KRIGING FRACTURE INDICATORS TO ESTIMATE RECOVERY IN DIMENSIONAL STONE EXPLORATION

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  • Kriging Fracture Indicators to Estimate

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Abstract

A study was conducted for a granite quarry producing dimensional stone in the Laurentides mountains (Québec, Canada) to forecast the recovery and waste amounts of blocks due to the presence of fractures. In this paper, the term “fracture” refers to any kind of natural structural discontinuities, i.e. fractures, joints, faults, veins, dykes. Equal area stereographic projection of fracture pole density was used to identify four sets of structural discontinuities in the quarry. For each of these sets, four binary indicator functions were defined as different levels in the quality of the rock mass. The value of these binary functions is deduced from two fracture density parameters calculated in two-dimensional unit cell: the number of fracture intersections and the cumulative fractured length. The database underlying the estimation of these parameters was obtained from a systematic field survey of fracture traces observed on the accessible working faces and floors.<BR>A quality index was estimated on a regular grid of elementary blocks according to a systematic production plan. The predicted values of the quality index for each set were combined to estimate a recovery ratio in three target areas. It was found that the geostatistical procedure presented in this paper can be used to optimize both the extent and the orientation of the working faces. The recovery index was estimated at 15% for the first quality blocks and 15% for the second quality blocks in a 40m x 30m x 6m volume of rock. This result indicates very high ratio for the building stone industry, but the selected volume is not sufficient to ensure quarry operation for several years. Other target areas were rejected and an exploration program is currently yield on the same property, but outside the actual limits of the quarry to find additional granite reserves.

Journal

  • Geoinformatics

    Geoinformatics 7 (1-2), 37-45, 1996

    Japan Society of Geoinformatics

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