Magnetotelluric Transfer Functions Research Articles

New robust remote reference estimator using robust multivariate linear regression

SUMMARY The solution of the remote reference method, a frequently used technique in magnetotelluric (MT) data processing, can be viewed as a product of the two-input–multiple-output relationship between the local electromagnetic field and the reference field at a remote station. By applying a robust estimator to the two-input–multiple-output system, one can suppress the influence of outliers in the local magnetic field as well as those in the local electric field based on regression residuals. Therefore, this study develops a new robust remote reference estimator with the aid of robust multivariate linear regression. By applying the robust multivariate regression S-estimator to the multiple-output system, the present work derives a set of equations for robust estimates of the transfer function, noise variances, and the scale of the Mahalanobis distance simultaneously. The noise variances are necessary for the multivariate analysis to normalize the residuals of dependent variables. The Mahalanobis distance, a distance measure for multivariate data, is a commonly used indicator of outliers in multivariate statistics. By updating those robust estimates iteratively, the new robust remote reference estimator seeks the transfer function that minimizes the robust scale estimate of the Mahalanobis distance. The developed estimator can avoid bias in the MT transfer function even if there are significant noises in the reference magnetic field and handle outlying data more robustly than previously proposed robust remote reference estimators. The authors applied the developed method to a synthetic data set and real-world data. The test results demonstrate that the developed method downweights outliers in the local electric and magnetic fields and gives an unbiased transfer function.

Mapping Geoelectric Field Hazards in Ireland

AbstractGeoelectric fields are generated at the Earth's surface and can lead to the induction of hazardous geomagnetically induced currents (GIC) in infrastructure like power grids, railways and pipelines during geomagnetic storms. Magnitude and orientation of the geoelectric fields, in relation to the infrastructure, are key features needed to determine the intensity of GIC. Here, we developed the first geoelectric hazard map for the island of Ireland, with the aim of providing detailed information that can help stakeholders mitigate the impact of GICs. The hazard map was developed by modeling and mapping the geoelectric field across Ireland for 28 years (1991–2018) using magnetic field data with magnetotelluric transfer functions. The approach for developing the hazard map calculates the probability of exceeding a hazardous geoelectric field threshold (500 mV/km) during large geomagnetic storms, taking directionality and amplitude into account. We found hazardous geoelectric fields to be mostly localized in areas in the west, south‐west and northern coast. We observed that the geoelectric field have a stronger dominant orientation than the orientation of the geomagnetic field, often constraining the hazardous geoelectric field in particular directions only. We demonstrate a seasonal/diurnal effect is present in the geoelectric field time series. The impact of galvanic distortion was also assessed, and we demonstrate that there is a significant difference in terms of amplitude and direction between both models.

Improved accuracy of plane-wave electromagnetic modelling by application of the total and scattered field decomposition and perfectly matched layers

SUMMARY In 2-D magnetotelluric modelling, the standard application of Dirichlet boundary conditions (BC) may severely diminish the solution accuracy, because the unknown scattered part of the electromagnetic field is erroneously reflected at the domain boundary. Therefore, we adapt the total and scattered field decomposition (TSFD) to geophysical modelling, enabling the application of fully absorbing boundary methods, here perfectly matched layers (PML), to the scattered field. Our novel TSFD divides the modelling domain into two regions. In the total-field region containing the area of interest, the solution is computed for the total field. In the scattered-field region containing the boundaries, the solution is obtained for the scattered field, which is fully absorbed by PML at the boundaries. The plane-wave source is excited at the TSFD interface between both regions. Thus, boundary reflections are eradicated leading to superior solution accuracy, and boundaries can be placed closer to the receivers, shrinking the computational problem. Especially for challenging models with strong lateral changes, the solution accuracy of the TSFD is superior to that of the standard Dirichlet approach. Owing to the linearity of Maxwell’s equations, the inaccuracy introduced to the electric and magnetic fields by using Dirichlet BC can be expected to partly cancel out in the magnetotelluric transfer functions, for example the impedance tensor. In this work, we quantify this cancellation effect. The inaccuracy is less than typical measurement errors in the vast majority of apparent resistivity and phase data, even, when the primary fields are strongly inaccurate.

