Airborne Electromagnetic Methods Research Articles

Physics-guided deep learning-based inversion for airborne electromagnetic data

SUMMARY The Earth's subsurface structure provides critical insights into sustainable resource management and geologic evolution. The airborne electromagnetic (AEM) method is an efficient data acquisition technique and can be used to image the underground resistivity structure with high spatial resolution. However, inversion of the increasingly huge volume of AEM data poses a heavy computational burden. In this study, we develop a hybrid deep learning-based approach by using the physics-guided neural network (PGNN) which incorporates the governing physical laws into the loss function to solve the AEM inverse problem. The PGNN integrates the strength of data-driven method for representation learning with electromagnetic laws and allows for the underlying physical constraints to be strictly satisfied. We validate the effectiveness of our approach using both synthetic and field datasets. Compared with the classic Gauss–Newton method, our PGNN inversion system shows strong robustness against multiple noise sources and reduces the risk of being trapped in local extrema. Moreover, the PGNN-inverted results are physically more consistent with the AEM observations compared to the purely data-driven approach. Application to the field AEM data from Northern Australia demonstrates that the PGNN-based inversion framework effectively estimates the subsurface electrical properties with considerable lateral continuity and significantly higher efficiency, completing the inversion of more than 2734000 AEM soundings taking only minutes on a common PC. Our proposed PGNN-based method shows great promise for large-scale underground resistivity imaging, and the well-identified subsurface resistivity structure can effectively improve our understanding of resource distributions and geological hazards.

High-order finite-element forward-modeling algorithm for the 3D borehole-to-surface electromagnetic method using octree meshes

The borehole-to-surface electromagnetic (BSEM) method complements surface and airborne electromagnetic (EM) methods. The borehole is typically filled with conductive media, which significantly impacts the responses. To accurately simulate the responses, the borehole needs to be modeled. However, the size of the borehole is very small compared with the entire computational domain, making it challenging to discretize the borehole accurately. We develop a high-accuracy 3D finite-element forward-modeling algorithm for the BSEM method using octree meshes. The basic idea of octree meshes is to locally refine the mesh by dividing the hexahedral element into eight smaller elements. This approach has the advantage of being able to accurately discretize small geometric features while using coarse meshes in other areas, thus reducing the computational cost. In addition, high-order basis functions are used to improve the accuracy of numerical solutions. We develop a 3D forward-modeling code for BSEM using the C++ programming language. We verify the correctness and accuracy of our implementation by comparing the numerical responses with analytical solutions. Furthermore, we determine the influence of the borehole on the EM responses, showing that the borehole will cause a decrease of several orders of magnitude in the responses when the borehole is filled with highly conductive media. We also use two 3D models to demonstrate the efficacy of octree meshes in the discretization of complex structures and to discuss the effectiveness and sensitivity of BSEM data in the exploration of mineral and oil-gas resources. The code is open source under the Massachusetts Institute of Technology license and can be used as an accurate modeling tool for BSEM responses, providing useful guidance for field exploration. The code is designed with a modular architecture, ensuring ease of maintenance and the ability to extend to other EM methods and serve as the foundation for 3D inversion.

Comparative analysis of divergence of tipper imaging with natural and orthogonal electric sources

ABSTRACT The divergence of the tipper (DT) is an important imaging method characterized by fast imaging speed and high lateral resolution. It has been recently adopted from the natural source airborne electromagnetic method to the orthogonal electric sources ground-airborne frequency-domain electromagnetic method. However, the imaging characteristics and patterns of DT in the two methods are unclear due to significant differences in the sources used. The application of DT in ground-airborne frequency-domain electromagnetic method is limited. Therefore, this study first identifies the similarities and differences between the two methods from the theory. Furthermore, based on the same simulation model, the response characteristics of the DT excited by natural and orthogonal electric sources are investigated. The similarities and differences between the two methods are clarified. It will contribute to the rapid development and application of the DT imaging in ground-airborne electromagnetic detection method.

A Footprint-Guided Algorithm for 3-D Simulation Based on BEM of Topography Effect in Frequency-Domain Airborne Electromagnetic Method

A Footprint-Guided Algorithm for 3-D Simulation Based on BEM of Topography Effect in Frequency-Domain Airborne Electromagnetic Method

Application Prospect of Airborne Electromagnetic Method in Engineering Exploration

Airborne electromagnetic method has developed rapidly since the twentieth century and has been maturely applied to uranium and polymetallic mineral exploration and railroad engineering survey in China. Engineering survey is an important foundation to guarantee the construction of cities and infrastructure in China, Further exploration of the introduction of airborne electromagnetic method in engineering survey can greatly promote the process of engineering construction in China and guarantee the strategic needs of national key projects.

