Characterisation of metavolcanic megaclast structures within the Moyston Fault hangingwall melange (Moornambool Metamorphic Complex), western Victoria: Insights from potential field modelling and machine learning
- 1. University of Melbourne, tom.mc@live.com.au
- 2. University of Melbourne, m.mclean@unimelb.edu.au
- 3. Geological Survey of Victoria, ross.cayley@ecodev.vic.gov.au
Description
The `Stawell Corridor', western Victoria, is a major goldfield where resurgent exploration is targeting metavolcanic bodies closely associated with major gold deposits. The Magdala Antiform hosts the Stawell Gold Mine and is the type deposit for the style of mineralisation sought. Additional structurally related metavolcanic domes have been identified throughout the corridor, however few have seen substantial exploration due to obfuscation by sedimentary cover. A significant contrast in density and magnetic susceptibility exists between the metabasalt domes and the turbidite metasediments that host them, and this contrast makes potential field methods an ideal method for discriminating and characterising Magdala-style domes during exploration. A ground gravity survey was conducted over the Magdala Antiform and two associated dome structures - Wildwood and Lubeck - to ascertain their signatures in gravity. The survey comprised profiles that transect the domes. Station spacing was varied, using 25 meters across dome surfaces and wider (50-100 meter) spacing beyond dome extents to establish background trends. The acquired gravity profiles were forward modelled together with public magnetic data using drillhole, petrophysical and reflection seismic constraints as available. The Magdala profile is well-constrained by drillhole data gathered at Stawell Gold Mine and provides an opportunity to study the dome expression in gravity with detail. Profiles for Wildwood and Lubeck are relatively lacking constraints, with only a few drill sites nearby. Survey results suggest there may be significantly more metabasalt bodies throughout the Moyston Fault hangingwall than previously identified. A second stage of the project aims to train a machine learning algorithm to identify potential Magdala-style dome structures from gridded potential field data, to assess the usefulness and reliability of machine learning methods in a melange setting. Automating the early stages of interpretation in mapping has the potential to significantly ease the manual load of mapping at regional scales, especially in a structurally complex area like the Stawell Corridor.
Notes
Files
AEGC_2023_ID184.pdf
Files
(426.1 kB)
Name | Size | Download all |
---|---|---|
md5:f3eac336f732fbb5fb34919226806373
|
426.1 kB | Preview Download |