3D time-domain airborne electromagnetic inversion based on secondary field finite-volume method

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. E219-E228 ◽  
Author(s):  
Xiuyan Ren ◽  
Changchun Yin ◽  
James Macnae ◽  
Yunhe Liu ◽  
Bo Zhang
Keyword(s):  
Finite Volume ◽  
Time Domain ◽  
High Efficiency ◽  
Background Field ◽  
Field Method ◽  
Secondary Field ◽  
Model Inversion ◽  
Airborne Electromagnetic ◽  
The Time Domain ◽  
Volume Method

We investigate an algorithm for 3D time-domain airborne electromagnetic (AEM) inversion based on the finite-volume (FV) method and direct Gauss-Newton optimization, where we obtain high efficiency by constraining the modeling volume to the AEM volume of influence (VOI) of a 3D source within the earth, rather than using the larger VOI of the AEM system. A half-space or layered earth is used to model the background field in the time domain, taking into account the transmitter waveform through convolution. Assuming that the 3D source of any secondary field detected at a survey point lies within the moving VOI of the airborne system, we conduct time-domain forward modeling and Jacobian calculation using an FV method within the 3D source VOI that requires a small number of cells for discretization. A local mesh and direct solver are shown to further speed up the computation. A synthetic isolated synclinal conductor inversion shows good agreement with the model geometry and provides a good fit to the data contaminated with noise. A synthetic multiple-body model inversion was also quite successful, showing that our algorithm is effective and about four times faster than inversion using the total-field method. Finally, we inverted GEOTEM data over the Lisheen deposit, where our inversion result was consistent with the published geology.

Broadband SIBC Formulation for a Low-Dispersion Finite Volume Method in the Time Domain

2016 ◽  
Vol 52 (3) ◽  
pp. 1-4 ◽  
Author(s):  
A. Tsakanian ◽  
E. Gjonaj ◽  
H. De Gersem ◽  
T. Weiland
Keyword(s):  
Finite Volume Method ◽  
Finite Volume ◽  
Time Domain ◽  
The Time Domain ◽  
Volume Method ◽  
Low Dispersion

A Finite-Volume Method for the Maxwell Equations in the Time Domain

2000 ◽  
Vol 22 (2) ◽  
pp. 449-475 ◽  
Author(s):  
C. D. Munz ◽  
R. Schneider ◽  
U. Voss
Keyword(s):  
Finite Volume Method ◽  
Finite Volume ◽  
Time Domain ◽  
Maxwell Equations ◽  
The Time Domain ◽  
Volume Method

scholarly journals Improving a real-time helicopter simulator model with linear input filters

2021 ◽  
Author(s):  
Pavle Šćepanović ◽  
Frederik A. Döring
Keyword(s):  
Feedback Control ◽  
Time Domain ◽  
Flight Test ◽  
Flight Mechanics ◽  
Mean Square ◽  
Qualification Test ◽  
Model Inversion ◽  
Helicopter Flight ◽  
The Time Domain ◽  
Mean Square Errors

AbstractFor a broad range of applications, flight mechanics simulator models have to accurately predict the aircraft dynamics. However, the development and improvement of such models is a difficult and time consuming process. This is especially true for helicopters. In this paper, two rapidly applicable and implementable methods to derive linear input filters that improve the simulator model are presented. The first method is based on model inversion, the second on feedback control. Both methods are evaluated in the time domain, compared to recorded helicopter flight test data, and assessed based on root mean square errors and the Qualification Test Guide bounds. The best results were achieved when using the first method.

scholarly journals A Novel Piezoceramic-Based Sensing Technology Combined With Visual Domain Networks for Timber Damage Quantification

2021 ◽  
Vol 8 ◽  
Author(s):  
Haibei Xiong ◽  
Lin Chen ◽  
Cheng Yuan ◽  
Qingzhao Kong
Keyword(s):  
Time Domain ◽  
Damage Assessment ◽  
Structural Damage ◽  
High Efficiency ◽  
Experimental Studies ◽  
Stress Wave Propagation ◽  
Timber Structures ◽  
Sensing Technology ◽  
The Time Domain ◽  
Visual Domain

Early detection of timber damage is essential for the safety of timber structures. In recent decades, wave-based approaches have shown great potential for structural damage assessment. Current damage assessment accuracy based on sensing signals in the time domain is highly affected by the varied boundary conditions and environmental factors in practical applications. In this research, a novel piezoceramic-based sensing technology combined with a visual domain network was developed to quantitatively evaluate timber damage conditions. Numerical and experimental studies reveal the stress wave propagation properties in different cases of timber crack depths. Through the spectrogram visualization process, all sensing signals in the time domain were transferred to images which contain both time and frequency features of signals collected from different crack conditions. A deep neural network (DNN) was adopted for image training, testing, and classification. The classification results show high efficiency and accuracy for identifying crack conditions for timber structures. The proposed technology can be further integrated with a fielding sensing system to provide real-time monitoring of timber damage in field applications.

