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.

scholarly journals Geomagnetic anomaly associated with Fukushima earthquake on February 13th, 2021

2021 ◽  
Vol 331 ◽  
pp. 07012
Author(s):  
Cipta Ramadhani ◽  
Bulkis Kanata ◽  
Abdullah Zainuddin ◽  
Rosmaliati ◽  
Teti Zubaidah
Keyword(s):  
Data Processing ◽  
Geomagnetic Field ◽  
Field Data ◽  
Low Frequency ◽  
Earthquake Precursors ◽  
Polarization Ratio ◽  
Magnetic Polarization ◽  
Central Frequency ◽  
Electromagnetic Data ◽  
Geomagnetic Anomaly

In this study, we performed research on electromagnetic anomalies related to earthquakes as early signs (precursors) that occurred in Fukushima, Japan on February 13th, 2021. The research focused on the utilization of geomagnetic field data which was derived from the Kakioka (KAK), Kanoya (KNY), and Memambetsu (MMB) observatories, particularly in the ultra-low frequency (ULF) to detect earthquake precursors. The method of electromagnetic data processing was conducted by applying a polarization ratio. In addition, we improved the methodology by splitting the ULF data (which ranged from 0.01-0.1 Hz) into 9 central frequencies and picking up the highest value from each central frequency to get the polarization ratio. The anomaly of magnetic polarization was identified 2-3 weeks before the mainshock in a narrowband frequency in the range of 0.04-0.05 Hz.

Estimation and geologic interpretation of regolith chargeability and superparamagnetic susceptibility in airborne electromagnetic data

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. E153-E162 ◽  
Author(s):  
James Macnae ◽  
Tim Munday ◽  
Camilla Soerensen
Keyword(s):  
Magnetic Permeability ◽  
Thin Sheet ◽  
Secondary Field ◽  
Conductivity Model ◽  
Electromagnetic Data ◽  
Delay Times ◽  
Airborne Electromagnetic ◽  
Geologic Interpretation ◽  
Airborne Electromagnetic Data ◽  
Dispersive Models

All available inversion software for airborne electromagnetic (AEM) data can at a minimum fit a nondispersive conductivity model to the observed inductive secondary field responses, whether operating in the time or frequency domain. Quasistatic inductive responses are essentially controlled by the induction number, the product of frequency with conductivity and magnetic permeability. Recent research has permitted the conductivity model to be dispersive, commonly using a single Cole-Cole parameterization of the induced polarization (IP) effect; but this parameterization slows down and destabilizes any inversion, and it does not account for the need for dual or multiple Cole-Cole responses. Little has been published on inverting AEM data affected by frequency-dependent magnetic permeability, or superparamagnetism (SPM), usually characterized by a Chikazumi model. Because the IP and SPM effects are small and are usually only obvious at late delay times, the aim of our research is to determine if these IP and SPM effects can be fitted and stripped from the AEM data after being approximated with simple dispersive models. We are able to successfully automate a thin-sheet model to do this stripping. Stripped data then can be inverted using a nondispersive conductivity model. The IP and SPM parameters fitted independently to each independent measured decay to provide stripping are proven to be spatially coherent, and they are geologically sensible. The results are found to enhance interpretation of the regolith geology, particularly the nature and distribution of transported materials that are not afforded by mapping conductivity/conductance alone.

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.

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.

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.

scholarly journals New regional stratigraphic insights from a 3D geological model of the Nasia sub-basin, Ghana, developed for hydrogeological purposes and based on reprocessed B-field data originally collected for mineral exploration

Solid Earth ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 349-361 ◽  
Author(s):  
Elikplim Abla Dzikunoo ◽  
Giulio Vignoli ◽  
Flemming Jørgensen ◽  
Sandow Mark Yidana ◽  
Bruce Banoeng-Yakubo
Keyword(s):  
Field Data ◽  
Mineral Exploration ◽  
Regional Scale ◽  
Geological Mapping ◽  
Northern Ghana ◽  
Geological Model ◽  
Electromagnetic Data ◽  
3D Geological Model ◽  
Geophysical Surveys ◽  
Airborne Electromagnetic

