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


Authors / CoAuthors

Taylor, R. | Ray, A. | Symington, N. | Ray, A.

Abstract

<div>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.&nbsp;</div>

Product Type

document

eCat Id

147042

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  Resource provider

 

  Point of contact

Commonwealth of Australia (Geoscience Australia)  
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia

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Keywords

( Project )
  • EFTF – Exploring for the Future
  • surface magnetic resonance
  • electromagnetic
  • modeling
  • bayesian
theme.ANZRC Fields of Research.rdf
  • Electrical and Electromagnetic Methods in Geophysics

Publication Date

Creation Date

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Australian Government Security Classification System    

Classification - unclassified

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Creative Commons Attribution 4.0 International Licence    

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Status

Purpose

Open source software

Maintenance Information

notPlanned

Topic Category

geoscientificInformation

Series Information

Lineage

<div>Part of the HiQGA module within EFTF, Strategic Innovation Research Fund 2021-22</div>

Parent Information

Extents

[-44.00, -9.00, 112.00, 154.00]

Reference System

Spatial Resolution

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Downloads and Links

Link to Australasian Groundwater Conference 2022  

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