Mining Goes Digital – Mueller et al. (Eds)
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
246
Declustering weights as a measure of average sample spacing,
applications in mineral resource classification
D.E. Hulse
Gustavson Associates L.L.C., Lakewood Colorado, Colorado
R.C. Bryan
Geostat Systems L.L.C., Golden Colorado, Colorado
ABSTRACT: Mineral resource classification is described in both the SME and CIM Standards
for Mineral Resource Reporting. The CIM Standard states “… sampling … is sufficient to
assume geological and grade or quality continuity between points of observation”, thus is a
function of continuity and sample spacing. Continuity can be measured by use of a variogram
model, but average sample spacing in three dimensions is more difficult to measure. The declustering algorithms provided with geostatistics software are commonly used to weight data for
statistical analysis due to the sometimes-irregular spacing between drill holes during exploration.
The weight values are lower when data is closer, reflecting shared influence between samples, and
higher for isolated samples reflecting independence. This paper will discuss the potential to use
estimates of these declustering weights as an inverse relative measure for average sample spacing
to gauge the confidence of the estimate independent of the single nearest sample.
1 INTRODUCTION
Classification of mineral resources and mineral reserves disclosure for stock exchanges is
coordinated internationally by a group formed from delegates of various national technical
mining associations. The Committee for Mineral Reserves International Reporting Standards
(CRIRSCO) includes representatives of the Society of Mining, Metallurgy and Exploration
(SME) of the U.S.A., Canadian Institute of Mining Metallurgy and Petroleum (CIM), the
Joint Ore Reserves Committee (JORC) of Australia, among others. The authors have chosen
to present definitions from the CIM Definition Standards for Mineral Resources and Mineral
Reserves (CIM Standing Committee 2014).
Measured mineral resource
A Measured Mineral Resource is that part of a Mineral Resource for which quantity,
grade or quality, densities, shape, and physical characteristics are estimated with
confidence sufficient to allow the application of Modifying Factors to support detailed
mine planning and final evaluation of the economic viability of the deposit.
Geological evidence is derived from detailed and reliable exploration, sampling and testing and
is sufficient to confirm geological and grade or quality continuity between points of observation.
(CIM Standing Committee 2014). Indicated and Inferred Mineral Resources have similar,
however less restrictive definitions. The guideline continues to state that criteria should be
applied to define the part of the estimate where the “geological evidence is derived … testing
that is sufficient to confirm geological grade or quality …” By this measure the quality of an
estimate and hence its classification is based on the availability of data in spatial proximity
to make an estimate.
The classification of mineral resources requires some decisions and interpretations be made
by the NI43-101 qualified person (QP) or a JORC competent professional (CP). These include
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
246
Declustering weights as a measure of average sample spacing,
applications in mineral resource classification
D.E. Hulse
Gustavson Associates L.L.C., Lakewood Colorado, Colorado
R.C. Bryan
Geostat Systems L.L.C., Golden Colorado, Colorado
ABSTRACT: Mineral resource classification is described in both the SME and CIM Standards
for Mineral Resource Reporting. The CIM Standard states “… sampling … is sufficient to
assume geological and grade or quality continuity between points of observation”, thus is a
function of continuity and sample spacing. Continuity can be measured by use of a variogram
model, but average sample spacing in three dimensions is more difficult to measure. The declustering algorithms provided with geostatistics software are commonly used to weight data for
statistical analysis due to the sometimes-irregular spacing between drill holes during exploration.
The weight values are lower when data is closer, reflecting shared influence between samples, and
higher for isolated samples reflecting independence. This paper will discuss the potential to use
estimates of these declustering weights as an inverse relative measure for average sample spacing
to gauge the confidence of the estimate independent of the single nearest sample.
1 INTRODUCTION
Classification of mineral resources and mineral reserves disclosure for stock exchanges is
coordinated internationally by a group formed from delegates of various national technical
mining associations. The Committee for Mineral Reserves International Reporting Standards
(CRIRSCO) includes representatives of the Society of Mining, Metallurgy and Exploration
(SME) of the U.S.A., Canadian Institute of Mining Metallurgy and Petroleum (CIM), the
Joint Ore Reserves Committee (JORC) of Australia, among others. The authors have chosen
to present definitions from the CIM Definition Standards for Mineral Resources and Mineral
Reserves (CIM Standing Committee 2014).
Measured mineral resource
A Measured Mineral Resource is that part of a Mineral Resource for which quantity,
grade or quality, densities, shape, and physical characteristics are estimated with
confidence sufficient to allow the application of Modifying Factors to support detailed
mine planning and final evaluation of the economic viability of the deposit.
Geological evidence is derived from detailed and reliable exploration, sampling and testing and
is sufficient to confirm geological and grade or quality continuity between points of observation.
(CIM Standing Committee 2014). Indicated and Inferred Mineral Resources have similar,
however less restrictive definitions. The guideline continues to state that criteria should be
applied to define the part of the estimate where the “geological evidence is derived … testing
that is sufficient to confirm geological grade or quality …” By this measure the quality of an
estimate and hence its classification is based on the availability of data in spatial proximity
to make an estimate.
The classification of mineral resources requires some decisions and interpretations be made
by the NI43-101 qualified person (QP) or a JORC competent professional (CP). These include