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.

A compressed implicit Jacobian scheme for 3D electromagnetic data inversion

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. F173-F183 ◽  
Author(s):  
Maokun Li ◽  
Aria Abubakar ◽  
Jianguo Liu ◽  
Guangdong Pan ◽  
Tarek M. Habashy
Keyword(s):  
Electric Fields ◽  
Jacobian Matrix ◽  
Iterative Solvers ◽  
Computational Time ◽  
Memory Usage ◽  
Inversion Algorithm ◽  
Linear System Of Equations ◽  
Electromagnetic Data ◽  
Data Inversion ◽  
Computational Overhead

We developed a compressed implicit Jacobian scheme for the regularized Gauss-Newton inversion algorithm for reconstructing 3D conductivity distributions from electromagnetic data. In this algorithm, the Jacobian matrix, whose storage usually requires a large amount of memory, is decomposed in terms of electric fields excited by sources located and oriented identically to the physical sources and receivers. As a result, the memory usage for the Jacobian matrix reduces from O(NFNSNRNP) to O[NF(NS + NR)NP], where NF is the number of frequencies, NS is the number of sources, NR is the number of receivers, and NP is the number of conductivity cells to be inverted. When solving the Gauss-Newton linear system of equations using iterative solvers, the multiplication of the Jacobian matrix with a vector is converted to matrix-vector operations between the matrices of the electric fields and the vector. In order to mitigate the additional computational overhead of this scheme, these fields are further compressed using the adaptive cross approximation (ACA) method. The compressed implicit Jacobian scheme provides a good balance between memory usage and computational time and renders the Gauss-Newton algorithm more efficient. We demonstrated the benefits of this scheme using numerical examples including both synthetic and field data for both crosswell and controlled-source electromagnetic (CSEM) applications.

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

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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