Petrophysical “Big Data” - case study from the Stavely Project, western Victoria

Abstract

SummaryThe application of recent technological advances to the acquisition of petrophysical datasets has significantly increased the amount of quality, systematic physical rock property measurements that can be captured efficiently and cost effectively. These large datasets provide a more comprehensive understanding of petrophysical values and, as importantly, their statistical distribution – particularly when encompassing a diverse set of rock types and stratigraphy. To date, these types of comprehensive datasets are limited in the mineral exploration space, in both number and their spatial distribution.This paper presents a case study from the Stavely Project area in western Victoria outlining the workflow from acquisition, compilation and analysis, to the application of a large, pre-competitive petrophysical dataset. These data, including gamma density, magnetic susceptibility, P-wave velocity, electrical resistivity and natural gamma, were acquired by scanning of diamond core from 21 stratigraphic and mineral exploration drill holes by Multi-Sensor Core Logger equipment, providing a combined final dataset of 216,699 petrophysical values. The precompetitive data and subsequent analyses are available for download.In developing a statistical analysis of the petrophysical values, the datasets were segregated into stratigraphic, lithological and spatial sub-populations, therefore giving a geological context for the data, and providing baseline values for regional geophysical interpretations, forward modelling and inversions, and the identification of regions of anomalous petrophysical values potentially associated with hydrothermal mineralisation. Crosscorrelation of various petrophysical properties highlights important relationships within the data, thus maximising its value. In western Victoria these data have been important in the delineation of prospective volcanic belts of the Stavely Arc beneath cover, and the development of a 3D model displaying the regional geometries and distributions of the belts at depth.