EM Response Research Articles

3-D Time-Domain Airborne EM Forward Modeling With IP Effect Based on Implicit Difference Discretization of Caputo Operator

As an efficient geophysical exploration method, the time-domain airborne electromagnetic (AEM) data often show sign reversal in late-time channels due to induced polarization (IP) effect. The traditional imaging and inversion methods without considering the IP effect cannot recover the true electrical structure of the earth, so it is necessary to develop 3D EM forward modeling and inversion techniques with IP effect. In this paper, we propose a 3D forward modeling method for time-domain AEM with IP effect based on unstructured finite-element (FE) method. To describe the IP effect of a medium, we introduce the Cole-Cole model and transform it into fractional derivative form using frequency-time conversion. Then, we discretize it using the difference discretization format of Caputo fractional derivative. Finally, we use the vector FE method based on unstructured tetrahedral mesh and unconditionally stable second-order backward Euler’s scheme to discretize Maxwell’s equations in space and time. In this way, we can solve the 3D forward modeling problem for AEM with IP effect in time domain. We verify the accuracy of our algorithm by comparing it with the 1D semi-analytical solution for a half-space model, and then calculate EM responses for typical abnormal models and analyze the characteristics of IP effect.

Outcome after Inotuzumab Ozogamicin for Patients with Relapsed or Refractory B-Cell Acute Lymphoblastic Leukemia and Extramedullary Disease

Outcome after Inotuzumab Ozogamicin for Patients with Relapsed or Refractory B-Cell Acute Lymphoblastic Leukemia and Extramedullary Disease

Processing of passive EM fields acquired during active-source airborne EM surveys

The recording of raw or streamed airborne electromagnetic (AEM) data, as done by CGG during MEGATEM surveys, allows for the extraction of passive EM signals also present, but not normally processed. These include (1) powerline responses, (2) responses in the very low frequency (VLF) range due to radio transmissions and (3) natural-source audio-frequency magnetic (AFMAG) and VLF responses in the frequency range 25 Hz–25 kHz extracted from individual atmospheric electrical discharges (sferics). The latter approach manages to extract good signal in the audio-frequency magnetotelluric (AMT) dead band (1–5 kHz) for one of the discussed data sets. The recording of the three-component AEM data allows for the vector processing of these passive EM responses, including the derivation and modelling of the vertical-to-horizontal magnetic field ratio (tipper) data. Conductivity information can be derived from the tipper data with an apparent conductivity transformation and, more rigorously, with 2D and 3D inversions that take into account the terrain’s topography. The extraction and modelling of passive EM responses is demonstrated on two data sets. A powerline apparent-conductivity grid derived from a MEGATEM survey near Timmins, Canada indicates conductivity structures similar to those in the corresponding active-source EM data. VLF and AFMAG responses derived from South American MEGATEM data show a strong correlation to topography. These data were successfully modelled with 2D and 3D inversions, and the derived shallow conductivity structures confirm and complement the information extracted from the active-source EM data.

Intrinsic vs Extrinsic Motivation as Drivers for Early Engagement in Research by Medical Students.

BackgroundA student’s motivation is a key factor in their success in undertaking an education endeavour. However, how this relates to involvement in research by medical students is unclear.MethodsAn electronic questionnaire was sent to all medical students at our institution. To ascertain students’ motivation to undertake research, they were asked an open-ended question to describe the single major factor that would encourage them to get involved in research as a medical student. A framework of self-determination theory was used to deductively code the responses as intrinsic motivation (“IM”; e.g., interest/passion) or extrinsic motivation (“EM”; e.g. improving CV). The two groups were then contrasted in relation to their research engagement.ResultsA total of 348 students were included in the survey, of whom 204 were coded as IM responses, and 144 were coded as EM responses. Students who engaged in extra-curricular research activities were more likely to report an underlying EM (48% vs 36%, p = 0.03). They were also older (23.7 ± 3.5 vs 21.9 ± 3.7, p = 0.005), and more likely to have completed a prior research degree (15% vs 3%, p = 0.01).ConclusionIn this study, EM was a bigger influencer on research involvement by medical students than IM. Future studies should explore promoters of IM, and include longitudinal data in order to assess whether EM students continue to be involved in research long-term.

