Geoscience Reference
In-Depth Information
1
Introduction
Abstract
The estimation of mineral resources is an important task for geoscientists and mining en-
gineers. The approaches to this challenge have evolved over the last 40 years. This topic
presents an overview of established current practice. The topic is intended for advanced
undergraduate students or professionals just starting out in resource estimation.
1.1
Objectives and Approach
Constructing numerical models for long, medium or
short-term resource assessment includes four major areas of
work:
1. Data collection and management;
2. Geologic interpretation and modeling;
3. Grades assignment; and,
4. Assessing and managing geologic and grade uncertainty.
Data collection and management involves a large number of
steps and issues. There are topics on drilling and sampling
theory, such as Peters (
1978
) and Gy (
1982
). The richness
and complexity of these subjects cannot be covered in detail;
nevertheless, it is important that the resource estimator con-
sider subjects that affect the quality of the ultimate estimates.
Some background information is provided.
Geologic interpretation and modeling requires that site
specific geologic concepts and models are integrated with
actual data to construct a three dimensional model of geo-
logical domains. This geologic model is a representation of
those variables that control the mineralization the most and
forms the basis for all subsequent estimation. Often, the geo-
logical model is the most important factor in the estimation
of mineralized tonnage.
The concentrations of different elements or minerals
(grades) are assigned within geological domains. The grades
within the different domains may be reasonably homogeneous;
however, there is always some variability within the domains.
The grades are predicted at a scale relevant for the anticipat-
ed mining method. The recoverable resources are calculated
considering a set of economic and technical criteria. There
are a wide variety of methods available and many implemen-
tation aspects must be considered. The chosen method will
Our objective is to explain important issues, describe com-
monly used geological and statistical tools for resource mod-
eling, present case studies that illustrate important concepts,
and summarize good resource estimation practice. Wherever
possible a common thread will be maintained through the sec-
tions including details of theory and references to appendices
and other authors, relevant examples, software tools avail-
able, required documentation trail for better practice, exten-
sions to handling multiple variables, modeling of other less
common variables such as metallurgical properties, and limi-
tations and weaknesses of the assumptions and models used.
There are a wide variety of minerals of interest including
industrial minerals such as gravel and potash, base metals
such as copper and nickel, and precious metals such as gold
and platinum. There are other spatially distributed geologi-
cal variables such as coal, diamonds, and variables used to
characterize petroleum reservoirs. Often, the constituent of
interest has variable concentration within the subsurface. A
resource
is the tonnage and grade of the subsurface mate-
rial of interest. The resource is in-situ and may not be eco-
nomic to extract. A
reserve
is that fraction of a resource
that is demonstrated to be technically and economically
recoverable. Estimation of resources and reserves requires
the construction of long-term models (life of asset) for the
entire deposit, which are updated every 1-3 years of opera-
tion. Medium-term models may be built for planning one
to 6 months into the future. Short-term models are built for
weekly or day-to-day decisions related to grade control or
detailed planning.
