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This episode features the following technical highlights:
• Characterising Regolith Interfaces Using Field-Based Techniques; and
•Fast Logging With Hylogger Data
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At MinEx CRC we have developed a semi-automated, objective workflow to characterise cover materials and detect important boundaries within the cover using data that can be acquired at the drilling site or core yard through field-based techniques.
During exploration drilling most drill holes intersect regolith, which can conceal or reveal signs of mineral deposits at deeper levels. To interpret the geochemical signals in regolith and assess their potential as indicators for mineralisation, it is crucial to identify facies interfaces or other discontinuities within the cover. Recognising these cover interfaces in drilling chip samples can be challenging, even for experienced geologists, and can be subjective to individual interpretation.
Our approach involves acquiring geochemical and mineralogical data from drill cores using field instruments such as portable XRF and handheld VNIR-SWIR-TIR spectrometers. These data are integrated with petrophysical parameters acquired from wireline logging and processed using multivariate classification and optimised Machine Learning (ML) algorithms. Using the Data Mosaic software, we integrate a range of data products, including geochemical ratios, spectral scalars, and weathering indices to generate a multiscale classification and identify interfaces. The output generated by Data Mosaic TM closely resembles a geological log but is data-driven and objective. This enhances the reliability and consistency of the results and often reveals subtle yet significant signals that conventional geological logging procedures might overlook.
The reliability of the data acquired by pXRF and field spectrometers has been evaluated through comparison with precise analytical methods such as super trace ICP-MS, Quantitative XRD and HyLogger TM. The measurements obtained with field portable instruments are comparable to the laboratory measurements and have significant advantages in that they are cheaper and offer the option of near real-time data analysis at the drill site or core yard.
The workflow was successfully tested during the Delamerian margins NDI campaign in far western NSW. During the trial we were able to identify stratigraphic boundaries and discriminate between stratigraphic units across multiple boreholes using field-based techniques. Moving forward, we will continue to refine and apply this workflow, both on legacy samples and during NDI campaigns.
We have developed a web app that allows rapid first-pass geology logs to be generated using mineral groups derived from HyLogger data.
The HyLogger hyperspectral scanning system is in regular use by Australian geological surveys to analyse drilling products.Over 1.5 million meters of HyLogger data are available to the public via the National Virtual Core Library through the AuScope Discovery Portal.
However, this valuable data resource is underutilised because it requires a high level of expertise and sophisticated software to analyse the data. The web app is designed to provide easy access and create geologically useful outputs from these data with basic levels of expertise. The user can also use the web app with their own hyperspectral data files.
The aim of the project is to provide a workflow to enable fast logging of major rock types. By following the workflow, and making a few simple decisions, the user can extract a first-pass geological log without an in-depth knowledge of hyperspectral mineralogy.
The workflow incorporates multiscale spatial analysis (also known as “wavelet tessellation”) to deliver the geological logs at two different scales for broader application.
The workflow, known as MyLogger, and documentation can be accessed here.
The geological logs produced using the workflow will facilitate decisions by the user. For example, whether the hole contains rock types of interest and so to proceed to expert analysis, and which parts of the hole to focus expert analysis on. The geological log will also help the user to decide how best to subsample the hole for detailed studies, such as geochronology or micro-scale scanning.