Nowcasting geoelectric fields in Ireland using magnetotelluric transfer functions

Geomagnetically induced currents (GIC) driven by geoelectric fields pose a hazard to ground-based infrastructure, such as power grids and pipelines. Here, a new method is presented for modelling geoelectric fields in near real time, to provide valuable information to help mitigate the impact of GIC. The method uses magnetic field measurements from the Magnetometer Network of Ireland (MagIE; https://www.magie.ie), interpolates the geomagnetic field variations between magnetometers using spherical elementary current systems (SECS), and estimates the local electric field using a high-density (< 40 km) network of magnetotelluric transfer functions (MT-TF) encompassing the island. The model was optimised to work in near real time, with a correction curve applied to the geoelectric field time series. This approach was successfully validated with measured electric fields at four sites for a number of geomagnetic storms, providing accurate electric fields up to a 1-minute delay from real time, with high coherence (0.70 – 0.85) and signal-to-noise ratio (SNR; 3.2 – 6.5) relative to measured electric field validation time series. This was comparable to a standard non-real-time geoelectric field model (coherence = 0.80 − 0.89 and SNR = 4.0 − 7.0). The impact of galvanic distortion on the model was also briefly evaluated, with a galvanic distortion correction leading to a more homogeneous representation of the direction of the electric field, at a regional scale.

Multi-scale imaging of 3-D electrical conductivity structure under the contiguous US constrains lateral variations in the upper mantle water content

The magnetotelluric (MT) component of the USArray survey is a unique data set that enables imaging the electrical conductivity distribution from the surface down to astenospheric depths. Here, we present a new 3-D electrical conductivity model (MECMUS-2022) derived by inverting data from 1291 USArray MT stations covering ∼80% of the contiguous United States on a quasi-regular 70-km grid. The inversion was performed using a novel multi-scale imaging approach that can consistently incorporate a large range of spatial scales and perform 3-D modeling directly in the spherical frame, completely avoiding the conventional flat-Earth assumption. Furthermore, the use of locally refined meshes allows us to take into account the complex coastline and mimic the natural resolution footprint of broadband MT transfer functions. We find conductivity variations that correlate with known continental structures such as due to the active tectonic processes within the western United States (e.g., Yellowstone hotspot, Basin and Range extension, and subduction of the Juan de Fuca slab) as well as the presence of deep roots beneath cratons. We further interpreted conductivity variations in terms of the upper mantle water content by coupling electrical conductivity with constrains on mantle thermo-chemical structure derived from the analysis of seismic data (in the form of P-to-s and S-to-p receiver functions). Our results suggest the existence of a relatively dry upper mantle beneath the United States, with a weak trend in the upper mantle water content from North to South.

Electrical resistivity structure of Danau Ranau geothermal prospect area based on integrated 3-D Inversion of impedance tensor and tipper vector

Subsurface electrical resistivity distribution needs to be revealed to explore the geothermal potential in The Danau Ranau prospect area, as the components in geothermal systems could be easily characterized by their resistivity contrasts. The magnetotelluric method is a geophysical method commonly used to perform this task. This paper performs a three-dimensional inversion based on the complete component of magnetotelluric transfer functions, including impedance tensor and tipper vector. Prior dimensionality analysis using phase tensor revealed that the MT data contains a high dimensionality distortion and shows significant horizontal geoelectrical variations. The analysis suggests using the MT full components in the inversion process to effectively recover all the geoelectrical features in such a geologically complex area. The three-dimensional inversion was then carried out after taking control of the model mesh dimension and the regularization parameter. The 3-D resistivity model showed an overburden layer with varying resistivity in the shallow depth. In the subsequent layer, a conductive anomaly representing impermeable cap rock is distributed from the center to the northern and western parts of the study area, bordered by faults and manifestations. The reservoir zone is located under the center of Mount Seminung at an approximate depth of 1500 m. The heat source is expected to be the residual eruption magma of the volcano, which sits far under the reservoir zone and is unreachable by the MT signal. All the findings agree with the existing geological and geochemical survey data and can explain the hydrothermal activities in the Danau Ranau geothermal prospect area.

