Mitigating Risk in the Mining Sector: Best Practice Implementation & Independent Audits Jean Richardson, Andre McKen, Russ Calow, SGS Minerals Services Outi Maatta, SGS Systems, Standards and Certifications Adrian Shaw, SGS Project Finance

Definition of Risk, Risk Management Risk - the effect of uncertainty on objectives Risk management identification, assessment, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor & control probability and/or impact of unfortunate events to maximize the realization of opportunities ISO 31000, Nov 2009

Risk in the Minerals Sector PROJECT FINANCE SSC

Top Risks to Mitigate, 2009/2010 Cost containment Industry consolidation Access to capital Keep social license to operate Climate change Skills shortage Lack of infrastructure access Access to secure energy Resources nationalization Pipeline shrinkage Technical/operational Strategic Financial Social Environmental Operational/Human Resources Location Location/Operational Political Ernst and Young, 2009.

54% Somewhat or extremely concerned CEOs’ Concerns, 2009/2010 2010 2009 54% Somewhat or extremely concerned Pricewaterhousecoopers, 2010

Energy Use 85% 14% 1% 3-4% of global energy consumption used for comminution. Of this 1% is used for grain size reduction. Alavadro et al 1998 South Africa (Eskom) generates 38 GV/yr AngloPlats uses 1 GV/yr 40% in comminution and smelting Less than 1% results in grain size reduction Countries heavily dependent on coal to generate electricity.   Rule 2009

Comminution Update Technology advancements Jaw, cone crushers → ball& rod mills → SAG & FAG mills → HPGR Complex deposits, complex mineralogy, fine grained ore Finer grinding needed – UFG, Activox, multiple regrinds 1998 High Definition Mineralogy 2000 Variability in hardness & grindability - geometallurgy Simulation and modeling in feasibility Process and systems control Technical and management audits Plant improvements & ISO 50001 Need, costs and availability of power Carbon emissions 1995 Escondita 34 foot mill – 13.4 MW power 34 foot mill – 9.3 MW power 2003 Chatree 21 2.75 MW 2005 Collahuasi 39 foot 21 MW 2001 Cadia 40 foot 20 MW (Newcrest) Optimize flowsheet to be energy efficient: a) exploit the mineralogy of the ore. Even within one deposit, various zones or domains have differenign graindability. Eg. Merenshy Reef vs UG 2 : Average energy requirement to smelt Platreef: 579 Merenshy reef 554 UG2 667 b)

Technology Advances Replace old equipment & assess technologies Design flowsheet for mineralogy – can require fine grinding HPGR more energy efficient 40% Reasons for the increasing popularity of HPGR technology include increases in energy efficiency within the comminution circuits, increased throughput in milling and processing and improvements in metallurgical efficiency. These improvements can be attributed to the unique breakage patterns associated with inter-particle crushing and the production of micro cracks in rock particles. The applicability of HPGR technology within a flowsheet is ore dependent and so requires testing to estimate the size of equipment required and the effect on throughput and metallurgical performance associated with its use. SGS Mineral Services offers a standardized laboratory scale test of high pressure grinding rolls and complements the test with the most extensive background in HPGR lab testing in the business. Proprietary models, a broad database and a depth of experience in data interpretation ensure that risk is minimized during investigations with this still-developing technology. The product generated by HPGR is also often finer than products from conventional grinding circuits, leading to increased throughput through the comminution circuit as a whole. An exciting application for HPGR makes use of the report of observed micro cracks within the rock particles themselves. Increased overall leach recovery or kinetics have been attributed to the formation of these fissures during crushing, and the subsequent contact of leach solution and fresh mineral surface. The boundaries of this new application for HPGR are still being explored and continue to produce new avenues for investigation. 20% coarse fine Rule et al., 2009

Complex Deposits Mapping Variability/Geometallurgy SGS SPI Grindability Test Tumbling (abrasive) test 2 kg of 22 mm top size Good for variability mapping Batch test Yields SPI & Ci for SAG design Hardness Domains

SGS SPI Database soft hard

Simulate & Populate the Block Model SAG MILL BALL MILL Comminution Economic Evaluation Tool Comminution Model SGS CEET Completed

Throughput Modeled in 3D 5000 4500 Peruvian Porphyry Cu-Au Blue / soft ore/ high tph Brown / hard ore/ low tph

Predict Power Needs by Year (SAG and Ball Mills) SAG MILL P80 hard Bulled, 2007a, b

Technical Audits Technical Audits (Plant optimization) Surveys, sampling, analysis, troubleshooting Many plant parameters PSA, critical size build-up, mill speed, pulp density

Results Oriented: Improved Profitability Cu plant Implementation of a pre-crusher improved power efficiency 31% for hard ores Capex = $US 11M New revenues $US 40M/yr Au oxide plant Optimization increased throughput by 9.5% at similar grind No CAPEX New revenue $US13M/yr Guidelines for Presentation: (left) In this case, the plant was encountering occasionally a harder ore, which decreased their throughput significantly. A simulation study was carried on to determine the effect that would have pre-crushing for this particular ore. The simulation study yielded to a ‘go ahead’ for the project. The installation of the crusher did cost $US11M, but the additional revenue from the additional throughput more than compensate for the investment. Guidelines for Presentation (Right) This is another example where plant optimization through computer simulation can increase profitability substantially, sometimes with zero capital expenditure. In this case, modification in operation allow for an throughput increase of 9.5%, which yielded in additional revenue

Management Audits: ISO Standards BS EN 16000 → ISO 50 0001 Energy supply and use including equipment and systems Procurement and use-related disposal issues Continuous improvement cycles ANSI/MSE 2000-2008

Value of Systematic Energy Management PRODUCTION Decreased energy use Controlled energy costs Improved operational efficiency PLANNING Data for fact-based decisions Operating and capital spending Purchasing strategies PROTECTION Protection against energy market instabilities Reduced environmental impacts, show corporate social responsibility Competitive advantages

SGS: a Partner in Risk Mitigation