Weighted adaptive finite-element method for 3D transient EM modelling

As we know, grid quality can produce big effect on the numerical precision of 3D forward modeling. How to generate high-quality grids becomes the key for high-accuracy EM responses. So we develop a weighted adaptive finite-element method based on hybrid posterior error estimation in combination with unstructured vector finite-element method and Backward Euler scheme. We introduce a weighting factor to adjust the relative weight of posterior errors defined by the continuities of normal current density and tangential magnetic field to create an effective mesh. The numerical experiments on a conductive cube model show that our algorithm performs better than the traditional adaptive method.

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.

Adaptively Weighted Yield-Driven EM Optimization Incorporating Neurotransfer Function Surrogate With Applications to Microwave Filters

In this article, we propose an adaptively weighted yield-driven EM optimization technique incorporating neurotransfer function (neuro-TF) surrogate. In the proposed technique, an adaptive weighting factor is set up for each frequency point of interest based on the degree to which the EM response may violate the design specification. These weighting factors are first incorporated into the error function for training the neuro-TF model and then involved in the objective function of yield optimization using the trained model. We identify the key frequency points where the EM response is likely to violate the design specification over the whole frequency range of interest. Using the adaptive weighting factor-incorporated error function to train the model enhances the model accuracy at the key frequency points while preserving the model accuracy at other ordinary frequency points. This improves the yield estimation accuracy using the trained surrogate model at each iteration of optimization and, consequently, facilitates the yield optimization process. By involving the weighting factors into the formulation of the objective function of neuro-TF-assisted yield optimization, higher priorities are given to the key frequency points than the ordinary frequency points. This allows the proposed technique to find a more effective update direction at each iteration of optimization and, consequently, achieves a similar yield increase with a fewer number of iterations compared with the conventional neuro-TF approach. Two microwave examples demonstrate the advantages of the proposed technique against other existing approaches, including the Monte Carlo (MC)-based approach, the polynomial chaos (PC)-based approach, and the conventional neuro-TF approach.

Time-lapse CSEM: how important is survey repeatability?

SUMMARYAn important concern for time-lapse studies using the controlled-source electromagnetic (CSEM) method is repeatability of acquisition parameters for the base and monitoring surveys. We consider a challenging case when variations in source and receiver positions, conductivity of seawater, etc. will lead to differences in the recorded EM fields that exceed EM response due to production-induced changes in the reservoir resistivity. We show that even in that case, 4-D response can often be clearly resolved if the base and monitor EM data sets are inverted to produce 3-D resistivity distributions. More precisely, for a synthetic model of the Snøhvit gas field, changes in the inverted resistivity maps caused by such non-repeatability will be at least 10 times smaller than the time-lapse differences in the reservoir resistivity. By contrast, measurement errors and poor knowledge of background resistivity may reduce the resolution of 4-D CSEM to a much stronger degree. Analysis of field CSEM data from the Wisting oil field supports our conclusion about strongly relaxed repeatability requirements when 4-D effects are established by examining inverted resistivity volumes rather than by looking at raw EM data.

Obtaining Strong, Broadband Microwave Absorption of Polyaniline Through Data‐Driven Materials Discovery

AbstractMicrowave absorbing materials (MAMs) are highly utilized in the defense and telecommunications industries, as means for reducing radar cross sections for stealth technology, and providing electromagnetic interference shielding for the information processing and transport capabilities in electronic devices. Polyaniline materials have attracted enormous attention in the field of MAM development due to their strong dielectric properties. In this manuscript, the strong dielectric action of polyaniline is utilized to demonstrate for the first time how to mathematically model the EM response of materials as a means for accurately simulating, predicting, and optimizing the microwave absorption performance. Using this process, the microwave absorbing properties of polyaniline are successfully optimized and record‐breaking performances are demonstrated for both the reflection loss and effective bandwidth, yielding experimentally‐derived responses of RL = −88.5 dB at 7.0 GHz, 3.8 mm and Δf10 = 5.5 GHz at 2.1 mm. The methods presented herein are generalizable and have the potential to be broadly applicable to MAM research and development.

A time-lapse CSEM monitoring study for hydraulic fracturing in shale gas reservoir

Hydraulic fracturing has been widely used in shale gas production. During the hydraulic fracturing, microcracks are open and filled with the conductive fluid, which enhances the overall hydraulic conductivity of the shale formulation. Undoubtedly, the monitoring of the fracturing process is crucially important for shale gas production. The controlled source electromagnetic method (CSEM) is sensitive to the electric conductivity change and can potentially be used for monitoring hydraulic fracturing. In this paper, we carried out numerical modeling and a field test on the CSEM monitoring of hydraulic fracturing at the Fuling shale gas field in southern China. Firstly, we perform the numerical modeling based on a synthetic model derived from the logging data of the field test site to investigate the effect of the steel-cased well on EM responses. Then, we investigate EM responses at the surface caused by the shale gas reservoir for different configurations to optimize survey parameters. Subsequently, the optimal broadside survey system is applied to investigate the effectiveness of CSEM monitoring on a synthetic hydraulic fracturing process. Finally, a real application is applied to carry out the time-lapse CSEM monitoring of the hydraulic fracturing during the shale gas production. Both the modeling results and the field data show the optimistic potential of use CSEM monitoring on the hydraulic fracturing process applied in the shale gas production.

