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.

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.

scholarly journals Swarm Satellite Magnetic Field Data Analysis Prior to 2019 Mw = 7.1 Ridgecrest (California, USA) Earthquake

Geosciences ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 502
Author(s):  
Dedalo Marchetti ◽  
Angelo De Santis ◽  
Saioa A. Campuzano ◽  
Maurizio Soldani ◽  
Alessandro Piscini ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Geomagnetic Latitude ◽  
Earthquake Forecasting ◽  
Magnetic Data ◽  
Epicentral Area ◽  
Magnetic Field Data ◽  
Preparation Phase ◽  
Swarm Satellite ◽  
The Magnetic Field

This work presents an analysis of the ESA Swarm satellite magnetic data preceding the Mw = 7.1 California Ridgecrest earthquake that occurred on 6 July 2019. In detail, we show the main results of a procedure that investigates the track-by-track residual of the magnetic field data acquired by the Swarm constellation from 1000 days before the event and inside the Dobrovolsky’s area. To exclude global geomagnetic perturbations, we select the data considering only quiet geomagnetic field time, defined by thresholds on Dst and ap geomagnetic indices, and we repeat the same analysis in two comparison areas at the same geomagnetic latitude of the Ridgecrest earthquake epicentre not affected by significant seismicity and in the same period here investigated. As the main result, we find some increases of the anomalies in the Y (East) component of the magnetic field starting from about 500 days before the earthquake. Comparing such anomalies with those in the validation areas, it seems that the geomagnetic activity over California from 222 to 168 days before the mainshock could be produced by the preparation phase of the seismic event. This anticipation time is compatible with the Rikitake empirical law, recently confirmed from Swarm satellite data. Furthermore, the Swarm Bravo satellite, i.e., that one at highest orbit, passed above the epicentral area 15 min before the earthquake and detected an anomaly mainly in the Y component. These analyses applied to the Ridgecrest earthquake not only intend to better understand the physical processes behind the preparation phase of the medium-large earthquakes in the world, but also demonstrate the usefulness of a satellite constellation to monitor the ionospheric activity and, in the future, to possibly make reliable earthquake forecasting.

scholarly journals Statistical and superposed epoch study of dipolarization events using data from Wind perigee passes

2005 ◽  
Vol 23 (3) ◽  
pp. 831-851 ◽  
Author(s):  
K. Sigsbee ◽  
J. A. Slavin ◽  
R. P. Lepping ◽  
A. Szabo ◽  
M. Øieroset ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Inclination Angle ◽  
Magnetic Energy ◽  
Neutral Sheet ◽  
Data Set ◽  
Magnetic Field Data ◽  
Wind Spacecraft ◽  
Using Data ◽  
The Magnetic Field ◽  
Field Inclination

Abstract. From 1995 to 2000, the Wind spacecraft spent over 500h in the magnetotail, much of it within ~2x104km of the predicted location of the neutral sheet. Wind passed through the near magnetotail at distances of -15 RE<X GSM<-6 RE on 35 occasions. Another 10 passes took place at distances of -30 RE<X GSM<-15 RE. We identified 65 dipolarization events in the Wind magnetic field data set between Y GSM~-16 and +16 RE based upon our requirements that the magnetic field inclination had to change by more than 15°, the maximum inclination angle had to be greater than 20°, and the inclination angle had to increase by a factor of at least 1.5. Most of the dipolarization events occurred in the pre-midnight region of the magnetotail and were accompanied by earthward flows with speeds greater than 100km/s. The properties of the dipolarization events did not depend upon the Y GSM position. However, they did vary with the distance to the neutral sheet. Isolated dipolarization events, defined as occurring more than 20min apart, were characterized by a decrease in Bx GSM and BTOTAL, and an increase in Bz GSM and the magnetic field inclination. Dipolarizations that occurred as part of a series of small dipolarizations spaced less than 20min apart were characterized by a transient increase in Bz GSM and the magnetic field inclination, but no significant change in Bx GSM and BTOTAL. The events consisting of a series of small dipolarizations occurred predominantly near midnight. We interpret these results in terms of two different modes of magnetotail convection: 1) a classical substorm pattern featuring storage of magnetic energy in the tail lobes which is explosively released at onset, and 2) a directly driven process.

scholarly journals Characteristics of the Taylor microscale in the solar wind/foreshock: magnetic field and electron velocity measurements

