Airborne Electromagnetic System Research Articles

Inversion for 3D Conductivity and Chargeability Models Using EM Data Acquired by the New Airborne TargetEM System in Ontario, Canada

This paper introduces an original approach to the joint inversion of airborne electromagnetic (EM) data for three-dimensional (3D) conductivity and chargeability models using hybrid finite difference (FD) and integral equation (IE) methods. The inversion produces a 3D model of physical parameters, which includes conductivity, chargeability, time constant, and relaxation coefficients. We present the underlying principles of this approach and an example of a high-resolution inversion of the data acquired by a new active time domain airborne EM system, TargetEM, in Ontario, Canada. The new TargetEM system collects high-quality multicomponent data with low noise, high power, and a small transmitter–receiver offset. This airborne system and the developed advanced inversion methodology represent a new effective method for mineral resource exploration.

Detecting and recovering critical mineral resource systems using broadband total-field airborne natural source audio frequency magnetotellurics measurements

Airborne geophysical methods offer a substantial advantage compared to ground-based techniques in exploring territories of different sizes, ranging from entire metallogenic provinces to the deposit scale, including those hosting critical minerals. An airborne method with measurements of natural magnetic field variations, known as audio frequency magnetotellurics (a passive field method), significantly increases the depth of investigation and expands the resistivity detection range compared with some controlled-source primary-field methods. We describe the technical solutions used in an airborne electromagnetic passive system with a mobile sensor of the total magnetic field variations and the stationary sensor of electric field variations, and its applications to recovering the complex geology of hydrothermal-magmatic systems often associated with critical minerals. The system’s ability to explore depths, typically beginning from the near-surface and down to 1–2 km, by recording responses in three orthogonal inductive coils over a broad bandwidth from 22 Hz to 21,000 Hz allows for mapping resistivities across a broad range. This capability is crucial for obtaining more comprehensive exploration models. Field case studies of the natural field system include application in exploring for unconformity uranium mineralization, along with other associated minerals, epithermal gold and polymetallic-bearing structures, and ferromanganese and polymetallic deposits formed in a continental rift valley. An extra case study involving kimberlites was incorporated as a proven example of the natural field system’s capability in conducting near-surface and deep investigations. The case histories illustrate the airborne natural electromagnetic field technology capabilities in recovering geoelectric models and their specific patterns.

An information theoretic Bayesian uncertainty analysis of AEM systems over Menindee Lake, Australia

SUMMARY Long-range, active-source airborne electromagnetic (AEM) systems for near-surface conductivity imaging fall into two categories: helicopter (rotary-wing) borne or fixed-wing aircraft borne. A multitude of factors such as flying height, transmitter loop area and current, source waveforms, aerodynamic stability and data stacking times contribute to the geological resolvability of the subsurface. A comprehensive comparison of the relative merits of each system considering all such factors is difficult, but test flights over well-constrained subsurface geology with downhole induction logs are extremely useful for resolution studies. However, given the non-linear nature of the electromagnetic inverse problem, handling transmitter–receiver geometries in fixed-wing aircraft is especially challenging. As a consequence of this non-linearity, inspecting the closeness of downhole conductivities to deterministic inversion results is not sufficient for studying resolvability. A more comprehensive picture is provided by examining the variation in probability mass of the depth-wise Bayesian posterior conductivity distributions for each kind of AEM system within an information theoretic framework. For this purpose, probabilistic inversions of data must be carried out. Each acquiring system should fly over the same geology, survey noise levels must be measured and the same prior probabilities on conductivity must be used. With both synthetic models as well as real data from over the Menindee calibration range in New South Wales, Australia, we shed new light on the matter of AEM inverse model uncertainty. We do this using two information theoretic attributes derived from different Kullback–Leibler divergences—Bayesian information gain, and a strictly proper scoring rule, to assess posterior probabilities estimated by a novel Bayesian inversion scheme. The inversion marginalizes fixed-wing geometry attributes as generic nuisance parameters during Markov chain sampling. This is the first time-domain AEM study we know of, that compares nuisance marginalized subsurface posterior conductivities from a fixed-wing system, with rotary-wing derived posterior conductivities. We also compare field results with induction log data where available. Finally, we estimate the information gain in each case via a covariate shift adaptation technique that has not been used before in geophysical work. Our findings have useful implications in AEM system selection, as well as in the design of better deterministic AEM inversion algorithms.

