Automatic interpretation of magnetic dike parameters using the analytical signal technique

Geophysics ◽  
2001 ◽  
Vol 66 (2) ◽  
pp. 551-561 ◽  
Author(s):  
Mehrdad Bastani ◽  
Laust B. Pedersen
Keyword(s):  
Source Parameters ◽  
Synthetic Data ◽  
Analytical Signal ◽  
Magnetic Data ◽  
Impact Structure ◽  
Horizontal Position ◽  
Coherent Signals ◽  
Automatic Interpretation ◽  
Horizontal Curvature ◽  
The Magnetic Field

The analytical signal of the magnetic field is used to automatically determine the source parameters of dikelike structures. The method is particularly useful for interpreting large amounts of data collected during airborne surveys because it makes full use of the high density of data along the flight lines while simultaneously checking for two‐dimensionality and strike directions by searching for coherent signals in neighboring profiles. The maximum horizontal curvature of the amplitude of the analytical signal is used to locate the dikes along a given profile. Tests with synthetic data show that the dike’s horizontal position is resolved accurately. Magnetic data from the Siljan impact structure in Sweden show that the estimated strikes are reliable and that dip, depth, and width estimates are coherent, especially for well‐isolated dikelike structures.

scholarly journals Three-dimensional interpretation of magnetic and gravity anomalies using the finite-difference similarity transform

Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. L79-L90 ◽  
Author(s):  
Daniela Gerovska ◽  
Marcos J. Araúzo-Bravo ◽  
Kathryn Whaler ◽  
Petar Stavrev ◽  
Alan Reid
Keyword(s):  
Finite Difference ◽  
Random Noise ◽  
Source Parameters ◽  
Magnetization Vector ◽  
Real Data ◽  
Index Formula ◽  
Magnetic Data ◽  
Horizontal Position ◽  
Structural Index ◽  
Similarity Transform

We present an automatic procedure for interpretation of magnetic or gravity gridded anomalies based on the finite-difference similarity transform (FDST). It is called MaGSoundFDST (magnetic and gravity sounding based on the finite-difference similarity transform) and uses a “focusing” principle in contrast to deriving multiple clusters of many solutions as in the widely used Euler deconvolution method. The source parameters are characterized by isolated solutions, and the interpreter obtains parallel images showing the horizontal position, depth, and structural index [Formula: see text] value. The underlying principle is that the FDST of a potential field anomaly becomes zero or linear at all observation points when the central point of similarity (CPS) of the transform coincides with a source field’s singular point and a correct [Formula: see text] value is used. The procedure involves calculating a 3D function that evaluates the linearity of the FDST for a series of [Formula: see text] values, using a moving window and sounding the subsurface along a verticalline under each window center. We then combine the 3D results for different [Formula: see text] values into a single map whose minima determine the horizontal position of the sources. The [Formula: see text] value and the CPS depth associated with each minimum determine the [Formula: see text] value and depth of the corresponding source. Only one estimate characterizes a simple source, which is a major advantage over other window-based procedures. MaGSoundFDST uses only the measured anomalous field and its upward continuation, thus avoiding the direct use of field derivatives. It is independent of the magnetization-vector direction in the magnetic data case. The procedure accounts for a linear background of local gravity or magnetic anomalies and has been applied effectively to several cases of synthetic and real data. MaGSoundFDST shares common features with the magnetic and gravity sounding based on the differential similarity transform (MaGSoundDST) but is more stable in estimating depth and structural index in the presence of random noise.

Automatic boundary extraction from magnetic field data using triangular meshes

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. J47-J60 ◽  
Author(s):  
Nathan Leon Foks ◽  
Yaoguo Li
Keyword(s):  
Magnetic Field ◽  
Synthetic Data ◽  
Magnetic Data ◽  
Lake Area ◽  
Boundary Extraction ◽  
Data Set ◽  
Magnetic Field Data ◽  
Line Segments ◽  
Extraction Algorithm ◽  
The Magnetic Field

