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AI-GEOSTATS: Re: Samples in a Block

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  • Marcel Vallée
    Hi, Mark, Donald Donald Myers final sentence opened a door for me: There is no definitive answer to the question since it depends on the question, i.e., what
    Message 1 of 1 , Aug 29, 2001
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      Hi, Mark, Donald

      Donald Myers final sentence opened a door for me:
      "There is no definitive answer to the question since it
      depends on the question, i.e., what is the data to be
      used for?

      In this perspective, I would line to raise several issues.
      My background and experience is mainly that of a mining
      geologist who is familiar with geostatistics, and has had
      the opportunity to work with several geostatisticians.
      Forgive me for broadening the problem, but such are geology
      and minng.

      In my opinion, the final purpose of aampling is
      estimation leading to mining extraction that achieves
      optimal metal recovery and minimal dilution. Estimating/
      modeling of the variogram and kriging are interim
      objectives. Geological mapping, interpretation and modeling
      are also essential steps with whom sampling methods,
      sampling grid dimensions and geostatistical aspects should
      be integrated in the determination of global and local
      continuity (Sinclair and Vallée, 1994).

      The basic problem of sampling grid size should be viewed in
      three dimensions. Our usual sampling grids are planned for
      efficiency, using a stratified drilling pattern
      perpendicular to the plane of apparent structural /
      geological continuity. So far, so good!

      However, once we have achieved a first delineation and can
      calculate a semivariogram along the drill hole axis,
      too often we neglect or forget to verify if these
      continuity parameters apply are present in the other two
      perpendicular directions.

      This problem has been detected by Michel David and described
      in a sampling paper titled "What happens if?" given at a
      sampling symposium in Australia in 1976 where he describes
      the problem and recommends sampling specifically designed
      to verify continuity parameters in the second and third
      dimensions. Sadly, there is only one sentence in
      "Geostatistical Ore Reserve Estimation (which was already
      in print at the time this paper was prepared and presented)
      that refers to this problem (around page 200).

      Journel and Huijbregts in "Mining Geostatistics" also
      describe this problem (1978) and recommend a few simple
      tools, for instance to lay out a cross of more closely
      spaced drill holes within the main grid.

      I consider, based on my mining experience, that sampling
      of rock in place should be targeted stratified sampling,
      not random sampling. Regionalized variables require
      regionalized sampling

      When the exploration or mining geologist halves the sampling
      grid dimension, he/she is basically using a similar
      strategy. I know the results of this effort are viewed by
      geostatisticians as the "clustering" problem! For the mining
      geologist, the objective is local estimation and close
      determination of ore limits, whether they are grade contacts
      or sharp contacts both for planning and extraction.

      What is the ideal sampling grid dimension for the mining
      geologist and the mining engineer? My answer: the one
      that allows to plan and develop and extract the ore (from
      stopes or open pit) efficiently as described above. I
      understand the student/researcher cannot rely on similar
      amounts of funds for drilling.

      Another important consideration in the Davil paper and in
      Geosatistical Ore Estimaion is that of sample preparation
      and assaying quality control. Quoting from the paper"
      " ... (frequently) it is the sanple preparation procedure
      whick generates the nugget effect rather than the real
      mineralization which generates the nugget effect"
      [underlined in the text]. This subject makes up almost a
      chapter of Geostatistical Ore Reserve Estimation.

      A higher "induced" nugget effect, that is a higher sampling/
      assaying variance of the values used for a selectin decision
      will reduce the accuracy of LOCAL estimation and mine
      selection.

      What is the final grid dimension (the one we call measured
      resource, proven reserve). This will vary depending on
      orebody configuration and mining method selected. In a open
      pit, with a fairly sizeable, not too complex and not too
      nuggetty ore body, you generally can get away with a wider
      grid for proven ore than yo can in the majority of cases
      underground,

      In an open pit you can sample more systematically,
      from bench to bench than you can in most underground mine.
      Also one has more flexibility for selection by adjusting
      blast limits based on test drilling on the pit floor and
      sampling of blast holes.

      For those this may interest, here are references of papers,
      including some I was involved in that deal with these
      subjects
      and perspectives.

      Best Regards

      Marcel Vallée Eng. Geol.
      Géoconseil Marcel Vallée Inc.
      706 Routhier St
      Sainte-Foy, Québec G1X 3J9
      Canada
      Tel: (1) 418 652 3497
      Fax: (1) 418 652 9148
      Email: vallee.marcel@...

      David M., 1976, What Happens If? A few remarks on Useful
      Geostatistical Concepts for the Design of Sampling Patterns.
      The Aus. I.M.M Melbourne Branch, Sampling Symposium, Sept.
      1976, preprint of proceedings, 16 p. (A major sampling
      paper)

      Postolski, T. A., Sinclair, A. J. (1998) Geology as a
      Basis for Refining Semivariogram Models for Porphyry-Type
      Deposits. Exploration and Mining Geology, Vol. 7, Nº 1-2,
      p. 45-50.

      Vallée, M, Dagbert, M, & Côte, D. (1993) Quality control
      requirements for more reliable mineral deposit and reserve
      estimates. CIM Bulletin, vol. 86. No 969, p. 65-74.
      (the ideas presented in this note have been developed here)

      Sinclair, A.J. and Vallée, M. (1994) Reviewing continuity:
      An essential element of quality control for deposit and
      reserve estimation. Exploration and Mining Geology, Vol.3,
      Nº 2, pp. 95-108. (Determination of continuity is at the
      core of estimation!)

      Vallée, M. (1998) Sampling Quality Control. Exploration and
      Mining Geology, Vol, 7, Nº 1-2, p. 107-116. (Some material
      on sampling strategy; sampling and assay variance work
      against good semivariograms and good estimation)

      Vallée, M. (1992) Guide to the evaluation of gold deposits.
      CIM Special Volume 45, Canadian Institute of Mining,
      Metallurgy and Petroleum, Montréal, Canada, 299 p.
      (A general perspective of the work of the geologist in
      estimation and mining. It was consdidered by Canadian
      miners,
      at the time of publication, to be oriented too much toward
      the use of geostatistics!)

      Vallée M. Draft Standards for Exploration and
      Resource/Reserve Estimation. Developed and expanded
      by the author from a report sponsored by the
      Québec Department of Natural Resources following
      the Bre-X affair, 110 pages, 800 k WordPerfect file.
      (This on-going work presents an ISO-9000:2000 compatible
      Quality Management and Continuous Improvement system
      that intends to integrate the geological, geostatistical
      and minng characteristics and constraints of mineral
      development.)

      The Volume 7, No 1-2 issue of Exploration and Mining Geology
      is a special issue on "Quality Assurance, Continuous
      Improvement and Standards in Resource Estimation.
      Abstracts of the papers can be viewed on the CIM web site
      (www.cim.org) at the Geological Society and/or Publications
      pages. Eight of the nineteen papers deal with sampling and
      assaying QA/QC.

      <30>

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