DL-RMD: a geophysically constrained electromagnetic resistivity model database (RMD) for deep learning (DL) applications

Abstract. Deep learning (DL) algorithms have shown incredible potential in many applications. The success of these data-hungry methods is largely associated with the availability of large-scale datasets, as millions of observations are often required to achieve acceptable performance levels. Recently, there has been an increased interest in applying deep learning methods to geophysical applications where electromagnetic methods are used to map the subsurface geology by observing variations in the electrical resistivity of the subsurface materials. To date, there are no standardized datasets for electromagnetic methods, which hinders the progress, evaluation, benchmarking, and evolution of deep learning algorithms due to data inconsistency. Therefore, we present a large-scale electrical resistivity model database (RMD) with a wide variety of geologically plausible and geophysically resolvable subsurface structures for the commonly deployed ground-based and airborne electromagnetic systems. Potentially, the presented database can be used to build surrogate models of well-known processes and to aid in labour-intensive tasks. The geophysically constrained property of this database will not only achieve enhanced performance and improved generalization but, more importantly, incorporate consistency and credibility into deep learning models. We show the effectiveness of the presented database by surrogating the forward-modelling process, and we urge the geophysical community interested in deep learning for electromagnetic methods to utilize the presented database. The dataset is publicly available at https://doi.org/10.5281/zenodo.7260886 (Asif et al., 2022a).

Remote Sensing of Groundwater: Current Capabilities and Future Directions

AbstractGlobally, groundwater represents a critical natural resource that is affected by changes in natural supply and renewal, as well as by increasing human demand and consumption. However, despite its critical role, groundwater is difficult to accurately quantify as it is beneath the Earth surface. Here, we review several state‐of‐the‐art remote sensing techniques useful for local‐ to global‐scale groundwater monitoring and assessment, including proxies for groundwater extraction. These include inferring changes in subsurface water from mass changes using gravitational measurements, and analyzing changes in the Earth surface height using Interferometric Synthetic Aperture Radar, Light Detection and Ranging, Airborne Electromagnetic Systems, and satellite altimetry. Remote sensing information is often used in tandem with ground‐based observations such as hydraulic head in wells, Global Navigational Satellite System monitoring, and numerical modeling to complement the space‐based approaches. In the future, fusing different remote sensing techniques capable of operating in various environments will yield additional insight on the state and rate of use for groundwater across the globe.

The Test Flight of iFTEM-I Fixed-Wing Airborne Time-Domain Electromagnetic System in Binxian, Heilongjiang Province, China

The fixed-wing time-domain airborne electromagnetic method (FTEM) has been widely used in metal mining exploration, groundwater mapping and other fields worldwide, and in recent decades, its use has gradually also become more prevalent in China. The first generation of the fixed-wing time-domain airborne electromagnetic system (iFTEM-I), researched and developed by the Institute of Geophysical and Geochemical Exploration (IGGE), has been demonstrated in recent years. In this article, we introduce the brief working principle and system parameters of iFTEM-I, and we show that the effective prospecting depth of iFTEM-I is up to 350 m, which is indicated by a comparison of the results between iFTEM-I and a ground TEM system (TEM-30B) carried out in Binxian.

3D Finite-Element Forward Modeling of Airborne EM Systems in Frequency-Domain Using Octree Meshes

The 3-D airborne electromagnetic (AEM) inversions have been restricted by the modeling efficiency resulting from the complex geology in exploration areas and massive amount of data collected by AEM systems. In order to improve the modeling efficiency, we develop an algorithm that combines the hexahedral vector finite element (FE) with octree meshes, in which the boundary conditions are imposed via an algebraic constraint to ensure the continuity of the FE solution. This makes the division with hexahedral meshes more flexible for complex geology such as rugged topography or underground structures so that we can reduce the number of elements while maintaining the accuracy. After formulating the forward problem, we check the accuracy of our algorithm by taking a homogeneous half-space model and comparing the results of our octree method with the semianalytical solutions. Furthermore, we demonstrate the efficiency of our octree method by comparing with the traditional FE method using tetrahedral meshes. Finally, we subdivide a complex topography constructed using the 2-D Gaussian rough surface and calculate the EM responses with and without anomaly embedded. The results show that the EM responses are overwhelmed by the Earth topography. We carry out the topographic correction by taking a method based on the ratio of EM responses with and without anomaly. The experiments show that after topographic correction to AEM data, the response of anomaly becomes more distinguishable so that the anomaly can be clearly identified. Furthermore, we also calculate the EM response for a realistic model—the Ovoid Zone ore body located at Voisey’s Bay, Labrador, Canada, to verify the flexibility and practicality of our algorithm.

