Toward subsurface magnetic permeability imaging with electromagnetic induction sensors: Sensitivity computation and reconstruction of measured data

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. E335-E345 ◽  
Author(s):  
Tim Klose ◽  
Julien Guillemoteau ◽  
François-Xavier Simon ◽  
Jens Tronicke
Keyword(s):  
Electrical Conductivity ◽  
Magnetic Permeability ◽  
Electromagnetic Induction ◽  
Synthetic Data ◽  
Forward Modeling ◽  
Measured Data ◽  
Modeling Method ◽  
Near Surface ◽  
Sensitivity Functions ◽  
Modeling Approach

In near-surface geophysics, small portable loop-loop electromagnetic induction (EMI) sensors using harmonic sources with a constant and rather small frequency are increasingly used to investigate the electrical properties of the subsurface. For such sensors, the influence of electrical conductivity and magnetic permeability on the EMI response is well-understood. Typically, data analysis focuses on reconstructing an electrical conductivity model by inverting the out-of-phase response. However, in a variety of near-surface applications, magnetic permeability (or susceptibility) models derived from the in-phase (IP) response may provide important additional information. In view of developing a fast 3D inversion procedure of the IP response for a dense grid of measurement points, we first analyze the 3D sensitivity functions associated with a homogeneous permeable half-space. Then, we compare synthetic data computed using a linear forward-modeling method based on these sensitivity functions with synthetic data computed using full nonlinear forward-modeling methods. The results indicate the correctness and applicability of our linear forward-modeling approach. Furthermore, we determine the advantages of converting IP data into apparent permeability, which, for example, allows us to extend the applicability of the linear forward-modeling method to high-magnetic environments. Finally, we compute synthetic data with the linear theory for a model consisting of a controlled magnetic target and compare the results with field data collected with a four-configuration loop-loop EMI sensor. With this field-scale experiment, we determine that our linear forward-modeling approach can reproduce measured data with sufficiently small error, and, thus, it represents the basis for developing efficient inversion approaches.

1D single-site and laterally constrained inversion of multifrequency and multicomponent ground-based electromagnetic induction data — Application to the investigation of a near-surface clayey overburden

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. WB19-WB35 ◽  
Author(s):  
Cyril Schamper ◽  
Fayçal Rejiba ◽  
Roger Guérin
Keyword(s):  
Magnetic Field ◽  
Electromagnetic Induction ◽  
Search Algorithm ◽  
Random Search ◽  
A Priori ◽  
Synthetic Data ◽  
Conductive Layer ◽  
Near Surface ◽  
Priori Information ◽  
Definition Of

Electromagnetic induction (EMI) methods are widely used to determine the distribution of the electrical conductivity and are well adapted to the delimitation of aquifers and clayey layers because the electromagnetic field is strongly perturbed by conductive media. The multicomponent EMI device that was used allowed the three components of the secondary magnetic field (the radial [Formula: see text], the tangential [Formula: see text], and the vertical [Formula: see text]) to be measured at 10 frequencies ranging from 110 to 56 kHz in one single sounding with offsets ranging from 20 to 400 m. In a continuing endeavor to improve the reliability with which the thickness and conductivity are inverted, we focused our research on the use of components other than the vertical magnetic field Hz. Because a separate sensitivity analysis of [Formula: see text] and [Formula: see text] suggests that [Formula: see text] is more sensitive to variations in the thickness of a near-surface conductive layer, we developed an inversion tool able to make single-sounding and laterally constrained 1D interpretation of both components jointly, associated with an adapted random search algorithm for single-sounding processing for which almost no a priori information is available. Considering the complementarity of [Formula: see text] and [Formula: see text] components, inversion tests of clean and noisy synthetic data showed an improvement in the definition of the thickness of a near-surface conductive layer. This inversion code was applied to the karst site of the basin of Fontaine-Sous-Préaux, near Rouen (northwest of France). Comparison with an electrical resistivity tomography tends to confirm the reliability of the interpretation from the EMI data with the developed inversion tool.

