Forward Modeling and 3D Inversion of EM Data Collected Over the McArthur River Uranium Deposit in the Athabasca Basin, Canada

Geophysics ◽  
2021 ◽  
pp. 1-86
Author(s):  
Reza Mir ◽  
Peter Fullagar ◽  
Mehrdad Darijani ◽  
Richard Smith ◽  
Shawn Scott ◽  
...  
Keyword(s):  
Field Data ◽  
Time Windows ◽  
Geophysical Methods ◽  
Synthetic Data ◽  
3D Inversion ◽  
Data Set ◽  
Athabasca Basin ◽  
Thickness Variations ◽  
Cover Thickness ◽  
Airborne Em

Detection and assessment of the deeply buried high-grade uranium deposits in the Athabasca Basin rely on geophysical methods to map conductive rocks. Variable Quaternary surface cover can mask the anomalous signals from depth and affect interpretation of inverted conductivity models. We present the analysis of a number of EM modeling studies and two field data sets, to demonstrate the effects of varying Quaternary cover resistivity and thickness, on the ability to resolve the parameters of underlying sandstone, alteration, and basement conductors. Synthetic data, assuming a typical shallow EM sounding system and realistic resistivities found in the Athabasca Basin, show that resistivity and thickness parameters of the Quaternary cover can be separately recovered in cases where this cover is more conductive than the underlying sandstone, but not when the cover is significantly more resistive. A 3D modeling study shows that using airborne EM data, it is possible to detect a basement conductor of 20 S at a depth of at least 600 m below surface, even in the presence of Quaternary cover thickness variations of the up to 20% (40 m to 60 m). Furthermore, while Quaternary cover variations and deeper sandstone alteration can produce comparable anomalous signal amplitudes in a time-domain EM response, their effects are most visible in distinctly separate time windows. Analysis of a GPR field data set to map the thickness of Quaternary cover in the McArthur River area, indicates that this cover consists mostly of sandy tills and ranges in thickness from 0 to 117 m. Constrained 3D inversion of an airborne EM data set from the same area shows basement conductors consistent with the depth and location of a known fault. Elevated conductivity in the sandstone by up to a factor of two over the background values could indicate possible alteration.

scholarly journals Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

2010 ◽  
Vol 14 (3) ◽  
pp. 545-556 ◽  
Author(s):  
J. Rings ◽  
J. A. Huisman ◽  
H. Vereecken
Keyword(s):  
Water Content ◽  
Particle Filtering ◽  
Field Data ◽  
Synthetic Data ◽  
Time Domain Reflectometry ◽  
Second Step ◽  
Parameter Estimates ◽  
Posterior Distributions ◽  
Data Set ◽  
Resistivity Tomography

Abstract. Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.

3D plane-wave migration in tilted coordinates: A field data example

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCA199-WCA209 ◽  
Author(s):  
Guojian Shan ◽  
Robert Clapp ◽  
Biondo Biondi
Keyword(s):  
Plane Wave ◽  
Field Data ◽  
Synthetic Data ◽  
Data Set ◽  
Wave Source ◽  
Surface Data ◽  
The One ◽  
Wave Migration ◽  
Wavefield Extrapolation ◽  
Slant Stacking

We have extended isotropic plane-wave migration in tilted coordinates to 3D anisotropic media and applied it on a Gulf of Mexico data set. Recorded surface data are transformed to plane-wave data by slant-stack processing in inline and crossline directions. The source plane wave and its corresponding slant-stacked data are extrapolated into the subsurface within a tilted coordinate system whose direction depends on the propagation direction of the plane wave. Images are generated by crosscorrelating these two wavefields. The shot sampling is sparse in the crossline direction, and the source generated by slant stacking is not really a plane-wave source but a phase-encoded source. We have discovered that phase-encoded source migration in tilted coordinates can image steep reflectors, using 2D synthetic data set examples. The field data example shows that 3D plane-wave migration in tilted coordinates can image steeply dipping salt flanks and faults, even though the one-way wave-equation operator is used for wavefield extrapolation.

A periodically varying code for improving deblending of simultaneous sources in marine acquisition

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. V213-V225 ◽  
Author(s):  
Shaohuan Zu ◽  
Hui Zhou ◽  
Yangkang Chen ◽  
Shan Qu ◽  
Xiaofeng Zou ◽  
...  
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Data Sets ◽  
Ocean Bottom ◽  
Data Set ◽  
Acceptable Model ◽  
Model Subspace ◽  
New Form ◽  
Simultaneous Source ◽  
Practical Field

We have designed a periodically varying code that can avoid the problem of the local coherency and make the interference distribute uniformly in a given range; hence, it was better at suppressing incoherent interference (blending noise) and preserving coherent useful signals compared with a random dithering code. We have also devised a new form of the iterative method to remove interference generated from the simultaneous source acquisition. In each iteration, we have estimated the interference using the blending operator following the proposed formula and then subtracted the interference from the pseudodeblended data. To further eliminate the incoherent interference and constrain the inversion, the data were then transformed to an auxiliary sparse domain for applying a thresholding operator. During the iterations, the threshold was decreased from the largest value to zero following an exponential function. The exponentially decreasing threshold aimed to gradually pass the deblended data to a more acceptable model subspace. Two numerically blended synthetic data sets and one numerically blended practical field data set from an ocean bottom cable were used to demonstrate the usefulness of our proposed method and the better performance of the periodically varying code over the traditional random dithering code.