Investigation of the electrical resistivity structure of the subsurface at Mogod valley in central Mongolia: Insight is using 1D Magnetotelluric inversion

In this paper, we report a preliminary result of the Magnetotelluric investigation of the Mogod area. The Mogod region is one of the most prominent fields for geophysical study since the region includes young and active faults and geothermal activities. We conducted magnetotelluric measurements at 20 sites during geophysical field seasons in 2018-2021 as a pilot survey to understand data property and the electromagnetic noise level for the detailed electromagnetic studies. During the fieldwork, we used Lemi Magnetotelluric instruments and measured all three orthogonal components of the magnetic field and the horizontal components of the electric field. For the data processing, we used Matlab code by using the M-estimate regression method, and estimated the magnetotelluric transfer function with a lownoise level. The electrical resistivity model of the subsurface of survey layout shows us the existing resistivity anomalies at shallow-depth, and thickness of the upper crust approximately 11-17 km. Here, suggest that the thickness of the upper crust is 17 km and crust is 40 km with local magnetotelluric measurements. Additionally, the electric conductor appears in the southwest of Mogod region, we interpret that conductor play as a source of geological activity of Mogod region, and it might be the signature of a remanent fluid.

Investigation of the electrical resistivity structure of the subsurface at Mogod valley in central Mongolia: Insight is using 1D Magnetotelluric inversion

In this paper, we report a preliminary result of the Magnetotelluric investigation of the Mogod area. The Mogod region is one of the most prominent fields for geophysical study since the region includes young and active faults and geothermal activities. We conducted magnetotelluric measurements at 20 sites during geophysical field seasons in 2018-2021 as a pilot survey to understand data property and the electromagnetic noise level for the detailed electromagnetic studies. During the fieldwork, we used Lemi Magnetotelluric instruments and measured all three orthogonal components of the magnetic field and the horizontal components of the electric field. For the data processing, we used Matlab code by using the M-estimate regression method, and estimated the magnetotelluric transfer function with a lownoise level. The electrical resistivity model of the subsurface of survey layout shows us the existing resistivity anomalies at shallow-depth, and thickness of the upper crust approximately 11-17 km. Here, suggest that the thickness of the upper crust is 17 km and crust is 40 km with local magnetotelluric measurements. Additionally, the electric conductor appears in the southwest of Mogod region, we interpret that conductor play as a source of geological activity of Mogod region, and it might be the signature of a remanent fluid.

Source effect impact on the magnetotelluric transfer functions

It is known that the deviation from the plane wave assumption (the so-called source effect) has an impact on the results of vertical transfer function (VTF) estimation, especially for long periods. We observe the so-called seasonal effect, i.e. the VTF calculated from the data measured in the summer months is different from the VTF estimated from the winter months data. This is related to the length of the day, as in the diurnal data the effect of deviation from the plane wave is greater. In the present work, its potential effect on the estimation of the impedance tensor for magnetotelluric soundings is investigated. A unique, very long series of magnetotelluric recordings at the Belsk Magnetic Observatory was used for the analysis. The results showed that we do not observe the summer-winter seasonal changes as it is in the case of VTF. Small differences can be noticed as a result of TF estimation separately for diurnal and nocturnal data. The analysis of prediction errors confirms this finding and proves that the daily data are more distorted (distant with the plane wave). More detailed analyzes were performed by making a precise selection of data, dividing them into those that fulfill and those that do not fulfill the assumptions of the plane wave. The results show that the impedances estimated from data separated in this way may differ by several percent.

Climatological Statistics of Extreme Geomagnetic Fluctuations With Periods From 1 s to 60 min