Evaluation of a rapid hybrid spectral-spatial domain 3D forward-modeling approach for loop-loop electromagnetic induction quadrature data acquired in low-induction-number environments

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. E447-E458 ◽  
Author(s):  
Julien Guillemoteau ◽  
Jens Tronicke
Keyword(s):  
Electrical Conductivity ◽  
Large Scale ◽  
Structural Information ◽  
Forward Modeling ◽  
Spatial Domain ◽  
Near Surface ◽  
Homogeneous Half Space ◽  
Subsurface Environments ◽  
Em Induction ◽  
The Right

When exploring subsurface environments using electromagnetic (EM) induction (EMI) tools, approximate forward-modeling methods based on a homogeneous half-space kernel have been extensively evaluated in the past. For large-scale exploration methods, such as magnetotellurics, marine EM, airborne EM, transient EM, and large offset loop-loop harmonic EM, such forward-modeling approaches are limited because the kernel depends strongly on the subsurface distribution of electrical conductivity. However, the response of small portable EMI loop-loop sensors applied in a low-induction number (LIN) context are known to be more linearly related to the true distribution of electrical conductivity. Thus, data collected using such sensors are more adapted to an approximate forward-modeling with a conductivity-independent kernel. We have evaluated the bias of such an approximate modeling for the case of portable multiconfiguration system measurements in 1D, 2D, and 3D contexts. Our result shows that the approximate approach tends to underestimate the conductivity of more conductive targets but is able to reproduce the right structural information. Compared with previous algorithms presented in the literature, we solved the approximate forward-modeling problem in the hybrid spectral-spatial domain to speed up the computation. Considering the level of accuracy in structural modeling as well as the computational efficiency of our hybrid spectral-spatial approach, we conclude that this method is especially suitable for near-surface, large-scale mapping applications in LIN environments as typically encountered in soil sciences and archaeological studies. For such applications, our approach can be implemented in rapid multichannel deconvolution procedures.

Simultaneous calibration and inversion algorithm for multiconfiguration electromagnetic induction data acquired at multiple elevations

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. EN1-EN14 ◽  
Author(s):  
Xihe Tan ◽  
Achim Mester ◽  
Christian von Hebel ◽  
Egon Zimmermann ◽  
Harry Vereecken ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Electromagnetic Induction ◽  
Synthetic Data ◽  
Ground Surface ◽  
Acquisition Time ◽  
Inversion Algorithm ◽  
Transect Line ◽  
Promising Tool ◽  
Reference Measurements ◽  
And Inversion

Electromagnetic induction (EMI) is a contactless and fast geophysical measurement technique. Frequency-domain EMI systems are available as portable rigid booms with fixed separations up to approximately 4 m between the transmitter and the receivers. These EMI systems are often used for high-resolution characterization of the upper subsurface meters (up to depths of approximately 1.5 times the maximum coil separation). The availability of multiconfiguration EMI systems, which measure multiple apparent electrical conductivity ([Formula: see text]) values of different but overlapping soil volumes, enables EMI data inversions to estimate electrical conductivity ([Formula: see text]) changes with depth. However, most EMI systems currently do not provide absolute [Formula: see text] values, but erroneous shifts occur due to calibration problems, which hinder a reliable inversion of the data. Instead of using physical soil data or additional methods to calibrate the EMI data, we have used an efficient and accurate simultaneous calibration and inversion approach to avoid a possible bias of other methods while reducing the acquisition time for the calibration. By measuring at multiple elevations above the ground surface using a multiconfiguration EMI system, we simultaneously obtain multiplicative and additive calibration factors for each coil configuration plus an inverted layered subsurface electrical conductivity model at the measuring location. Using synthetic data, we verify our approach. Experimental data from five different calibration positions along a transect line showed similar calibration results as the data obtained by more elaborate vertical electrical sounding reference measurements. The synthetic and experimental results demonstrate that the multielevation calibration and inversion approach is a promising tool for quantitative electrical conductivity analyses.

3D inversion of magnetotelluric data by using a hybrid forward-modeling approach and mesh decoupling

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. E191-E205
Author(s):  
Deniz Varılsüha
Keyword(s):  
Graphics Processing Units ◽  
Hybrid Approach ◽  
Synthetic Data ◽  
Forward Modeling ◽  
Impedance Tensor ◽  
Inversion Algorithm ◽  
Data Types ◽  
Fe Method ◽  
Magnetotelluric Data ◽  
Modeling Approach