Least-squares Gaussian beam migration

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. S87-S100 ◽  
Author(s):  
Hao Hu ◽  
Yike Liu ◽  
Yingcai Zheng ◽  
Xuejian Liu ◽  
Huiyi Lu
Keyword(s):  
Least Squares ◽  
Gaussian Beam ◽  
Spatial Resolution ◽  
Field Data ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Seismic Acquisition ◽  
Gaussian Beam Migration ◽  
Least Squares Migration

Least-squares migration (LSM) can be effective to mitigate the limitation of finite-seismic acquisition, balance the subsurface illumination, and improve the spatial resolution of the image, but it requires iterations of migration and demigration to obtain the desired subsurface reflectivity model. The computational efficiency and accuracy of migration and demigration operators are crucial for applying the algorithm. We have developed a test of the feasibility of using the Gaussian beam as the wavefield extrapolating operator for the LSM, denoted as least-squares Gaussian beam migration. Our method combines the advantages of the LSM and the efficiency of the Gaussian beam propagator. Our numerical evaluations, including two synthetic data sets and one marine field data set, illustrate that the proposed approach could be used to obtain amplitude-balanced images and to broaden the bandwidth of the migrated images in particular for the low-wavenumber components.

scholarly journals Imaging near-surface heterogeneities by natural migration of backscattered surface waves: Field data test

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. S197-S205 ◽  
Author(s):  
Zhaolun Liu ◽  
Abdullah AlTheyab ◽  
Sherif M. Hanafy ◽  
Gerard Schuster
Keyword(s):  
Surface Waves ◽  
Field Data ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
3D Data ◽  
Strong Surface ◽  
Migration Method ◽  
Recorded Data

We have developed a methodology for detecting the presence of near-surface heterogeneities by naturally migrating backscattered surface waves in controlled-source data. The near-surface heterogeneities must be located within a depth of approximately one-third the dominant wavelength [Formula: see text] of the strong surface-wave arrivals. This natural migration method does not require knowledge of the near-surface phase-velocity distribution because it uses the recorded data to approximate the Green’s functions for migration. Prior to migration, the backscattered data are separated from the original records, and the band-passed filtered data are migrated to give an estimate of the migration image at a depth of approximately one-third [Formula: see text]. Each band-passed data set gives a migration image at a different depth. Results with synthetic data and field data recorded over known faults validate the effectiveness of this method. Migrating the surface waves in recorded 2D and 3D data sets accurately reveals the locations of known faults. The limitation of this method is that it requires a dense array of receivers with a geophone interval less than approximately one-half [Formula: see text].

A ray inversion method for refraction analysis

Geophysics ◽  
1985 ◽  
Vol 50 (11) ◽  
pp. 1701-1720 ◽  
Author(s):  
Glyn M. Jones ◽  
D. B. Jovanovich
Keyword(s):  
Field Data ◽  
Opposite Sign ◽  
Synthetic Data ◽  
Head Wave ◽  
Inversion Method ◽  
Data Set ◽  
Near Surface ◽  
Left And Right ◽  
A New Technique ◽  
Good Agreement

A new technique is presented for the inversion of head‐wave traveltimes to infer near‐surface structure. Traveltimes computed along intersecting pairs of refracted rays are used to reconstruct the shape of the first refracting horizon beneath the surface and variations in refractor velocity along this boundary. The information derived can be used as the basis for further processing, such as the calculation of near‐surface static delays. One advantage of the method is that the shape of the refractor is determined independently of the refractor velocity. With multifold coverage, rapid lateral changes in refractor geometry or velocity can be mapped. Two examples of the inversion technique are presented: one uses a synthetic data set; the other is drawn from field data shot over a deep graben filled with sediment. The results obtained using the synthetic data validate the method and support the conclusions of an error analysis, in which errors in the refractor velocity determined using receivers to the left and right of the shots are of opposite sign. The true refractor velocity therefore falls between the two sets of estimates. The refraction image obtained by inversion of the set of field data is in good agreement with a constant‐velocity reflection stack and illustrates that the ray inversion method can handle large lateral changes in refractor velocity or relief.

scholarly journals Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

2009 ◽  
Vol 6 (5) ◽  
pp. 6387-6424 ◽  
Author(s):  
J. Rings ◽  
J. A. Huisman ◽  
H. Vereecken
Keyword(s):  
Water Content ◽  
Particle Filtering ◽  
Field Data ◽  
Synthetic Data ◽  
Time Domain Reflectometry ◽  
Second Step ◽  
Parameter Estimates ◽  
Posterior Distributions ◽  
Data Set ◽  
Resistivity Tomography

