The geometry and structural history of high-grade granite-gneiss units, which host the Venetia diatremes in South Africa, have been modelled in 3D using an implicit, rules-based, conditional geometrical technique. The volume contains a pervasive, dominant foliation, which forms the main plane of strength anisotropy in ongoing design and mining of the Venetia pit, which has a planned final depth of approximately 465 m below surface. The well-developed S2 foliation is a continuous feature that was locally re-oriented during D3 and D4 and localised ‘wrapping’ around competent amphibolite/hornblendite lenses or boudins. These local variations have important implications for pit design and operational risk management, particularly where they dip adversely out of the slope, or occur at the base of bench stacks, or in inter-ramp areas. These structures, when undercut by dips steeper than their friction angle, may result in planar sliding, presenting an operational safety risk. Best practice requires early identification of these occurrences, to make design adjustments where warranted. Lithological contacts, which have been transposed into parallelism with the S2 foliation, and a robust set of structural data collected over the last 10 years, are analysed to quantify and represent the variable orientation of S2 in 3D space. This contribution describes several methods, using leading software packages such as Leapfrog Geo™, Micromine™ and Python, to generate representative S2 form surfaces and anisotropy block models, both of which are used for downstream geotechnical engineering analysis. Outputs are also translated into apparent dip “heat” maps that show the angular interaction between S2 foliation and a pit design surface. These methods augment, and lessen the dependence on, typical 2D wedge-shaped design sectors that are commonly employed in pit design. This approach has important safety and economic benefits. As the rock mass fabric is characterised, it supports quick identification of potentially higher-risk areas (e.g. adverse undercut fabric with greater likelihood of slope instability) in current mine plans, which justifies more detailed analysis and/or additional monitoring controls to ensure safe and efficient mining. It also allows rapid mine design optimisation.
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