Airborne Transient Electromagnetic Research Articles

Noise suppression of airborne transient electromagnetic data with minimum curvature

The airborne transient electromagnetic (ATEM) method is a geophysical exploration technique that offers several advantages, including rapid exploration, minimal interference from complex terrains, dense data sampling, and environmental friendliness. However, the full-frequency time-domain secondary field signal acquisition of the ATEM data is susceptible to various electromagnetic interferences, resulting in noise in the collected data. This noise complicates subsequent processing and interpretation. To address this issue, we have developed a 1D minimum-curvature difference equation with unequal spacing based on minimum-curvature differential equations. Through research, we develop an ATEM noise-suppression method based on multiple single-step and multiple superposition-step implicit iterative formats. In addition, we have investigated the convergence of explicit and implicit iterative schemes via Fourier spectrum analysis and proven that the implicit iterative schemes converge. This method effectively suppresses noise in synthetic and real ATEM data during processing. Our results show that the minimum-curvature method is particularly effective in suppressing sferic and Gaussian noises in ATEM data. As a result, our method provides high-quality and reliable ATEM data for further data processing and interpretation. Moreover, the minimum-curvature method is also capable of suppressing noise in ground and ground-space transient electromagnetic data, as well as magnetotelluric data noise. Therefore, this method exhibits a wide range of potential applications.

Intelligent algorithm of extreme gradient boosting based perfectly matched monolayer and its efficient absorption on airborne transient electromagnetics problems

In addition to requiring the accuracy and computational efficiency for solving low-frequency subsurface sensing problem on the airborne transient electromagnetics (ATEMs), to the best of our knowledge, the complexity of subsurface sensing problems should also be considered in order to reduce more and more computational resources, particularly for a large-scale complicated multis-cale problem with a difference between background and targets. For simulating the open-domain, the finite-thickness perfectly matched layer is used to truncate the computational region, while the whole domain becomes larger so that the problem turns more complex. As a result, we propose a novel perfectly matched monolayer (PMM) model based on the extreme gradient boosting (XGB), which is selected and added to further improve the performance during the finite-difference time-domain (FDTD) simulation. The proposed XGB-based PMM model can achieve higher accuracy by using the ensemble learning method of feature attention, and has less memory and time consumption at the same time. Besides, this model has significant advantages in terms of model training stability and its lightweight due to the fact that it relies on the characteristics of traditional machine learning models. Finally, three-dimensional numerical simulations of ATEM problems are carried out to prove the validity and stability of the proposal. The proposed model can not only achieve advantages in numerical accuracy, efficiency and problem complexity, but also be integrated into the FDTD solver to deal with the low-frequency ATEM problems.

Weighted Laterally Constrained Inversion of Airborne Transient Electromagnetic Data with IP Effects

Due to the induced polarization (IP) effects, abnormal fast decay and sign reversals are often observed in the field airborne transient electromagnetic (ATEM) responses, this phenomenon can well be explained by introducing the four-parameter Cole-Cole resistivity model. However, the introduction of multiple parameters makes the non-uniqueness of inversion more serious. To improve this problem, a weighted 1D laterally constrained inversion is proposed to recover the four IP parameters and thickness via adding different weighted factors chosen by lateral constraint conditions, in this paper, a synthetic polarization model is developed and 1D forward modeling with synthetic natural noise is conducted to imitate the field response. The proposed inversion is employed on the synthetic data and the results demonstrate that the method can improve the inversion stability and obtain more reliable result.

A method to construct statistical prior models of geology for probabilistic inversion of geophysical data

In probabilistic inversion of geophysical data, one must describe the expected noise in the system, and any prior information. In a geoscience context, prior information can provide a quantitative description of the expected spatial variability and correlations of the geology. But in practical inversion cases, driven by difficulty in quantifying geological information and computational complexity, an analytical mathematical smooth prior model is often chosen to describe the spatial variability. This is one of the primary reasons that realistic geological structures are difficult to resolve in geophysical models. Thus, there is currently a need for investigating and proposing practical ways of capturing complex (and often qualitative) geological information in statistical prior models that can be used in probabilistic inversion, which satisfies both the geologist, geophysicist, engineer and the geostatistician. In this research we show how a 1D statistical prior model can be designed that emulates the spatial distribution found in 188 boreholes with Miocene and Quaternary deposits from a study area (approx. 177,5 km2) near Horsens, Denmark. The prior model is built in two major steps 1) a multidimensional distribution describing the sub-division of major geological elements (here represented by lithologies from defined geological periods) and 2) a truncated pluri-Gaussian distribution describing the internal structure of lithologies within each element. The presented prior model can both be used to generate independent realizations, which can be used as part of the extended rejection sampler, as well as allowing the possibility of doing a “random walk” in the model space, as required by the extended Metropolis algorithm. We demonstrate, as an example, how the developed prior model can be used in a probabilistic inversion of airborne transient electromagnetic (AEM) data and discuss the implications the use of such informed prior models can have.

