Curie depth estimation from magnetic anomaly data: a re-assessment using multitaper spectral analysis and Bayesian inference

2019 ◽  
Vol 218 (1) ◽  
pp. 494-507 ◽  
Author(s):  
Pascal Audet ◽  
Jeremy M Gosselin
Keyword(s):  
Spectral Analysis ◽  
Bayesian Inference ◽  
Magnetic Anomaly ◽  
Depth Estimation ◽  
Curie Depth

On application of fractal magnetization in Curie depth estimation from magnetic anomalies

2019 ◽  
Vol 67 (5) ◽  
pp. 1319-1327
Author(s):  
Chun-Feng Li ◽  
Duo Zhou ◽  
Jian Wang
Keyword(s):  
Depth Estimation ◽  
Magnetic Anomalies ◽  
Curie Depth

Determination of depth to the magnetic sources using spectral analysis with application to Sicily, Southern Italy

2020 ◽  
Author(s):  
Yemane Kelemework ◽  
Maurizio Fedi
Keyword(s):  
Spectral Analysis ◽  
Critical Evaluation ◽  
Power Spectra ◽  
Window Size ◽  
Depth Estimation ◽  
Careful Consideration ◽  
Source Distribution ◽  
Distribution Models ◽  
Theoretical Frameworks ◽  
Potential Field Data

<p>Spectral analysis is among the most old and common techniques for the processing and interpretation of potential field data. This is related to the decay properties of the field power spectra which allows an easy estimation of the depths to the top and to the bottom of the sources of magnetic and gravity field anomalies. Such analysis can be accomplished however in different theoretical frameworks, assuming either a statistical ensemble of homogeneous sources or random fractal source distribution. Here, we present the many existing spectral analysis techniques to compare them with respect to estimating the depth to the source top and bottom. We evidence practical constraints on the depth estimation and inherent assumptions/limitations of the different approaches. Depth estimation using spectral methods requires a critical evaluation of window size, window location, and wavenumber range. Careful consideration of the merits and of the limitations of these different spectral techniques for different source distribution models may lead to robust and geologically meaningful outcomes. In fact, despite the several different approaches all the methods give quite consistent and often similar estimates of the source depths. However, due to ambiguities on the correction spectral factor, the best estimates are obtained if this factor is constrained by a priori information. Finally, we estimate the depth to the magnetic sources beneath Sicily, which may provide additional constraints to better understand the deep crustal geometry and thermal gradients of the region.</p>

scholarly journals Magnetic Anomaly Interpretation of the Northern Congo Craton Boundary: Results from Depth Estimation and 2.5D Modeling

2017 ◽  
Vol 05 (12) ◽  
pp. 90-101
Author(s):  
Basseka Charles Antoine ◽  
Eyike Yomba Albert ◽  
Kenfack Jean Victor ◽  
Njiteu Tchoukeu Cyrille Donald ◽  
Som Mbang Constantin Mathieu ◽  
...  
Keyword(s):  
Magnetic Anomaly ◽  
Depth Estimation ◽  
Anomaly Interpretation

scholarly journals Radioisotope Identification and Nonintrusive Depth Estimation of Localized Low-Level Radioactive Contaminants Using Bayesian Inference

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 95 ◽  
Author(s):  
Jinhwan Kim ◽  
Kyung Taek Lim ◽  
Kilyoung Ko ◽  
Eunbie Ko ◽  
Gyuseong Cho
Keyword(s):  
Bayesian Inference ◽  
Estimation Method ◽  
Depth Estimation ◽  
Credible Interval ◽  
Acquisition Time ◽  
Depth Information ◽  
Burial Depth ◽  
Short Acquisition Time ◽  
Low Level ◽  
Depth Analysis

Obtaining the in-depth information of radioactive contaminants is crucial for determining the most cost-effective decommissioning strategy. The main limitations of a burial depth analysis lie in the assumptions that foreknowledge of buried radioisotopes present at the site is always available and that only a single radioisotope is present. We present an advanced depth estimation method using Bayesian inference, which does not rely on those assumptions. Thus, we identified low-level radioactive contaminants buried in a substance and then estimated their depths and activities. To evaluate the performance of the proposed method, several spectra were obtained using a 3 × 3 inch hand-held NaI (Tl) detector exposed to Cs-137, Co-60, Na-22, Am-241, Eu-152, and Eu-154 sources (less than 1μCi) that were buried in a sandbox at depths of up to 15 cm. The experimental results showed that this method is capable of correctly detecting not only a single but also multiple radioisotopes that are buried in sand. Furthermore, it can provide a good approximation of the burial depth and activity of the identified sources in terms of the mean and 95% credible interval in a single measurement. Lastly, we demonstrate that the proposed technique is rarely susceptible to short acquisition time and gain-shift effects.

scholarly journals Auto- and cross-power spectral analysis of dual trap optical tweezer experiments using Bayesian inference

2012 ◽  
Vol 83 (9) ◽  
pp. 095116 ◽  
Author(s):  
Yann von Hansen ◽  
Alexander Mehlich ◽  
Benjamin Pelz ◽  
Matthias Rief ◽  
Roland R. Netz
Keyword(s):  
Spectral Analysis ◽  
Bayesian Inference ◽  
Power Spectral Analysis ◽  
Optical Tweezer ◽  
Power Spectral
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