Study on the Three-component Response Characteristics of Ground-airborne Electromagnetic Field

At any point in space, an electromagnetic field consists of three components: Hx, Hy, and Hz. The ground airborne electromagnetic method (GAEM) does not usually retrieve the Hx and Hy components of the electromagnetic field, less data may result in less accurate goaf interpretations. In this study, we numerically simulate the characteristics of the frequency-domain ground-airborne electromagnetic signal sources, quantify the induction signal distribution laws in the x-, y-, and z- directions, and identify the various factors that influence ground-airborne electromagnetic signals. The results of this study provide theoretical support for the future development of a three-component receiver for ground airborne electromagnetic field surveys. Furthermore, this data also provides information that will prove valuable in the design of field work construction.

Application of Helicopter-Borne and Ground–Airborne Electromagnetic Detection to Tunnel Engineering Investigation

The Cedaya-S340 Holgutu Highway Construction Project is located in the Mongolian Autonomous Prefecture of Bayingolin in the Xinjiang Uygur Autonomous Region. It is an important traffic channel that connects Luntai County and Hejing County at the southern foot of Tianshan Mountains. As the major component of the highway project, the Huola Mountain Tunnel has a sharp topographic relief, and, therefore, commonly used land geophysical detection instruments cannot work on it. Therefore, we conducted a qualitative survey on the ground-to-air and airborne electromagnetic detection methods used at the Huola Mountain Tunnel site to provide basic data for the design of highway tunnels. The geophysical survey summarized the ground–airborne frequency-domain electromagnetic method (GAFEM) and the helicopter-borne time-domain electromagnetic method (HTEM) developed by Jilin University, and measured 15 measuring lines. Apparent resistivity imaging was performed for each section, and the results were consistent. This study comprehensively analyzed the apparent resistivity profile and geological mapping data. Then, the study inferred the major stratigraphic boundaries, fault fracture zones, rock fragmentation, weakness, karst development, and water content in accordance with background value, low-resistivity anomaly shape, low-resistivity anomaly value, and gradient value in the apparent resistivity profile. Finally, the study identified the scope of two main low-resistivity anomalies, located at the tunnel entrance and exit, respectively, which are basically consistent with the known fault location. The results of this study show that on the basis of the apparent resistivity maps of GAFEM and HTEM, the overall distribution law is basically consistent with site landform, hydrogeology, tectonic geology, and aerial image data. The results provide guidance for the construction of the Huola Mountain Tunnel and ensure the construction safety and progress of the tunnel.

3D joint inversion of airborne ZTEM and ground MT data using the finite element method with unstructured tetrahedral grids

As an airborne electromagnetic method induced by natural sources, the Z-axis tipper electromagnetic (ZTEM) system can primarily recover near-surface shallow structures, due to band-limited frequencies (usually 30–720 Hz) of the airborne survey and high sample rate acquisition along the terrain. In contrast, traditional ground magnetotellurics (MT) allows better recovery of deep structures as the data acquired are typical of large site intervals (usually higher than 1 km) and lower frequencies (usually lower than 400 Hz). High-resolution MT surveys allow for shallow small and deep large anomalies to be adequately interpreted but need large site intervals and broadband frequency range, which are seldom used as they are quite costly and laborious. ZTEM data are tippers that relate local vertical to orthogonal horizontal fields, measured at a reference station on the ground. As the 1D structures produce zero vertical magnetic fields, ZTEM is not sensitive to background resistivity. Thus, in general, ZTEM can only reveal relative resistivities and not real resistivities. A combination of the ZTEM and MT methods can be an effective technique, alleviating the shortcomings of the individual methods. At present, complex underground structures and topography introduce difficulties for data inversion and interpretation, as conventional ZTEM and MT forward modeling are generally used on structured grids with limited accuracy. To effectively recover complex underground structures with topography, we developed a 3D framework for joint MT and ZTEM inversion with unstructured tetrahedral grids. The finite element method is used for the forward problem because of its flexibility with unstructured tetrahedral meshes. The limited-memory quasi-Newton algorithm (L-BFGS) for optimization is used to solve the joint inverse problem, which saves memory and computational time by avoiding the explicit calculation of the Hessian matrix. To validate our joint inversion algorithm, we run numerical experiments on two synthetic models. The first synthetic model uses two conductive anomalous bodies of different sizes and depths. At the same time, a simple quadrangular is used for comparing the inversions with and without topography. In contrast, the second synthetic model represents a realistic topography with two different conductivities and the same depth. Both single-domain and joint inversions of the ZTEM and MT data are carried out for the two synthetic models to demonstrate the complementary advantages of joint inversion, while the second model is also used to test the adaptability of the joint inversion to complex topography. The results demonstrate the effectiveness of the finite element method with unstructured tetrahedral grids and the L-BFGS method for joint MT and ZTEM inversion. In addition, the inversion results prove that joint MT and ZTEM inversion can recover deep structures from the MT data and small near-surface structures from the ZTEM data by alleviating the weaknesses of the individual methods.