Denoising for airborne transient electromagnetic data using noise-whitening-based weighted nuclear norm minimization

Abstract Recovering anomalous information covered under noise in late gates can enhance airborne transient electromagnetic (ATEM) detection. Conventional denoising mainly comprises filtering and gate correlation-based decomposition algorithms; the former fails to extract anomalies contaminated by noise and the latter relies on the correlation between gates, which may yield false late gate anomalies caused by early large-amplitude anomalies in early gates. In ATEM profiles, the correlation between anomalies in adjacent gates makes the anomalies to be measured to have low-rank characteristics relative to the noise-contaminated profiles; the noise is uniformly distributed in the profiles, which have nonlocal self-similarity. Therefore, the low-rank matrix approximation algorithm is applicable to ATEM data denoising. In this study, an algorithm—noise-whitening-based weighted nuclear norm minimization (NW-WNNM)—is designed to remove ATEM profile noise. First, we analyze the influence of patch size in block matching on anomalous and noisy patches and estimate the profile patch size adaptively. Then, we combine the estimation of noise variance in weighted nuclear norm minimization (WNNM) with the noise whitening of similar patch matrices to reduce the noise interference on the nuclear norm and add a whitening factor in the weight vector to make the soft-thresholding function applicable to the low-rank reconstruction of the whitened matrix. By analyzing the reconstructed low-rank matrix and its feature distribution, compared with WNNM, NW-WNNM can detect the feature information more accurately and eliminate the influence of noise on the nuclear norm. Simulation and field profile results indicate that NW-WNNM is superior to comparison denoising methods.

An efficient 2.5‐D forward algorithm based on the spectral element method for airborne transient electromagnetics data

AbstractThe airborne transient electromagnetics method has been widely used in geophysical exploration in recent years, but it still faces challenges in balancing the accuracy and efficiency of electromagnetic data interpretation. As far as forward modelling is concerned, the higher the dimension of the geophysical model, the higher the accuracy of data interpretation, but, correspondingly, the more computing resources need to be consumed, which will greatly reduce investigation efficiency and practicability. In this paper, the spectral element method is first introduced for solving the 2.5‐dimensional forward modelling of the airborne transient electromagnetic system, which has a smaller computing scale than three‐dimensional modelling and is closer to the actual geological structure than either one‐ or two‐dimensional modelling. In the forward algorithm, a non‐uniform quadrilateral structured mesh is adopted to simplify the computing scale, and the Talbot algorithm rather than Gaver–Stefest algorithm is applied to the inverse Laplace transform to improve the numerical precision of this conversion. Moreover, we use parallel computing technology to improve the algorithm efficiency while keeping satisfactory accuracy. The study shows that, whether a low‐resistivity or high‐resistivity layered geophysical model, the numerical solutions of the proposed spectral element method forward algorithm agree well with the analytical solutions of the corresponding models; furthermore, the key factors affecting the accuracy of the numerical solution are analysed by experiments. Finally, we successfully applied it to the 2.5‐dimensional geoelectric model simulation.

Three-Dimensional Transient Electromagnetic Forward Modeling for Simulating Arbitrary Source Waveform Using Convolution Approach

The transient electromagnetic (TEM) method utilizes artificial transmitters and measures electromagnetic responses to reveal the resistivity information of the subsurface. The current waveform of transmitters has non-negligible effects on induced fields. Therefore, 3-D TEM forward modelling algorithms need the capability of simulating arbitrary waveforms to obtain accurate responses. In time-stepping-based 3-D TEM forward modelling, the source term approach is frequently used, which employs the source current density to model the waveform variation during time-stepping. The source term approach, however, requires fine-time discretization to describe complex waveforms, which could significantly raise the computational cost. We present a robust convolution approach that computes the convolution between the time derivative of the waveform and the step-off response to incorporate the waveform effects in 3-D TEM modelling. The convolution approach does not discretize the waveform using time steps. Hence, it is advantageous when modelling full-waveform cases. The developed algorithm is based on the finite-element method using unstructured grids and the implicit backward Euler approach. Both galvanic and inductive transmitters are incorporated. Ground and airborne TEM surveys are tested using an actual airborne TEM waveform, a full waveform of the 2( <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>n</i></sup> )-sequence pseudo-random signal, and various synthetic waveforms. Accuracy is validated against the 1-D and 3-D solutions of published studies. The source term and convolution approaches are compared. Synthetic examples show that the latter approach simplifies the waveform incorporation in TEM modelling and substantially improves time-stepping efficiency without sacrificing accuracy.

