Transformation of magnetic data to the pole and vertical dip and a related apparent susceptibility transform: exact and approximate approaches

Geophysics ◽  
2021 ◽  
pp. 1-66
Author(s):  
Richard S. Smith ◽  
Eric A. Roots ◽  
Rajesh Vavavur
Keyword(s):  
Magnetic Field ◽  
Remanent Magnetization ◽  
Synthetic Data ◽  
South Australia ◽  
Signal Amplitude ◽  
Discrete Source ◽  
Magnetic Data ◽  
Subsequent Transformation ◽  
Single Positive ◽  
Positive Feature

The dipolar character of magnetic data means that there is a high and a low associated with each source. The relative positions and sizes of these highs and lows, varies depending on the magnetic latitude or the inclination of the Earth’s magnetic field. One method for dealing with this complexity is to transform the data to what would collected if the inclination were vertical (as at the magnetic pole); a process that is unstable at low magnetic latitudes. Unfortunately, remanent magnetization adversely impacts the success of this transformation. A second approach is to calculate the analytic-signal amplitude (ASA) of the data, which creates a single positive feature for each source or edge, with the shape being only weakly dependent on the inclination and the presence of remanent magnetization. The ASA anomalies can appear to be relatively broad, so features sometimes merge together on map views of the ASA. A subsequent transformation of the ASA using an appropriate transforming tilt angle can generate a magnetic field of a body that is at the pole and has a vertical dip. The transformation is exact for contacts when calculated from the first-order ASA, but the sign of the transformed data can be incorrect depending on whether you are over one edge or the other edge of a discrete source body. Another, approximate transformation of the zeroth-order ASA does not have this issue and gives good results on synthetic data provided that any noise is handled appropriately. The resulting maps outline the magnetic source bodies and have amplitudes proportional to an apparent magnetic susceptibility. On field data from Black Hill, South Australia, the approximate transformation generates an image that is simple to interpret and enhances some features less obvious on other enhancements of the data.

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.

Estimating the Magnetization Direction of Sources through Correlation between Reduced-to-Pole Anomaly and Normalized Source Strength

2014 ◽  
Vol 644-650 ◽  
pp. 3793-3796
Author(s):  
Liang Hui Guo ◽  
Rui Gao ◽  
Guo Li Zhang
Keyword(s):  
Geomagnetic Field ◽  
Remanent Magnetization ◽  
Cross Correlation ◽  
Synthetic Data ◽  
Field Direction ◽  
Magnetic Data ◽  
Source Strength ◽  
Magnetization Direction ◽  
New Approach ◽  
Total Magnetization

Under the effects of remanent magnetization, total magnetization direction is different from geomagnetic field direction, which makes magnetic data processing and interpretation complexity. In this paper, we present a new approach for estimating the total magnetization direction of sources via cross-correlation between the reduced-to-pole anomaly and the normalized source strength (who is less sensitive to remanent magnetization). The geomagnetic field direction is used to calculated the normalized source strength, while various assumed total magnetization directions are used to calculated the RTP anomalies. The maximum correlation between the RTP anomalies and the normalized corresponds to the estimated total magnetization direction. Test on synthetic data showed that the new approach is simple and effective.

Mitigating remanent magnetization effects in magnetic data using the normalized source strength

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. J25-J32 ◽  
Author(s):  
Mark Pilkington ◽  
Majid Beiki
Keyword(s):  
Magnetic Field ◽  
Remanent Magnetization ◽  
Field Data ◽  
Magnetic Data ◽  
Magnetization Distribution ◽  
Source Strength ◽  
Inversion Algorithm ◽  
Data Set ◽  
Magnetic Field Data ◽  
The Magnetic Field

We have developed an approach for the interpretation of magnetic field data that can be used when measured anomalies are affected by significant remanent magnetization components. The method deals with remanent effects by using the normalized source strength (NSS), a quantity calculated from the eigenvectors of the magnetic gradient tensor. The NSS is minimally affected by the direction of remanent magnetization present and compares well with other transformations of the magnetic field that are used for the same purpose. It therefore offers a way of inverting magnetic data containing the effects of remanent magnetizations, particularly when these are unknown and are possibly varying within a given data set. We use a standard 3D inversion algorithm to invert NSS data from an area where varying remanence directions are apparent, resulting in a more reliable image of the subsurface magnetization distribution than possible using the observed magnetic field data directly.

