Mining Goes Digital – Mueller et al. (Eds)
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
201
Critical review of mineral resource classification techniques
in the gold mining industry
S.K.A. Owusu & K. Dagdelen
Mining Engineering Department, Colorado School of Mines, Golden, Colorado, USA
ABSTRACT: This paper investigates the different classification techniques used by the
gold mining industry professionals to classify mineral resources into measured, indicated
and inferred categories. The research is based on forty-five (45) public disclosure reports
from System for Electronic Document Analysis and Retrieval (SEDAR) and one general
classification guideline of a major gold producer unlisted on SEDAR. The survey includes
public documents categorized by various geologic types of deposits and companies considered
as major, mid-tier and junior gold mining operators. It encompasses 19 NI 43-101 technical
reports filed in 2018 and 26 reports filed between 2006 and 2017. The purpose of the research
is to explore and understand how the different mining companies perform classification of
mineral resources in terms of the requirements used and different deposit type consideration.
The paper summarizes the survey results, discusses the general implications and the need for
developing more formal approach to mineral resource classification.
1 INTRODUCTION
1.1 Purpose of the study
Capital-intensive investment decisions are made in the mining industry with respect to confidence levels displayed in the mineral resources and reserves. The quality and quantity of
materials estimated to be mined from a deposit have economic implications on the production schedule. The uncertainties with regards to the composition of a deposit may result in
unreliable estimates and misclassification of resources. Although the various industry mineral resource reporting standard codes provide guidelines to be followed in generating classification reports, different mining companies use various procedures because each Competent
Person (CP) or Qualified Person (QP) uses different assumptions, since none of the codes
provides consistent assumptions to be adopted for reporting purposes. This has created classification categorization inconsistencies, leading to the disclosure of mineral resource reports
with different accuracies in the industry. Mineral resource classification is a key requirement
for public reporting of economic assessment and investor confidence in a mineral project.
1.2 Mineral resource definitions and standards
To protect investors and mineral project advisors from misleading public disclosure of
mineral resources, the Council of Mining and Metallurgical Institutes (CMMI) introduced
classification standard codes in 1994 to provide guidelines to categorize mineral resources
into measured, indicated and inferred classes in decreasing order of geological confidence
reposed in the blocks in a deposit. The authenticity of the available data for estimation and
classification determines the geological confidence assigned by the CP or QP. The main factors that are evaluated to justify the credibility of a data include nature, quality, quantity and
distribution. The distribution of most earth science data are skewed or lognormal. Effective
and credible resource estimation and classification lead to reliable mine designs, production
schedules, robust business plans and financial forecasts. Forty-five (45) different public
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
201
Critical review of mineral resource classification techniques
in the gold mining industry
S.K.A. Owusu & K. Dagdelen
Mining Engineering Department, Colorado School of Mines, Golden, Colorado, USA
ABSTRACT: This paper investigates the different classification techniques used by the
gold mining industry professionals to classify mineral resources into measured, indicated
and inferred categories. The research is based on forty-five (45) public disclosure reports
from System for Electronic Document Analysis and Retrieval (SEDAR) and one general
classification guideline of a major gold producer unlisted on SEDAR. The survey includes
public documents categorized by various geologic types of deposits and companies considered
as major, mid-tier and junior gold mining operators. It encompasses 19 NI 43-101 technical
reports filed in 2018 and 26 reports filed between 2006 and 2017. The purpose of the research
is to explore and understand how the different mining companies perform classification of
mineral resources in terms of the requirements used and different deposit type consideration.
The paper summarizes the survey results, discusses the general implications and the need for
developing more formal approach to mineral resource classification.
1 INTRODUCTION
1.1 Purpose of the study
Capital-intensive investment decisions are made in the mining industry with respect to confidence levels displayed in the mineral resources and reserves. The quality and quantity of
materials estimated to be mined from a deposit have economic implications on the production schedule. The uncertainties with regards to the composition of a deposit may result in
unreliable estimates and misclassification of resources. Although the various industry mineral resource reporting standard codes provide guidelines to be followed in generating classification reports, different mining companies use various procedures because each Competent
Person (CP) or Qualified Person (QP) uses different assumptions, since none of the codes
provides consistent assumptions to be adopted for reporting purposes. This has created classification categorization inconsistencies, leading to the disclosure of mineral resource reports
with different accuracies in the industry. Mineral resource classification is a key requirement
for public reporting of economic assessment and investor confidence in a mineral project.
1.2 Mineral resource definitions and standards
To protect investors and mineral project advisors from misleading public disclosure of
mineral resources, the Council of Mining and Metallurgical Institutes (CMMI) introduced
classification standard codes in 1994 to provide guidelines to categorize mineral resources
into measured, indicated and inferred classes in decreasing order of geological confidence
reposed in the blocks in a deposit. The authenticity of the available data for estimation and
classification determines the geological confidence assigned by the CP or QP. The main factors that are evaluated to justify the credibility of a data include nature, quality, quantity and
distribution. The distribution of most earth science data are skewed or lognormal. Effective
and credible resource estimation and classification lead to reliable mine designs, production
schedules, robust business plans and financial forecasts. Forty-five (45) different public