Dedicated to all mining students; BY Wajid Hussain UET Peshawar

1. Definitions
• Ore minerals: Naturally occurring compounds valued for their
metal content that needs further processing and refining.
• Industrial minerals: Compounds or elements used for their
own specific physical/chemical properties.
• Energy minerals: Coal, oil and gas
• Incremental ore: The portion of ore that must be drilled,
blasted and moved in the course of mining “bonafide ore” but
contains sufficient value to pay the incremental costs
(difference between delivery to the waste are, the feed bin,
stockpile pad or crusher and cost of crushing, processing,
royalties etc) for itself and provide some profit as well.

2. • Deposit: for the purpose of this document means: “a natural
occurrence of mineral or mineral aggregate, in such quantity
and quality to invite exploitation”.
• Classification and Categorization: “a mineral deposit may be
subdivided into two Classes, Mineral Resources and Mineral
Reserves. Each of these Classes may be subdivided into
Categories: Measured, Indicated and Inferred in the case of
Mineral Resources and Proven and Probable in the case of
Mineral Reserves”.
• Uncertainty: Imprecision or inaccuracy, expressing the
deviation of measurements from the true value.

3. • Resource: An in situ mineral occurrence quantified on the
basis of geologic data and a geologic cutoff grade only.
• Reserve: If the study of technical and economic criteria and
data relating to the resource has been carried out and stated
in terms of mineable tons of reserve or volume and grade.
• Selective mining unit (SMU): The smallest block on which
selection as ore or waste is commonly made.
• Grade-tonnage curve: As the cutoff grade increases, the
tonnage of ore decreases and the average grade of that
tonnage increases.
• Geological cutoff grade: A subjective quantity that define the
boundary of mineralization in an ore body.
• Anisotropic geology: When a particular geologic characteristic
is directional in nature, and differ in their character as a
function of direction in the space.

4. • Linear estimation: It uses a linear combination of surrounding sampled
values to make predictions.
• Cross correlation: Correlation between the paired values of two
different variables, the paired values being separated in either time or
space.
• Bias: A systematic favouritism that is present in the data collection
process resulting in misleading results.
• Support: The mass shape and orientation of the sample volume that is
sub sampled for assaying.
• Error of Estimation: Errors of extensions made in extending the grades
of samples to a much larger volume of rock. The estimation must be
unbiased and random error must not exceed an acceptable quality
criterion.
• Global estimation: Average grade and tonnage of very large volume of
a deposit, represents a justification for long term production planning.
• Local estimation: Estimation of average grade values for each block in
an array. commonly used for short term planning and medium range
production planning both at feasibility stage and in operating mines.

5. • Block: A single entity in a discretized array of
fixed dimension and volume in a given
geological model of a mineral deposit.
• Geologic continuity: Spatial continuity in
physical occurrence of geologic features e.g.
vein that control mineralization.
• Domain: A geologic domain is a spatial entity
that represents a well defined mineralized
body.

6. • Frequency Distribution: Important characteristics of large
mass of data can be readily assessed by grouping the data
into different classes and then determining the number of
observations that fall in each class. Such an arrangement in
tabular form is called frequency distribution.
• Histogram: A graph showing the frequency of a variable
within contiguous value intervals (commonly a uniform class
interval) that extend over the range of the variable.
• Continuous distribution: Continuous distributions are used to
describe data and it may be useful to fit such a distribution to
a histogram. Probability density function (PDFs) are
mathematical models used to describe the probability that
random draws from populations defined by the function
meets particular specifications (i.e. above or below a certain
value, quantile).

7. • Normal distribution: Normal or Gaussian probability density
function is the common bell shaped curve, symmetric about
the mean value.
• Distribution parameters: The parameters that define a certain
continuous distribution function are called the distribution
parameters for that distribution.
• Accuracy: Nearness to the truth
• Precision: Measure of reproducibility of a result by repeated
attempts.
• Isotropic geology: When a particular geologic character
persists in much the same manner in all directions within a
domain, a geological feature is isotropic.
• Cut off grade: A grade below which the value of the contained
metal/mineral in a volume of rock does not meet certain
specified economic requirements.

8. • Estimation: Quantification of naturally occurring materials,
estimated by a variety of empirically or theoretically based
procedures. As a verb estimation is “to judge or approximate
the value, worth, or significance of; to determine the size,
extent, or nature of”. As a noun “an approximate calculation;
a numerical value obtained from a statistical sample and
assigned to a population parameter”.

9. • Models: Representation of Some Phenomenon that often
describe relationships between variables
• Deterministic Models: Hypothesize Exact Relationships.
Suitable When Prediction Error is Negligible. Example: Force
Is Exactly = m·a
• Probabilistic Models: Hypothesize 2 Components
Deterministic and Random Error Example: Sales Volume Is 10
Times Advertising Spending + Random
Error =Y = 10X + e i.e. Random Error May Be Due to Factors
Other Than Advertising
• Nonlinear estimation: Instead of using linear combinations of
the data, linear combinations of _functions_ of the data are
used.

10. • Correlation: The measure of similarity between variables.
• Autocorrelation: Correlation between the paired values of a
variable, or correlation of the variable with itself, the paired
values being separated in either time or space.
• Dispersion: The measures of spread of data values e.g. range,
variance.

11. • Compositing: Combining raw samples from a variety of
supports in such a way as to produce combinations of such
samples in order to obtain samples of approximately uniform
support is called compositing. Specimen: Specimens are
preferentially selected by geologists to exemplify particular
features of mineralogy, texture, structure or geologic
relations and are unlikely to be representative of ore grades
in much larger volumes.

12. • Statistical Sample: n individual values combine to make a
sample (n items) of a deposit.
• Mining sample: A physical quantity of rock material,
representative fraction of which can be analyzed to produce
numeric measures of quality (e.g. grades)
• Continuity: The state of being connected or unbroken in
space

13. • Value continuity: Value continuity can be defined as
the continuous mineralization within the part of the
continuous geologic feature e.g. ore shoot that is
mineralized with economically important minerals.
• A measure of the spatial character of grades, mineral
abundances, vein thickness or some other value
measure throughout a specific domain.

14. • Sampling patterns: The spatial layout of the sampling scheme.
• Representative Sample: A sample having minimum bias and
random error. How well a given assay value represent a mass
being estimated. A representative sample for each sampling
scheme depends upon different factors like the size of
individual sample, the number of individual samples, and the
sampling pattern.
• Sample reduction: Procedures used to extract a much smaller
representative amount for actual analysis from a large sample
volume. Series of alternating particle size reduction and mass
reduction steps are involved in sample reduction.

15. • Salting: Surreptitious introduction of material into
samples.
• Univariate procedures for data evaluation:
Histogram, probability plots
• Outlier: An observation that appears to be
inconsistent to the vast majority of data values.
• Dilution: Mixing of non-ore-grade material with ore-
grade material during production, generally leading
to increase in tonnage and decrease in mean grade
relative to original expectation.