Airborne Electromagnetic Inversion Research Articles

3D airborne electromagnetic data inversion based on the block coordinate descent method

Airborne electromagnetic (AEM) surveys usually cover a large area and create a large amount of data. This has limited the application of 3D AEM inversions. To make 3D AEM data inversion at a large scale possible, the local mesh method has been developed to avoid solving large matrix equations in 3D AEM modeling. However, the local mesh only saves the computational cost and memory during forward modeling and Jacobian calculations. When the survey area is very large, the cost for storing and solving the inversion equations can be very high. This brings significant challenges to practical 3D AEM inversions. To solve this problem, we develop a 3D scheme based on the block coordinate descent (BCD) method for inversions of large-scale AEM data. The BCD method divides the inversion for large models into series of small-local inversions, so that we can avoid solving the large matrix equations. Numerical experiments determine that the BCD method can obtain very similar results to those from the existing inversion methods but saves huge amounts of memory.

Exploring geothermal resources using electromagnetic methods in coastal areas of volcanic islands: Challenges of nearshore and land 3D controlled-source electromagnetic data

Three-dimensional geophysical exploration is essential in identifying favorable areas and derisking high-temperature geothermal projects. In particular, electrical resistivity imaging plays a key role in this exploration due to its sensitivity to the presence of alteration products, geothermal fluid circulation, and temperature. As 3D seismic exploration is rarely effective in volcanic environments, resistivity methods such as magnetotellurics (MTs) are often used to extract deep structural information. However, deep electromagnetic (EM) imaging in coastal areas of volcanic islands with MT can be challenging due to anthropogenic noise induced by urbanized areas concentrated around the coast. The use of active EM sources, such as airborne EM (AEM) and controlled-source EM (CSEM), as a complement to MT is a solution for overcoming anthropogenic noise. However, applying these methods in this context is still challenging due to the proximity to the sea/land interface, large variations in topography and nearshore bathymetry, and the heterogeneity of the near surface. Our approach outlines the challenges of acquiring, processing, and inverting nearshore and land 3D CSEM data in such complex environments. The CSEM data are part of a multimethod geothermal exploration on the island of Martinique in the French West Indies, and its 3D inversion result is compared with the previous regional 3D MT and AEM inversion results. In addition to MT, CSEM may highlight the location of a potential high-temperature paleo-reservoir at shallow depths under the urbanized area of Petite-Anse covered by a paleo-clay cap ranging from a few meters to several hundred meters in thickness. We conclude by proposing possible improvements for CSEM and multimethod methodologies to obtain more reliable exploratory models.

Three-Dimensional Separate and Joint Inversions of Multi-Component Frequency-Domain Airborne Electromagnetic Data: Synthetic Model Studies.

Airborne electromagnetic (AEM) surveys using airborne mobile platforms enable rapid and efficient exploration of areas where groundwork is difficult. They have been widely used in fields such as shallow resource exploration and environmental engineering. Three-dimensional AEM inversion is the main technique used in fine structural interpretation. However, most current methods focus on separate component data inversions, which limit the kinds of structures that can be recovered in the inversion results. To address this issue, a method for the robust 3D joint inversion of multicomponent frequency-domain AEM data was developed in this study. First, a finite element method based on unstructured tetrahedral grids was used to solve the forward problem of frequency-domain AEM data for both isotropic and anisotropic media. During inversion, a limited-memory quasi-Newton (L-BFGS) method was used to reduce the memory requirements and enable the joint inversion of large-scale multicomponent AEM data. The effectiveness of our algorithm was demonstrated using synthetic models for both isotropic and anisotropic cases, with 5% Gaussian noise added to the modeling data to simulate the measured data for separate and joint inversions. The results of the synthetic models show that joint inversion has advantages over separate inversion in that it enables the recovery of finer underground structures and provides a novel approach for the fine interpretation of frequency-domain AEM data.

Three-Dimensional Airborne Electromagnetic Data Inversion With Flight Altitude Correction

The flight altitude has a large effect on the airborne electromagnetic (AEM) responses. Due to the dynamic environment of the aircraft, the recorded sensor altitudes may contain errors. Research demonstrates that the AEM responses caused by a several meters altitude errors can be larger than caused by some anomalous body. Ignoring these errors will create erroneous results in AEM data interpretation. Considering that there is not yet a published 3D AEM inversion method that takes into account the flight altitude, we develop in this paper a 3D inversion algorithm for AEM with the flight height treated as an inversion parameter. For the forward modeling we use the finite element method, while for the inversion we use the Gauss-Newton optimization method. To make our inversion works for variable flight altitudes, we propose a scheme of 3D Jacobean matrix calculation for both the resistivities and flight altitudes without much increasing the computational cost. The numerical simulation result confirms that the flight altitude really has a large effect on the AEM responses. The inversions of synthetic data show that our 3D inversion method can both recover the resistivity distribution in the underground and decrease the altitude errors recorded, while the field data inversion demonstrates that our method can deliver a better inversion model with a smaller data misfit.