Abstract. Reprocessing of regional-scale airborne electromagnetic data is used to build a 3D geological model of the Nasia sub-basin, northern Ghana. The resulting 3D geological model consistently integrates all the prior pieces of information brought by electromagnetic data, lithologic logs, ground-based geophysical surveys, and geological knowledge of the terrain. The geo-modeling process is aimed at defining the lithostratigraphy of the area, chiefly to improve the stratigraphic definition of the area, and for hydrogeological purposes. The airborne electromagnetic measurements, consisting of GEOTEM B-field data, were originally collected for mineral exploration purposes. Thus, those B-field data had to be (re)processed and properly inverted as the original survey and data handling were designed for the detection of potential mineral targets and not for detailed geological mapping. These new geophysical inversion results, compared with the original conductivity–depth images, provided a significantly different picture of the subsurface. The new geophysical model led to new interpretations of the geological settings and to the construction of a comprehensive 3D geo-model of the basin. In this respect, the evidence of a hitherto unexposed system of paleovalleys could be inferred from the airborne data. The stratigraphic position of these paleovalleys suggests a distinctly different glaciation history from the known Marinoan events, commonly associated with the Kodjari formation of the Voltaian sedimentary basin. Indeed, the presence of the paleovalleys within the Panabako may be correlated with mountain glaciation within the Sturtian age, though no unequivocal glaciogenic strata have yet been identified. Pre-Marinoan glaciation is recorded in rocks of the Wassangara group of the Taoudéni Basin. The combination of the Marinoan and, possibly, Sturtian glaciation episodes, both of the Cryogenian period, can be an indication of a Neoproterozoic Snowball Earth. Hence, the occurrence of those geological features not only has important socioeconomic consequences – as the paleovalleys can act as reservoirs for groundwater – but also from a scientific point of view, they could be extremely relevant as their presence would require a revision of the present stratigraphy of the area.

scholarly journals New regional stratigraphic insights from a 3D geological model of the Nasia Sub-basin, Ghana, developed for hydrogeological purposes and based on reprocessed B-field data, originally collected for mineral exploration

2019 ◽  
Author(s):  
Elikplim Abla Dzikunoo ◽  
Giulio Vignoli ◽  
Flemming Jørgensen ◽  
Sandow Mark Yidana ◽  
Bruce Banoeng-Yakubo
Keyword(s):  
Field Data ◽  
Mineral Exploration ◽  
Regional Scale ◽  
Geological Mapping ◽  
Northern Ghana ◽  
Geological Model ◽  
Electromagnetic Data ◽  
3D Geological Model ◽  
Geophysical Surveys ◽  
Airborne Electromagnetic

Abstract. Re-processing of regional-scale airborne electromagnetic data is used in building a 3D geological model of the Nasia Sub-Basin, Northern Ghana. The resulting 3D geological model consistently integrates all the pieces of information brought by the electromagnetic data, lithologic logs, ground-based geophysical surveys and the prior geological knowledge of the terrain based on previous research. The geo-modelling process is aimed at defining the lithostratigraphy of the area, chiefly to improve the stratigraphic definition of the area as well as for hydrogeological purposes. The airborne electromagnetic measurements, consisting of GEOTEM B-field data, were originally collected for mineral exploration purposes. Thus, those B-field data had to be (re)processed and properly inverted as the original survey and data handling were designed for the detection of potential mineral targets and not for detailed geological mapping. These new geophysical inversion results, compared with the original Conductivity Depth Images, provided a significantly different picture of the subsurface. The new geophysical model led to new interpretations of the geological settings and to the construction of a comprehensive 3D geomodel of the basin. In this respect, the evidences of a hitherto unexposed paleovalley could be inferred from the airborne data. The stratigraphic position of these paleovalleys suggests a distinctly different glaciation history from the Marinoan events, commonly associated with the Kodjari formation of the Voltaian sedimentary basin. Indeed, their presence may be correlated to mountain glaciation within the Sturtian period though no unequivocal glaciogenic strata have yet been identified. This pre-Marinoan glaciation is recorded in rocks of the Wassangara group of the Taoudeni basin. The combination of the Marinoan and, possibly, Sturtian glaciation episodes, both of the Cryogenian period, can be an indication of a Neoproterozoic Snowball Earth. Hence, the occurrence of those geological features, do not only have an important socio-economic consequences – as the paleovalleys can act as reservoirs for groundwater – but, also from a scientific point of view, could be extremely relevant – as their presence would require a revision of the present stratigraphy of the area.

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