AbstractUsing a global database of 125 magnetometers covering several decades, we present occurrence statistics for fluctuations of the horizontal geomagnetic field (dBh/dt) exceeding the 99.97th percentile (P99.97) for both ramp changes (Rn) and the root‐mean‐square (Sn) of fluctuations over periods,τ, from 1 to 60 min and describe their variation with geomagnetic latitude and magnetic local time (MLT). Rates of exceedance are explained by reference to the magneto‐ionospheric processes dominant in different latitude and MLT sectors, including ULF waves, interplanetary shocks, auroral substorm currents, and traveling convection vortices. By fitting generalized Pareto tail distributions aboveP99.97, we predict return levels (RLs) forRnandSnover return periods of between 5 and 500 years. P99.97and RLs increase monotonically with frequency (1/τ) (with a few exceptions at auroral latitudes) and this is well modeled by quadratic functions whose coefficients vary smoothly with latitude. For UK magnetometers providing 1‐s cadence measurements, the analysis is extended to cover periods from 1 to 60 s and empirical Magnetotelluric Transfer functions are used to predict percentiles and return levels of the geoelectric field over a wide frequency range (2 × 10−4to 4 × 10−2 Hz) assuming a sinusoidal field fluctuation. These results help identify the principal causes of field fluctuations leading to extreme geomagnetically induced currents (GIC) in ground infrastructure over a range of timescales and they inform the choice of frequency dependence to use withdBh/dtas a GIC proxy.

Comparison of stable maximum likelihood estimator with traditional robust estimator in magnetotelluric impedance estimation

The newly developed stable maximum likelihood estimator (MLE) has been considered to be superior to the traditional robust estimation for Magnetotelluric (MT) transfer functions, based on the examination of field data. However, due to the unknown MT response function for real data, it is difficult to judge the validity of any comparisons between the performance of the two estimators. This can be realized by comparing the performances on synthetic data, as different ideal error distributions can be modeled (e.g., noise contaminated magnetic fields can be simulated by adding desired noise into the assumed clean version). In this paper, we generate synthetic MT data with desired error distributions (e.g. Gaussian and Cauchy distributions) based on the estimated MT impedance and Fourier transformed measured magnetic data (as the input) from one MT site located in southeast part of Tibet Plateau collected under the SinoProbe project. The comparison is demonstrated in terms of the apparent resistivity and phase, and their estimated standard deviations. The performance of the two methods and their variants are tested based on generated synthetic data with various noise patterns. Synthetic tests indicate that their performance in terms of handling noisy data is generally comparable. The bias in the estimation is more sensitive to noise in the input. Then they are applied to process real data from two MT sites in the same region, indicating their solutions are generally similar.

Magnetotelluric multiscale 3-D inversion reveals crustal and upper mantle structure beneath the Hangai and Gobi-Altai region in Mongolia

SUMMARY Central Mongolia is a prominent region of intracontinental surface deformation and intraplate volcanism. To study these processes, which are poorly understood, we collected magnetotelluric (MT) data in the Hangai and Gobi-Altai region in central Mongolia and derived the first 3-D resistivity model of the crustal and upper mantle structure in this region. The geological and tectonic history of this region is complex, resulting in features over a wide range of spatial scales, which that are coupled through a variety of geodynamic processes. Many Earth properties that are critical for the understanding of these processes, such as temperature as well as fluid and melt properties, affect the electrical conductivity in the subsurface. 3-D imaging using MT can resolve the distribution of electrical conductivity within the Earth at scales ranging from tens of metres to hundreds of kilometres, thereby providing constraints on possible geodynamic scenarios. We present an approach to survey design, data acquisition, and inversion that aims to bridge various spatial scales while keeping the required field work and computational cost of the subsequent 3-D inversion feasible. MT transfer functions were estimated for a 650 × 400 km2 grid, which included measurements on an array with regular 50 × 50 km2 spacing and along several profiles with a denser 5–15 km spacing. The use of telluric-only data loggers on these profiles allowed for an efficient data acquisition with a high spatial resolution. A 3-D finite element forward modelling and inversion code was used to obtain the resistivity model. Locally refined unstructured hexahedral meshes allow for a multiscale model parametrization and accurate topography representation. The inversion process was carried out over four stages, whereby the result from each stage was used as input for the following stage that included a finer model parametrization and/or additional data (i.e. more stations, wider frequency range). The final model reveals a detailed resistivity structure and fits the observed data well, across all periods and site locations, offering new insights into the subsurface structure of central Mongolia. A prominent feature is a large low-resistivity zone detected in the upper mantle. This feature suggests a non-uniform lithosphere-asthenosphere boundary that contains localized upwellings that shallow to a depth of 70 km, consistent with previous studies. The 3-D model reveals the complex geometry of the feature, which appears rooted below the Eastern Hangai Dome with a second smaller feature slightly south of the Hangai Dome. Within the highly resistive upper crust, several conductive anomalies are observed. These may be explained by late Cenozoic volcanic zones and modern geothermal areas, which appear linked to mantle structures, as well as by major fault systems, which mark terrane boundaries and mineralized zones. Well resolved, heterogeneous low-resistivity zones that permeate the lower crust may be explained by fluid-rich domains.

