Combining airborne electromagnetic data from alternating flight directions to form a virtual symmetric array

Geophysics ◽  
2006 ◽  
Vol 71 (2) ◽  
pp. G35-G41 ◽  
Author(s):  
Richard S. Smith ◽  
Michel C. Chouteau
Keyword(s):  
Field Data ◽  
Structural Features ◽  
Measured Data ◽  
Normal Direction ◽  
Symmetric System ◽  
Reverse Direction ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data ◽  
Measured Response

Fixed-wing towed-bird airborne electromagnetic (AEM) systems are asymmetric because the receiver flies behind and below the transmitter. As a consequence, the measured response is quite different when the aircraft flies a traverse line in the reverse direction, even when the causative bodies are symmetric. Because fixed-wing AEM survey traverses are parallel and are flown in alternating directions, the response of bodies can change markedly from one line to the next. This means that images of the measured data are complicated and difficult to interpret. In a survey in Quebec, Canada, each traverse line was flown twice, once in the normal direction and once in the reverse directions. These data were combined to give a response measured by a symmetric system termed the virtual symmetric array (VSA). The VSA response can enhance the S/N ratio, and the response will be symmetric if the con ductive targets are symmetric. Hence, any response asymmetry is indicative of asymmetry in the ground. This means that dip direction can be inferred from the VSA response. Images of VSA data show similar properties, making them a very useful tool for interpreting fixed-wing EM data. A field example is used to illustrate that the standard presentations (filtered images and energy envelope images) are smeared and blocky, whereas the VSA images show sharper resolution, better trending, and better subtle structural features on maps. In most cases, data are not collected in reverse-line directions, but it is possible to create an interpolated VSA image using the reverse line direction data from adjacent lines. When this process is applied to field data, the resulting images have all of the advantage of VSA images, except for somewhat lower S/N ratio improvements. Also, short strike-length features are elongated, and sudden changes in amplitude are not well imaged.

Imaging subsurface orebodies with airborne electromagnetic data using a recurrent neural network

Geophysics ◽  
2021 ◽  
pp. 1-66
Author(s):  
Minkyu Bang ◽  
Seokmin Oh ◽  
Kyubo Noh ◽  
Soon Jee Seol ◽  
Joongmoo Byun
Keyword(s):  
Neural Network ◽  
Magnetic Fields ◽  
Recurrent Neural Network ◽  
Field Data ◽  
Vertical Direction ◽  
Prediction Performance ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data ◽  
2D Resistivity

Conventional interpretation of airborne electromagnetic data has been conducted by solving the inverse problem. However, with recent advances in machine learning (ML) techniques, a one-dimensional (1D) deep neural network inversion that predicts a 1D resistivity model using multi-frequency vertical magnetic fields and sensor height information at one location has been applied. Nevertheless, bacause the final interpretation of this 1D approach relies on connecting 1D resistivity models, 1D ML interpretation has low accuracy for the estimation of an isolated anomaly, as in conventional 1D inversion. Thus, we propose a two-dimensional (2D) interpretation technique that can overcome the limitations of 1D interpretation, and consider spatial continuity by using a recurrent neural network (RNN). We generated various 2D resistivity models, calculated the ratio of primary and induced secondary magnetic fields of vertical direction in ppm scale using vertical magnetic dipole source, and then trained the RNN using the resistivity models and the corresponding electromagnetic (EM) responses. To verify the validity of 2D RNN inversion, we applied the trained RNN to synthetic and field data. Through application of the field data, we demonstrated that the design of the training dataset is crucial to improve prediction performance in a 2D RNN inversion. In addition, we investigated changes in the RNN inversion results of field data dependent on the data preprocessing. We demonstrated that using two types of data, logarithmic transformed data and linear scale data, which having different patterns of input information can enhance the prediction performance of the EM inversion results.

Inversion of helicopter electromagnetic data to a magnetic conductive layered earth

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1211-1223 ◽  
Author(s):  
Haoping Huang ◽  
Douglas C. Fraser
Keyword(s):  
Magnetic Permeability ◽  
Field Data ◽  
Model Parameters ◽  
Relative Importance ◽  
Magnetic Polarization ◽  
Inversion Algorithm ◽  
Layered Earth ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
True Values

Inversion of airborne electromagnetic (EM) data for a layered earth has been commonly performed under the assumption that the magnetic permeability of the layers is the same as that of free space. The resistivity inverted from helicopter EM data in this way is not reliable in highly magnetic areas because magnetic polarization currents occur in addition to conduction currents, causing the inverted resistivity to be erroneously high. A new algorithm for inverting for the resistivity, magnetic permeability, and thickness of a layered model has been developed for a magnetic conductive layered earth. It is based on traditional inversion methodologies for solving nonlinear inverse problems and minimizes an objective function subject to fitting the data in a least‐squares sense. Studies using synthetic helicopter EM data indicate that the inversion technique is reasonably dependable and provides fast convergence. When six synthetic in‐phase and quadrature data from three frequencies are used, the model parameters for two‐ and three‐layer models are estimated to within a few percent of their true values after several iterations. The analysis of partial derivatives with respect to the model parameters contributes to a better understanding of the relative importance of the model parameters and the reliability of their determination. The inversion algorithm is tested on field data obtained with a Dighem helicopter EM system at Mt. Milligan, British Columbia, Canada. The output magnetic susceptibility‐depth section compares favorably with that of Zhang and Oldenburg who inverted for the susceptibility on the assumption that the resistivity distribution was known.

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

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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