2.5D forward modeling and inversion of frequency-domain airborne electromagnetic data

2016 ◽  
Vol 13 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Wen-Ben Li ◽  
Zhao-Fa Zeng ◽  
Jing Li ◽  
Xiong Chen ◽  
Kun Wang ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Forward Modeling ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data ◽  
And Inversion

scholarly journals 2.5D Inversion Algorithm of Frequency-Domain Airborne Electromagnetics with Topography

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jianjun Xi ◽  
Wenben Li
Keyword(s):  
Frequency Domain ◽  
Large Scale ◽  
Jacobian Matrix ◽  
Sparse Matrix ◽  
Inversion Algorithm ◽  
Linear System Of Equations ◽  
Electromagnetic Data ◽  
Electric And Magnetic Fields ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data

We presented a 2.5D inversion algorithm with topography for frequency-domain airborne electromagnetic data. The forward modeling is based on edge finite element method and uses the irregular hexahedron to adapt the topography. The electric and magnetic fields are split into primary (background) and secondary (scattered) field to eliminate the source singularity. For the multisources of frequency-domain airborne electromagnetic method, we use the large-scale sparse matrix parallel shared memory direct solver PARDISO to solve the linear system of equations efficiently. The inversion algorithm is based on Gauss-Newton method, which has the efficient convergence rate. The Jacobian matrix is calculated by “adjoint forward modelling” efficiently. The synthetic inversion examples indicated that our proposed method is correct and effective. Furthermore, ignoring the topography effect can lead to incorrect results and interpretations.

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.

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

Upward and downward continuation of airborne electromagnetic data

1990 ◽  
Author(s):  
Clyde Bergeron ◽  
Terrence L. Morris ◽  
Juliette W. Ioup
Keyword(s):  
Downward Continuation ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data

Resistive limit modeling of airborne electromagnetic data

Geophysics ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 492-500 ◽  
Author(s):  
James E. Reid ◽  
James C. Macnae
Keyword(s):  
Current Flow ◽  
Integral Equation Method ◽  
Near Surface ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Source Current ◽  
Numerical Model Experiments ◽  
Airborne Electromagnetic Data ◽  
Airborne Em ◽  
Direct Induction

When a confined conductive target embedded in a conductive host is energized by an electromagnetic (EM) source, current flow in the target comes from both direct induction of vortex currents and current channeling. At the resistive limit, a modified magnetometric resistivity integral equation method can be used to rapidly model the current channeling component of the response of a thin-plate target energized by an airborne EM transmitter. For towed-bird transmitter–receiver geometries, the airborne EM anomalies of near-surface, weakly conductive features of large strike extent may be almost entirely attributable to current channeling. However, many targets in contact with a conductive host respond both inductively and galvanically to an airborne EM system. In such cases, the total resistive-limit response of the target is complicated and is not the superposition of the purely inductive and purely galvanic resistive-limit profiles. Numerical model experiments demonstrate that while current channeling increases the width of the resistive-limit airborne EM anomaly of a wide horizontal plate target, it does not necessarily increase the peak anomaly amplitude.

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