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An open source modelling and Bayesian inversion package for surface magnetic resonance data

Created 17/10/2025

Updated 17/10/2025

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Surface magnetic resonance (SMR) techniques image subsurface water using the electromagnetic response of resonant hydrogen nuclei in water. Here we introduce the SMRPInv (Surface Magnetic Resonance Probabilistic Inversion) package, which couples a high-performance forward modeller for SMR data, and a Gaussian process based non-linear Bayesian inversion. Both the forward and inverse codes are part of the freely available, open source HiQGA (High Quality Geophysical Analysis) codebase written entirely in Julia. We summarise the relevant forward physics, the necessary data processing of free induction decay at an SMR sounding, followed by the estimation of subsurface water content with a non-linear parameterisation. Results are presented for synthetic inversions as well as field data from Western Davenport (Northern Territory). Comparisons are made against downhole logging data, together with results from a deterministic inversion of the same SMR soundings. Through this, we demonstrate that a probabilistic approach is key to conceptualising variability of subsurface water content. 

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Field Value
Title An open source modelling and Bayesian inversion package for surface magnetic resonance data
Language eng
Licence Not Specified
Landing Page https://data.gov.au/data/dataset/9ba57037-0bf8-4da3-90d9-d13ebe0d3a7d
Contact Point
Geoscience Australia Data
clientservices@ga.gov.au
Reference Period 27/07/2022
Geospatial Coverage
Map data © OpenStreetMap contributors
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Data Portal Geoscience Australia

Data Source

This dataset was originally found on Geoscience Australia "An open source modelling and Bayesian inversion package for surface magnetic resonance data". Please visit the source to access the original metadata of the dataset:
https://ecat.ga.gov.au/geonetwork/srv/eng/csw/dataset/an-open-source-modelling-and-bayesian-inversion-package-for-surface-magnetic-resonance-data