Mining Goes Digital – Mueller et al. (Eds)
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
59
An approach for drilling pattern simulation
G. Usero & S. Misk
Regional Director Latin America, Geovariances, Belo Horizonte, Brazil
Geovariances, Belo Horizonte, Brazil
A. Saldanha
MCB Serviços de Mineração, Belo Horizonte, Brazil
ABSTRACT: Drilling is one of the most relevant expenditure in the mining industry. This
cost depends on location, geology feature and complexity of the operation, but in general,
it could typically cost 150 to 300 USD/meter. This paper presents an approach to assess the
geological and financial risk related to different drilling patterns with the use of conditional
simulations. The methodology has been successfully applied in different operating mines and
mineral exploration projects located in different geological contexts and for commodities such
as iron, bauxite, niobium, zinc, copper and gold. The first step of perform a set of conditional
simulations using the real dataset available. From the total realizations some are selected, based
on a cluster analysis, as the simulated realities that will form the basis of the study. The selected
realizations are resampled in different patterns (at least five) and these virtual drilling patterns
are then used as an input for additional conditional simulations. The result of the conditional
simulations with the virtual drilling patterns are then rescaled to the production increments,
based on the actual production of the operating site or the production forecast of the mineral
exploration projects. The increments used are consistent with monthly or quarterly and annual
production, and the risk assessment is performed within a confidence interval of 90% of the
simulated results according to the methodology proposed by Harry Parker. From this study, the
degree of accuracy related to each drilling pattern is assessed and used as a guide for additional
drilling campaign, based on the risk that the company is willing to take and budgetary forecast.
1 INTRODUCTION
An appropriate mineral resource estimation requires enough geological knowledge of the
target which may be achieved through an adequate drilling mesh in order to assess the unique
geological, chemical, mineralogical and structural characteristics of each mineral occurrence
(JORC 2012). Since drilling plays an important role in budget constraint, it is crucial for the
mining companies to be able to assess the relevant quantity of drillholes required to be within
an acceptable risk boundary.
One of the main challenges faced by companies, especially during early stage mineral
exploration programs, is to define the drilling pattern/densities that are adaptive for a robust
mineral resources classification, considering that just a few drillholes are available and consequently the geological knowledge of the deposit is yet sparse. A possible approach is to use
the available data to perform conditional simulations to create possible and equiprobable
realities that represent the scant dataset available and may be used as a starting point to assess
the risk related to different drilling pattern/densities.
Although the methodologies for an appropriate risk assessment are still under
research and debated, geostatistical conditional simulations have been considered as the
best practice by various mining codes and consequently for robust mineral resources
classification. Geostatistical simulation generates stochastic models that accurately represent the actual distribution and spatial variability of the variables of interest: grades,
© 2019 Taylor & Francis Group, London, ISBN 978-0-367-33604-2
59
An approach for drilling pattern simulation
G. Usero & S. Misk
Regional Director Latin America, Geovariances, Belo Horizonte, Brazil
Geovariances, Belo Horizonte, Brazil
A. Saldanha
MCB Serviços de Mineração, Belo Horizonte, Brazil
ABSTRACT: Drilling is one of the most relevant expenditure in the mining industry. This
cost depends on location, geology feature and complexity of the operation, but in general,
it could typically cost 150 to 300 USD/meter. This paper presents an approach to assess the
geological and financial risk related to different drilling patterns with the use of conditional
simulations. The methodology has been successfully applied in different operating mines and
mineral exploration projects located in different geological contexts and for commodities such
as iron, bauxite, niobium, zinc, copper and gold. The first step of perform a set of conditional
simulations using the real dataset available. From the total realizations some are selected, based
on a cluster analysis, as the simulated realities that will form the basis of the study. The selected
realizations are resampled in different patterns (at least five) and these virtual drilling patterns
are then used as an input for additional conditional simulations. The result of the conditional
simulations with the virtual drilling patterns are then rescaled to the production increments,
based on the actual production of the operating site or the production forecast of the mineral
exploration projects. The increments used are consistent with monthly or quarterly and annual
production, and the risk assessment is performed within a confidence interval of 90% of the
simulated results according to the methodology proposed by Harry Parker. From this study, the
degree of accuracy related to each drilling pattern is assessed and used as a guide for additional
drilling campaign, based on the risk that the company is willing to take and budgetary forecast.
1 INTRODUCTION
An appropriate mineral resource estimation requires enough geological knowledge of the
target which may be achieved through an adequate drilling mesh in order to assess the unique
geological, chemical, mineralogical and structural characteristics of each mineral occurrence
(JORC 2012). Since drilling plays an important role in budget constraint, it is crucial for the
mining companies to be able to assess the relevant quantity of drillholes required to be within
an acceptable risk boundary.
One of the main challenges faced by companies, especially during early stage mineral
exploration programs, is to define the drilling pattern/densities that are adaptive for a robust
mineral resources classification, considering that just a few drillholes are available and consequently the geological knowledge of the deposit is yet sparse. A possible approach is to use
the available data to perform conditional simulations to create possible and equiprobable
realities that represent the scant dataset available and may be used as a starting point to assess
the risk related to different drilling pattern/densities.
Although the methodologies for an appropriate risk assessment are still under
research and debated, geostatistical conditional simulations have been considered as the
best practice by various mining codes and consequently for robust mineral resources
classification. Geostatistical simulation generates stochastic models that accurately represent the actual distribution and spatial variability of the variables of interest: grades,