Error Analysis of Programmable Metasurfaces for Beam Steering

Recent years have seen the emergence of programmable metasurfaces, where the user can modify the EM response of the device via software. Adding reconfigurability to the already powerful EM capabilities of metasurfaces opens the door to novel cyber-physical systems with exciting applications in domains such as holography, cloaking, or wireless communications. This paradigm shift, however, comes with a non-trivial increase of the complexity of the metasurfaces that will pose new reliability challenges stemming from the need to integrate tuning, control, and communication resources to implement the programmability. While metasurfaces will become prone to failures, little is known about their tolerance to errors. To bridge this gap, this paper examines the reliability problem in programmable metamaterials by proposing an error model and a general methodology for error analysis. To derive the error model, the causes and potential impact of faults are identified and discussed qualitatively. The methodology is presented and exemplified for beam steering, which constitutes a relevant case for programmable metasurfaces. Results show that performance degradation depends on the type of error and its spatial distribution and that, in beam steering, error rates over 20% can still be considered acceptable.

Authentication Using Metallic Inkjet-Printed Chipless RFID Tags

A high-level (i.e., in terms of security) authentication method is proposed in this communication, where the chipless RFID is extended to the chipless authentication. The proposed method is based on low-cost inkjet-printed square-check-patterned chipless tags, whose design is explicitly optimized keeping the randomness inherent to the inkjet-printing process in view. These optimized chipless tags are very difficult to duplicate, as their unique backscattered EM responses depend on proximate coupling among the possible separated squares that happened naturally due to the randomness of inkjet printing. The performance of the proposed method is analyzed by a low-cost impulse radio (IR) UWB chipless RFID reader as well as by the highly accurate VNA-based chipless RFID reader. The achieved probability of error is comparable to the various fingerprint evaluation campaigns found in the literature.

An Efficient Footprint-Guided Compact Finite Element Algorithm for 3-D Airborne Electromagnetic Modeling

The airborne electromagnetic (AEM) method is an efficient tool for assessing conductivity structures near the earth’s surface. The huge amounts of collected data over a survey area of tens to thousands of square kilometers result in an extremely high computational cost for rigorous modeling. Fortunately, for each transmitter and receiver (Tx–Rx) station, a volume of limited scale beneath the transmitter, called the footprint, contains the majority of the induced current and contributes most of the EM response at the receiver. In this letter, we develop a footprint-guided compact finite element method (CFEM), in which the inhomogeneous conductivity structure in the entire survey area is divided into small subareas based on the footprint so that the forward modeling for each subarea can be performed efficiently. The computational domain for every single Tx–Rx station consists of a small subarea and a surrounding layer. The accuracy of the algorithm is verified by comparing its solutions with semianalytical solutions on a layered earth model, and its applicability and efficiency are demonstrated with a more complex 3-D model consisting of a large inhomogeneous structure.

REFINING AN ELDER MISTREATMENT SCREENING AND RESPONSE TOOL TO IMPROVE ACCEPTABILITY IN AN EMERGENCY DEPARTMENT

Elder mistreatment (EM) is a public health problem that is rarely recognized or addressed in emergency departments (ED) where a lack of evidence-based protocols leave clinicians to rely on intuition and inconsistent action plans. In this presentation we will share findings from focus groups and online surveys with ED clinicians and administrators to evaluate the perceived value and likelihood of adopting the National Collaboratory’s third core element: the EM Screening and Response Protocol (EM-SAR). Results indicated a strong support for the EM-SAR tool in general and highlighted specific considerations for refining the tool. Considerations include resistance to adding to the ED workload, need to clarify roles and responsibilities for administering the tool, hesitancy to rely on clinical judgement to assess EM, concerns over Adult Protective Services’ ability to respond to increased reports, and a desire for cross-training and cooperation. These findings and implications for ongoing feasibility testing will be discussed.