AEM in Norway: A Review of the Coverage, Applications and the State of Technology

From the first use of airborne electromagnetic (AEM) systems for remote sensing in the 1950s, AEM data acquisition, processing and inversion technology have rapidly developed. Once used extensively for mineral exploration in its early days, the technology is increasingly being applied in other industries alongside ground-based investigation techniques. This paper reviews the application of onshore AEM in Norway over the past decades. Norway’s rugged terrain and complex post-glacial sedimentary geology have contributed to the later adoption of AEM for widespread mapping compared to neighbouring Nordic countries. We illustrate AEM’s utility by using two detailed case studies, including time-domain and frequency domain AEM. In both cases, we combine AEM with other geophysical, geological and geotechnical drillings to enhance interpretation, including machine learning methods. The end results included bedrock surfaces predicted with an accuracy of 25% of depth, identification of hazardous quick clay deposits, and sedimentary basin mapping. These case studies illustrate that although today’s AEM systems do not have the resolution required for late-phase, detailed engineering design, AEM is a valuable tool for early-phase site investigations. Intrusive, ground-based methods are slower and more expensive, but when they are used to complement the weaknesses of AEM data, site investigations can become more efficient. With new developments of drone-borne (UAV) systems and increasing investment in AEM surveys, we see the potential for continued global adoption of this technology.

Fast 3D time-domain airborne EM forward modeling using random under-sampling

The high sampling rate of airborne electromagnetic (AEM) systems can create huge data volumes, causing major challenges for three-dimensional (3D) electromagnetic modeling and inversions and constraining the practical applicability of AEM. Rapid and accurate forward modeling is the key to efficient 3D inversion. Here a new strategy for improving the efficiency of 3D time-domain AEM forward modeling is presented, based on compressed-sensing theory combined with the finite-volume method. A Poisson disk random under-sampling method was used to obtain random survey stations and to calculate AEM responses via the finite-volume method at these sampling stations. Coefficients from the curvelet transform with anisotropic characteristics for sparse expression were used to analyze the sparsity of AEM data, with the AEM responses of all survey stations being obtained by reconstruction. Key factors influencing the accuracy of the reconstruction are also discussed, including the sampling method and rate, the sparse transformation, and the noise. To test the effectiveness of the method, reconstructed results were compared with those from traditional schemes for forward modeling using all stations. Results indicate that the new strategy requires only 20% ~ 50% of samples to achieve high-precision reconstruction of the AEM signal even for complex geoelectrical structures, and the efficiency of 3D forward modeling can be enhanced by a factor of two to five, laying a foundation for fast AEM inversions of large datasets and complex models.

Early time data processing in shallow AEM exploration

For shallow exploration, high-frequency pseudo-random binary sequence is used in the time-domain airborne electromagnetic system. This system is working in the on-time and the earth response could be derived from system identification, which is different from the previous time-domain electromagnetic systems. The early time data is crucial for obtaining a detailed resolution. It could be severely disturbed by the primary field, the receiver response and noise. Here we present an approach for removing the primary field by matching subtraction in transformation of correlation calculation. The noise is suppressed as not correlated with the pseudo-random binary sequence. This approach is proved efficient by applying to simulation data based on forward modeling. The receiver influence is analyzed through the response of the equivalent electronic circuit. The 1D inversion results indicate that critical damping state and high cut-off frequency could reduce the adverse effect on the resolution of shallow exploration.