2013 ◽  
Vol 31 (11) ◽  
pp. 2063-2075 ◽  
Author(s):  
C. Gurgiolo ◽  
M. L. Goldstein ◽  
W. H. Matthaeus ◽  
A. Viñas ◽  
A. N. Fazakerley
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Fluid Velocity ◽  
Electron Velocity ◽  
Data Sets ◽  
Velocity Data ◽  
Data Set ◽  
Magnetic Field Data ◽  
Spacecraft Data ◽  
The Magnetic Field

Abstract. The Taylor microscale is one of the fundamental turbulence scales. Not easily estimated in the interplanetary medium employing single spacecraft data, it has generally been studied through two point correlations. In this paper we present an alternative, albeit mathematically equivalent, method for estimating the Taylor microscale (λT). We make two independent determinations employing multi-spacecraft data sets from the Cluster mission, one using magnetic field data and a second using electron velocity data. Our results using the magnetic field data set yields a scale length of 1538 ± 550 km, slightly less than, but within the same range as, values found in previous magnetic-field-based studies. During time periods where both magnetic field and electron velocity data can be used, the two values can be compared. Relative comparisons show λT computed from the velocity is often significantly smaller than that from the magnetic field data. Due to a lack of events where both measurements are available, the absolute λT based on the electron fluid velocity is not able to be determined.

An assessment of long-wavelength magnetic anomalies over Canada

1996 ◽  
Vol 33 (1) ◽  
pp. 12-23 ◽  
Author(s):  
Mark Pilkington ◽  
Walter R. Roest
Keyword(s):  
Magnetic Field ◽  
Magnetic Anomalies ◽  
Time Span ◽  
Magnetic Data ◽  
Data Sets ◽  
Independent Data ◽  
Data Set ◽  
Long Wavelength ◽  
The Magnetic Field

The reliability of the long-wavelength portion (> 300 km) of the magnetic field over Canada, as represented by the national aeromagnetic anomaly database compiled by the Geological Survey of Canada (GSC), is assessed by comparison with two independent data sets: a high-altitude country-wide survey carried out by the former Earth Physics Branch (EPB) and data from the MAGSAT and POGO satellite missions. The different altitudes at which each data set was measured (300 m, ~4 km, and ~400 km), and their different resolution and time span of observations allow a determination of the integrity of selected wavelength bands in each data set. The (upward-continued) EPB and MAGSAT–POGO fields compare well for wavelengths of 300–2500 km. The GSC data show significant differences to the former, indicating that the levelling and merging of several hundred individual surveys has degraded the longer wavelength components of the magnetic field. Replacing the GSC wavelength components >300 km with those from the EPB field produces a magnetic data set containing more dependable information within the largest possible waveband.

scholarly journals Estimation of Indoor Location Through Magnetic Field Data: An Approach Based On Convolutional Neural Networks

2020 ◽  
Vol 9 (4) ◽  
pp. 226
Author(s):  
Carlos E. Galván-Tejada ◽  
Laura A. Zanella-Calzada ◽  
Antonio García-Domínguez ◽  
Rafael Magallanes-Quintanar ◽  
Huizilopoztli Luna-García ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Area Under The Curve ◽  
Training Data ◽  
Spectral Evolution ◽  
Data Set ◽  
Magnetic Field Data ◽  
Indoor Location ◽  
Location Data ◽  
The Magnetic Field

Estimation of indoor location represents an interesting research topic since it is a main contextual variable for location bases services (LBS), eHealth applications and commercial systems, among others. For instance, hospitals require location data of their employees, as well as the location of their patients to offer services based on these locations at the correct moments of their needs. Several approaches have been proposed to tackle this problem using different types of artificial or natural signals (i.e., wifi, bluetooth, rfid, sound, movement, etc.). In this work, it is proposed the development of an indoor location estimator system, relying in the data provided by the magnetic field of the rooms, which has been demonstrated that is unique and quasi-stationary. For this purpose, it is analyzed the spectral evolution of the magnetic field data viewed as a bidimensional heatmap, avoiding temporal dependencies. A Fourier transform is applied to the bidimensional heatmap of the magnetic field data to feed a convolutional neural network (CNN) to generate a model to estimate the user’s location in a building. The evaluation of the CNN model to deploy an indoor location system (ILS) is done through measuring the Receiver Operating Characteristic (ROC) curve to observe the behavior in terms of sensitivity and specificity. Our experiments achieve a 0.99 Area Under the Curve (AUC) in the training data-set and a 0.74 in a total blind data set.