On airborne IP effects in standard AEM systems: tightening model space with data space

ABSTRACTIP effects in AEM data are subject of current research around the world. There have been success stories and it is now practical to model AIP. It is widely accepted that failure to account for IP effects, when present, will produce artefacts in the resistivity model. However there still is a need to study more accurately the boundaries of the effect on AEM data and of its relevance, beyond common past acceptance. This paper provides a clear and extensive overview of detectable AIP effects in the data space, without imposing simplistic assumptions (e.g. fixing some parameters to arbitrary values or limited boundaries), beside using a 1D approach. We produce forward responses with dispersive resistivity for hundreds of thousands of combinations of Cole–Cole model parameters (different rock types) and AEM system transfer functions. The results are analysed using various metrics (e.g. sum of negative voltages, exponential fitting), presented with a series of 3D plots that capture different AIP signatures in the transients. Experiments include half spaces, 2 and 3 layer models, combined with different waveforms, Rx types (dB/dt and B), Tx-Rx geometries, flying heights, base frequencies. The results allow a clear assessment of the different aspects of AIP effects over a wide range of geological and geophysical situations. Measured AIP effects are mostly focused in the range of τ from 10−2 s to 10−4 s. Measurable AIP effects depend on AEM system’s specs, are often unpredictable, can originate from chargeable layers at considerable depth, are heavily affected by layering and can occur over a wide range of situations. Deeper chargeable layers do not necessarily produce fainter AIP anomalies. What can be generalised is that AIP effects are increased most often by the presence of a resistive bedrock, often using slow turn-off of the waveform, are generally better observed with B field instead of dB/dt and lowering base frequencies. They can vary abruptly, due to the rapidly changing relative contribution of pure EM and pure IP responses. AIP effects can occur more often than previously thought and should not be discarded a-priori from any AEM survey.

Characteristic electromagnetic waves caused by tensorial and possible nontensorial thermal high-frequency gravitational waves from magnetars

Interaction between the gravitational waves (GWs) and the strong magnetic fields would lead to the perturbed electromagnetic waves (EMWs). Magnetars can have ultra-strong surface magnetic fields ∼1011Tesla, and meanwhile, they would generate the thermal high-frequency GWs (HFGWs) caused by the Fermi liquid phonons and the gravitational bremsstrahlung inside. Here, we for the first time address the perturbed EMWs caused by such thermal-HFGWs interacting with the ultra-strong surface magnetic fields of the magnetars. It is expected that the perturbed EMWs would distribute in very characteristic patterns that have never been predicted before, which may deliver and reflect the crucial information of the polarizations (tensorial and possible nontensorial) of the thermal-HFGWs and the particular features of the structures of magnetars. The estimated power density of such perturbed EMWs would reach ∼106–108 W/m2 in the area around the surface of magnetar, and the strengths of perturbed EMWs in the observational direction would appear in characteristic pulse-like envelopes. Obtained results may suggest the novel effect of potential evidences of the possible nontensorial GWs, the thermal-HFGWs from magnetars, the mechanism of EM response to the GWs, and the models of magnetars and their magnetic fields.

Accelerating implant RF safety assessment using a low-rank inverse update method.

PurposePatients who have medical metallic implants, e.g. orthopaedic implants and pacemakers, often cannot undergo an MRI exam. One of the largest risks is tissue heating due to the radio frequency (RF) fields. The RF safety assessment of implants is computationally demanding. This is due to the large dimensions of the transmit coil compared to the very detailed geometry of an implant.MethodsIn this work, we explore a faster computational method for the RF safety assessment of implants that exploits the small geometry. The method requires the RF field without an implant as a basis and calculates the perturbation that the implant induces. The inputs for this method are the incident fields and a library matrix that contains the RF field response of every edge an implant can occupy. Through a low‐rank inverse update, using the Sherman–Woodbury–Morrison matrix identity, the EM response of arbitrary implants can be computed within seconds. We compare the solution from full‐wave simulations with the results from the presented method, for two implant geometries.ResultsFrom the comparison, we found that the resulting electric and magnetic fields are numerically equivalent (maximum error of 1.35%). However, the computation was between 171 to 2478 times faster than the corresponding GPU accelerated full‐wave simulation.ConclusionsThe presented method enables for rapid and efficient evaluation of the RF fields near implants and might enable situation‐specific scanning conditions.