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.

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.

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.

Sparse-Promoting 3-D Airborne Electromagnetic Inversion Based on Shearlet Transform

The conventional, L2-norm-based, regularization term in electromagnetic (EM) inversions implements smooth constraints on model complexity in the space domain, which can smoothen the boundaries of complex underground structures. To improve the resolution of 3-D frequency-domain airborne EM (AEM) inversions, we propose a new algorithm for sparse-regularized inversion based on the shearlet transform. Unlike traditional methods that invert the model parameters in the space domain, we first transform the 3-D resistivity model into the frequency domain and then invert the sparse coefficients using an L1-norm measure to ensure the sparseness of the solution. Finally, we transform the shearlet coefficients back to the space domain to update the model. The shearlet transform has inherent multiscale and multidirectional properties, making it capable of effectively extracting complex geometries such as curved boundaries. We adopt the finite-difference method and the iteratively reweighted least-squares scheme for our 3-D AEM modeling and inversions and apply the “moving footprint” technique to speed up the inversion. Tests using synthetic data show that sparse-regularized inversion based on the shearlet transform can obtain more-focused inversion results than conventional smoothness-constrained inversions based on the L2-norm. Tests using field survey data also reveal that the new method can achieve more realistic underground structures.

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.

2.5D Airborne Electromagnetic inversion: A review of the benefits of moving to a higher dimension

Intrepid Geophysics began operating a 2.5D Airborne Electromagnetic (AEM) inversion service in early 2016, following two years of software development by Intrepid Geophysics and Jovan Silic, the pr...

Using machine learning to interpret 3D airborne electromagnetic inversions

Although 3D airborne electromagnetic inversions have improved greatly in recent years, the presence of smooth boundaries has often been a strong criticism. This smoothness can easily be remedied by...

Large Scale 3D Airborne Electromagnetic Inversion - Recent Technical Improvements

3D airborne electromagnetic (AEM) inversion has routinely been applied to frequency and time-domain problems over the past few years, however this research field continues to undergo rapid improvements with the implementation of new ideas and faster computational resources. To keep pace with these developments, we have rewritten our 3D AEM inversion software suite to leverage the rapid growth in parallel processing, and to create a flexible inversion framework capable of standard inversion plus many additional types: joint, cooperative or parametric, all on semi-structured octree meshes. Our resulting framework further improves recent key ideas such as the decoupling of forward meshes from the inverse mesh, to allow the forward problem to be easily distributed on separate nodes of a cluster for fast and efficient modelling of the fields.We present two large-scale field examples, one in the frequency domain and one in the time domain. The frequency domain survey demonstrates our ability to recover thin conductors, in this case representing orogenic gold targets, across a large region (40km x 35km). The time domain example focuses on a smaller area within a larger survey area where mapping groundwater resources is the primary goal. Here the fine-scale results are compared to a 1D inversion, and we see a good correlation between the 3D and 1D results due to an approximately 1D layered-earth environment. However we see a removal of 1D artifacts in the neighbourhood of vertical conductors and topographic changes in the 3D result with the added bonus of information between lines in which decisions regarding groundwater management can be made.

3D Inversion of Large Scale Marine Controlled-Source Electromagnetics

Three-dimensional controlled-source electromagnetic (CSEM) surveys can be a useful technique for oil and gas hydrate detection in marine environments. Electromagnetic waves are emitted from sources, and the ensuing electric and/or magnetic fields are recorded at one, or more receivers. The number, frequency, and position of sources and the placement of receivers depends on the particular application. The solution of an inverse problem is required to recover the earth’s conductivity, which can be either isotropic or anisotropic in nature.A major issue with either an isotropic or anisotropic CSEM inversion is the computational cost associated with the solution of many linear systems of equations. This is a result of a large spatial domain potentially containing complicated bathymetry, as well as the existence of thousands of source and frequency combinations. Overall, there could be thousands or even millions of systems of equations to solve on expansive meshes. To assist with these numerical issues, we use ideas developed for airborne electromagnetic inversions. First, we incorporate a locally refined mesh for the forward problem, specifically optimized for a source and set of receivers. Second, we use stochastic programming techniques to solve the CSEM problem with many sources and receivers. These methods dramatically reduce the numerical cost of each forward model as well as the total number of simulations. In this work we describe the methods used to overcome these computational difficulties.

