Reducing the dependence of the analytic signal amplitude of aeromagnetic data on the source vector direction

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. J55-J60 ◽  
Author(s):  
Gordon R. J. Cooper
Keyword(s):  
Synthetic Data ◽  
Magnetization Vector ◽  
Signal Amplitude ◽  
Analytic Signal ◽  
Data Sets ◽  
Aeromagnetic Data ◽  
3D Data ◽  
Vector Direction ◽  
2D Data ◽  
Derivatives Of

The analytic signal amplitude (As) is commonly used as an edge-detection filter for aeromagnetic data. For profile (2D) data, its shape is independent of the source magnetization vector direction, but this is not the case for map (3D) data. A modified analytic signal amplitude ([Formula: see text]) is introduced here which has a much reduced dependence on this vector for both contact and dike models. When the modified analytic signal amplitude was applied to synthetic data sets, it was more effective in enhancing the edges of the bodies than the standard As. Because it uses second-order derivatives of the magnetic field, the method is sensitive to noise and so an additional formulation was developed for noisy data sets that only use first-order derivatives.

Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain

2003 ◽  
Vol 42 (05) ◽  
pp. 215-219
Author(s):  
G. Platsch ◽  
A. Schwarz ◽  
K. Schmiedehausen ◽  
B. Tomandl ◽  
W. Huk ◽  
...  
Keyword(s):  
Data Sets ◽  
3D Mri ◽  
Clinical Routine ◽  
Fusion Procedure ◽  
3D Data ◽  
Mri Scans ◽  
2D Data ◽  
Time Required ◽  
The Brain ◽  
Manual Correction

Summary: Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and Method: In 32 patients regional cerebral blood flow was measured using 99mTc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

Automatic 3-D interpretation of potential field data using analytic signal derivatives

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Nicole Debeglia ◽  
Jacques Corpel
Keyword(s):  
Signal Amplitude ◽  
Vertical Gradient ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Practical Implementation ◽  
Potential Field Data ◽  
Gravity And Magnetic ◽  
Second Derivatives ◽  
Gravity And Magnetic Data ◽  
Derivatives Of

A new method has been developed for the automatic and general interpretation of gravity and magnetic data. This technique, based on the analysis of 3-D analytic signal derivatives, involves as few assumptions as possible on the magnetization or density properties and on the geometry of the structures. It is therefore particularly well suited to preliminary interpretation and model initialization. Processing the derivatives of the analytic signal amplitude, instead of the original analytic signal amplitude, gives a more efficient separation of anomalies caused by close structures. Moreover, gravity and magnetic data can be taken into account by the same procedure merely through using the gravity vertical gradient. The main advantage of derivatives, however, is that any source geometry can be considered as the sum of only two types of model: contact and thin‐dike models. In a first step, depths are estimated using a double interpretation of the analytic signal amplitude function for these two basic models. Second, the most suitable solution is defined at each estimation location through analysis of the vertical and horizontal gradients. Practical implementation of the method involves accurate frequency‐domain algorithms for computing derivatives with an automatic control of noise effects by appropriate filtering and upward continuation operations. Tests on theoretical magnetic fields give good depth evaluations for derivative orders ranging from 0 to 3. For actual magnetic data with borehole controls, the first and second derivatives seem to provide the most satisfactory depth estimations.

Balancing images of potential-field data

Geophysics ◽  
2009 ◽  
Vol 74 (3) ◽  
pp. L17-L20 ◽  
Author(s):  
G. R. Cooper
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Large Range ◽  
Signal Amplitude ◽  
Analytic Signal ◽  
Aeromagnetic Data ◽  
Hilbert Transforms ◽  
Potential Field Data ◽  
Total Gradient ◽  
Data Source

Horizontal and vertical gradients, and filters based on them (such as the analytic signal), are used routinely to enhance detail in aeromagnetic data. However, when the data contain anomalies with a large range of amplitudes, the filtered data also will contain large and small amplitude responses, making the latter hard to see. This study suggests balancing the analytic signal amplitude (sometimes called the total gradient) by the use of its orthogonal Hilbert transforms, and shows that the balanced profile curvature can be an effective method of enhancing potential-field data. Source code is available from the author on request.

