June/July 2015

CIM Journal

Excerpts taken from abstracts in CIM Journal, Vol. 6, No. 3.
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Spatial modelling of geological domains with multiple training images: Application to the Red Dog mine, Alaska, United States

D. A. Silva, Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada; K. J. Palmer, Teck Resources Ltd., Vancouver, British Columbia, Canada; and C. V. Deutsch, Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada

ABSTRACT Evaluating resources and reserves requires the reliable modelling of geological domains and their grades. “Multiple point statistics” simulation is a relatively new geostatistical method to generate complex, high-resolution geological models by extracting high-order spatial relations from training images. A method based on combining multiple training images is developed to obtain the correct amount of large-scale continuity and short-scale variability. A calibration process matches the geological spatial variability between the final realizations and the drillhole dataset. A case study with data from the Red Dog mine, Alaska, United States, shows an appropriate reproduction of short-scale variability along boundaries between geological units.

Quantifying losses in support capacity due to corrosion

J.-F. Dorion, Langlois mine, Nyrstar, Quebec, Canada; J. Hadjigeorgiou, Lassonde Institute of Mining, University of Toronto, Toronto, Ontario, Canada; and E. Ghali, Université Laval, Québec City, Quebec, Canada

ABSTRACT Corrosion of support system components (e.g., bolts, mesh, plates) is a safety and economic concern in underground mines. This paper reports the results of a five-year study wherein corrosion coupons were installed at select locations in participating mines, recovered at regular intervals, analyzed for signs of corrosion, and tested to quantify loss in capacity. Complementary tests were conducted on recovered mesh and friction bolt specimens. The data provide insights into contributing factors for support systems corrosion, which aid in the selection of appropriate support strategies and reliable assessment of the useful life and need for rehabilitation of a support system.

Use of local average subdivision to characterize marine mineral reserves—A conceptual framework

T. Wambeke and M. Alvarez Grima, MTI Holland (Member of IHC Merwede Group), Kinderdijk, Netherlands; G. A. Fenton, Department of Civil Engineering, Dalhousie University, Halifax, Nova Scotia, Canada; J. Benndorf, Department of Resource Engineering, Delft University of Technology, Delft, Netherlands; and A. Vervoort, Department of Civil Engineering, KU Leuven, University of Leuven, Leuven, Belgium

ABSTRACT High-risk underwater mining operations necessitate characterizing spatial heterogeneity and resource uncertainty. Local average subdivision is a method of simulating spatial deposit variability inside a cell through a sequence of discretization stages, during which a cell is further subdivided into four or eight cells. New developments are presented to validate simulated deposit models and deal with point measurements of geotechnical and oregrade properties. This paper illustrates the relevance of translating spatial deposit variability into financial or operational performance indicators during underwater resource exploitation. Two synthetic case studies highlight the challenges of underwater mining in relation to production plans and equipment selection.

Process description and aerosol exposures at Vale Canada’s (Inco’s) Copper Cliff nickel refinery

B. R. Conard, BRConard Consulting, Inc., Oakville, Ontario, Canada

ABSTRACT As part of a series describing the nickel operations of Vale Canada (formerly known as Inco), this paper focuses on the 1973 to current operations of the Copper Cliff nickel refinery in Ontario, Canada. The process used there employs the formation of Ni tetracarbonyl at high CO (gas) pressure and its subsequent decomposition at somewhat elevated temperatures to produce highly pure Ni pellets and powders. Personal sampling of workplace aerosol dusts is reported, with information on specific Ni compounds in the aerosols.

Framework for resource uncertainty prediction and data valuation: An application to diamond deposits

J. G. Manchuk, Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada; J. Stiefenhofer and M. Thurston, Global Mining Division, De Beers Group Services (Pty) Limited, Southdale, South Africa; and C. V. Deutsch, Centre for Computational Geostatistics, University of Alberta, Edmonton, Alberta, Canada

ABSTRACT The degree of uncertainty associated with a natural diamond resource is important to quantify from the time of discovery through the production lifetime. Data collection occurs during the discovery, exploration, delineation, and production or recovery phases. Quantifying the relationship between data and uncertainty is an important component of project valuation. The value of data is measured as their potential to reduce uncertainty if they are collected. A method is developed using Monte Carlo simulation for predicting resource uncertainty and valuing data during critical phases of development, particularly discovery and exploration. The technique is applied to diamond pipe deposits.

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