Two-dimensional fast imaging of airborne EM data based on U-net

As an efficient geophysical exploration tool, the airborne electromagnetic (AEM) method has been widely used in mineral exploration, geological mapping, environmental and engineering investigation, etc. Currently, the imaging and 1D inversions are the mainstream means for AEM interpretation as the amount of AEM data is huge and 2D and 3D inversions are not efficient. In this paper, we propose a 2D fast imaging method for frequency-domain AEM data based on U-net network. The U-net is a symmetric full-convolution neural network, in which the partial pooling operation between the convolution layers is replaced by the up-sampling operation, while the target location is achieved by skipping connection. This method does not need to consider the complex coupling between the EM responses and underground structures, but instead it establishes a mapping relationship between EM responses and the resistivity model and can quickly achieve accurate imaging of AEM data. We use this network to image both synthetic and field survey data and compare the results with the traditional inversion algorithms. The results show that the U-net imaging have high resolution at high speed that provides a new way for interpreting large amounts of AEM data.

Modelling the electromagnetic response of a sphere located in a layered earth

Estimating the electromagnetic response of a conductive sphere in a layered earth is of great interest in terms of both modelling and interpretating data acquired via geophysical electromagnetic methods where the target is at some distance from the source and receiver. This is particularly the case when using Airborne Electromagnetic Method (AEM) where the source and receiver are located at some height above the subsurface. This problem can be solved by utilising field expansions representing derivatives of cylindrical functions, which describe the fields propagating in the layered earth, and spherical functions, which describe the fields reflected by the sphere. Furthermore, these representations allow the development of relationships between cylindrical and spherical functions. These functions and subsequent relationships have been used to develop an algorithm for estimating the electromagnetic response of a conductive sphere in an isotropic layered earth. Software based on this algorithm has been tested on both synthetic and field data. The field data presented were collected with the AEM AirTEM system over the Reid-Mahaffy test site, Ontario, Canada. Results from these tests prove the importance and utility of integrating the sphere in a layered earth model in the AEM interpretation toolbox.

Airborne geophysical method images fast paths for managed recharge of California’s groundwater

Given the substantial groundwater level declines in the Central Valley of California, there is an urgent need to supplement the recharge of the groundwater systems by implementing managed aquifer recharge. With approximately 170 km3 (140 million acre-feet) of available groundwater storage space, water deemed to be excess during wet years could be spread on the ground surface at selected locations allowing it to move downward to recharge the underlying aquifer system. Along the eastern edge of the Central Valley there are large paleovalleys that can act as fast paths expediting the downward movement of water. These paleovalleys, incised and then filled with coarse-grained materials—sand, gravel, cobbles—at the end of the last glacial period, are referred to as incised valley fill (IVF) deposits. An IVF deposit has been mapped at one location in the Kings River alluvial fan, with others proposed to exist in the fans of major rivers. If located, these deposits would be optimal sites for managed recharge. In this study, we assessed the use of a helicopter-deployed geophysical method to efficiently locate IVF deposits throughout the Central Valley. We acquired 542 line-kilometers of airborne electromagnetic (AEM) data in the Kings River alluvial fan, with dense line-spacing over the Kings River IVF deposit which had been mapped as ∼2 km wide, extending over 20 km into the Central Valley, from the ground surface to a depth of 30 m. The IVF deposit was unambiguously imaged in the AEM data as an extensive linear feature that was more electrically resistive than the surrounding materials due to the high percentage of coarse-grained sediments. This study provides the evidence to support the rapid adoption of the AEM method to locate IVF deposits along the eastern edge of the Central Valley. These deposits provide valuable natural infrastructure for recharging California’s groundwater.