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].

Calculation of magnitude magnetic transforms with high centricity and low dependence on the magnetization vector direction

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. I21-I30 ◽  
Author(s):  
Daniela Gerovska ◽  
Marcos J. Araúzo-Bravo
Keyword(s):  
Magnetic Field ◽  
Magnetization Vector ◽  
Field Vector ◽  
Data Sets ◽  
Volcanic Area ◽  
Square Root ◽  
Anomalous Magnetic Field ◽  
Total Magnitude ◽  
Vector Direction ◽  
Magnitude Magnetic Transforms

We present a Matlab tool that calculates five magnitude magnetic transforms (MMTs) from an input measured anomalous magnetic field. The MMTs are all based on the total magnitude anomaly (TMA), and consist of the TMA itself, the modulus of the gradient of the TMA, the Laplacian of the TMA, half of the square root of the Laplacian of the square of the TMA, and the square root of the product of the TMA plus the Laplacian of the TMA. These MMTs produce anomalies that are closer to the magnetic source’s true horizontal position and are simpler to interpret than the measured anomalous magnetic field itself. While the conventional magnetic transforms of reduction-to-the-pole (RTP), the pseudogravity field, and the analytic signal (AS) also have these properties, these MMTs have several additional advantages. They require only first-order, horizontal derivatives for their calculation. They are also more stable at low magnetic latitudes than the RTP, and have a pattern that is independent of the geomagnetic-field vector direction, in contrast to the AS. The Matlab tool is designed to deal with big data sets and is compatible with common data formats, GS ASCII grid files, and XYZ data files. A calculation of the MMTs of the total magnetic anomaly of a synthetic example at a low magnetic latitude and with a field example from the Kuju volcanic area, Japan demonstrate the effectiveness of the program.

Determining the distance to magnetic sources

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. J25-J34 ◽  
Author(s):  
Gordon R. J. Cooper ◽  
Rob C. Whitehead
Keyword(s):  
A Priori ◽  
Analytic Signal ◽  
Data Sets ◽  
Aeromagnetic Data ◽  
Local Minima ◽  
Source Depth ◽  
Structural Index ◽  
Different Depths ◽  
Comparison Of The Results ◽  
Different Altitudes

The distance to sources of magnetic field anomalies of a known structural index can be determined by using ratios of the analytic signal amplitudes ([Formula: see text]) of different orders, and this can be performed in several different ways. Local minima of the distance correspond to the source depth. If an incorrect structural index has been used, then the different methods will yield different depths. Hence, a comparison of the results obtained from the different methods can help us to differentiate between valid and invalid source depths. These methods are computationally straightforward, and in some of the methods, the orders of the [Formula: see text] that are used can be chosen based on the noise level of the data. Some approaches that do not require the a priori specification of the structural index of the source are introduced, including methods that use data from two different altitudes (obtained by vertical continuation). We have applied the methods to aeromagnetic data sets from the Giyani and Kuruman regions of South Africa with plausible results.

scholarly journals Thermomagnetic Features of Crust in Southern Parts of the Structural Provinces of Tocantins and São Francisco, Brazil

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Suze Nei P. Guimaraes ◽  
Valiya M. Hamza
Keyword(s):  
Regional Scale ◽  
Analytic Signal ◽  
Magnetic Characteristics ◽  
Data Sets ◽  
Aeromagnetic Data ◽  
Euler Deconvolution ◽  
Spatial Dimensions ◽  
Magmatic Intrusions ◽  
Tertiary Period