3-D Time-Domain Airborne EM Inversion for a Topographic Earth

The topography has serious effects on time-domain airborne electromagnetic (AEM) signal, and the EM responses resulted from the topography frequently overwhelm those from the underground abnormal bodies. This brings big challenges to the traditional AEM interpretations based on a flat ground model. In this article, we develop a 3-D AEM inversion algorithm for a topographic earth model. The time-domain finite-element algorithm based on unstructured mesh is used to model the AEM responses. The tetrahedral grids provide the flexibility to fit the rugged topography. Furthermore, we adopt the Gauss–Newton method for our inversion of time-domain AEM data. In the forward modeling and the calculation of Jacobian matrix, we introduce an unstructured local mesh and decouple the meshes for forward modeling and inversion to improve the computational efficiency. For that purpose, we first set up an unstructured inversion mesh and then extract those cells corresponding to the sensitive area of AEM system for each survey station from the inversion mesh and construct a local forward mesh with the extracted cells as the core. After that, we take advantage of the spatial relationship between the local forward meshes and the inversion ones to set up the global sensitivity matrix for Gauss–Newton inversion. We test the effectiveness of our algorithm by applying our 3-D inversion code to both synthetic and survey data. The numerical experiments show that the Earth topography can have big influence on AEM inversions, and ignoring the topography can create serious distortion to AEM inversion results.

DESMEX: A novel system development for semi-airborne electromagnetic exploration

There is a clear demand to increase detection depths in the context of raw material exploration programs. Semi-airborne electromagnetic (semi-AEM) methods can address these demands by combining the advantages of powerful transmitters deployed on the ground with efficient helicopter-borne mapping of the magnetic field response in the air. The penetration depth can exceed those of classic airborne EM systems because low frequencies and large transmitter-receiver offsets can be realized in practice. A novel system has been developed that combines high-moment horizontal electric bipole transmitters on the ground with low-noise three-axis induction coil magnetometers, a three-axis fluxgate magnetometer, and a laser gyro inertial measurement unit integrated within a helicopter-towed airborne platform. The attitude data are used to correct the time series for motional noise and subsequently to rotate into an earth-fixed reference frame. In a second processing step, and as opposed to existing semi-AEM systems, we transform the data into the frequency domain and estimate the complex-valued transfer functions between the received magnetic field components and the synchronously recorded injection current by regression analysis. This approach is similar to the procedure used in controlled-source EM. For typical source bipole moments of 20–40 kAm and for rectangular current waveforms with a fundamental frequency of approximately 10 Hz, we can estimate reliable three-component (3C) transfer functions in the frequency range from 10 to 5000 Hz over a measurement area of [Formula: see text] for a single source installation. The system has the potential to be used for focused exploration of deep targets.

Fast imaging of time-domain airborne EM data using deep learning technology

Due to the huge amount of data generated by time-domain airborne electromagnetic (AEM) systems, conductivity depth imaging methods are widely used to help in the interpretation of these data because they can be generated quickly and easily. We have introduced a new imaging method generated using a deep neural network. The network structure combines four convolutional neural networks with a long short-term memory technique and adopts an error back-propagation scheme to update the parameters. A deep hierarchical structure is used to extract and store the complex nonlinear relationship between the model and electromagnetic (EM) responses, creating results close to 1D inversions. To check the effectiveness, we have examined our algorithm on synthetic and survey AEM data. The imaging result shows that this method, when using reasonable network parameters, can not only image well at high speed, but the method also is not very sensitive to noise. Another advantage of this method is that once the training is completed on a well-distributed training set, the network can be used without any changes to process other data sets from an identically configured AEM system.

Improved near-surface resolution in geotechnical applications using very early AEM time gates

ABSTRACTIn a majority of geotechnical projects and in geohazard studies, knowledge of sediment thickness is crucial, along with information about sediment types such as possible occurrence of sensitive clay. We test the recently improved system response (SR) method on data from an airborne electromagnetic (AEM) survey carried out in Norway to support ground investigations for linear infrastructure projects. In geotechnical projects, especially the upper metres are important to resolve. The acquisition systems, calibration and data processing and inversion are continuously improved to increase the sensitivity of the AEM systems. SR is applied in the inversion of time-domain AEM data making it possible to utilise the very earliest time gates, which provide information about the shallower layers, aiming to increase the near-surface resolution of the models. We test this new method on data from a site where comparably small resistivity contrasts (5–10 Ωm embedded in 10–50 Ωm) are crucial to resolve, to successfully identify hazardous quick clay. The AEM field data inverted with the full SR provide models with more pronounced structures in the near surface, better reflecting true structures observed in resistivity borehole measurements. We see the same outcome when conducting synthetic modelling. In the synthetic models where these early gates were included, thinner layers with smaller resistivity contrasts are resolved. This is a promising result considering to further use AEM in projects where high resolution in the near surface is essential.