We have developed a new algorithm for the inversion of magnetotelluric (MT) data. The developed algorithm is built to be fast, versatile, and accurate. A fast inversion algorithm has to include a fast forward-modeling routine. To achieve that, a hybrid approach consisting of finite-difference (FD) and finite-element (FE) methods is used to benefit from the speed of the FD method and the flexibility to add topographic features of the FE method. To reduce the number of cells, and thus reducing the size of the system to be solved in the forward and pseudoforward solutions, different meshes for various groups of frequencies are used. Then, these are mapped onto the inversion mesh by a mesh-decoupling technique to further accelerate the inversion. To build a versatile inversion algorithm, the capability of using different data types is implemented. In addition to the impedance tensor and the magnetic transfer function, the algorithm also computes the phase tensor and phase vector, which are distortion-free forms of MT data. It is also possible to invert intersite data and their respective phase tensors using the developed code. Furthermore, the distortion matrix can also be estimated as a parameter. The new code is tested with different noisy and distorted synthetic data measured on a surface with topography to evaluate the inversion accuracy and computational efficiency. The results indicate that the code is accurate and that the runtimes are reasonable for the large 3D models considered. Using four graphics processing units, the hybrid forward-modeling approach and the mesh-decoupling technique together result in a 12 times speedup for the examples presented in this study.

scholarly journals An evaluation of water quality at Sandhill Wetland: implications for reclaiming wetlands above soft tailings deposits in northern Alberta, Canada

2021 ◽  
Author(s):  
Jeremy A. Hartsock ◽  
Jessica Piercey ◽  
Melissa K. House ◽  
Dale H. Vitt
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Surface Water ◽  
Water Chemistry ◽  
Water Quality Monitoring ◽  
Total Alkalinity ◽  
Near Surface ◽  
Water Quality Guidelines ◽  
Quality Guidelines ◽  
Annual Water

AbstractThe experimental Sandhill Wetland is the first permanent reclamation of a composite tailings deposit, and annual water quality monitoring is of specific interest for evaluating and predicting long-term reclamation performance. Here, we present water chemistry monitoring data obtained from Sandhill Wetland (years 2009–2019) and compare results to twelve natural reference wetlands and to environmental quality guidelines for Alberta surface waters. By comparing water quality at Sandhill Wetland and natural sites to established guidelines, we can begin to document the natural background water quality of wetlands in the region and examine if guideline exceedances are seen in natural undisturbed environments, or appear only at active reclamation sites. At Sandhill Wetland the dominant ions in near-surface water were bicarbonate, sulfate, chloride, sodium, calcium, and magnesium. Since the first growing season concentrations for these ions have increased annually, causing concurrent increases in electrical conductivity. In year 2019, water chemistry at Sandhill Wetland was most comparable to regional saline fens, systems that exhibit elevated electrical conductivity and high sodicity. Near-surface water at Sandhill Wetland exceeded water quality guidelines for three substances/properties (dissolved chloride, iron, and total alkalinity) in the most recent year of monitoring. The saline fen natural sites also exceeded water quality guidelines for the same chemical substances/properties, suggesting guideline exceedances are a norm for some natural wetland site types in the region. Of note, in each year of monitoring at Sandhill Wetland, dissolved organic compounds evaluated in sub- and near-surface water were below detection limits.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

Enabling isotropic reflectivity modeling and inversion in anisotropic media

2021 ◽  
Vol 40 (4) ◽  
pp. 267-276
Author(s):  
Peter Mesdag ◽  
Leonardo Quevedo ◽  
Cătălin Tănase
Keyword(s):  
Synthetic Data ◽  
Anisotropic Media ◽  
Forward Modeling ◽  
Seismic Inversion ◽  
Stratified Medium ◽  
Effective Parameters ◽  
Elastic Parameters ◽  
Pp Wave ◽  
Anisotropic Elastic ◽  
And Inversion

Exploration and development of unconventional reservoirs, where fractures and in-situ stresses play a key role, call for improved characterization workflows. Here, we expand on a previously proposed method that makes use of standard isotropic modeling and inversion techniques in anisotropic media. Based on approximations for PP-wave reflection coefficients in orthorhombic media, we build a set of transforms that map the isotropic elastic parameters used in prestack inversion into effective anisotropic elastic parameters. When used in isotropic forward modeling and inversion, these effective parameters accurately mimic the anisotropic reflectivity behavior of the seismic data, thus closing the loop between well-log data and seismic inversion results in the anisotropic case. We show that modeling and inversion of orthorhombic anisotropic media can be achieved by superimposing effective elastic parameters describing the behavior of a horizontally stratified medium and a set of parallel vertical fractures. The process of sequential forward modeling and postinversion analysis is exemplified using synthetic data.

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