EMTF XML: New data interchange format and conversion tools for electromagnetic transfer functions

Initial processing of magnetotelluric (MT) data collected at a site results in a small data file that defines the MT transfer functions (MT TFs) or variants at a discrete set of frequencies. Although not data intensive, the TF represents almost all of the information about earth’s conductivity found in the raw data and provides a key input to geophysical inversion and to geomagnetic hazard-mitigation procedures. However, to be useful for scientific interpretation, MT TFs must be accompanied by carefully recorded metadata. The value of these data is amplified if they are collected into a common database in a discoverable fashion; to achieve this, the metadata must also be searchable. We have developed a new format for MT and related electromagnetic transfer function extensible markup language (EMTF XML), which is a novel, self-describing, searchable, and extensible way to store the data. We also evaluate our open-source, highly capable conversion tools that implement format conversion between historical MT TF formats (electrical data interchange [EDI], EDI SPECTRA, Z-files, and potentially others) and EMTF XML and we examine the associated issues of data rotation. We have paired our work with the open-source format conversion tools, EMTF FCU v4.0, with a user guide and a set of use case examples. We hope that this effort will assist the MT community in creating a more open data-sharing culture and practices.

Comparison Between 1-D and 3-D Geoelectric Field Methods to Calculate Geomagnetically Induced Currents: A Case Study

Severe Geomagnetic Disturbances (GMD) pose a threat to the reliability of the United States bulk electrical power system. The NERC reliability standard TPL-007 requires transmission planners to assess potential problems in their service territories due to Geomagnetically Induced Currents (GIC) including transformer thermal assessment. If the assessment indicates a vulnerability, the standard requires the development of a corrective action plan to resolve potential issues. GIC calculation accuracy is critical to the assessment. In this paper, the impact of various geoelectric field calculation methods on the accuracy of calculated GIC is evaluated by comparing with observations for a geomagnetic storm that occurred on 07–08 September, 2017. The GIC calculation is carried out for a fairly large-scale power system model and the comparison with observation indicates that better results are achieved using magnetotelluric transfer functions that incorporate the effects of 3-D earth conductivity. The results also indicate an improvement in the comparisons when the transfer-function derived E-fields are interpolated between the original survey site locations.

Topographic distortions of magnetotelluric transfer functions: a high-resolution 3-D modelling study using real elevation data

Topographic distortions of magnetotelluric transfer functions: a high-resolution 3-D modelling study using real elevation data

Constrained smoothness optimization of bootstrapped transfer functions for handling noisy MT data

In the Magnetotelluric (MT) method which generally handles noisy data, data processing is a key-procedure, robust methods with a remote reference are in standard use. However, there are often situations, where no method yields useable transfer functions (TF) due to ultimately high noise levels.For such situations, we propose a new method, based on the bootstrap inference that yields many candidate estimates of MT TFs and their errorbars immediately via resampling, and on their constrained optimization to pick one set of TFs smoothly varying with period and ranging within feasible region.We show field illustrations, using MT data on the Korean peninsula and long-period MT datasets from EMSLAB and SAMTEX projects. We conclude that the method extracts usable impedance estimates even from heavily contaminated MT data objectively without making fabrication.

Robust data processing of noisy marine controlled-source electromagnetic data using independent component analysis

