Better laser focusing on improved reproducibility of U-Pb isotope analysis by LA-ICP-MS

Huang, Hui-Qing1; Guillong, Marcel2; Hu, Yi3; Spandler, Carl1

1Economic Geology Research Center, Division of Tropical Environments and Societies, James Cook University, Townsville, QLD 4811, Australia. Email:, 2Department of Earth Sciences, ETH Zurich, 8092 Zurich, Switzerland, 3Advanced Analytical Centre, James Cook University, Townsville, QLD 4811, Australia

Spatial resolution and precision of U-Pb isotope analysis by LA-ICP-MS has been greatly improved in the last two decades. However, reproducibility of this most widely used in situ technique is still relatively poor, and error sources remain challenging to determine. Factors such as matrix composition, air, laser fluence have been systematically examined. Here we evaluate a previously underappreciated source of error on U-Pb isotope determination associated with laser focus. Using two different LA-ICP-MS systems but similar ablation parameters (a circular spot of ~20 µm and a final depth of ablation of ~10 µm only with a laser fluence of 2 J/cm2, an ablation time of 30 seconds and a repetition rate of 4 and 5 Hz), we show that sole variation of laser focus by 30 µm can lead to a systematic offset in 206Pb/238U of ~4 – 6% for zircons. Focus position variation led to change of laser irradiance on sample surface and shape of ablation craters. The degree of age offset is controlled by the final depth of ablation and crater aspect ratios (depth to diameter). We demonstrate further that the impact of focus variation on U-Pb isotope fractionation is matrix dependent. Using same conditions, defocus of laser beam by 30 µm can cause an offset in 206Pb/238U by <1% for NIST610 glass, ~3% for titanite, and up to 12% for rutile. The uncertainty related to laser focus appear random. We suggest that enhanced repeatability of laser focusing is required for improved uncertainty and better reproducibility in the determination of elements and particularly high precision U-Pb isotopes by LA-ICP-MS.


Huiqing did his PhD at Curtin University. His research involves using geochemistry and igneous and experimental petrology to understand continental crust formation and evolution. He currently works for James Cook University as a laboratory specialist with a focus on method development using LA-ICP-MS.

Multi-Scale Characterisation of Australia’s Deepest Drill Hole

Birchall, Renee1, Pearce, Mark1, Walshe, John1, Powell, Helen1, Shelton, Tina1 & Woodall, Katie1.

1CSIRO Mineral Resources, Kensington, WA, Australia.

The Jundee Gold Camp (Jundee), located in the northern Yandal Greenstone Belt of the Yilgarn Craton, is relatively understudied compared to the adjacent historic Wiluna Gold Camp. In 2018, Northern Star Resources drilled an Australian-record-breaking 3,217 m drill hole through Jundee’s Zodiac Discovery to complement a recently acquired 3D seismic dataset. In this study, the entire stratigraphy of this world-class gold camp was characterised by combining 3.2 km of continuous chemistry measurements made using the Minalyze X-ray Fluorescence (XRF) Core Scanner and over 400 mineral maps acquired using a Tescan Integrated Mineral Analyzer (TIMA) scanning electron microscope. The Minalyze XRF dataset was used to inform the sampling for mineral maps and additional portable X-Ray Fluorescence (pXRF) measurements were taken, to allow the XRF data to be used to benchmark future pXRF analyses on site. The high-spatial resolution of the Minalyze XRF enabled the lithogeochemistry of the 3.2 km of stratigraphy to be characterized in detail. Locally, the Jundee stratigraphy consists of two Archaean basalt-sediment sequences that have been intruded by multiple dolerites and later by lamprophyres, porphyries, granodiorites, granites and further, Proterozoic dolerite dykes. The dolerite and basalt units in the stratigraphy were classified using spatial patterns of elemental variations resulting from igneous fractionation, which can be used to fingerprint individual dolerites in the stratigraphy. Comparison of the Minalyze XRF and pXRF datasets support using immobile elements (Zr, Cr and Ti) to classifying the lithostratigraphy at Jundee. The automated mineralogy data were integrated with the Minalyze XRF and concurrent pXRF lithogeochemical datasets to discriminate between spatial variations in mineralogy caused by lithological changes and those associated with alteration. Interrogation of textural information available in the automated mineralogy phase maps is critical in underpinning the key metamorphic and hydrothermal alteration assemblages in the stratigraphy. The primary gold-bearing mineral assemblage at the Zodiac Discovery is summarised by chlorite (clinochlore and chamosite), calcite, pyrite, titanite, actinolite ± arsenopyrite ± scheelite ± tourmaline (dravite and schorl). Quantifying changes in mineral assemblages and their paragenetic relationships provides information on fluid compositions and pressure-temperature conditions during metamorphism, hydrothermal alteration and mineralisation events. At Jundee, four events were defined through the TIMA SEM method, which may or may not be temporally continuous: Stage 1a: Metamorphic assemblage (greenschist to amphibolite facies), Stage 2a: Alteration assemblages from K-rich fluids, Stage 2b: Alteration assemblages from CO2-bearing fluids (± Au), and, Stage 2c: Assemblages from late, low-CO­2 fluids. Further, fluid pathways and during mineralisation are easily identified because of the high spatial resolution, and quantitative nature of the techniques used.