Application of Time-Domain Airborne Electromagnetic Method to the Study of Qingchengzi Ore Concentration Area in China

Qingchengzi is an important polymetallic mineral concentration zone in China. However, long-term mining has led to the depletion of proven reserves in the Qingchengzi ore concentration zone. Therefore, it is necessary to carry out prospecting in the periphery of the existing ore bodies. Taking into account the complex surface conditions of the Qingchengzi mining area, we carried out an airborne time-domain electromagnetic survey in this region and obtained a high-precision underground resistivity model which covers the whole area. The quasi-3D inversion result shows a good agreement with the surface geological information. After analyzing the relationship between the underground geological structures and the resistivity model, we constructed a geological model with the distribution of the main strata, the rock masses and the faults. The reconstructed resistivity distribution of the entire region added new knowledge to understand the geology of the Qingchengzi survey area.

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.

Instantaneous Inversion of Airborne Electromagnetic Data Based on Deep Learning

AbstractThe airborne electromagnetic (AEM) method is becoming an effective means for subsurface electrical property reconstruction with the merits of terrain adaptability and acquisition efficiency. However, instantaneous inversion of time‐domain AEM data is still a challenge, owing to the huge amount of data. Inspired by Google's neural machine translation system, we develop a fast inversion operator guided by deep learning to translate time‐domain AEM measurements directly into subsurface resistivity structures. Trained by synthetic data, our system shows impressive adaptability to field observations and strong robustness against noise disturbance. Applied to the AEM data set acquired by the U.S. Geological Survey in Leach Lake Basin, CA, USA, our system successfully delivers results in seconds for a common PC from more than 740,000 AEM soundings. The inverted structures clearly delineate the geometries of the lake, surrounding mountains and faults. The inversion operator can support instantaneous subsurface resistivity reconstruction for AEM observations.

Constructing the resistivity-to-sediment-type transform for the interpretation of airborne electromagnetic data

A novel Markov chain Monte Carlo (MCMC)-based methodology was developed for the transformation of resistivity, derived from airborne electromagnetic (AEM) data, into sediment type. This methodology was developed and tested using AEM data and well sediment type and resistivity logs from Butte and Glenn Counties in the California Central Valley. Our methodology accounts for the spatially varying sensitivity of the AEM method by constructing different transforms separated based on the sensitivity of the AEM method. The large spatial separation that typically exists between the AEM data and the wells with sediment type logs was avoided by planning the acquisition of AEM data so as to fly as close as possible to the well locations. We had 55 locations with sediment type logs and AEM data separated by 100 m, determined to be the maximum acceptable separation distance. Differences in vertical resolution between the AEM method and the sediment type logs were addressed by modeling the physics of the AEM measurement, allowing for a comparison of field and AEM data generated during the MCMC process. The influence of saturation state was captured by creating one set of transforms for the region above the top of the saturated zone and another for below. Using the set of transforms developed at the 55 locations, an inverse distance weighting scheme that included a well quality ranking was used to construct a set of 12 (six sensitivity bins, and two saturation states) resistivity-to-sediment-type transforms at every AEM data location. These represent a set of transforms that accommodate the variation in AEM sensitivity and are independent of the inversion used to retrieve the resistivity model. Thus, these transforms avoid two of the significant limitations common to resistivity-to-sediment-type transforms used to interpret AEM data.

Drone-based electromagnetic survey system for geophysical applications

Geophysical electromagnetic (EM) methods are used in geological mapping, mineral exploration, groundwater studies and geotechnical investigations. Airborne EM methods have the benefit of avoiding terrain obstacles such as lakes, rivers, swamps, and ravines. Compared to manned aircrafts, drones or unmanned aerial vehicles (UAVs) have benefits of their own. Drone-based surveys are versatile, fast to deploy, economical and ecologically more friendly. Presently, magnetic surveying is the only geophysical method that is routinely conducted with drones. The modest maximum payload limit of drones imposes severe restrictions on the applicability of other methods including EM and radiometric methods, for example. Finnish company, Radai Ltd has been developing Louhi, a novel drone-based frequency-domain EM survey system, in an EU funded Horizon 2020 project NEXT – New Exploration Technologies. The EM system has two operation options – the first uses a large loop on the ground as an EM source and the other uses a small portable EM transmitter loop. Both systems utilize a stand-alone and light-weight three-component EM receiver that can be towed by a drone. This article presents the theoretical background of the EM methods, the solution developed by Radai Ltd, the current version of the EM device, and results from field and flight tests that demonstrate the applicability of the drone-based EM system under development.

