Geochemistry in Diamond exploratiom

Although diamond exploration usually relies
on a combination of methods, geochemical
techniques (in the broad sense) have been
very successful in detecting diamondiferous
pipes. A number of distinctive, dense minerals
 are associated with
kimberlites and lamproites and it is these
minerals that have been used to indicate the
locations of pipes, hence their name indicator
(or, in translation from Russian, satellite) minerals.
The chemistry of some of these minerals
also indicates their sources and transport history
and, by comparison with known deposits,
can be used to predict whether the source is
diamondiferous as well as some indication of
grade.
The indicator minerals used since the late
nineteenth century and
garnet (both pyrope and eclogitic), chrome diopside,
chromite, and picro (Mg-rich) ilmenite
(Gurney & Zweistra 1995, Muggeridge 1995).

Typical indicator
minerals. Minerals from top left,
clockwise: picro-ilmenites,
ecologitic garnets (G3), chrome
pyrope garnets (G9/G10),
chromites, chrome diopsides,
chrome Fe-titanium pyrope
garnets (G1/G2), olivines. (With
permission from SRC Vancouver.)

Selection of Mining Method

The hard massive marlstone which forms
the overburden will require blasting before
removal can take place and this rules out the
use of a dragline or a bucket wheel excavator.
Rear-dump trucks and face shovels will have to
be used. Three alternative mining configurations
may be considered using this equipment:
(i) advance down the dip;
(ii) advance up the dip; or
(iii) advance along the strike.
The third method, also known as terrace mining, was
considered the most suitable with the particular
geological and geotechnical conditions
which exist at Soma.
Following this method a box-cut would be
excavated down the full dip of the deposit from
the outcrop until an economic stripping limit,
or practical mining depth limit, is reached.
This study concluded that a maximum mining
depth of 150 m was feasible, although constraints
were generally related to the geological
configuration and consideration of maintaining
footwall stability, rather than to stripping
ratio economics. Advance could then be in one

or both directions along the strike line, depending
on the box-cut location within the proposed
mining area. Waste disposal within the excavation
is practical (and usually desirable) as the
box-cut excavation is enlarged. Horizontal
benches would be formed in the overburden
along the advancing face and along the
highwall formed on the deep side of the excavation.
As much spoil as possible from the
advancing face would be removed along the
highwall benches for disposal to form an internal
spoil dump within the excavation and
behind the advancing face; the remainder having
to be dumped outside the pit. The front
of the spoil dump and the advancing face then
advance in unison as mining continues along
the strike of the deposit. The final
highwall is expected to have a maximum slope
angle of 45 degrees.
The application of this mining method will
bring several advantages:
(i) a minimum area of footwall clay will be uncovered at any time, thus reducing the risk of footwall failure; (ii) internal dumping of waste reduces transport costs, helps stabilize the footwall, and begins reclamation at an early stage of mining; and
(iii) the stripping ratio is more or less constant over the life of the mine, and hence the mining costs

are stabilized.

Lignite Quality : Under Ground Mining Options

The areas down dip of the 7:1 stripping ratio
line defined that part of the basin that could be
potentially mined by underground methods.
Within this area it was possible to calculate the
average in situ lignite quality and the mineable
lignite quality values.


13.7 LIGNITE RESERVE ESTIMATES :-
           The lignite reserves were calculated by assessing
the data provided from borehole logs
(Whateley 1992) obtained by drilling,
within the limits of the open pit. These
limits were established between the outcrop
line and the 7:1 stripping ratio line. On the
northwest and the east sides of the pit, the
limit is determined at the depositional edge of
the seam. This limit was determined by using
the basement and basal KM2 structure contour
maps. The pit outline was
placed on the isopach map of the total vertical
thickness of the KM2 seam, and the area between
each isopach was measured with the aid
of a planimeter. The areas
were multiplied by the average vertical thickness
between the isopach lines (the thickness
value at the midpoint) to obtain the in situ
volume. The volume was multiplied by the
average specific gravity to obtain the in situ
tonnage.
The mineable lignite tonnage was calculated
from the in situ tonnage by applying a recovery
factor, examples of which are given in the final
row of Table 13.4. The weighted average recovery
for the open pit is 91%, but this varies from
as low as 45% in borehole 208 to 100% in many
of the remaining holes. The recoveries of mineable
lignite from the total lignite will change
during mining depending on the local geology.
Development drilling immediately in advance
of production will determine these recoveries.
The reserve figures were calculated as follows:
in situ reserves 49.4 Mt, mineable reserves
40.6 Mt, and kriged estimate of in situ reserves
46.3 Mt (Lebrun 1987).