In the present work we report results of a regional scale investigation of the thermal and magnetic characteristics of the crust in the southern sector of the geologic provinces of Tocantins and São Francisco, Brazil. Updated compilations of aeromagnetic and geothermal data sets were employed for this purpose. Use of such techniques as vertical derivative, analytic signal, and Euler deconvolution in analysis of aeromagnetic data has allowed precise locations of the sources of magnetic anomalies and determination of their respective depths. The anomalies in the Tocantins province are considered as arising from variations in the magnetic susceptibilities and remnant magnetizations of alkaline magmatic intrusions of the Tertiary period. The lateral dimensions of the bodies are less than 10 km, and these are found to occur at shallow depths of less than 20 km. On the other hand, the anomalies in the cratonic areas are related to contrasts in magnetic properties of bodies situated at depths greater than 20 km and have spatial dimensions of more than 50 km. Analysis of geothermal data reveals that the cratonic area is characterized by geothermal gradients and heat flow values lower when compared with those of the Tocantins province.

Denoising of aeromagnetic data via the wavelet transform

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1793-1804 ◽  
Author(s):  
George E. Leblanc ◽  
William A. Morris
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Random Noise ◽  
Synthetic Data ◽  
Analysis Procedure ◽  
Data Sets ◽  
Aeromagnetic Data ◽  
Wavelet Method ◽  
Southern Alberta ◽  
Geologic Data

Noise has traditionally been suppressed or eliminated in aeromagnetic data sets by the use of Fourier analysis filters and, to a lesser degree, nonlinear statistical filters. Although these methods are quite useful under specific conditions, they produce undesirable effects when denoising features of moderate to large amplitude and spatial extent. In this study, a new wavelet analysis procedure is presented that substantially reduces the contribution from high‐frequency random noise and noise that is user defined. Applications to both synthetic data and aeromagnetic data from southern Alberta, Canada, show that the wavelet method eliminates the noise portion of the signal more efficiently and retains a greater amount of geologic data than other methods.

Using the analytic signal amplitude to determine the location and depth of thin dikes from magnetic data

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. J1-J6 ◽  
Author(s):  
Gordon R. J. Cooper
Keyword(s):  
Magnetic Field ◽  
Magnetic Anomaly ◽  
Magnetization Vector ◽  
Signal Amplitude ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Local Minima ◽  
First Order ◽  
Higher Order Derivative ◽  
The Magnetic Field

A semiautomatic method to determine the location and depth of thin dykes is introduced. The ratio of analytic signal amplitudes of orders 0 and 1 of the magnetic anomaly from a thin dike was used to give the distance [Formula: see text] to the dike. Local minima of [Formula: see text] gave the depth to the dike, and the position of these minima gave its horizontal location. Because in the method we used just the magnetic field and its first-order derivatives, it was less sensitive to noise than were higher order derivative-based methods. Once the position of the dike has been determined, then its dip and susceptibility-thickness product can be calculated from the analytic signal amplitude, providing that the magnetization vector is known.

Magnetic gradient techniques on digitized aeromagnetic data of Ibadan area, south-western Nigeria

2013 ◽  
Vol 5 (3) ◽  
Author(s):  
Biodun Badmus ◽  
Musa Awoyemi ◽  
Olukayode Akinyemi ◽  
Ganiyu Saheed ◽  
Oluwaseun Olurin
Keyword(s):  
Magnetic Field ◽  
Signal Amplitude ◽  
Analytic Signal ◽  
Maximum Depth ◽  
Horizontal Gradient ◽  
Aeromagnetic Data ◽  
Magnetic Gradient ◽  
Gradient Magnitude ◽  
Local Wavenumber ◽  
Intensity Magnetic Field

AbstractLocations and depths to magnetic contacts were estimated from the total intensity magnetic field using the Horizontal Gradient Magnitude (HGM), Analytic Signal Amplitude (ASA) and Local Wavenumber (LWN) methods. Aeromagnetic data from the Ibadan area, in south-western Nigeria, were analyzed to estimate depths to magnetic sources as well as source locations. The minimum/maximum depth limits of the HGM and LWN are relatively close and comparable, while shallow source depths limits are greater than expected in the ASA method when compared with the HGM and LWN functions.

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