Computation of Analytical Derivatives for Airborne TEM Inversion Using a Cole–Cole Parameterization Based on the Current Waveform of the Transmitter

Airborne transient electromagnetic (ATEM) technology is a technique often used in mineral exploration and geological mapping. Due to inductive polarization (IP) phenomena, the ATEM response curve often shows a negative response or declines rapidly to the attenuation curve. Traditional resistivity inversion techniques do not explain the IP response of a signal well, so the negative response is usually removed during data processing, resulting in a reduced correctness and authenticity of the findings. In this paper, in the parameter inversion based on the Cole-Cole model, the Jacobian matrix chain analysis method is used to calculate, and the current waveform calculation is also considered in the inversion. The results show that compared with the perturbation method, the analysis technique can greatly reduce the calculation time and improve the inversion efficiency. In the single-point one-dimensional inversion and lateral constraint quasi-two-dimensional inversion, the Cole-Cole four-parameter forward response has strong inversion accuracy, which can successfully invert the actual exploration content and the Cole-Cole four-parameter response. Some measured sounding data in the Qingchengzi survey area of Liaoning Province, China have a negative response to IP, and the resistivity scheme cannot be used alone for inversion, but the real underground resistivity structure can be obtained through the method studied in this paper, and good exploration results can be obtained.

An ATEM 1D inversion based on K-Means clustering and MLP deep learning

Abstract Traditional geophysical inversion methods rely on an assumption of prior knowledge, starting from the establishment of the initial model and ending with the model being modified many times. This iterative process makes the forward modelling results move increasingly closer to the observed data. However, each inversion step requires multiple forward calculations, which consumes considerable time and computing resources. This is the greatest obstacle to real-time inversion at present. Airborne transient electromagnetic (ATEM) response data are collected in a time-channel manner. The different stratigraphic structures reveal different time-varying electromagnetic response laws. In this paper, deep learning technology is used to advance the ‘model correction-forward iteration’ step in the geophysical inversion process to the data preprocessing stage, to better adapt to the specialty of ATEM, improve the efficiency of the inversion and shorten the inversion time. In this method, a sample set composed of a ‘stratigraphic texture model—ATEM response’ is established, the K-Means clustering technique of unsupervised learning is used to complete the sample tag attachment, and the multilayer perceptron (MLP) deep learning network with supervised learning is used to complete the multiclassification tasks. Then, the sample sets are input into the deep learning network for training to build the inversion from the input response data to the output of the stratigraphic model. Finally, the inversion flow is verified with test set samples. The prediction results are consistent with the simulated data, and the inversion, from the test data to the prediction model, is implemented efficiently.

3-D modelling and analysis of superparamagnetic effects in ATEM based on the FDFD

SUMMARY Superparamagnetic (SPM) effects lead to 1/t power-law delay approximately during the middle and late periods of transient electromagnetic responses. Ignoring SPM effects can produce large errors and cause incorrect data interpretation. Furthermore, because of the non-linearity of the Chikazumi magnetic susceptibility model, it is difficult to discretize the model in the time domain. Therefore, developing an algorithm for 3-D modelling of SPM effects in the time domain directly is difficult. In view of the above problems, we propose a 3-D modelling method of SPM effects for airborne transient electromagnetic (ATEM) data. We also introduce the widely used Chikazumi magnetic susceptibility model into the finite-difference frequency-domain (FDFD) method. According to the mapping relations between the magnetic field intensity and the magnetic permeability on the grid after discretization, we re-establish the scientific matrix of the magnetic permeability. And we adopt arithmetic averaging of the two adjacent cubes’ magnetic permeability as the magnetic permeability in boundary, which is a different setting method with the electrical conductivity. The 3-D modelling of SPM effects is successfully realized, and its maximum relative error is less than 7 per cent. We subsequently analyse the intrinsic properties of the abnormal magnetic medium, as well as the effect of the SPM unit's parameters, such as the depth, thickness, electrical conductivity, zero-frequency magnetic susceptibility, and the height of the receiver, on the response. Then, we calculate the SPM responses of 3-D magnetic bodies and analyse the influence of magnetic susceptibility and electrical conductivity on magnetite responses. The present study can provide theoretical guidance for ATEM detection in magnetic media and lay a foundation for 3-D inversion of SPM effects.