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 vector inversion using  XYZ measured by fluxgate magnetometer in UAV 

2021 ◽  
Author(s):  
Arto Karinen
Keyword(s):  
Magnetic Field ◽  
Remanent Magnetization ◽  
Magnetization Vector ◽  
Field Direction ◽  
Magnetic Data ◽  
Total Field ◽  
Main Field ◽  
Vector Inversion ◽  
The Magnetic Field ◽  
Measured Magnetic Field

<p>Traditionally, the inversion of magnetic data assumes the magnetization of the local geology to run parallel to the Earth’s internal magnetic field that is usually modelled using International Geomagnetic Reference Field (IGRF). Assuming the magnetization parallel to the main field, only the total (scalar) magnetic data are the sufficient input for the inversion of source susceptibility.</p><p>Local magnetization may alter from the main field direction in areas of remanent magnetization. Recently, magnetization vector inversion (MVI) using the total field has become an important tool trying to distinguish magnetic data affected by remanenence. Total field as a scalar field exclude all information of the direction of the internal magnetization and more information is required to reveal any remanent magnetization from the main field direction.  Compared to total field using the 3-component XYZ vector magnetic measurements provide more information of the source.  More measurements increase the unambiguous nature of data and may reveal the areas of possible remanence. </p><p>To measure XYZ vector magnetic field we use fluxgate 3-component magnetometer with rigid installation on a fixed-wing UAV. With the help of accurate inertial measurement units the measured magnetic field can be determined in the direction of fixed coordinate system. The components of the measured magnetic field rotated into the geographical coordinate represent the magnetic field at survey area.</p><p>UAV survey provided the data as the input for the inversions. We made the inversion separately for both susceptibility and magnetization vector. Susceptibility inversion means inversion of induced magnetization, i.e., a single component of magnetization parallel to the main field direction. Magnetization vector inversion, however, resolves all three components of magnetization, which may or may not include remanent magnetization in addition to induced one.</p><p>The benefits from utilizing XYZ components of the magnetic field with magnetization inversion seem promising in finding remanenence magnetization.</p><p> </p><p> </p>

Modelling of airborne Full Tensor Magnetic Gradiometry using data from the INFACT project

2020 ◽  
Author(s):  
Jouni Nevalainen ◽  
Elena Kozlovskaya ◽  
Jukka-Pekka Ranta ◽  
Joan Marie Blanco ◽  
Moritz Kirsch ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Quantum Interference ◽  
Remanent Magnetization ◽  
Magnetic Field Gradient ◽  
Magnetic Data ◽  
Joint Analysis ◽  
Horizon 2020 ◽  
Airborne Measurements ◽  
Magnetic Gradiometry ◽  
The Magnetic Field

<p>The measurement of the magnetic field has been a “backbone” geophysical method in mineral exploration since the 17th century. The existing instrumentation that measures Total Magnetic field Intensity (TMI) are a routinely used in ground, borehole and airborne surveys. In the TMI intensity data it is possible to observe certain signatures of magnetised objects, but retrieval of both magnetisation intensity and shape of 3-D magnetised objects from TMI can be difficult due to the vector nature of magnetisation and fundamental non-uniqueness of potential fields interpretation. Moreover, the presence of magnetic material in the host rock and/or presence of remanent magnetisation are challenges for TMI data interpretation.</p><p>Full Tensor Magnetic Gradiometry (FTMG) measurements provide the complete description of the magnetic field and hence an opportunity to get more information on the size, shape and material property of the magnetic rock mass. This is because the signatures in magnetic field originating from a specific magnetic object is observed in all independent components of magnetic field gradient tensor and thus, joint analysis of these tensor components constrains the number of possible magnetic models that fit the same data. In addition, observing the full tensor of magnetic field makes it possible to estimate the remanent magnetization with respect to the induced magnetization field if no a-priori information of remanent magnetization is available.</p><p>Highly sensitive magnetometers based on SQUID (Superconducting QUantum Interference Devices) technology has been successfully adopted in FTMG airborne measurements during the past decade. This achievement has given magnetic methods a new opportunity in terms of purely magnetic data modelling. In our work the benefits of interpretation of tensor airborne FTMG data are demonstrated through forward modelling and inversion with the grid search multiobjective global optimisation. As a case study, we consider airborne FTMG data measured with Supracon® JESSY STAR system in Northern Finland during the INFACT project.</p><p>Acknowledgements: This study has been done in the framework of EU Horizon 2020 funded INFACT project (webpage: https://www.infactproject.eu).</p>