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.

scholarly journals KELURUSAN ANOMALI MAGNET BENDA X DI DAERAH Y DARI HASIL REDUKSI KE KUTUB

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Ketut Gede Aryawan ◽  
Subarsyah Subarsyah
Keyword(s):  
Magnetic Field ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Magnetic Anomaly ◽  
Field Data ◽  
Transformation Process ◽  
Gas Pipeline ◽  
Magnetic Data ◽  
Magnetic Field Data ◽  
The Magnetic Field

Kita mengalami kesulitan untuk mendeteksi anomali secara langsung dari data medan magnet karena mempunyai polaritas positif dan negatif. Untuk itu diperlukan teknik pemrosesan data magnet untuk memperoleh delineasi pipa yang lebih baik. Pada kasus delineasi pipa gas di laut daerah X, diterapkan teknik reduksi ke kutub (RTP) untuk mengolah data magnet total. Fast Fourier Transform (FFT) diterapkan pada proses transformasi RTP dalam 2-dimensi dan 3-dimensi menggunakan perangkat lunak Matlab dan Magpick. Hasilnya menunjukkan arah dari pipa utara-selatan dan memperlihatkan posisi dari pipa semakin jelas yang diperkirakan tepat berada di bawah puncak kurva anomali. Kata kunci: anomali magnet total, delineasi, reduksi ke kutub, transformasi fourier, klosur. We have the problem to detect anomaly directly from the magnetic field data because it have two polarities, positive and negative. We need a technique of data processing to detect magnetic anomaly better. In the case of gas pipeline delineation in X-area, Reduce to Pole (RTP) technique was applied to process total magnetic data. Fast Fourier Transform (FFT) was applied on RTP transformation process in 2-Dimension and 3-Dimension using Matlab and Magpick softwares. The result indicate that the gas pipeline is north-south direction and the position is under the peak of anomaly curve. Keywords: total magnetic anomaly, delineation, reduce to pole, fast fourier transform, closur.

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.

scholarly journals First in-orbit results of the vector magnetic field measurement of the High Precision Magnetometer onboard the China Seismo-Electromagnetic Satellite

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Bin Zhou ◽  
Bingjun Cheng ◽  
Xiaochen Gou ◽  
Lei Li ◽  
Yiteng Zhang ◽  
...  
Keyword(s):  
Magnetic Field ◽  
High Precision ◽  
Magnetic Field Measurement ◽  
Vector Data ◽  
Magnetic Field Data ◽  
Night Side ◽  
The Difference ◽  
The Magnetic Field ◽  
Ground Calibration ◽  
Data Calibration

Abstract The High Precision Magnetometer (HPM) is one of the main payloads onboard the China Seismo-Electromagnetic Satellite (CSES). The HPM consists of two Fluxgate Magnetometers (FGM) and the Coupled Dark State Magnetometer (CDSM), and measures the magnetic field from DC to 15 Hz. The FGMs measure the vector components of the magnetic field; while the CDSM detects the magnitude of the magnetic field with higher accuracy, which can be used to calibrate the linear parameters of the FGM. In this paper, brief descriptions of measurement principles and performances of the HPM, ground, and in-orbit calibration results of the FGMs are presented, including the thermal drift and magnetic interferences from the satellite. The HPM in-orbit vector data calibration includes two steps: sensor non-linearity corrections based on on-ground calibration and fluxgate linear parameter calibration based on the CDSM measurements. The calibration results show a reasonably good stability of the linear parameters over time. The difference between the field magnitude calculated from the calibrated FGM components and the magnitude directly measured by the CDSM is just 0.5 nT (1σ) when the linear parameters are fitted separately for the day- and the night-side. Satellite disturbances have been analyzed including soft and hard remanence as well as magnetization of the magnetic torquer, radiation from the Tri-Band Beacon, and interferences from the rotation of the solar wing. A comparison shows consistency between the HPM and SWARM magnetic field data. Observation examples are introduced in the paper, which show that HPM data can be used to survey the global geomagnetic field and monitor the magnetic field disturbances in the ionosphere.

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