Renee is a geoscientist who has expertise in applied research of Archaean orogenic gold systems. Renee joined CSIRO in 2015 from industry where she worked across Western Australia in both mining and exploration settings.

Building a cloud-hosted exploration data platform and its application

Kohlmann, Dr Fabian1; Noble, Dr Wayne1; Theile, Moritz1

1Lithodat Pty. Ltd., Melbourne, Australia

Well managed, standardized data is vital for the exploration industry as it currently undergoes an intense digitalization phase. As most available geoscientific datasets are regionally bound and have bespoke implementations, it is challenging to merge all data into a consistent global framework. Lithodat’s vision is to provide geoscientists with global geoscientific databases and analytics to decrease the time taken to gain new insights about regions of interest. Currently, LithoSurfer offers the largest global, standardised thermochronology and geochronology repository available. The detailed analytical data and advanced analytical tools allow the options to query data and thermal histories through time, or even rerun thermal history models.

To achieve this Lithodat has developed LithoSurfer, an online platform for viewing, analysing and extracting data. LithoSurfer gives quick access to a wealth of information (analytical details, lab information, literature etc.) across multiple analytic techniques and localities. Lithodat’s team of experts’ extract, validate and integrate data in our cloud-hosted database. This consolidation opens up the full potential that spatial geoscience data has to offer and is a vast improvement on storing data in separate spreadsheets and folders as often happens within laboratories and research projects. LithoSurfer makes disperse and complicated research datasets understandable and usable for the wider geoscience community.

Lithodat’s strong links with academia and industry help bring the geoscience community together with a consistent platform for their global geospatial research data. LithoSurfer allows academic communities to enter, organize and analyse their data and collaborate with researchers and industry. Data owners have the opportunity to share their published data with the entire global research community or with just selected co-researchers or customers. Unpublished data or data which needs to be kept private is only accessible to authorized researchers. Although protected, this data can still be integrated with other already published data. In addition, LithoSurfer also details the analytical origin and techniques to enable users to filter the data they want and trust.

Using the right tools means researchers can help to solve scientific questions and industrial demands.

With LithoSurfer researchers can now visualize, combine and export data from areas of interest including diagrams, graphs and auto generated reports on the fly. However, LithoSurfer does not constrain the researcher to its tools, and data can be extracted in multiple formats to take full advantage new techniques such as machine learning (ML) and artificial intelligence (AI).


After a post-doc at Bergen University, Fabian worked with Neftex and Halliburton as a Senior Geoscientist. Fabian left Halliburton in 2018 to join Lithodat Pty. Ltd., a spatial exploration data company based in Melbourne.