Comparison of ground-based and airborne transient electromagnetic methods for mapping glacial and permafrost environments: Cases from McMurdo Dry Valleys, Antarctica

The transient electromagnetic (TEM) method is a non-invasive geophysical tool well-suited for subsurface imaging in cold and polar regions, where common targets are associated with strong contrasts in electrical resistivity. By imaging the electrical properties of the subsurface, the TEM methods can discriminate between geological units such as frozen ground (permafrost), fresh/saline groundwater systems, and bedrock/glacier ice. In this study, we compare TEM data acquired with ground-based and airborne TEM systems. We demonstrate the mapping capabilities of these two approaches in high latitude polar environments with datasets from Taylor Glacier, Lake Vanda, and Canada Glacier in the McMurdo Dry Valleys of Antarctica. The results show a high consistency between the airborne and ground-based TEM data, both with a high resolution and a deep penetration depth down to hundreds of meters due to the resistive background material, which makes both approaches capable of mapping hydrological systems and identifying the base of glaciers. The airborne TEM approach offers an unmatched spatial data coverage in difficult terrain and a far improved lateral resolution compared to the static ground-based system. The ground-based TEM system offers the possibility for using larger transmitter coils and longer stacking times and therefore has potential for reaching deeper penetration depths. The ground-based TEM approach is hence a valuable tool that can provide consistent imaging results while also being far more accessible in terms of cost and field logistics compared to an airborne TEM campaign.

Airborne Transient Electromagnetic Simulation: Detecting geoelectric structures for HVdc monopole operation

Geoelectric structures have great influence on the earth surface potential (ESP) induced by ground return currents (GRCs) in high-voltage dc (HVdc) monopolar operations. Traditional ground-detection methods are cumbersome due to the long distances between the grounding electrodes of substations. The airborne transient electromagnetic (ATEM) method has become a popular technique for exploring large-scale geoelectric structures. First, we analyze the influences of different 3D geoelectric models on the fluctuation in GRCs and propose a 3D model to evaluate ATEM simulations. Second, we present an efficient ATEM simulation method based on a finite-element (FE) algorithm to obtain the 3D geoelectric structure used to calculate the ESP. The stability and convergence rate of solving FE systems are improved by using an induced dimension reduction (IDR) solution algorithm. The detectability of the ATEM method is validated by an inversion case based on the Occam algorithm. The numerical results demonstrate that our robust ATEM simulation method is useful for detecting the 3D geoelectric structure used in ESP analysis.

Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Airborne and semi-airborne transient electromagnetic (TEM) surveys have high efficiency but may suffer from systematic errors due to the inexact shape, position, and orientation of the transmitter and receiver, which can deviate from the nominal design because of complex terrain, platform instability, or external forces. Without considering actual survey geometry, modeling and inversion can bias the interpretation of results. We develop a universal approach to layered earth capable of modeling arbitrarily complex transmitter and receiver geometry used in airborne and semi-airborne surveys. Our algorithm decomposes an airborne loop or grounded wire source to a set of x-, y-, or z-oriented electric dipoles. An arbitrarily oriented receiver coil is simulated by projecting three-component data to the actual direction of receiving. In airborne TEM, the transmitter loop and receiver coil are often bound together on a rigid frame and tilt during the flight. Our simulations and synthetic inversion show that such a tilt may reduce responses relative to the data obtained with the nominal geometry; an inversion without considering the tilt can underestimate near-surface conductivity. In semi-airborne TEM, the transmitter wire on the surface can be crooked, and the airborne receiver coil can also tilt. Our modeling shows that the simulated data can change significantly if the actual transmitter and receiver geometry does not exactly follow the nominal survey design; if not appropriately accounted for, such an error may distort the recovered conductivity model. Finally, the benefit of our algorithm is demonstrated by an airborne TEM field data inversion of groundwater problems with the tilt angle of the transmitter–receiver frame accurately modeled. Our work provides a tool for improving the resolution of airborne and semi-airborne TEM in near-surface conductivity characterization.

