processing are continuously improved to increase the sensitivity of the AEM systems. In an area with conductive shales over resistive bedrock, the recently introduced system response method was tested. It is applied in the inversion of SkyTEM data and makes it possible to utilize the very earliest time gates, providing information about the shallower layers. The models showed to give more pronounced structures in the near-surface, reflecting true structures observed in resistivity borehole measurements. The same outcome was observed when conducting synthetic modelling. In another setting AEM measurements were carried out along a planned road project to provide information about the extent of very conductive, possible alum shale. A volume estimate of excavated masses was sought, as alum shale poses an environmental and health risk due to the decomposition to sulfuric acid by weathering and high uranium content giving radon gas. Preliminary AEM models had a tendency to overestimate the thickness of the very resistive overburden. Experimenting with and optimizing the inversion settings resulted in models better fitting a priori information from the survey area. Limited low moment data were available due to a noisy environment. This affected the reliability of the models, illustrated by modelling and resulting real data models. 
ER  -