Fabian holds a PhD from University of Melbourne and a MSc from LMU in Munich, Germany.

Digitalizing the Mining Industry – Core scanner for geochemistry, images, RQD, structures, specific gravity and volume bulk density

Arthursson, Mikael2, Annelie, Lundström1, Angus Tod2

1Minalyze AB, Gothenburg, Sweden. 2Minalyze Pty Ltd, Perth, Australia.

Minalyzer CS is a scanner which in a contactless and non-destructive way generates geochemistry, high-resolution images, rock quality designation (RQD), structures, specific gravity and bulk density for drill cores and other drill samples.

The patented scanner is designed for handling large volumes of drill samples and is capable of scanning drill cores directly in core trays. A laser (LiDAR) generates a 3D-model of the topology of the core and trays, which enables the control and precision of the continuous XRF scanning. RQD and structures are also derived based on the 3D-model.

The objective, continuous and consistent nature of the datasets as well as the high but compact data density generated by the scanning technology is paramount in machine learning and deep learning applications and approaches to geology. Machine learning and deep learning have been demonstrated to be effectively used, based on the data from the scanning, for prediction of host rock lithologies.

A cloud-based software for visualisation and generation of datasets through digital tools facilitates remote access to a digital version of the drill sample. Remote access to data has become critical in order to keep project and operations moving forward when travel has become impossible and/or risky due to the pandemic.

The bulk density can be derived based on measured volume from LiDAR scan of the Minalyzer CS, combined with the weight of the core tray. The method is suitable for friable sediment core where a true representation of the friable or heavily fractured sample through manual measurements and estimates can be error prone. The new method has been tested and applied in live application by Iron ore companies in Western Australia where extensive comparisons between the new method and the traditional have been made. The method has also been tested on known volumes and densities for verification and demonstrate both a high level of repeatability and accuracy. Other benefits with the method are that it can be automated to a high degree and provides a non-subjective measurement. Due to its implementation the bulk density value derived would represent a conservative measurement of the bulk density.


Mikael Arthursson is the CTO and co-founder of Minalyze. Mikael has a M. Sc. in Mechanical Engineering from Chalmers University of Technology, Gothenburg, Sweden. Through his visionary and entrepreneurial mindset he has played a key role in the development of the Minalyzer CS core scanner and the cloud software

Laser-Induced Breakdown Spectroscopy integrated with Multi-variate Wavelet Tesselation – a new and rapid methodology for lithogeochemical analysis and interpretation

Fontana, F. Fernando1,2; Tassios, Steven2,3; Stromberg, Jessica2,4; Tiddy, Caroline1,2; van der Hoek, Ben1,2; Uvarova, Yulia2,4.

1Future Industries Institute, University of South Australia, Mawson Lakes, Australia, 2Mineral Exploration Cooperative Research Centre – MinEx CRC, 3CSIRO Mineral Resources, Clayton, Australia, 4CSIRO Mineral Resources, Kensington, Australia.

