Applying advanced gravity and magnetic inversion methods to expand the Platreef PGE-Ni-Cu resource in the Bushveld Complex. Issue 1 (1st December 2016)

• Record Type: Journal Article
• Authors: Williams, Nicholas; de Wet, Barry; Kekana, Sello; Nielsen, Shane; Broughton, David
• Is Part Of: ASEG Extended Abstracts (Online). Volume 2016:Issue 1(2016)
• Page Start: 1
• Page End: 7
• Publication Date: 2016-12-01
• Subjects: magnetic -- gravity -- inversion -- constraints -- exploration; Prospecting -- Geophysical methods -- Periodicals; Prospecting -- Geophysical methods; Periodicals
• DOI: 10.1071/ASEG2016ab187
• Languages: English
• ISSNs: 2202-0586

Abstract

Abstract : There are many potential field inversion algorithms available, and all are sufficiently capable of generating a model that explains supplied geophysical observations. The challenge is extracting a model that provides real geological insight. Here we present applications of two different styles of advanced inversions to a deep exploration program at the Platreef PGE-Ni-Cu deposit in the Bushveld Igneous Complex of South Africa. The initial approach was to apply generalised focussing constraints to a 3D magnetic vector inversion, an approach chosen to manage the effect of expected strong remanent magnetisation. This resulted in successful prediction and drill definition of inferred resources within a deep, west-dipping extension to the shallow-dipping "Flatreef" deposit. Later, a detailed 3D model of geological constraints based on drilling and mapping was constructed and used to tightly constrain inversions of gravity data derived from a FALCON airborne gravity gradiometer survey. The resulting 3D density model accurately predicted a continuation of the Flatreef host rocks to shallower levels than previously anticipated. This facilitated further drilldefinition of additional inferred resources within a southern extension of the Flatreef deposit. Key to the success of the inversions at accurately targeting mineralisation at depths of 700-1300 m depth, was the inclusion and integration of all available information to ensure that predictions were consistent with prior observations.