Characterising the Subsurface Architecture and Stratigraphy of the McArthur Group through Integrated Airborne EM and Gravity Inversion

The Caranbirini sediment-hosted Zn-Pb-Ag prospect is located west of the Emu Fault, ~20 km north of McArthur River Mine (formally HYC), within the Batten Fault Zone of the McArthur Basin (Northern Territory). The Caranbirini area exposes stratigraphy from McArthur Group and shows some structural complexity with post-depositional folding and faulting. In order to better characterize the subsurface basin architecture we combine structural, sedimentological, and stratigraphic interpretations with 3D gravity inversion, and a 1D airborne electromagnetic inversion. Results are integrated to build a 3D model of the subsurface basin architecture, and identify prospective stratigraphy such as the Barney Creek Formation. 3D gravity inversions were performed using a preliminary 3D geological model of the project area as a reference model for a constrained property inversion. The gravity inversion identified an anomalous density zone immediately west of the Emu Fault. Interpretation of the inverted AEM data provided stratigraphic constraint for the geological model by defining the depth and geometry of the Barney Creek Formation. They also indicated the presence of several N-S trending faults to the west of the Emu Fault coincident with the western boundary of the anomalous density zone. The interpretation suggests that the depth to the Barney Creek Formation increases westwards of the Emu Fault. We interpret the increase in depth to the Barney Creek Formation, in combination with the zone of increased density as a fault-bounded sub-basin, bounded in the west by a paleo-high. Recognition of the sub-basin and controlling faults has implications for targeting Zn-Pb-Ag mineralization.

Rate of success for a groundwater drilling program planned from AEM, Gascoyne River, WA

In a collaboration between Department of Agriculture and Food, Western Australia (DAFWA) and CSIRO, funded by the Western Australia Government's Royalties for Regions Program and the Gascoyne Foodbowl Project, the Gascoyne River AEM Aquifer and Groundwater Characterization Project was established with the aim of determining whether airborne electromagnetic (AEM) data can be employed to better map attributes of the unconfined alluvial aquifer beneath and adjacent to the ephemeral Gascoyne River. One major aspect of the project was to produce drilling targets, based on interpretation of AEM data, for groundwater production. In this presentation, we briefly recapitulate our method and discuss the result of the drilling campaign that ensued. We show that our exploration targets have resulted in overwhelming success in the conversion of exploration wells to production bores; and that the production wells produce greater yields of better quality groundwater than previous campaigns that were conducted through step-out drilling. We show that interpretation of the AEM inversions allowed us to map the aquitard layers that define the bottom of the Gascoyne River Old Alluvium aquifer system, determine the extent of the saltwater intrusion from the nearby Indian Ocean, and to calculate the overall volume of the aquifer system. These calculations allow us to provide estimates of total groundwater volume contained in the aquifer for sustainable production.

Comparative Evaluation of 1D, 2.5D and 3D Inversions for Resolving Tectonic Elements in Floodplains and Near-Surface Inverted Sedimentary Basins

This study reports the results of a comparative evaluation of 1D, 2.5D and 3D AEM inversions for resolving hydrostratigraphy and structural elements in two contrasting settings: unconsolidated Quaternary floodplain sediments affected by Neogene deformation; and a tectonically inverted Palaeozoic sedimentary basin.Previous studies have demonstrated the importance of airborne electromagnetic (AEM) data optimization to ensure that key elements of the hydrogeological system, including geological faults, are appropriately represented in inversion models. In the inverted sedimentary basin study, 1D inversions of AEM data indicated greater structural complexity than previously known. Initially, a suite of equivalent 1D inversion models produced very similar inversion model results. However, 2.5D inversions produced a disparity in solutions in key locations. To resolve these differences, 3D AEM inversion methods have been trialled. In the second study (floodplain setting), 3D inversions have helped resolve the geometry of hydrostratigraphic units and tectonic elements (folds and faults). In both study areas, independent validation of inversion results has involved an inter-disciplinary approach incorporating a range of borehole and ground geophysics techniques (e.g. passive seismic and Ground Magnetic Resonance (GMR)), tectonic mapping and analysis, hydrochemistry and drilling.In summary, comparative evaluation of 1D, 2.5D, and 3D AEM inversions in two contrasting settings demonstrates the importance of optimizing inversion procedures, taking into consideration all available geological, hydrogeological and tectonic data. The benefits of using 2.5D and/or 3D inversion procedures are particularly evident in areas of structural complexity. Confidence in 3D inversions is maximised when all elements of the system response are modelled appropriately.

