3D potential-field inversions and alteration mapping in the Gawler Craton and Curnamona Province, South Australia

3D potential-field inversions and alteration mapping in the Gawler Craton and Curnamona Province, South Australia Richard Chopping, Nick Williams, Tony Meixner and Indrajit Roy

Outline Inversions Introduction to inversions Constraining an inversion Gawler and Curnamona inversion results Alteration mapping Alteration mapping basics Alteration mapping in the Gawler and Curnamona

Potential-field inversions Geophysical data (gravity shown) Property model (density shown) (Gawler-Curnamona gravity) (Gawler-Curnamona gravity inversion)

Available data: gravity

Available data: magnetics

Potential-field inversions There are an infinite number of physical property models that would reproduce any given potential-field data To make the inversion possible, mathematical constraints are added to allow the inversion to converge on a solution It is also possible to guide the inversion result by including known geological observations Not including any geological observations/interpretations => unconstrained or default inversion Including geological observations/interpretations => constrained inversion

Constraints Just add physical properties and Surface geology maps Basement geology maps Surface sample measurements 3D models, seismic Drilling geology & measurements

Obtaining constraints in the Gawler

Constraining potential-field inversions Ideally, all geological knowledge would be incorporated in an inversion Inversion results would then accommodate all known geology and still reproduce the observed geophysics (a perfect inversion result) This perfect result is still not possible: Our ability to include constraints is mainly limited by known physical properties Including as much as we can still pays dividends

Synthetic example

Seismic lines in the available in the Gawler-Curnamona region

Constraints: even the simplest can help Unconstrained Constrained by lower-density material in top layer of cells (Results from seismic line 08GA-C1)

Inversions: Providing the third dimension to seismic

Inversions: Providing the third dimension to seismic Line 08GA-G1

Inversions: Providing the third dimension to seismic Isosurfaces > 2.7 g/cm 3 Iron Knob (Oblique view from south-south east, colours are density recovered along 08GA-G1) Characteristics of body to the east of Iron Knob Dense but non-magnetic Inversion smears body to depth (typical trait of inversions) but extension of body out of plane of seismic v. reliable in inversion results. If body was constrained in depth, density would better match forward-modelling results (~2.95 g/cm 3 ). Dense (gabbroic) non-magnetic intrusion or hematite alteration?

Alteration mapping

Quartz Back to first year geology: How do we identify minerals? Magnetite DIAGNOSTIC PROPERTIES! Biotite Gold

and now first-year geophysics! Geophysics measures signals that arise from some physical phenomenon These signals result from changes in physical properties (density, magnetic susceptibility, seismic velocity) underneath the surface Physical properties, such as density, depend on mineralogy, especially in crystalline rocks that commonly host ore bodies (For example: A rhyolite is less dense than a basalt because of differing mineralogy) Chemical alteration affects mineralogy, hence chemical alteration can affect physical properties Lithology and alteration provide our signals!

Quantifying alteration using linear programming The proportion of alteration can be calculated using 3 linear equations These equations are simply the weighted averages of densities and magnetic susceptibilities and the total proportion of all minerals in each cell is 100% With constraints on the mineral system in the form of inequalities (e.g. magnetite > pyrrhotite), the solution can be solved using linear programming toolkits in software such as MATLAB

Quantifying alteration

Mapping alteration: Olympic Dam Geologically-constrained constrained gravity and magnetic inversion models Understanding of mineral system model for Olympic Dam style deposits 2 % Chalcopyrite / 0.5 km 3 cell 1.5-2 2 % Chalcopyrite / 0.5 km 3 cell Sericite-altered

Predicted basement hematite + sulphides map Subsurface map: All All below 300m depth Hematite + sulphides (% / 0.5 km 3 ) > 3.0 1.5 0 Olympic Dam Cu deposits Cu prospects Exploration target: Sulphides & hematite, near magnetite N 25 km

Predicted basement magnetite map Subsurface map: All All below 300m depth Magnetite (% / 0.5 km 3 ) > 1.0 Cu deposits Cu prospects 0.5 0 Olympic Dam Exploration target: Sulphides & hematite, near magnetite N 25 km

Area selection based on predicted alteration Subsurface map: All All below 300m depth Magnetite (% / 0.5 km 3 ) > 1.0 Contours: Black: 1 % sulph + hem White: 1 % sericite Cu deposits Cu prospects 0.5 Olympic Dam Exploration target: Sulphides & hematite, near magnetite N 25 km

Olympic Dam 3D mineralogy map YELLOW: >0.25 % sulphides / ½ km 3 GREEN: >0.25 % sericite / ½ km 3 Cu deposits Cu prospects GREY: >0.25 % magnetite / ½ km 3 Olympic Dam Olympic Dam Acropolis Wirrda Well 15 km

Taking it into the very regional scale Magnetite (% / 4 km 3 ) > 1.25 Prominent Hill 600 km 0.5 0 Olympic Dam 510 km 0 1 km depth slice

Conclusions Potential-field inversions allow us to recover 3D models of densities and magnetic susceptibilities Physical properties allow us to both constrain these inversions and interpret their results in terms of chemical alteration Quantifying the amount of alteration in any inversion cell allows us an avenue to interpret inversions in terms of mineral potential rather than physical properties