Lignite Quality : Surface Mining Options

Once the limits of the potential open pit had
been established using the outcrop line and the
stripping ratio limit down dip, it was possible
to calculate the average quality of the in situ
and the mineable lignite. The weighted average
quality data. The in
situ lignite quality includes small areas of
lignite which may be included in the lignite
resource of the basin but were considered to be
inaccessible to open pit mining. All the analyses
were reported on an as-received basis. The
air-dried moisture content was calculated for
several of the lignite samples from the final
series of holes. The results showed that the inherent
moisture (air dried) was approximately
8% and the surface moisture was approximately
7%, totalling 15% on an as-received
basis. The moisture content does not precisely
represent that of the mined lignite because

of the presence of drilling fluid in the core
samples and also the additional moisture that
would be picked up during mining.
The sulfur content of the KM2 seam was
analyzed in a few cases. The results indicate
that the KM2 is a low sulfur lignite. The
weighted average is as follows: combustible
sulfur 0.53% and sulfur in the ash 0.42%, giving
a total sulfur at 0.95%.

Under Ground Mining options

This section has been included to show that
different mining methods require different
selection criteria. During the study, alternative
underground mining methods suitable for the
extraction of a medium-dipping, thick seam,
were examined. In-seam mining (a) and crossseam
(b) mining were considered.
As a computer database was being used, it was
possible to try sensitivity analyses on the various
selection criteria. These were used to assist
in the selection of the best mining methods
and in the calculation of the ROM tonnages
and qualities. The weighted average quality
of the in situ and mineable lignite was calculated
using tabulated data examples.

In-seam mining :-
        The mineable lignite was determined once
waste partings (material with >55% ash content
and/or <1800 kcal kg−1) greater than 1.5 m
thick were rejected. Occasionally thin lignite
beds within the thick waste partings were also
rejected. The top and bottom of the in situ and
mineable lignite are the same. It was assumed
that there would be a 100% recovery of the lignite
in the longwall slice, and 60% recovery of
lignite and 40% dilution by waste in the caved
zones above the longwall zones. The mineable
quality takes into account the lignite losses
and waste dilution which would occur during
caving. It was considered that selective mining
could be implemented above and below a waste
parting greater than 1.5 m thick.

Cross-seam mining :-
         The mineable lignite was determined once the
top and bottom waste material were excluded.
As this method is less selective, dilution of the
lignite is inevitable. This is accounted for by
expecting a 60% recovery of lignite and a 40%
dilution by waste.

Drilling

Augar Drilling :-

                   Augers are hand-held or truck-mounted 
drills,which have rods with spiral flights to bring soft

material to the surface. They are used particularly

to sample placer deposits. Power augers

are particularly useful for deep sampling in

easily penetrable material where pitting is not

practicable (Barrett 1987). They vary in size

from those used to dig fence post holes to large,

truck-mounted rigs capable of reaching depths

of up to 60 m, but depths of less than 30 m are

more common. Hole diameters are from 5 to

15 cm in the larger units, although holes 1 m

in diameter were drilled to evaluate the Argyle

diamond deposit in Australia. In soft ground

augering is rapid and sampling procedures need

to be well organized to cope with the material

continuously brought to the surface by the

spiralling action of the auger. Considerable care

is required to minimize cross-contamination

between samples. Augers are light drills and are

incapable of penetrating either hard ground or

boulders. For this purpose, and holes deeper

than about 60 m, heavier equipment is necessary

and this is described in the next section.



Drilling Other :-
          For anyone interested in understanding the

subsurface, drilling is the most frequently used

technology. The various methods of drilling

serve different purposes at various stages of

an exploration program (Annels 1991). The

Australian Drilling Industry Training Committee

(1997) gives a comprehensive account of

methods, applications, and safety issues. Early

on when budgets are low, inexpensive drilling is

required. The disadvantage of cheaper methods,

such as augering, rotary or percussion drilling,

is that the quality of sampling is poor with considerable

mixing of different levels in the hole.