An Integrated Hydrogeophysical Approach to Exploring for Groundwater Resources in Southern Northern Territory

In Australia’s semi-arid and arid interior, groundwater resources provide water supply security for agriculture and community consumptive use and are critical for underpinning economic development. . The Southern Stuart Corridor Project in central Australia, is an inter-disciplinary study which aims to better characterise regional groundwater systems and identify the location, quantity and quality of new groundwater resources. The main aims of the project are(1) to de-risk investment in development of a potential agricultural precinct in the Western Davenport Basin, and expansion of horticulture in Ti-Tree Basin, (2) to identify future water supplies for Alice Springs and Tennant Creek, and (3) for regional water supplies for mineral resource development.The project is funded by Geoscience Australia (GA) as part of the Exploring for the Future (EFTF) Programme. The project integrates airborne electromagnetic (AEM), ground geophysics (ground magnetic resonance (GMR) and borehole geophysics (Induction, gamma and nuclear Magnetic Resonance (NMR)) with drilling and pump testing; hydrochemistry and geochronology; and geomorphic, geological, hydrogeological and structural mapping and modelling. Advancements in temporal remote sensing technologies for surface hydrology, vegetation and landscape mapping are also used to facilitate the identification of recharge and discharge zones and groundwater-dependent vegetation.This paper reports on initial AEM inversion results for the Alice Springs, Ti-Tree Basin, Western Davenport and Tennant Creek areas and the use of a machine learning approach for rapid geological and hydrogeological interpretation of the AEM data. These machine learning approaches have the potential to significantly reduce interpretation time and facilitate the rapid delivery of project results.

Interpretation attributes derived from airborne electromagnetic inversion models using the continuous wavelet transform

ABSTRACTPlanning, contracting, data acquisition and processing plus the inverter's quality assessment and inversion of a regional airborne electromagnetic survey may take some months, while the interpretation of the results is a considerably more complex and comprehensive process. Most often an interpretation necessitates additional data that are time consuming to collect and complicated to integrate into an overall model, for example borehole logs, borehole core samples, water chemistry, surface vegetation, satellite imagery plus all existing geological background knowledge. Interpretation basically has to do with identifying categories and finding boundaries between them so that depths, thicknesses and a whole range of other model attributes can be estimated, qualitatively and/or quantitatively. I present two methods using the continuous wavelet transform of finding attributes intended to assist the interpreter: one finds layer boundaries in the smooth multi‐layer models that are most often used in the inversion of large airborne electromagnetic data sets, and the other finds the natural categories of the model parameter. Naturally, being based on the subsurface conductivity distribution, the boundaries and categories suggested are useful only to the extent that they coincide with geological/hydrogeological boundaries and categories – which is for the interpreter to decide.

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

A novel approach to comparing AEM inversion results with borehole conductivity logs

Borehole conductivity logs, besides being useful for identifying, interpreting and correlating geological formations, also find widespread use as auxiliary information in the inversion of airborne electromagnetic (AEM) data. One of the quality checks often applied to AEM inversion results is a comparison between the conductivity structures revealed by borehole conductivity logs in the survey area and the AEM inversion model closest to the borehole, often called an ‘FID point comparison’.Another use of borehole conductivity logs is found in modern AEM inversion procedures, where the borehole conductivity information is included as prior information in a laterally constrained inversion. In most former and present practices, AEM layer conductivities are compared with the measured conductivity in the borehole. However, the borehole conductivity is essentially an apparent conductivity – it is a measured data value – while the AEM layer conductivities are model parameters resulting from inverting AEM data. To avoid comparing data and model parameters we suggest a conceptually clear approach based on an inversion of the borehole conductivity data to obtain a borehole conductivity model, which in turn can be compared with the AEM model. Furthermore, the AEM forward response of the borehole model can, in a consistent way, be compared with the AEM data. In both approaches, we keep track of uncertainty and define quantitative, uncertainty-normalised measures of the difference between borehole and AEM values, and we find simple functional relationships between the two. The methodology is demonstrated on the AEM data and conductivity logs of the Broken Hill Managed Aquifer Recharge (BHMAR) project.