3-D Inversion of Z-Axis Tipper Electromagnetic Data Using Finite-Element Method With Unstructured Tetrahedral Grids

<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Z$ </tex-math></inline-formula> -axis tipper electromagnetic (ZTEM) technique is an airborne electromagnetic method that detects anomalies in the deep earth that are induced by natural sources. Conventional ZTEM forward modeling is generally conducted using structured grids that have limited accuracy and cannot be used to invert complex underground structures and topography. However, unstructured grids can accurately model complex underground structures with fewer cells. Therefore, to effectively model and recover the complex underground structures, we developed a 3-D framework with unstructured tetrahedral grids for ZTEM forward modeling and inversions. The forward problem was formulated using the finite-element method with unstructured tetrahedral grids. To solve the inverse problem, we used a limited-memory quasi-Newton algorithm (L-BFGS) with a parallel direct solver for optimization in order to avoid the explicit calculation of the Hessian matrix and save the memory and computational time. To validate our forward and inversion algorithms, we conducted numerical experiments on three synthetic models and inverted a survey dataset acquired for a tunnel project in Tibet, China. The experimental results demonstrate the effectiveness of our unstructured finite-element and L-BFGS method for modeling and inverting ZTEM data.

3D nonlinear conjugate gradient inversion for frequency-domain airborne EM based on vector finite element method

The 3D inversion is a challenging task in the research of the frequency-domain airborne electromagnetic (AEM) method due to the massive amounts of data and limited computational efficiency. In this paper, we introduce the 3D FAEM inversion based on the vector finite element method (FEM). Compare with the traditional nodal FEM, the vector FEM can improve the computational efficiency by reducing the number of variables and the scale of linear equations. To tackle the computational demands, in the calculation process we apply the PARDISO solver with shared-memory distributed-memory multi-processors to solve the multi-source forward linear equations and calculate the gradient of the objective function by adjoint equations. Then typical resistivity model with the anomalous body is carried out to verify the validity of the proposed method. Meanwhile, in allusion to the multi-solution problem caused by the inversion problem, we study the influence of typical initial models on inversion results. Finally, we applied our algorithm to invert field data. The inversion results demonstrate that the proposed method can obtain reliable AEM resistivity inverted results.

3D inversion of large-scale frequency-domain airborne electromagnetic data using unstructured local mesh

Airborne electromagnetic (AEM) methods have been more and more widely used in mineral exploration, environmental and engineering studies, and ground water investigation. However, compared with ground-based electromagnetic (EM) methods, such as magnetotelluric or controlled-source EM, AEM methods generally produce large amounts of data, which leads to very costly 3D EM inversions. We have developed a new 3D AEM inversion scheme based on the finite-element method and unstructured tetrahedral local meshes. This is different from the traditional local mesh method in that the traditional method uses regular cuboids for 3D AEM inversions, whereas our scheme uses irregular tetrahedral meshes that can easily accommodate the topography and complex underground structure. Moreover, because we create our local mesh by extracting from part of the global model mesh, the relationship between the local and global meshes is straightforward, so we can easily create a projection of the Jacobian matrix between global and local meshes and rapidly construct the global Jacobian matrix for 3D EM inversions. After formulating the boundary value problem based on the finite-element method, we verify the accuracy of our modeling algorithm by checking against the semianalytical solution for a homogeneous half-space model, and we test our inversion algorithm by running inversions on synthetic and survey data collected over Vesterålen, Norway. The numerical experiments demonstrate that our method can model the AEM responses at high accuracy and recover the subsurface main resistivity structures from synthetic and field data.

Stratigraphic identification with airborne electromagnetic methods at the Hanford Site, Washington

Stratigraphic units can influence the fate and transport of subsurface contaminants within groundwater. Units having coarse-grained sediments act as preferential flow pathways, and therefore can accelerate the transport of contaminants to reach human and ecological receptors. At legacy waste sites, detailed knowledge of subsurface stratigraphy can be used for effective monitoring and remediation planning to help minimize risk to human health and the environment. Airborne electromagnetic (AEM) methods can non-invasively provide information on kilometer-scale or larger subsurface stratigraphic features and fill informational gaps in directly sampled data from sparsely located boreholes. In this paper, we present inversion results of a 412 line-km frequency-domain AEM survey to delineate subsurface stratigraphic features at the Hanford Site, located in southeastern Washington State. The inversion was performed using a massively parallel 3D electromagnetic modeling and inversion code, where the modeling is based on solving frequency-domain Maxwell's equations using an unstructured-mesh finite-element method and the inversion employs a Gauss-Newton optimization scheme. The results are compared to an underlying geologic framework model (GFM), built by interpolating contact depths of stratigraphic units interpreted from site borehole datasets. In areas with good borehole coverage, the inversion results show a good match with the GFM to a depth of about 60 m. Outside of these areas, the inversion results exhibit inconsistencies from the assumptions made to create the GFM, demonstrating that the AEM survey results can be used to improve the understanding of the geological conceptual model.