Quality Assessment/Quality Control (QA/QC) for Resource Estimation at Inco Technical Services Limited

Resource modelling is the basis for any economic appraisal of a mining project and includes a number of steps from data acquisition and validation to resource reporting and classification. At each step in the modelling process it is necessary to define the specific objectives, the methodology proposed to achieve those objectives and to establish a set of checks and validation tools to assess the effectiveness of the proposed methodology. The data used has to be both reliable and relevant for the purpose of the modelling. QA/QC for database validation requires verification of sample location; including correct collar location, topographic modelling and down-hole surveying. Validation is also performed on assaying information such as checks for sampling bias and accuracy of core splits, proper use of pulp duplicates and standards, handling of calculated values, explicit/implicit absent data and data entry errors. The second step involves identifying the mineralized domains resulting from the mineralization process. This step requires a geometric interpretation of all relevant geological features that have influenced the spatial distribution of the mineralization including dykes, faults and alteration. In addition, a geologic reference system rather than a standard Cartesian system is established to measure distances between samples. Once the mineralized domains are established and the database has been validated, statistical and spatial description of the mineralized samples are examined in order to establish the histogram and the variogram of all variables of interest and their correlation. Results are also used to calibrate the global resource estimate within the mineralized domain and to establish the search strategy for grade interpolation. The mineral envelope is filled with polyhedral cells representing mining blocks. The average grade of these blocks is estimated using kriging techniques in order to eliminate global bias and to minimize the local error in the block grade estimate. Visual checks are made to validate the spatial trends in grade distribution while global bias and smoothing effect are assessed from the declustered sample statistics. When required, smoothing correction may be applied using ?change of support? techniques. Simulations are used to perform sensitivity analysis and the simulation models are used if severe smoothing of spatial variability makes the interpolated model inappropriate for mine planning. The keys to successful resource estimation are an integrated team of geologists, geophysicists, geostatisticians and mine engineers using the best available technology and reviews by independent auditors. The resource team is also responsible for performing a QA/QC program in order to measure the effectiveness of the methods in meeting the specific objectives at each step of the modelling process.