Data processing techniques are often used to estimate the noise-free response of marine controlled-source electromagnetic (CSEM) data and magnetotelluric transfer functions. We have implemented a new CSEM data processing scheme that uses a robust method based on independent component analysis (ICA) to extract interpretable datasets from noisy marine CSEM data. We applied the data processing scheme to signals from a new CSEM observation system comprising a remotely operated vehicle (ROV) and an ocean bottom electromagnetometer (OBEM). These datasets were obtained around the Iheya North hydrothermal field, Okinawa Trough, Japan. The observation system allows a small-scale CSEM survey to be conducted in areas of steep topography, such as hydrothermal fields, because the ROV can deploy the OBEM at the exact observation site. The results show that the coherent and environment noise that exists in the raw time series is reduced sufficiently by ICA processing. It makes interpretation of the resulting electric field data possible. The results also show that the processed data has a higher signal-to-noise ratio in the middle-to-high-frequency band than the data without ICA. The normalised spectrum, obtained by normalising the observed data from the hydrothermal area, indicates that a conductive anomaly exists in the near-offset area around the OBEM. We apply 2D inversion to the electric field data and find that a low resistivity body exists beneath the OBEM and 50 m offset from the OBEM. This resistivity structure is consistent with images taken by the ROV that show characteristic organisms in hydrothermal seepage around the OBEM site.

Magnetotelluric Transfer Functions: Phase Tensor and Tipper Vector above a Simple Anisotropic Three-Dimensional Conductivity Anomaly and Implications for 3D Isotropic Inversion

The influence of anisotropic conductivity structures on magnetotelluric transfer functions is not easy to analyse in its entire complexity. In this study, we investigate the spatial and frequency-dependent behaviour of phase tensors and tipper vectors above a 3D anisotropic conductivity anomaly. The anomaly consists of a simple cubic block embedded in a homogeneous half space. Using a 3D FD code, we compare an isotropic, 2 anisotropic models with an anisotropy factor of 10 and one anisotropic model with the anisotropy factor of 100. The results show characteristic differences between the isotropic and anisotropic cases. For the anisotropic anomalies, the tipper vectors are parallel over the entire area despite the 3D geometry of the anomalous body. The size of the tipper vectors depends on the position of the site relative to the anomaly’s boundaries and the direction of the anisotropic strike. Above the anomalous anisotropic body, the main diagonal elements of the phase tensor show the well-known split. Outside the anomaly, the phase tensor principal axis rotates according to the site position in contrast to the constant tipper direction. The 3D inversion of the forward data using an isotropic 3D code (ModEM) yields a very good fit for all cases. Whereas the inversion result matches the isotropic model, wave-like structures with high conductivity contrast occur for the anisotropic models. These structures extend far beyond the extension of the original anomalous body. Thus, the study reveals important indications of the existence of anisotropic conductivity structures for observed magnetotelluric transfer functions.

Horizontal magnetovariational responses in geothermal exploration: synthetic model studies

Horizontal magnetic inter-station transfer functions, which are less distorted by near surface inhomogeneities and more sensitive to the deep targets, have been incorporated with other magnetotelluric data sets to delineate the electrical conductivity distribution in geothermal zones. Geothermal settings composed of salty fluid saturated faults and fractures, and hydrothermal alterations show a wide variation of the bulk resistivity. This makes electromagnetic methods, particularly magnetotellurics which is able to detect the geoelectric structures of deep targets, ideal techniques for the exploration of geothermal regions. In this research, the horizontal magnetovariational data are combined with other magnetotelluric transfer functions and their capabilities for improving the electrical conductivity structure obtained from 2D inversion process are examined. To this end, several synthetic models-representative of the conductivity changes in geothermal fields or conceptual modelshave been utilized. The results from two-dimensional (2D) inversion confirm the effectiveness of horizontal magnetic tensor as a part of the transfer functions, especially for the detection of deep conductive features.

A combinatorial filtering method for magnetotelluric data series with strong interference

In highly industrialized areas, magnetotelluric (MT)-induced variations are contaminated by strong manmade noise signals. A method is described as an alternative approach for noise removal, based on a combination of empirical mode decomposition (EMD) with independent component analysis (ICA). The filtering procedure takes advantage of the fact that data are analyzed through different scale levels, which requires a minimum of human intervention and leaves good data sections unchanged. Principle and steps of method are discussed, and de-noising results are evaluated by some parameters. After the filtering stage, data is processed in the frequency domain to yield two sets of reliable MT transfer functions and the result was compared with that of the EMD-Wavelet method. Simulated signal and measured MT data series are processed. The results show that this procedure can lead to greatly improved apparent resistivity and phase curves after processing. Point defects are filtered out to eliminate their deleterious influence, which yields reliable estimates of the MT transfer functions. The EMD-ICA method provides a new method for the de-noising of MT data series under the condition of low SNR.