Spectral-element method with arbitrary hexahedron meshes for time-domain 3D airborne electromagnetic forward modeling

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. E37-E46 ◽  
Author(s):  
Xin Huang ◽  
Changchun Yin ◽  
Colin G. Farquharson ◽  
Xiaoyue Cao ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Time Domain ◽  
Forward Modeling ◽  
Spectral Element ◽  
Earth Model ◽  
System Of Equations ◽  
Primary Field ◽  
Secondary Field ◽  
Efficient Treatment ◽  
Mixed Order ◽  
Airborne Electromagnetic

Mainstream numerical methods for 3D time-domain airborne electromagnetic (AEM) modeling, such as the finite-difference (FDTD) or finite-element (FETD) methods, are quite mature. However, these methods have limitations in terms of their ability to handle complex geologic structures and their dependence on quality meshing of the earth model. We have developed a time-domain spectral-element (SETD) method based on the mixed-order spectral-element (SE) approach for space discretization and the backward Euler (BE) approach for time discretization. The mixed-order SE approach can contribute an accurate result by increasing the order of polynomials and suppress spurious solutions. The BE method is an unconditionally stable technique without limitations on time steps. To deal with the rapid variation of the fields close to the AEM transmitting loop, we separate a secondary field from the primary field and simulate the secondary field only, for which the primary field is calculated in advance. To obtain a block diagonal mass matrix and hence minimize the number of nonzero elements in the system of equations to be solved, we apply Gauss-Lobatto-Legendre integral techniques of reduced order. A direct solver is then adopted for the system of equations, which allows for efficient treatment of the multiple AEM sources. To check the accuracy of our SETD algorithm, we compare our results with the semianalytical solution for a layered earth model. Then, we analyze the modeling accuracy and efficiency for different 3D models using deformed physical meshes and compare them against results from 3D FETD codes, to further show the flexibility of SETD for AEM forward modeling.

scholarly journals Three-Dimensional Anisotropic Inversions for Time-Domain Airborne Electromagnetic Data

Minerals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 218
Author(s):  
Yang Su ◽  
Changchun Yin ◽  
Yunhe Liu ◽  
Xiuyan Ren ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Time Domain ◽  
Three Dimensional ◽  
Model Parameters ◽  
Anisotropic Model ◽  
Regularized Inversion ◽  
Earth Structures ◽  
Airborne Electromagnetic ◽  
Speed Up ◽  
The Time Domain ◽  
Airborne Electromagnetic Data

Rocks and ores in nature usually appear macro-anisotropic, especially in sedimentary areas with strong layering. This anisotropy will lead to false interpretation of electromagnetic (EM) data when inverted under the assumption of an isotropic earth. However, the time-domain (TD) airborne EM (AEM) inversion for an anisotropic model has not attracted much attention. To get reasonable inversion results from TD AEM data, we present in this paper the forward modeling and inversion methods based on a triaxial anisotropic model. We apply three-dimensional (3D) finite-difference on the secondary scattered electric field equation to calculate the frequency-domain (FD) EM responses, then we use the inverse Fourier transform and waveform convolution to obtain TD responses. For the regularized inversion, we calculate directly the sensitivities with respect to three diagonal conductivities and then use the Gauss–Newton (GN) optimization scheme to recover model parameters. To speed up the computation and to reduce the memory requirement, we adopt the moving footprint concept and separate the whole model into a series of small sub-models for the inversion. Finally, we compare our anisotropic inversion scheme with the isotropic one using both synthetic and field data. Numerical experiments show that the anisotropic inversion has inherent advantages over the isotropic ones, we can get more reasonable results for the anisotropic earth structures.

Numerical Modeling of Scattering Problems Using a Time Domain Finite Volume Method

1997 ◽  
Vol 11 (8) ◽  
pp. 1165-1189 ◽  
Author(s):  
P. Bonnet ◽  
X. Ferrieres ◽  
F. Issac ◽  
F. Paladian ◽  
J. Grando ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Finite Volume Method ◽  
Finite Volume ◽  
Time Domain ◽  
Scattering Problems ◽  
Volume Method

scholarly journals Integration of Energetic Model for Ferromagnetic Hysteresis in Finite Volume Method for Electromagnetic Field Calculation

2021 ◽  
Vol 21 (1) ◽  
pp. 23-27
Author(s):  
Ali Hammouche ◽  
Mourad Hamimid ◽  
Abdelkader Kansab ◽  
Bachir Belmadani
Keyword(s):  
Finite Volume ◽  
Control Volume ◽  
Model Parameters ◽  
Magnetic Vector Potential ◽  
Field Calculation ◽  
Control Volume Method ◽  
Ferromagnetic Hysteresis ◽  
Energetic Model ◽  
The Time Domain ◽  
Volume Method

In this article, a coupled algorithm between the control volume method and the hysteresis dynamic energetic model for ferromagnetic hysteresis is presented. To illustrate the dynamic behavior of ferromagnetic materials, the quasi-static model is extended by adding two components to the applied magnetic field “Hedd”, and “Hexc”. The added fields are related to the excess losses and classical eddy losses. Thus, two new supplementary coefficients are added to the model parameters. The determination of those coefficients is attained by measuring the energy density for two distinct frequencies. This model introducing the magnetic induction as an independent variable is presented in order to be directly used in time-stepping finite volume calculations applied to the magnetic vector potential formulation. The calculated results are validated by experiences performed in an Epstein’s frame. To check the effectiveness of this model combined with the control volume method in the time domain, the obtained results are compared with experiments.

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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