Systematic error analysis of demagnetization and implications for magnetic interpretation

Demagnetization can affect the interpretation of magnetic data significantly. However, little attempt has been made to understand its effects by analyzing systematically the differences between demagnetization‐ corrected and uncorrected magnetic properties. A systematic error analysis is made in this paper using a 2-D elliptic cylinder model. Generally, demagnetization changes the effective susceptibility and remanence or the effective magnetization in both magnitude and direction. Error analyses show that demagnetization causes the magnitude of effective magnetization of a magnetic body to be less than its intrinsic magnetization. This implies that a theoretical anomaly computed without accounting for demagnetization will overestimate the amplitude of the anomaly associated with the body. The decrease in magnetization magnitude depends on the intrinsic magnetic susceptibility of a body as well as on the body’s geometry (flattening ratio) and its relative orientation (magnetic dip) in the geomagnetic field. The magnitude of the effective magnetization, relative to the intrinsic magnetization, decreases with increasing intrinsic magnetic susceptibility. This factor dominates the body’s effective magnetization. When intrinsic magnetic susceptibility is less than 0.1 SI, the demagnetization effects are generally insignificant and may be ignored in magnetic anomaly modeling. The magnetic dip and flattening ratio only cause minor fluctuations in the effective magnetization. Demagnetization also changes the direction of the effective magnetization vector by making it approach the plane of flattening of any flattened body. The difference between the inclinations of the effective and intrinsic magnetization changes the horizontal positions of extreme values of an anomaly, which may affect the precision of magnetic interpretations. Generally, the inclination difference is significant for magnetic dips of 30° to 70° and increases with increasing susceptibility and decreasing flattening ratio. In particular, for large flat‐lying magnetic geological units located at middle magnetic latitudes (30° to 70°), significant magnetic inclination deflections are expected because of demagnetization effects. Theoretical, experimental, and practical examples of magnetic interpretation are presented to illustrate these demagnetization effects.

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

Journal of Geological Research ◽

10.30564/jgr.v1i3.1316 ◽

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.

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Systematic Error Analysis for the Enhancement of Biometric Systems Using Soft Biometrics

IEEE Signal Processing Letters ◽

10.1109/lsp.2012.2221701 ◽

2012 ◽

Vol 19 (12) ◽

pp. 833-836 ◽

Cited By ~ 2

Author(s):

Anastasios Drosou ◽

D. Tzovaras ◽

K. Moustakas ◽

M. Petrou

Keyword(s):

Error Analysis ◽

Systematic Error ◽

Soft Biometrics ◽

Biometric Systems

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Magnetic susceptibility of the body-centred orthorhombic La2CuO4system

Journal of Physics Condensed Matter ◽

10.1088/0953-8984/17/42/010 ◽

2005 ◽

Vol 17 (42) ◽

pp. 6701-6728 ◽

Cited By ~ 2

Author(s):

Kyrylo V Tabunshchyk ◽

R J Gooding

Keyword(s):

Magnetic Susceptibility ◽

The Body

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ESTIMATION OF SOURCE PARAMETERS IN IBADAN, SOUTH â€“ WESTERN NIGERIA USING DIGITIZED AEROMAGNETIC DATA

Journal of Natural Sciences Engineering and Technology ◽

10.51406/jnset.v14i2.1751 ◽

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 7000â€ŸN to 7030â€ŸN and longitudes of 3 30â€²E to 4 00â€²E 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 â€“ 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.

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Classifying Copper-Molybdenum-Gold Porphyry Deposit Alteration using Magnetic and Spectral data

10.5194/egusphere-egu21-15817 ◽

2021 ◽

Author(s):

Oliver Dixon ◽

William McCarthy ◽

Nasser Madani ◽

Michael Petronis ◽

Steve McRobbie ◽

...

Keyword(s):

Machine Learning ◽

Magnetic Susceptibility ◽

Spectral Data ◽

Learning Algorithm ◽

Copper Production ◽

Magnetic Data ◽

Machine Learning Algorithm ◽

Porphyry Deposit ◽

Remanent Magnetisation ◽

Magnetic Remanence

Copper is one of the most important critical metal resources needed to achieve carbon neutrality with a projected increase in demand of >300% over the next half century from electronics and renewables. &#160;Porphyry deposits account for most of the global copper production, but the discovery of new reserves is ever more challenging. Machine learning presents an opportunity to cross reference new and traditionally under-utilised data sets with a view to developing quantitative predictive models of hydrothermal alteration zones to guide new, ambitious exploration programs.The aim of this study is to demonstrate a new alteration classification scheme driven by quantitative magnetic and spectral data to feed a machine learning algorithm. The benefits of an alteration model based on quantitative data rather than subjective observations by geologists, are that there is no bias in the data collected, the arising model is quantifiable and therefore easy to model and the process be fully automated. Ultimately, this approach aids more detailed exploration and mine modelling, in turn, reducing the extraction process carbon footprint and more effectively identifying new deposits.Presented here are magnetic susceptibility and shortwave infrared (SWIR) data collected from the KazMinerals plc. owned Aktogay Cu-Mo giant porphyry deposit, eastern Kazakhstan, which has a throughput of 30Mtpa of ore. These data are cross referenced using a newly developed machine learning algorithm. Generated autonomously, our results reveal twelve statistically and geologically significant clusters that define a new alteration classification for porphyry style mineralisation. Results are entirely non-subjective, reproducible, quantitative and modellable.Importantly, magnetic susceptibility measurements improve the algorithm&#8217;s ability to identify clusters by between 29-36%; enhancing the sophistication of the included magnetic data promises to yield substantially better statistical results. Magnetic remanence data are therefore being complied on representative samples from each of the twelve identified clusters, including hysteresis, isothermal remanent magnetisation (IRM) acquisition, FORC measurements, natural remanent magnetisation (NRM) and anhysteretic remanent magnetisation (ARM). Through collaboration with industry partners, we aim to develop an automated means of collecting these magnetic remanence data to accompany the machine learning algorithm.