Comparing induced polarization effect on semi-airborne and airborne transient electromagnetic data: A numerical study

In a transient electromagnetic (TEM) survey, when a chargeable body presents, its induced polarization (IP) will generate an additional electromagnetic field that further superposes on the TEM data. If the added fields are not considered properly when designing a TEM survey or inverting the TEM datasets, erroneous results may be obtained. Thus, we compare the IP effects on the airborne and semi-airborne TEM methods in this study. One big difference between the two methods is that the semi-airborne method mainly uses the ground-based galvanic source and the airborne method utilizes the air-based inductive source. To fully illustrate this difference, we calculated the IP-TEM coupled responses at a time range of 10−6 s to 10 s. Despite the commonly known reversal of signs in the transient, we found that in some cases of airborne TEM response, the sign will reverse twice. The relative errors caused by the IP effect are further demonstrated. A minimum peak at the early time that is closely related to the IP parameters is revealed, indicating that the IP fields will drop rapidly at the early time and then decay slowly. Finally, a misfit space analysis is performed, showing that both methods can well resolve the resistivity and the IP parameters of a conductive target, while it is difficult to recover the IP parameters of a resistivity target.

Convolutional neural network inversion of airborne transient electromagnetic data

ABSTRACTAs an efficient geophysical exploration technique, airborne transient electromagnetics shows strong adaptability to complex terrains and can provide subsurface resistivity information rapidly with a dense spatial coverage. However, the huge volume of airborne transient electromagnetic data obtained from a large number of spatial locations presents a great challenge to real‐time airborne transient electromagnetic interpretation due to the high computational cost. Moreover, the inherent non‐uniqueness of the inverse problem also limits our ability to constrain the underground resistivity structure. In this study, we develop an entirely data‐driven convolutional neural network to solve the airborne transient electromagnetic inverse problem. Synthetic tests show that the convolutional neural network is computationally efficient and yields robust results. Compared with the Gauss–Newton method, convolutional neural network inversion does not depend on the choices of an initial model and the regularization parameters and is less prone to getting trapped in a local minimum. We also demonstrate the general applicability of the convolutional neural network to three‐dimensional synthetic airborne transient electromagnetic responses and the field observations acquired from Leach Lake Basin, Fort Irwin, California. The efficient convolutional neural network inversion framework can support real‐time resistivity imaging of subsurface structures from airborne transient electromagnetic observations, providing a powerful tool for field explorations.

Airborne geophysical investigations for landslide risk investigation along the Ångerman River, central Sweden

A study of landslide risks along the Ångerman River in Sweden is currently being performed by the Swedish Geotechnical Institute (SGI) with assistance from the Geological Survey of Sweden (SGU). In this work, knowledge of the distribution of different types of sediment is crucial. The area shows large variations in both sediment stratigraphy and sediment thickness (depth to bedrock) which makes it difficult to describe geotechnical properties for larger areas based on sparse geotechnical field investigations (soundings and sampling). Within the study area, the Ångerman River valley contains numerous fluvial terraces at various elevations separated from the river by steep erosional scarps. Although fluvial sand caps the terraces, their heights are often derived from the underlying silt and clay, which in turn overlies till or glaciofluvial sediment. The thickness of these general stratigraphic units is difficult to determine from existing data. Thus, in 2018, an airborne transient electromagnetic (ATEM) survey was performed along the river and the surrounding river banks with the objective of mapping and characterizing the sediments down to bedrock. The surveyed area is 2 km wide and covers 80 km along the river with a flight line distance of 75 m. From the ATEM data, the 3D resistivity distribution of the ground down to about 100 m below the surface can be determined. The silt and clay show very low resistivity compared to the overlaying sand layers. Therefore, they can be easily distinguished in the resistivity models from the ATEM data. Furthermore, the depth to the more resistive underlaying till and bedrock can be delimited in most areas. The 3D resistivity model derived from the ATEM data was integrated with other geoscientific data such as; geotechnical drillings, information from water wells and surficial deposits maps using 3D modeling software (Geoscene 3D from I-GIS). Based on the modelling results, the area was divided into six different classes based on the soil stratigraphy. The current method of analysis uses detailed geotechnical investigations performed in one location to ground truth the interpretation of geophysical data over a broad area. With the new results based on the ATEM data, the planning of new geotechnical drillings can be better focused on more poorly-understood areas. Furthermore, the number of geotechnical field investigations can be reduced.