The Forrestania and Nepean electromagnetic test ranges, Western Australia – a comparison of airborne systems

SummaryElectromagnetic (EM) systems are often described with varying technical specifications and standards, making it difficult to directly compare and assess their application to practical field examples. Exemplar case studies provided by contractors, whilst highlighting system capabilities, do not necessarily help to refine the suitability of the system across different geological targets and environments. Test ranges provide an opportunity for direct and consistent comparison of multiple systems for objective assessment.The Forrestania and Nepean EM test ranges in Western Australia consist of readily accessible land, openly available for testing by airborne, ground and downhole EM systems. Multiple conductors at varying depths beneath 10-20 Siemens (S) conductive overburden provide challenging, real-world conductive targets. Surveying using different EM systems allows for a direct comparison of system detection and resolution capabilities in a conductive regolith environment. The conductors have been well defined by drilling and provide a large range of metrics available for measurement, varying from 60-400 m in depth, 5,000-10,000 S in conductance, and with variable lateral profiles and depth extents.Multiple airborne, ground and downhole EM systems have utilised these test ranges, and several have made their data freely available for review. These include ground methods such as moving loop EM, fixed loop EM, SAMSON, downhole EM, and helicopter systems including HeliSAM FLEM, SkyTEM, VTEM, HELITEM, HeliGEOTEM, XTEM, HoistEM and AeroTEM. The SPECTREM, and Xcite airborne systems plan to fly the test range in the near future. Comparison of the airborne results, show that most of the post-2007 systems have been adequate to good at detecting the shallow IR2 conductor at Forrestania under conductive regolith. Only the hybrid grounded loop HeliSAM system has successfully detected the deep IR4 conductor at Forrestania.

On the time decay constant of AEM systems: a semi-heuristic algorithm to validate calculations.

ABSTRACTThe time decay constant or “tau” of airborne electromagnetic (AEM) systems is commonly used to indicate the presence and relative conductivity or conductance of conductors in the survey area. In fact, it is not a constant because it depends on the system, the survey design and the method of calculation. The system dependence is a consequence of parameters relating to the acquisition and pre- and post-processing of the signal. Here, we propose a method for calculating tau, which is the time at which the transient voltage decays to 37%, or V37, of some initial value. The model utilises a semi-heuristic algorithm to estimate V37 for each transient in the database and then calculates the delay time at which that voltage is measured, which estimates tau. No calculation is involved with the data, instead, tau is given by a weighted average of the delay times associated with windows either side of the V37 value. We illustrate how this algorithm works using data collected using MEGATEM II at the Reid Mahaffy test site. The results show good agreement between tau-grids reported previously and those calculated using our V37 method. To account for all effects due to the acquisition and processing of EM data, the algorithm allows emphasis to be shifted away from early-time to late-time parts of the transient. It is envisaged that because this method does not apply any mathematical operation to the data it may serve as a robust means of validating other methods.

Geological significance of delineating paleochannels with AEM

ABSTRACTPaleochannels typically act as pathways for groundwater movement and provide a potential source of groundwater. Their presence can be helpful in identifying areas suitable for recharge and at times in mitigating contamination problems in afflicted regions. Thus, mapping of paleochannels is significant in the planning and management of groundwater resources. An airborne electromagnetic (AEM) system employing dual pulse moments has been used extensively for this purpose in India. This paper presents the results over paleochannels defined in three different terranes. In northwest India, a 100 m wide by 80 m deep paleochannel within alluvium overlaying a Proterozoic basement illustrates the impact of neotectonic disturbances in changing the river course. In northeast India’s Ganga Plains, a paleochannel is mapped that provides insight into managing groundwater resources of areas polluted with arsenic. In south India, a paleochannel buried under ∼ 100 m thick sequence of coastal sediments is imaged with implications on submarine groundwater discharge.

