Authors: Hayman, LJ

Open access courtesy of:

DOI https://doi.org/10.36487/ACG_repo/2025_38

Cite As:
Hayman, LJ 2020, 'Utilising data science to test similarity of rock mass unit strength distributions in the Pilbara', in PM Dight (ed.), Proceedings of the 2020 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 625-636, https://doi.org/10.36487/ACG_repo/2025_38

Download citation as:   ris   bibtex   endnote   text   Zotero


Abstract:
Rio Tinto Iron Ore (Rio Tinto) undertakes diamond drilling within the Pilbara to geotechnically characterise the rock mass pertaining to proposed pit walls prior to implementation every year. Data from the diamond core is logged, tested in the field and in the laboratory; then committed to a local database and analysed for that particular pit or deposit when the need arises. Currently there is the assumption that each deposit within the Pilbara has independent strength properties and is diamond drilled extensively as a result. Within the Pilbara rock masses there are a series of continuous, stratified units whose genesis are from the same depositional, folding, faulting and weathering events. This paper aims to utilise diamond core logging data to statistically verify that there are similarities of strength properties for some of the rock units across the Pilbara in neighbouring deposits. Proving this to be the case potentially will provide statistical evidence and the impetus to enable the Rio Tinto geotechnical department to reduce the metres of diamond drilling undertaken with a zero net effect on slope stability and safety in implemented slope designs. A total of 39,815 test observations from 2008 to 2018 from five separate neighbouring deposits were used in this study; and were derived from three different tests including field estimated strength (FES), point load (PLT) and unconfined compressive strength (UCS) which are key parameters in slope stability design. The data was interrogated using state-of-the-art data visualisation and statistical software appropriately chosen based on the size of the samples and nature of the distribution. This research follows on from recommendations made by Maldonado & Haile (2015) applying non-parametric statistical methods to the skewed data for a more appropriate approach. This study found sufficient statistical evidence that there is similarity in rock strength properties between five proximal deposits with 95% confidence in the vast majority of cases.

Keywords: drilling, statistics, optimisation

References:
Barton, N, Bamford, WE, Barton, CM, MacMahon, B, Kanji, MA, Babcock, K, … & Obradovic, J 1978, ‘Suggested Methods for the Quantitative Description of Discontinuities in Rock Masses’, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, pp. 319‒368.
Brown, ET 1981, Rock Characterization, Testing and Monitoring: ISRM Suggested Methods, International Society for Rock Mechanics, Pergamon Press.
Cochran, WG 1963, Sampling Technique 2nd Edition, John Wiley and Sons Inc., New York.
Donders, H 2009, The Relationship between Rock Mass Conditions and Alteration and Weathering in the Lower Hamersley Group Iron Formations, Western Australia, MSc thesis, University of Canterbury, Christchurch.
Green, R & Borden, RK 2011, ‘Geochemical risk assessment process for Rio Tinto’s Pilbara Iron Ore Mines’, vol. I, InTech, viewed: 27 April 2019,
Heslin, J 2014, Site-Specific Correlation of the Point Load Index for the Hamersley Formation, Undergraduate Thesis, The University of Queensland, Queensland.
ISRM 1979, ‘Suggested methods for determining the uniaxial compressive strength and deformability of rock materials’, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, vol. 16, no. 2, pp. 135-140.
ISRM 1985, ‘Suggested method for determining point load strength’, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, vol. 22, no. 2, pp. 51–60.
Maldonado, A & Haile, A 2015, ‘Application of ANOVA and Tuckey-Cramer, statistical analysis to determine similarity of rock mass strength properties across Banded Iron Formations of the Pilbara region in Western Australia’, International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Slope Stability 2015, The Southern African Institute of Mining and Metallurgy.
Mann, HB & Whitney, DR 1947, ‘On a test of whether one of two random variables is stochastically larger than the other’, Annals of Mathematical Statistics, vol. 18, no. 1, pp. 50‒60.
Rio Tinto 2019, Chartbook August 2019, press release, Rio Tinto, London.
Standards Australia 2007, Methods of Testing Rocks for Engineering Purposes Method 4.2.1: - Rock Strength Tests - Determination of Uniaxial Compressive Strength of 50 MPa and Greater (AS 4133.4.2.1), Standards Australia, Sydney.




© Copyright 2020, Australian Centre for Geomechanics (ACG), The University of Western Australia. All rights reserved.
Please direct any queries or error reports to repository-acg@uwa.edu.au