Boundary extraction is a collective term that we use for the process of extracting the locations of faults, lineaments, and lateral boundaries between geologic units using geophysical observations, such as measurements of the magnetic field. The process typically begins with a preprocessing stage, where the data are transformed to enhance the visual clarity of pertinent features and hence improve the interpretability of the data. The majority of the existing methods are based on raster grid enhancement techniques, and the boundaries are extracted as a series of points or line segments. In contrast, we set out a methodology for boundary extraction from magnetic data, in which we represent the transformed data as a surface in 3D using a mesh of triangular facets. After initializing the mesh, we modify the node locations, such that the mesh smoothly represents the transformed data and that facet edges are aligned with features in the data that approximate the horizontal locations of subsurface boundaries. To illustrate our boundary extraction algorithm, we first apply it to a synthetic data set. We then apply it to identify boundaries in a magnetic data set from the McFaulds Lake area in Ontario, Canada. The extracted boundaries are in agreement with known boundaries and several of the regions that are completely enclosed by extracted boundaries coincide with regions of known mineralization.

A combined analytic signal and Euler method (AN‐EUL) for automatic interpretation of magnetic data

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1952-1961 ◽  
Author(s):  
Ahmed Salem ◽  
Dhananjay Ravat
Keyword(s):  
Source Parameters ◽  
Euler Method ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Euler Deconvolution ◽  
Automatic Interpretation ◽  
Different Depths ◽  
Ground Magnetic ◽  
Theoretical Simulations ◽  
Airborne Magnetic

We present a new automatic method of interpretation of magnetic data, called AN‐EUL (pronounced “an oil”). The derivation is based on a combination of the analytic signal and the Euler deconvolution methods. With AN‐EUL, both the location and the approximate geometry of a magnetic source can be deduced. The method is tested using theoretical simulations with different magnetic models placed at different depths with respect to the observation height. In all cases, the method estimated the locations and the approximate geometries of the sources. The method is tested further using ground magnetic data acquired above a shallow geological dike whose source parameters are known from drill logs, and also from airborne magnetic data measured over a known ferrometallic object. In both these cases, the method correctly estimated the locations and the nature of these sources.

scholarly journals Determination of source parameters of simple-shaped geologic subsurface structures from self-potential anomalies using enhanced local wavenumber method

2019 ◽  
Vol 35 (1) ◽  
Author(s):  
Luan Pham Thanh
Keyword(s):  
Random Noise ◽  
Source Parameters ◽  
Synthetic Data ◽  
Horizontal Position ◽  
Subsurface Structures ◽  
Geometry Model ◽  
Simple Geometry ◽  
Local Wavenumber ◽  
Real Self ◽  
Self Potential

Simple geometry model structures can be useful in quantitative evaluation of self-potential data. In this paper, we solve local wavenumber equation to estimate the horizontal position,  the depth and the type of the causative source geometry by using a linear least-squares approximation. The advantages of the algorithm in determining the horizontal position and depth measure are its independency to shape factor of the sources and also its simple computations. The algorithm is built in Matlab environment. The validity of the algorithm is illustrated on variable noise-free and random noise included synthetic data from two-dimensional (2-D) models where the achieved parametric quantities coincide well with the actual ones. The algorithm is also utilized to real self-potential data from Ergani Copper district, Turkey. The results from the actual data application are in good agreement with the published literature for the study area. The source code of the algorithm is available from the authors on request.

The automatic determination of the location, depth, and dip of contacts from aeromagnetic data

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. J35-J41 ◽  
Author(s):  
Gordon R. J. Cooper
Keyword(s):  
Magnetic Field ◽  
Tilt Angle ◽  
Synthetic Data ◽  
Magnetic Data ◽  
Aeromagnetic Data ◽  
Third Order ◽  
Contour Lines ◽  
Derivatives Of ◽  
The Magnetic Field

A simple new method (termed the contact-depth method) for the determination of the depth, location, and dip of contacts from pole reduced magnetic data was evaluated. The depth was obtained by computing the horizontal derivative of the tangent of the tilt angle of the magnetic field over the contact. Although it is based upon the tilt-depth method, it does not require the distance between contour lines to be measured, and it additionally allows the dip of the contact to be estimated from the gradient of the depth estimates. The horizontal location of the contact is that of the zero value of the tilt angle. The method uses second- and third-order derivatives of the magnetic field to obtain the parameters of the contact, so it is sensitive to noise. When tested on synthetic data and on aeromagnetic data from southern Africa, the method gave plausible results.