The frequency-domain airborne electromagnetic method with a grounded electrical source

For surveys in areas with difficult access, ground-based electromagnetic (EM) systems are difficult to operate, time-consuming, and expensive, whereas airborne EM (AEM) systems are unsafe and uneconomic for small survey areas. We have developed a new frequency-domain airborne electromagnetic (FAEM) system called the ground-airborne frequency-domain EM (GAFEM) system to achieve rapid data acquisition in complex terrains with high safety and low cost. The system consists of a grounded electrical source and an airborne receiver carried by an unmanned rotorcraft. The grounded electrical source transmits a [Formula: see text] pseudorandom series obtaining signals at [Formula: see text] frequencies in one flight, which can maintain the resolution without reducing efficiency. The airborne receiver based on the unmanned rotorcraft makes the system flexible, convenient, and economical to operate in areas with difficult access. The system can conduct surveys in far- and non-far-field regions and can obtain the apparent resistivity to present a quick overview of the subsurface structure. To demonstrate the GAFEM system’s effectiveness and practical detection potential, we have performed two field surveys that revealed the shallow structure with tunnels and the deep structure at source-receiver distances of 3 and 6 km, respectively. The GAFEM system effectively revealed the apparent-resistivity difference with a sufficient investigation depth at large source-receiver distances. Thus, the system can be extended to various important applications for rapid surveys or deep investigations in areas with difficult access.

Calculation and application of full-wave airborne transient electromagnetic data in electromagnetic detection

Airborne electromagnetic transient method enjoys the advantages of high-efficiency and the high resolution of electromagnetic anomalies, especially suitable for mining detection around goaf areas and deep exploration of minerals. In this paper, we calculated the full-wave airborne transient electromagnetic data, according to the result of numerical research, the advantage of switch-off time response in electromagnetic detection was proofed via experiments. Firstly, based on the full-wave airborne transient electromagnetic system developed by Jilin University (JLU-ATEMI), we proposed a method to compute the full-waveform electromagnetic (EM) data of 3D model using the FDTD approach and convolution algorithm, and verify the calculation by the response of homogenous half-space. Then, through comparison of switch-off-time response and off-time response, we studied the effect of ramp time on anomaly detection. Finally, we arranged two experimental electromagnetic detection, the results indicated that the switch-off-time response can reveal the shallow target more effectively, and the full-waveform airborne electromagnetic system is an effective technique for shallow target detection.

Resolving Changes to Freshwater Lens Systems in a “Sea of Salinity” using Multi-date Airborne EM

Saline aquifers in the Murray River or SE Australia are traversed by freshwater rivers, with adjoining riparian and floodplain regions containing freshwater lenses. Bore data and more recent Airborne electromagnetic (AEM) surveys have determined that these lenses are spatially extensive, but have widely varying geometries. The maintenance of these lens systems is important as they support ecologically significant riparian vegetation communities such as Red Gum and Black Box. A more complete understanding of their hydrogeology is required to ascertain how they develop and degrade. Limited ground investigations including 14C geochemistry have determined that the lens systems contain recent water, indicating that they are dynamic systems with their development defined by the relative rates of recharge from the river and mixing with groundwater. Changes in groundwater gradients and depth, floodplain extent, and topography are believed to control their initial location. The same controls also govern their stability.The potential of AEM systems for defining the geometry of these lens systems in 3D is considered along with an assessment of their value for monitoring variations associated with these ecosystems. The advent of “calibrated” AEM systems and robust inversion tools have given added impetus to their use for environmental monitoring. Spatio-temporal variations are observed in the near surface (top 20m) from a multi-temporal assessment of Clark’s Floodplain, adjacent to the Bookpurnong irrigation area, with co-incident AEM surveys acquired between 2008 and 2015. Spatial changes in ground conductivity, attributed to changing groundwater quality have been observed. The freshwater lens systems appear to have contracted significantly over the last decade. This is attributed, in part, to land use patterns and the development of an irrigation-related groundwater mound on the highlands adjacent to the floodplain, and an increased hydraulic gradient towards the river. The results indicate the geometry of the hyporheic zone may have also changed along the river.