Abstract. Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.

scholarly journals Waveform inversion using a logarithmic wavefield

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R31-R42 ◽  
Author(s):  
Changsoo Shin ◽  
Dong-Joo Min
Keyword(s):  
Objective Function ◽  
Field Data ◽  
Velocity Structure ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Velocity Model ◽  
Matrix Formalism ◽  
Inversion Algorithm ◽  
Data Set ◽  
Short Period

Although waveform inversion has been studied extensively since its beginning [Formula: see text] ago, applications to seismic field data have been limited, and most of those applications have been for global-seismology- or engineering-seismology-scale problems, not for exploration-scale data. As an alternative to classical waveform inversion, we propose the use of a new, objective function constructed by taking the logarithm of wavefields, allowing consideration of three types of objective function, namely, amplitude only, phase only, or both. In our wave form inversion, we estimate the source signature as well as the velocity structure by including functions of amplitudes and phases of the source signature in the objective function. We compute the steepest-descent directions by using a matrix formalism derived from a frequency-domain, finite-element/finite-difference modeling technique. Our numerical algorithms are similar to those of reverse-time migration and waveform inversion based on the adjoint state of the wave equation. In order to demonstrate the practical applicability of our algorithm, we use a synthetic data set from the Marmousi model and seismic data collected from the Korean continental shelf. For noise-free synthetic data, the velocity structure produced by our inversion algorithm is closer to the true velocity structure than that obtained with conventional waveform inversion. When random noise is added, the inverted velocity model is also close to the true Marmousi model, but when frequencies below [Formula: see text] are removed from the data, the velocity structure is not as good as those for the noise-free and noisy data. For field data, we compare the time-domain synthetic seismograms generated for the velocity model inverted by our algorithm with real seismograms and find that the results show that our inversion algorithm reveals short-period features of the subsurface. Although we use wrapped phases in our examples, we still obtain reasonable results. We expect that if we were to use correctly unwrapped phases in the inversion algorithm, we would obtain better results.

scholarly journals Convolutional sparse coding for noise attenuation in seismic data

Geophysics ◽  
2021 ◽  
Vol 86 (1) ◽  
pp. V23-V30
Author(s):  
Zhaolun Liu ◽  
Kai Lu
Keyword(s):  
Sparse Coding ◽  
Seismic Data ◽  
Field Data ◽  
Synthetic Data ◽  
Basis Functions ◽  
High Signal ◽  
Noise Attenuation ◽  
Coherent Noise ◽  
Denoising Method ◽  
Data Set

We have developed convolutional sparse coding (CSC) to attenuate noise in seismic data. CSC gives a data-driven set of basis functions whose coefficients form a sparse distribution. The noise attenuation method by CSC can be divided into the training and denoising phases. Seismic data with a relatively high signal-to-noise ratio are chosen for training to get the learned basis functions. Then, we use all (or a subset) of the basis functions to attenuate the random or coherent noise in the seismic data. Numerical experiments on synthetic data show that CSC can learn a set of shifted invariant filters, which can reduce the redundancy of learned filters in the traditional sparse-coding denoising method. CSC achieves good denoising performance when training with the noisy data and better performance when training on a similar but noiseless data set. The numerical results from the field data test indicate that CSC can effectively suppress seismic noise in complex field data. By excluding filters with coherent noise features, our method can further attenuate coherent noise and separate ground roll.

scholarly journals A computation scheme based on field attenuation rate for improving regional-residual separation of potential field data set

2019 ◽  
Author(s):  
Jun Wang ◽  
Xiaohong Meng ◽  
Fang Li
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Synthetic Data ◽  
Regional Trend ◽  
Data Set ◽  
Potential Field Data ◽  
Attenuation Rate ◽  
Original Field ◽  
Computation Scheme ◽  
The Difference

Abstract To further improve the accuracy of regional-residual separation of potential field data set, this paper presents a novel computation scheme based on different attenuation rate of the fields induced from deep and shallow sources respectively. For the new scheme, the observations are first upward continued to a plane above it to get an updated field. Then, the difference between the original field and the updated field is calculated. Next, a controlling parameter is set to select those data points whose amplitudes have been much reduced. The adverse effects from the residual anomalies on the fitting of the regional trend can be reduced by removing the identified local points from the original field. Finally, a low-order polynomial is utilised for approximating the regional trend, and the corresponding residual field can be obtained by simple subtraction. Compared with gradient-based methods, the proposed new scheme has better noise adaptability for distinguishing different anomalies. The accuracy of the presented scheme was tested on synthetic data with and without noise. All tests showed that the new scheme reduces subjectivity and inaccuracy of the conventional methods significantly. In addition, the scheme was applied to Bouguer gravity anomaly of the Dida orebodies in Jilin Province, northeast China. This application also verified the superiority of the proposed scheme.

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