Spatial Modelling of Heavy-Tailed Mineral Grades Using a Spatial Point Process

• Author / Creator

  Mooney, Cole R

• Evaluating the resource contained in a precious metals deposit is a challenging task because they are often characterized by heavily-skewed grade distributions and outlier values. Traditional geostatistical modelling methods are difficult to apply in the presence of outlier values because they can lead to overestimation and bias. The economic viability of these deposits often depends on the upper few percent of samples. These outlier samples are important and should be retained; however, their influence should be reduced to prevent potential overestimation and bias.

  This thesis examines the implications of modelling heavy-tailed, precious metals deposits. The limitations of traditional geostatistical modelling techniques are discussed in the context of heavy-tailed deposits and the use of a spatial point process to model grade is presented. An overview of the geologic processes that create gold deposits is presented in order to understand the nature of gold mineralization as well as provide justification for the proposed modelling technique.

  A spatial point process is used to model the tail of the distribution as discrete events. A particle size distribution is given to the simulated points to calculate grade. Following that, a discrete fracture network is adapted to model mineralized quartz veins in the deposit. High-grade gold is spatially restricted to the simulated vein structures. The automatic processing of drill core photos generates the necessary input distributions for a fracture network. Finally, a thorough case study demonstrates the application of grade modelling with a spatial point process and discrete fracture network. The results are compared to traditional geostatistical techniques and limitations are discussed.

  The proposed methodology presents a geologically realistic method of simulation which reduces the effect of outlier values by spatially limiting their influence. Capping or other subjective ad-hoc manipulation of assay data is not required. Final models of grade have the correct mean, variance and spatial continuity.

• Subjects / Keywords

  • Spatial point process
  • Geostatistics
  • Resource estimation
  • Discrete fracture network

• Graduation date

  Spring 2015

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R34J0B55D

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.