Mapping and Modeling Sources of Natural Remanent Magnetization in the Microcline–Sillimanite Gneiss, Northwest Adirondack Mountains: Implications for Crustal Magnetism

Abstract

• Magnetic measurements and microscopic observation indicate exsolved titanohematite is the main source of natural remanent magnetization • Data inversions confirm magnetic enhancement from microstructure in titanohematite and weak contribution of multidomain hematite to the NRM • Inversion results are consistent with bulk measurements, and indicate little effect of alternating field demagnetization on the NRM Accepted Article This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Microscale Magnetic Inversion of Remanent Magnetization Mineral Sources From the Black Hill Norite, South Australia

“…Inversion is conducted using Tensor Research ModelVision software (Oldenburg & Pratt, 2007; Pratt et al., 2006). The software allows 3D modeling of magnetic anomaly sources and solves the nonlinear inverse problem using the Levenberg–Marquardt algorithm (Levenberg, 1944; Marquardt, 1963; Pastore et al., 2019, 2021), where the intensity, declination, and inclination vary independently. The software inversion procedure runs along multiple parallel profiles until the standardized residual error between the input/observed data, and modeled data are minimized along all profiles.…”

“…However, as discussed by Pastore et al. (2021), the ideal modeling size of 100 μm does not represent the mineralogical and microstructure variability that we intend to investigate here. The expectation is that tabular arrays will display heterogeneous properties of an ilmenite grain, which contains reduction‐exsolution lamellae of magnetite e .…”

“…However, reliable interpretations may be hampered by disregarding what is occurring with the magnetic minerals at a microscale (Austin & Foss, 2014; Grant, 1984; McEnroe et al., 2009). Microscale magnetic mapping of thin sections is becoming more common with the development of scanning magnetic microscopy (SMM) (Church & McEnroe, 2018; Egli & Heller, 2000; Hankard et al., 2009; Oda et al., 2016; Pastore et al., 2021; Thomas et al., 1992; Weiss et al., 2000, 2007) and provides insight on small‐scale variations that in summation contribute to anomalies mapped at regional scales. In aeromagnetic interpretation, the magnetic anomaly is largely influenced by both the depth and volume of the source, and its intensity and direction of magnetization (Bhattacharyya, 1966; Phillips, 2005; Roest et al., 1992; Spector & Grant, 1970).…”

3D Joint Inversion of Scanning Magnetic Microscopy Data

“…Traditional rock magnetic methods, used to investigate the magnetization in natural rock samples, are bulk measurements resulting from magnetic properties' average contributions from all sources in proximity of the sensor. Scanning magnetic microscopy (SMM) is a high‐resolution mapping technique that allows us to characterize magnetic contributions of individual mineral phases (deGroot et al., 2018; Egli & Heller, 2000; Hankard et al., 2009; Oda et al., 2011; Pastore et al., 2018, 2019, 2021; Weiss et al., 2007, 2016). SMM generates a map of the magnetic field distribution over a planar surface of a rock sample with sub‐millimeter resolution which can be used to attribute specific magnetic signals to the underlying mineralogy.…”

Estimating the Net Magnetic Moment of Geological Samples From Planar Field Maps Using Multipoles

“…For such magnetometers, one possible approach consists of first computing the inversion of magnetic data for the entire magnetization distribution within the sample (henceforth denoted "full inversion") and then integrating the solution to calculate the net magnetic moment, either in a sub-volume or over the whole sample. While this approach is more general and allows for the reconstruction of extended sources, this type of reconstruction unfortunately requires carefully chosen regularization strategies and selection of regularization parameters, and possibly additional analyses to constrain physical characteristics of the sources, to overcome ill-posedness and obtain physically meaningful solutions [e.g., (Egli & Heller, 2000;Lima et al, 2013;Myre et al, 2019;Pastore et al, 2018Pastore et al, , 2021Pastore et al, , 2022Usui et al, 2012;Weiss et al, 2007)]. In practice, taking this approach is often too laborious and time-consuming for processing complete demagnetization sequences of geological samples, with no guarantee of obtaining accurate results for samples containing spatially extended and nonuniform magnetization patterns except in a handful of special cases [e.g., unidirectional or unidimensional magnetizations (Baratchart et al, 2013)].…”