An Inversion Toolbox for Frequency- and Time-domain Airborne Electromagnetic Data from Surveys in Ireland

2017 ◽  
Author(s):  
D. Kiyan ◽  
V. Rath ◽  
R. Delhaye
Keyword(s):  
Time Domain ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data

3D parametric hybrid inversion of time-domain airborne electromagnetic data

Geophysics ◽  
2015 ◽  
Vol 80 (6) ◽  
pp. K25-K36 ◽  
Author(s):  
Michael S. McMillan ◽  
Christoph Schwarzbach ◽  
Eldad Haber ◽  
Douglas W. Oldenburg
Keyword(s):  
Time Domain ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data

Current channelling in time-domain airborne electromagnetic data

2000 ◽  
Vol 31 (1-2) ◽  
pp. 150-157 ◽  
Author(s):  
James Reid ◽  
James Macnae
Keyword(s):  
Time Domain ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data

3D inversion of airborne electromagnetic data

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. WB59-WB69 ◽  
Author(s):  
Leif H. Cox ◽  
Glenn A. Wilson ◽  
Michael S. Zhdanov
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Test Site ◽  
Electromagnetic Data ◽  
Model Study ◽  
Airborne Electromagnetic ◽  
The Time Domain ◽  
Airborne Electromagnetic Data ◽  
Viable Method

Time-domain airborne surveys gather hundreds of thousands of multichannel, multicomponent samples. The volume of data and other complications have made 1D inversions and transforms the only viable method to interpret these data, in spite of their limitations. We have developed a practical methodology to perform full 3D inversions of entire time- or frequency-domain airborne electromagnetic (AEM) surveys. Our methodology is based on the concept of a moving footprint that reduces the computation requirements by several orders of magnitude. The 3D AEM responses and sensitivities are computed using a frequency-domain total field integral equation technique. For time-domain AEM responses and sensitivities, the frequency-domain responses and sensitivities are transformed to the time domain via a cosine transform and convolution with the system waveform. We demonstrate the efficiency of our methodology with a model study relevant to the Abitibi greenstone belt and a case study from the Reid-Mahaffy test site in Ontario, Canada, which provided an excellent practical opportunity to compare 3D inversions for different AEM systems. In particular, we compared 3D inversions of VTEM-35 (time-domain helicopter), MEGATEM II (time-domain fixed-wing), and DIGHEM (frequency-domain helicopter) data. Our comparison showed that each system is able to image the conductive overburden and to varying degrees, detect and delineate the bedrock conductors, and, as expected, that the DIGHEM system best resolved the conductive overburden, whereas the time-domain systems most clearly delineated the bedrock conductors. Our comparisons of the helicopter and fixed-wing time-domain systems revealed that the often-cited disadvantages of a fixed-wing system (i.e., response asymmetry) are not inherent in the system, but rather reflect a limitation of the 1D interpretation methods used to date.

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