Weak Coupling Technology With Noncoplanar Bucking Coil in a Small-Loop Transient Electromagnetic System

Small-loop transient electromagnetic (TEM) method can be used for urban underground space detection. Given the mutual inductance between transmitting and receiving coils, the early secondary field signals are contaminated by primary field signals. To compensate for the primary field, bucking coil technology has been utilized in the airborne TEM system due to attractive features of the technology, which include a compensation effect and a strong coupling strength between the receiving coil and the underground body. However, many problems arise when the bucking coil technology is used directly in a ground small-loop TEM system. One is that the size of the receiving coil is limited, resulting in insufficient bandwidth; the other is that the bucking coil brings the near-field effect, which causes the loss of shallow information. To solve these problems, in this article, we propose a new TEM structure with noncoplanar bucking compensation. Compared with the traditional design, the new structure overcomes not only the near-field effect but also reduces the constraint of the receiving coil size. Furthermore, the approach can suppress the primary field coupling more effectively, and has a better fault tolerance for the installation accuracy. The simulation and field experiment results verify the effectiveness and practicability of the new structure.

Lithology Identification of Alluvial and Lacustrine Aquifers in Baiyangdian Area by an Airborne Transient Electromagnetic Survey

An airborne transient electromagnetic (TEM) has been conducted in Baiyangdian Area to map resistivity distribution within the alluvial and lacustrine aquifers. This investigation evaluated the reliability of resistivity models of the TEM data to infer lithological distribution in alluvial and lacustrine aquifers. The collected airborne TEM data were processed and inverted using spatially constrained 1D inversion method. And the 3D electrical structure, which maps electrical resistivity trends to depths of about 160 m, can be established through interpolation. Comparison of the resistivity models to drill logs indicates resistive permeable coarse-grained sediments and conductive fine-grained sediments which are relatively impermeable. Hence, the 3D electrical structure that are related to lateral and vertical variation in lithology, can serve as baseline information for groundwater potential identification. This research indicates that groundwater detection is an ideal target for mapping with airborne TEM techniques because of the high electrical resistivity of permeable coarse-grained deposits and its contrast with impermeable fine-grained deposits.

Stratigraphy of the Gorstian and Ludfordian (upper Silurian) Hemse Group reefs on Gotland, Sweden

ABSTRACT The Hemse Group is one of the least understood stratigraphic units of the Silurian sequence of Gotland, Sweden. New results from airborne transient electromagnetic (ATEM) measurements in combination with previously published data from field studies and geophysical investigations shed new light on carbonate platform development during the early- to mid-Ludlow Hemse Group. ATEM reveals a transgressive phase that began near the Wenlock-Ludlow boundary, which resulted in deposition of marls and corresponds roughly to the Hemse limestone units a-c and the Hemse Marl NW. In this phase little or no reef development occurs. The end of the transgressive phase coincides with the weak Linde Event. The following highstand favoured extensive reef growth forming a reef barrier system of both fringing reefs and more rampiform settings with stromatoporoid biostromes and occasional biohermal buildups. The Kuppen-Snabben Unconformity Complex marks an erosional (karstic) sequence boundary and rocky shoreline and the transition from a rampiform setting with reef biostromes towards a more rimmed setting with patch reefs.

On-time modelling using system response convolution for improved shallow resolution of the subsurface in airborne TEM

ABSTRACTWe describe a new approach for modelling airborne transient electromagnetic (TEM) data which combines the use of on- and off-time data for inversion. Specifically, the response is modelled using system response convolution both during and after transmitter ramp-down. High near-surface sensitivity can be achieved through a combination of fast transmitter ramp-down, broad receiver system bandwidth, efficient suppression or explanation of the primary field, and by combining the use of on-time gates with accurate knowledge of the system response. The system response can either be calculated based on the transfer function of the individual system components (i.e. receiver coil, amplifiers, low-pass filters and current waveform) or it can be measured at high altitude. The latter approach has the advantage of avoiding the specific modelling of individual system components. By comparing model parameter uncertainty when the on-time gates are included in the inversion versus when they are not, we show that a significant improvement in near-surface sensitivity is obtained. The method is used to invert both synthetic and field data. In the inversion of synthetic data, we see clear improvements in the determination of thin shallow layers, especially when they are resistive. This is confirmed by inversion of field data where we observe more pronounced structures with better definition of layer boundaries and layer resistivities.