Square-wave processing of MEGATEM data

The recording of raw or streamed EM survey data, as done by CGG during MEGATEM surveys, allows for the reprocessing of the acquired EM data, including square-wave processing. During the latter, the recorded EM response to the actual half-sine waveform is replaced by the EM response to a square-wave, derived via deconvolution/convolution in the frequency domain. This makes the on- and early-time information more accessible for data modelling, including 1D inversions and conductivity-depth transformations. Square-wave EM data can also be corrected for survey height, transmitter-receiver offset and transmitter attitude. That correction allows for the interpretation of early-time EM response grids, which generally offer better spatial resolution than derived conductivity-depth slices. The advantages of square-wave processing are demonstrated on a MEGATEM data set acquired in 2013 in South America. With survey terrain clearance ranging from 100 – 1600 m, due to the rugged topography, early-time grids of elevation-corrected square-wave data outlined the shallow conductivity structure, whereas early-time grids of the original half-sine data mostly reflected the variable system elevation. Further, derived conductivity-depth sections of the square-wave data show more lateral continuity than the sections derived from the original half-sine data. These results show that the early-time information of square-wave is more accessible than in the original data, facilitating interpretation of shallow conductivity structures.

2.5D vs 1D AEM Forward and Inversion Methods at a Survey Scale : A Case Study

The McArthur basin/EMU fault study has a classic 2D fault feature and a buried conductor with an off-end effect with other 2D/3D effects away from the EMU fault. The collected AEM data has demonstrable AIP effects. This has stimulated an investigation of a simple 2D geology cross-section of a dipping fault with a strong conductor on one side of the fault. A forward model of the predicted response near the EMU fault represents a synthetic observed signal from the cross-section in agreement with the AEM data. Our modelling shows that the 1D inversion gives results which do not reproduce the survey data whereas 2.5D performs well reconciling the inverted section with the observed EM response. Away from the 2D geology region and other 2D/3D EM effects, 1D does perform well as expected. Therefore 2.5D gets it right in significantly more situations by honouring the information in the observed data raising questions about the use of 1D. Emerging AEM systems can provide estimates of economic rock unit thicknesses, dips, faults and anticline/syncline definition at an accuracy that mitigates the need for pattern drilling. The use of 2.5D allows marker beds of more conductive material to stand out at a depth of 500 m or more on sections created beneath individual flight lines. Routine treatment of all survey data is now possible without supercomputing capability. CSIRO has also recently undertaken comparative studies of the available AEM 1D, 2.5D and 3D inversion codes. Their work raises some stark reminders of what is different in the methodologies and how the progression to higher-order geophysics methods requires not just careful test work but also effective education of the user community. the fundamental differences between 1D and 2.5D and point out issues with the 1D forward modelling and inversion technology. Importantly, Maxwell’s equations are used to constrain 2.5D whilst empirical methods are commonly used in 1D. This leads to the situation where a near zero average misfit using stitched 1D models can be achieved with families of 1D inversions, whilst incorrectly predicting the geology. Therefore a low misfit does not necessarily indicate a good solution for 1D. The 2.5D method is a least-squares best fit of the observations and so the quoted misfit for 2.5D is a very different measure than for 1D. The study demonstrates that 2.5D yields a much more satisfactory geology section and a better reconciliation with information contained in the survey data

Electrical Resistivity Maps of the Australian Lower Crust

Crustal silicate rocks at sub-solidus temperatures normally have high electrical resistivities. However, although upper crust is typically > 103 .m, it is not unusual for lower crust to be < 102 .m, and in places < 100 .m. That lower crust (below 10-15 km) can be as electrically conducting as seawater is remarkable, and indicates a substantial and highly-connected mineral, melt or aqueous phase. To date, temporal and spatial mechanisms to give rise to the low resistivity are speculative and poorly constrained by observation and laboratory measurement. We present new maps of the Australian crust resistivity inferred from the regional EM responses. The project addresses the question as to whether the low resistivity is primary in the formation of the crust, or overprint due to melt and fluid migration from a deeper thermal source. A secondary question is how regions of low resistivity from an interconnected phase can be preserved through time-scales of billions of years. Observations are drawn from: the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP); 2D MT transects; and legacy MT and geomagnetic depth sounding (GDS) data. Our research demonstrates a strong spatial correlation of crustal resistivity with tectonic domains in Australia. Lowest resistivities are often imaged just below the rheological boundary between upper and lower crust at ~10-15 km. Below, low resistivity appears as a broad zone, tens or hundreds of kilometres wide, and tens of kilometres thick; above the boundary, regions of low-resistivity appear as narrower pathways. Such maps are correlated with long-wavelength Bouguer gravity data, suggesting a common origin that changes both density and resistivity.