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.

An Augmented Iteratively Re-weighted and Refined Least Squares Method for lp Minimization Problem in Inverse Modeling of Potential Field Magnetic Data

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Maysam Abedi
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
Least Squares ◽  
Minimization Problem ◽  
Potential Field ◽  
Field Data ◽  
Least Squares Method ◽  
Porphyry Copper ◽  
Magnetic Data ◽  
Magnetic Field Data

The presented work examines application of an Augmented Iteratively Re-weighted and Refined Least Squares method (AIRRLS) to construct a 3D magnetic susceptibility property from potential field magnetic anomalies. This algorithm replaces an lp minimization problem by a sequence of weighted linear systems in which the retrieved magnetic susceptibility model is successively converged to an optimum solution, while the regularization parameter is the stopping iteration numbers. To avoid the natural tendency of causative magnetic sources to concentrate at shallow depth, a prior depth weighting function is incorporated in the original formulation of the objective function. The speed of lp minimization problem is increased by inserting a pre-conditioner conjugate gradient method (PCCG) to solve the central system of equation in cases of large scale magnetic field data. It is assumed that there is no remanent magnetization since this study focuses on inversion of a geological structure with low magnetic susceptibility property. The method is applied on a multi-source noise-corrupted synthetic magnetic field data to demonstrate its suitability for 3D inversion, and then is applied to a real data pertaining to a geologically plausible porphyry copper unit.  The real case study located in  Semnan province of  Iran  consists  of  an arc-shaped  porphyry  andesite  covered  by  sedimentary  units  which  may  have  potential  of  mineral  occurrences, especially  porphyry copper. It is demonstrated that such structure extends down at depth, and consequently exploratory drilling is highly recommended for acquiring more pieces of information about its potential for ore-bearing mineralization.

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.

Constrained 3D inversion of magnetic data with structural orientation and borehole lithology: A case study in the Macheng iron deposit, Hebei, China

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. B121-B133 ◽  
Author(s):  
Shida Sun ◽  
Chao Chen ◽  
Yiming Liu
Keyword(s):  
Remanent Magnetization ◽  
Magnetic Data ◽  
Iron Deposit ◽  
Reference Field ◽  
Total Field ◽  
Equivalent Source ◽  
Structural Orientation ◽  
Amplitude Data ◽  
Ore Bodies

We have developed a case study on the use of constrained inversion of magnetic data for recovering ore bodies quantitatively in the Macheng iron deposit, China. The inversion is constrained by the structural orientation and the borehole lithology in the presence of high magnetic susceptibility and strong remanent magnetization. Either the self-demagnetization effect caused by high susceptibility or strong remanent magnetization would lead to an unknown total magnetization direction. Here, we chose inversion of amplitude data that indicate low sensitivity to the direction of magnetization of the sources when constructing the underground model of effective susceptibility. To reduce the errors that arise when treating the total-field anomaly as the projection of an anomalous field vector in the direction of the geomagnetic reference field, we develop an equivalent source technique to calculate the amplitude data from the total-field anomaly. This equivalent source technique is based on the acquisition of the total-field anomaly, which uses the total-field intensity minus the magnitude of the reference field. We first design a synthetic model from a simplified real case to test the new approach, involving the amplitude data calculation and the constrained amplitude inversion. Then, we apply this approach to the real data. The results indicate that the structural orientation and borehole susceptibility bounds are compatible with each other and are able to improve the quality of the recovered model to obtain the distribution of ore bodies quantitatively and effectively.

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