Rock classification and discrimination is commonly performed by geologists through visual inspection of rocks in the field or by geological logging of drill cores. However, this visual interpretation of rock lithology is notoriously subjective and inconsistent. The utilisation of handheld and core scanning instruments for collecting standardized data coupled with rapid and consistent methods for extracting geological information (e.g. clustering algorithms and boundary detection techniques) is gaining popularity for supplementing traditional geological classification. Such techniques are objective and reduce inconsistencies, improving rock classification and geological logging outputs. Laser-Induced Breakdown Spectroscopy (LIBS) is an emission spectroscopy technique of interest for lithogeochemical analysis due to its sensitivity to light elements common in geological materials (e.g. Li, Be, Na, Mg), that are difficult to quantify using other techniques such as X-ray fluorescence (XRF). The wavelet tessellation method utilises the wavelet transform for edge detection in spatialized data and can be used for determination of boundaries in downhole geochemical data which may represent lithological contacts. Wavelet tessellation can be applied to raw LIBS data outputs (counts vs wavelength) with no requirement for data filtering or manipulation. In this study we demonstrate the application of wavelet tessellation for rapid analysis of LIBS geochemical data to produce pseudo-logs that are representative of a test-block geological stratigraphy. A test-block stratigraphy was created using 22 rock slabs glued together to produce a block ~16 cm in length.  The samples were chemically (XRF) and mineralogically (XRD) characterised and selected to represent two discrete and geochemically distinct rock types (granitoid and marble). LIBS spectral data for nine major elements (Al, Ca, Fe, K, Mg, Na, Si, Ti and Mn) was generated along a continuous line at a constant speed of 10 mm/min at 5 Hz in which every group of 10 spectra were averaged into 1 spectrum, creating 460 spectra that each correspond to an interval of ~0.35 mm. Clustering algorithms were used to separate the samples into groups reflective of rock-types based on the LIBS outputs for those 9 elements. Wavelet tessellation was undertaken to produce pseudo-logs of the test-block stratigraphy. Comparison of the known test-block stratigraphy from laboratory XRF and XRD data with the wavelet tessellation pseudo-logs generated from the LIBS data shows the potential application of multi-variate wavelet tessellation analysis for rapid interpretation of stratigraphic boundaries and rock-type from LIBS geochemical data. The discrete lithological groups of marble and granitoid were effectively separated, and less obvious distinctions between Ca and Mg-rich and Ca-rich marble slabs, and mafic to alkali-rich granitoids were also successfully made.  The methodology presented here highlights how a workflow using LIBS coupled with wavelet tessellation can be used for rapid lithogeochemical interpretation to produce reliable and objective lithogeochemical pseudo-logs to supplement subjective visual drill core logging.  Moreover, the sensitivity of LIBS analysis for light elements provides the opportunity for the development of new lithogeochemical interpretation workflows for exploration campaigns and characterisation of alteration halos.


Fernando is a geologist interested in geochemistry and mineral exploration. Currently, he is a PhD candidate at the University of South Australia and postgraduate researcher in the MinEx CRC, where he is applying LIBS in geosciences including for downhole assays.

Extracting more from exploration soil samples. The evolution of UltraFine+ and next generation analytics

Noble, Ryan R.P.1, Cole, David T.1, Williams, Morgan J.1, Lau, Ian C.1, Anand, Ravi R.1

1CSIRO Mineral Resources, Kensington, Perth, Western Australia

Continued exploration success requires consistent innovation. While large geochemical surveys conducted by mining companies are common, the suite of data we collect beyond standard soil chemistry has remained stagnant. A novel integration of analytical  methods known as UltraFine+™ extracts the “standard soil chemistry” of the <2 µm soil clay fraction, which is combined with soil VIS-NIR and FTIR spectral mineralogy proxies and physicochemical properties to improve interpretation of soil chemistry leading to better targeting for gold and base-metal exploration.

At numerous study sites across Australia, we demonstrate how the integration of spectral mineralogy proxies and particle-size variation can assist in understanding landscape processes and anomaly formation, and in some settings provide explanations for false positives. Through providing uncertainty estimates on spatial geochemical predictions and reducing the influence of explainable false positives, key information is communicated to decision makers for more confident targeting. A marked decrease in censored results using UltraFine+TM for gold (from 63% to 10% below detection limit) is a major improvement over historical techniques. Automated analytics pipelines using a variety of unsupervised machine learning techniques (e.g. dimensionality reduction, clustering) ensure the rapid interpretation of survey datasets, and accelerate the path to discovery.


Ryan is a principal research scientist with CSIRO working in soil and groundwater chemistry applied to mineral exploration

About the GSA

The Geological Society of Australia was established as a non-profit organisation in 1952 to promote, advance and support Earth sciences in Australia.

As a broadly based professional society that aims to represent all Earth Science disciplines, the GSA attracts a wide diversity of members working in a similarly broad range of industries.

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