ESTIMATION OF SOURCE PARAMETERS IN IBADAN, SOUTH – WESTERN NIGERIA USING DIGITIZED AEROMAGNETIC DATA

2018 ◽  
Vol 14 (2) ◽  
pp. 15-28
Author(s):  
A A ALABI ◽  
O OLOWOFELA
Keyword(s):  
Magnetic Susceptibility ◽  
Source Parameters ◽  
Granite Gneiss ◽  
Geological Structure ◽  
Magnetic Data ◽  
Susceptibility Map ◽  
Rock Types ◽  
Upward Continuation ◽  
Magnetic Basement ◽  
Local Wavenumber

Airborne magnetic data covering geographical latitudes of 7000‟N to 7030‟N and longitudes of 3 30′E to 4 00′E within Ibadan area were obtained from Nigeria Geology Survey Agency. The data were ana-lyzed to map the sub surface structure and the source parameters were deduced from the quantitative and qualitative interpretation of magnetic data. The upward continuation technique was used to de-emphasize short – wavelength anomaly while the depth to magnetic sources in the area was deter-mined using local wavenumber technique, the analytic signal was also employed to obtain the depths of the magnetic basement. Analysis involving the local wavenumber, upward continuation and appar-ent magnetic susceptibility techniques significantly improves the interpretation of magnetic data in terms of delineating the geological structure, source parameter and magnetic susceptibility within Iba-dan area.. These depth ranges from 0.607km to 2.48km. The apparent susceptibility map at the cut-off wavelength of 50 m ranges from -0.00012 to 0.00079 which agree with the susceptibility value of some rock types; granite gneiss, migmatite biotite gneiss, biotite muscovite granite, hornblende granite, quartz and schists. The result of the local wavenumber suggests variation along the profiles in the surface of magnetic basement across the study area.

scholarly journals Performance of Two Different Flight Configurations for Drone-Borne Magnetic Data

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5736
Author(s):  
Filippo Accomando ◽  
Andrea Vitale ◽  
Antonello Bonfante ◽  
Maurizio Buonanno ◽  
Giovanni Florio
Keyword(s):  
Electromagnetic Interference ◽  
Source Parameters ◽  
Spectral Characteristics ◽  
Magnetic Data ◽  
Prototype System ◽  
Control Dataset ◽  
Periodic Data ◽  
Ground Magnetic ◽  
The Stability ◽  
Careful Processing

The compensation of magnetic and electromagnetic interference generated by drones is one of the main problems related to drone-borne magnetometry. The simplest solution is to suspend the magnetometer at a certain distance from the drone. However, this choice may compromise the flight stability or introduce periodic data variations generated by the oscillations of the magnetometer. We studied this problem by conducting two drone-borne magnetic surveys using a prototype system based on a cesium-vapor magnetometer with a 1000 Hz sampling frequency. First, the magnetometer was fixed to the drone landing-sled (at 0.5 m from the rotors), and then it was suspended 3 m below the drone. These two configurations illustrate endmembers of the possible solutions, favoring the stability of the system during flight or the minimization of the mobile platform noise. Drone-generated noise was filtered according to a CWT analysis, and both the spectral characteristics and the modelled source parameters resulted analogously to that of a ground magnetic dataset in the same area, which were here taken as a control dataset. This study demonstrates that careful processing can return high quality drone-borne data using both flight configurations. The optimal flight solution can be chosen depending on the survey target and flight conditions.

Imaging depth, structure, and susceptibility from magnetic data: The advanced source-parameter imaging method

Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. L31-L38 ◽  
Author(s):  
Richard S. Smith ◽  
Ahmed Salem
Keyword(s):  
Source Parameters ◽  
Thin Sheet ◽  
Signal Amplitude ◽  
Horizontal Cylinder ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Imaging Method ◽  
Structural Index ◽  
Synthetic Test ◽  
Vertical Contact

