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Statistics & Geostatistics

Statistical and geostatistical analyses are essential in understanding the grade distribution and continuity in your deposit. SRK can apply knowledge and experience in this field to assist in optimising drilling and sampling strategies and grade estimation domaining and kriging parameters. Understanding geostatistics can assist in Mineral Resource classification and quantifying mining selectivity issues.


SRK's approach to statistical and geostatistical analyses combines our strengths in the undeerstanding of geostatistical theory combined with our expertise in structural and ore deposit geology and 3D modelling. Fundamental to SRK's approach is to ensure that any statistical or geostatistical analysis is tailored to the deposit under scrutiny, and reflects the underlying geology.


SRK has considerable expertise in statistics and geostatistics applied to mineral resources. Our technical experts have benefitted from global exposure to a wide range of mineral deposit types and commodities and have conducted and supervised complex geostatistical evaluations.

SRK also has a large base of Competent/Qualified persons as defined by the various internationally accepted resource reporting codes.

SRK continue to build long lasting relationships with both small and large clients and through continued involvement have seen many projects go from early grass roots exploration through to production.


Building from our extensive three dimensional geological modelling skills, SRK offers a wide range of statistical, geostatistical and grade interpolation skills. Statistical and geostatistical methodologies utilised by SRK geologists include:

  • Composite length analysis.
  • Geological and statistical domaining.
  • Statistical analysis (uni-, bi-, or multi-variate).
  • Spatial considerations (declustering).
  • Multivariate correlations, interdependencies and regression analysis.
  • Variographic analyses which are suitable for your deposit (e.g. raw, pairwise, Gaussian transforms).
  • 2 verses 3D environments for statistics and geostatistics.
  • Outlier and top-cut analysis.
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