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Bias correction of extreme values of high resolution climate simulations for risk analysis.

10.21203/rs.3.rs-264479/v1 ◽

2021 ◽

Author(s):

luis Augusto sanabria ◽

Xuerong Qin ◽

Jin Li ◽

Robert Peter Cechet

Keyword(s):

Climate Change ◽

Bias Correction ◽

Extreme Values ◽

The Body ◽

Future Climate ◽

Return Periods ◽

Climate Conditions ◽

Mitigation And Adaptation ◽

Climate Simulations ◽

The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

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Magnetic concentration and polymorphism in di-n-octyl-, di-n-decyl-, and di-n-dodecylphosphinates of copper(II)

Canadian Journal of Chemistry ◽

10.1139/v85-188 ◽

1985 ◽

Vol 63 (5) ◽

pp. 1111-1117 ◽

Cited By ~ 11

Author(s):

John S. Haynes ◽

Katherine W. Oliver ◽

Robert C. Thompson

Keyword(s):

Differential Scanning Calorimetry ◽

Magnetic Susceptibility ◽

Heisenberg Model ◽

Variable Temperature ◽

Electronic Spectroscopy ◽

Chain Structure ◽

Magnetic Data ◽

Scanning Calorimetry ◽

Extended Chain ◽

Linear Chains

Phosphinates of copper(II) of the type Cu(R2PO2)2 where R is n-octyl, n-decyl, and n-dodecyl have been synthesized and characterized by differential scanning calorimetry, vibrational and electronic spectroscopy, and variable temperature (300 to 4.2 K) magnetic susceptibility studies. Each of these compounds was obtained in distinct α and β structural forms. All materials appear to have the double phosphinate bridged extended chain structure and the magnetic data have been successfully analyzed according to the isotropic Heisenberg model for linear chains. The α forms exhibit antiferromagnetic behaviour with J values of −25, −29, and −29 cm−1 for the octyl, decyl, and dodecyl derivatives respectively. The β forms are ferromagnetic and have corresponding J values of 1.8, 2.1, and 2.3 cm−1 respectively. Magneto-structural correlations in these extended chain coordination polymers are discussed.

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Linking cave sediments and soil magnetism in the Urșilor cave (Romania)

10.5194/egusphere-egu21-2973 ◽

2021 ◽

Author(s):

Cristian George Panaiotu ◽

Cristian Necula ◽

Relu D. Roban ◽

Alexandru Petculescu ◽

Ionut-Cornel Mirea ◽

...

Keyword(s):

Magnetic Susceptibility ◽

Frequency Dependence ◽

Remanent Magnetization ◽

Rock Magnetism ◽

Magnetic Mineral ◽

Magnetic Data ◽

Sediment Samples ◽

Superparamagnetic Particles ◽

Susceptibility Data ◽

Cave Sediments

Cyclical changes in the magnetic mineral assemblages have been observed in numerous sedimentary records confirming the relationship between rock magnetism and past global change. Several studies have shown that the magnetic susceptibility data of cave sediments reflect both long- and short-term climatic oscillations. These magnetic susceptibility variations are attributed to changes in climate-controlled pedogenesis which influence the production of low coercivity magnetic mineral phases, magnetite, and maghemite outside the cave. These soils with climate-dependent magnetic properties are then washed, blown, or tracked into the cave where they accumulate, creating the changes observed in rock magnetic data. We present a rockmagnetism study of the sediments from the Ur&#537;ilor cave and the soils above the cave. Our focus is the detailed characterization of the ferromagnetic mineralogy preserved in the cave sediments and its links with potential soil sources. In the cave, we sampled four sections (2-3 m high) consisting mainly of silts and clays, with some sand layers. The age of the sediments is older than 40 ka. At the surface, we sampled various types of soils from 9 sites. For all samples, we measured: variation of magnetic susceptibility with frequency (976 and 15616 Hz), the anisotropy of magnetic susceptibility, isothermal remanent magnetization, and anhysteretic remanent magnetization. Because soils are characterized by the presence of superparamagnetic magnetite produced by pedogenesis which can be detected by the frequency dependence of magnetic susceptibility, we also measured the frequency dependence of soils and selected cave sediment samples at 13 frequencies (between 128 and 512000 Hz). Multi-frequencies measurements of the magnetic susceptibility of recent soils show that all the sampled soils have a strong frequency dependence indicating the presence of superparamagnetic particles produced by pedogenesis. Most of the sediment samples have an important frequency dependence similar to the one observed in the recent soils. As a preliminary conclusion, we can state that most of the fine cave sediments contain superparamagnetic particles, which can be probably attributed to soils transported into the cave by erosion. These results suggest that during the deposition of high magnetic susceptibility sediments it was a climate favorable for intense pedogenesis. The interpretation of the intervals with lower values of magnetic susceptibility is still under investigation to decide if represents a climatic signal or a change in the dynamics of sediment transport. Acknowledgment: The research leading to these results has received funding from the EEA Grants 2014-2021, under Project contract no. EEA-RO-NO-2018-0126.

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