An important problem in the interpretation of magnetic data is quantifying the source parameters that describe the anomalous structure. We present a new method that uses various combinations of the local wavenumbers for estimating the depth and shape (structural index) of the structure. Because the estimates are derived from third derivatives of the magnetic data, they are noisy. However, there are multiple ways of calculating the depth and index, and these solutions can be averaged to give a stable estimate. Even so, a synthetic test shows that the results are erratic away from the locations where the analytic-signal amplitude is large. Hence, when we generate images of the depth and structural index, we make the results most visible where the analytic-signal amplitude is large and less visible where the signal is small. The advantage of the method is that estimates can be obtained at all locations on a profile and used to generate continuous profiles or images of the source parameters. This can be used to help identify the locations where interference might be corrupting the results. The structural index image can be used to determine the most appropriate type of model for an area. Assuming this model, it is possible to calculate the depth that would be consistent with the model and the data. Knowing both the depth and model, the analytic-signal amplitude can be converted to apparent susceptibility. If a vertical-contact model is assumed, the susceptibility contrast across the contact can be imaged. For the thin-sheet and horizontal-cylinder models, we can image the susceptibility-thickness and susceptibility-area products, respectively.

Interpretation of airborne magnetic survey of Gabel Um Tineidba area, south eastern desert, Egypt

2015 ◽  
Vol 12 (6) ◽  
pp. 563-576
Author(s):  
Tharwat H. Abdel Hafeez
Keyword(s):  
Analytical Signal ◽  
Eastern Desert ◽  
Structural Features ◽  
Geological Mapping ◽  
Magnetic Data ◽  
Magnetic Survey ◽  
Aeromagnetic Survey ◽  
Reasonable Proportion ◽  
The Cost ◽  
Airborne Magnetic

The study area is regionally covered by rock exposures ranging in age from the Precambrian to Quaternary. The aeromagnetic survey is a useful tool that help in geological mapping, providing information at a reasonable proportion of the cost of ground mapping. The reduced to the northern magnetic pole (RTP) map was separated into regional and residual magnetic component maps by the computed power spectrum of the magnetic data. The estimated mean depths of both regional and residual magnetic sources were found to be 2510 m and 383 m respectively. Also, two advanced techniques were used to analyze the depth magnetic data. These methods are analytical signal (AS) and source parameter imaging (SPI). The results of average depth estimates both methods (–950 m). These depth values were helped -to great extent- for define the direction of throw for the interpreted faults in the basement tectonic map. The statistical analysis shows that, most of the welldeveloped structural features are oriented mostly in the N-S, NNE-SSW, NW-SE and NNWSSE trending faults are considered the main trends affecting the distribution of the radioactive minerals.

Enhanced interpretation of magnetic survey data from archaeological sites using artificial neural networks

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. H45-H53 ◽  
Author(s):  
David. J. Bescoby ◽  
Gavin C. Cawley ◽  
P. Neil Chroston
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Data Processing ◽  
Survey Data ◽  
Source Parameters ◽  
Magnetic Data ◽  
Burial Depth ◽  
Training Procedure ◽  
Wide Range ◽  
Artificial Neural

The use of magnetic surveys for archaeological prospecting is a well-established and versatile technique, and a wide range of data processing routines are often applied to further enhance acquired data or derive source parameters. Of particular interest in this respect is the application of artificial neural networks (ANNs) to predict source parameters such as the burial depths of detected features of interest. Within this study, ANNs based upon a multilayer perceptron architecture are used to perform the nonlinear mapping between buried wall features detected within the magnetic data and their corresponding burial depth for surveys in the ancient city of Butrint in southern Albania, achieving a greater level of information from the survey data. Suitable network training examples and test data were generated using forward models based upon ground-truth observations. The training procedure adopts a supervised learning routine that is optimized using a conjugate gradient method, while the learning algorithm also prunes network elements to prevent overregularization by reducing model complexity. Data processing was further enhanced by introducing rotational invariance using Zernike moments and by utilizing the combined output of a number, or committee, of networks. When applied to a section of survey data from Butrint, the ANN routine successfully predicted the burial depth of a number of detected wall features, with an rms error on the order of [Formula: see text], and provided a coherent map of the buried building foundations. The neural network approach offered advantages in terms of efficiency and flexibility over more conventional data-inversion techniques within the context of the study, giving fast solutions for large, complex data sets while having high noise tolerance.

Sign in / Sign up

Export Citation Format

Share Document