Later, more expensive, but quality samples are

usually collected using reverse circulation or

diamond core drilling

Pitting & Trenching

In areas where soil cover is thin, the location

and testing of bedrock mineralisation is made

relatively straightforward by the examination

and sampling of outcrops. However in locations

of thick cover such testing may involve

a deep sampling program by pitting, trenching,

or drilling. Pitting to depths of up to 30 m is

feasible and, with trenching, forms the simplest

and least expensive method of deep sampling

but is much more costly below the water table.

For safety purposes, all pits and trenches are

filled in when evaluation work is completed.

Drilling penetrates to greater depth but is more

expensive and requires specialized equipment

and expertise that may be supplied by a contractor.

Despite their relatively shallow depth,

pits and trenches have some distinct advantages

over drilling in that detailed geological

logging can be carried out, and large and, if

necessary, undisturbed samples collected.



1) Pitting :-
            In areas where the ground is wet, or labor is

expensive, pits are best dug with a mechanical

excavator. Pits dug to depths of 3–4 m are common

and with large equipment excavation to

6 m can be achieved. In wet, soft ground any pit

deeper than 1 m is dangerous and boarding

must be used. Diggers excavate rapidly and pits

3–4 m deep can be dug, logged, sampled, and

re-filled within an hour. In tropical regions,

thick lateritic soil forms ideal conditions for

pitting and, provided the soil is dry, vertical

pits to 30 m depth can be safely excavated. Two

laborers are used and with a 1 m square pit,

using simple local equipment, advances of up

to 2 m per day down to 10 m depth are possible,

with half that rate for depths from 10 to 20 m,

and half again to 30 m depth.



2) Trenchimg :-
           Trenching is usually completed at right angles

to the general strike to test and sample over

long lengths, as across a mineralized zone.

Excavation can be either by hand, mechanical

digger, or by bulldozer on sloping ground.

Excavated depths of up to 4 m are common.

Co-ordinate systems & projections

Geologists have in the past generally managed

to avoid dealing with different coordinate

systems in any detail, as the areas they were

dealing with were small. The advent of GPS

and computerized data management has

changed this. The plotting of real world data on

a flat surface is known as projection and is the

result of the need to visualize data as a flat

surface when the shape of the earth is best

approximated by a spheroid, a flattened sphere.

For small areas the distortion is not important

but for larger areas there will be a compromise

between preserving area and distance relationships.

For example, the well-known Mercator

projection emphasizes Europe at the expense of

Africa. The scale of the data also governs the

choice of projection. For maps of scales larger

than 1:250,000, either a national grid or a

Universal Transverse Mercator (UTM) grid is

generally used. In the latter projection, the

earth is divided into segments of 6 degrees

longitude with a value of 500,000 m E given to

the central meridian of longitude and a northing

origin of 0 m at the equator, if north of the

equator, or large number, often 10,000,000 m,

if south of the equator.

There are a variety of different values in use

for the ellipsoid that approximates the shape

of the earth, known as the datum. The most

commonly used datum for GPS work is World

Geodetic System (WGS 1984) but the datum

used on the map must be carefully checked,

as the use of different datums can change coordinates

by up to 1500 m. The reader is advised

to read about the problems in more detail in

texts such as Longley et al. (2001) and Snyder

(1987).

Corporate solutions

As large amounts of money are invested in collecting

the data, it is crucial that the data are

safely archived and made available to those

who need them as easily as possible. Integrity

of data is paramount for any mining or exploration

company, both from a technical and

legal viewpoint (acQuire 2004). However this

integrity has often been lacking in the past and

many organizations have had poor systems

giving rise to inconsistencies, lost data, and

errors. Increasingly, in the wake of incidents

such as the Bre-X fraud (see section 5.4), both

industry and government departments require

higher levels of reporting standards. Relational

databases provide the means by which data can

be stored with correct quality control procedures

and retrieved in a secure environment.

Many proprietary technical software products

provide such storage facilities, for example

acQuire (acQuire 2004) provides such a solution

for storage and reporting of data that also

interfaces with files in text formats such as csv,

dif, txt (tab delimited and fixed width formats),

as well as numerous proprietary formats.

The strategy for collection and evaluation

(checking) of data (Walters 1999) is often a matter

of company procedure. Most errors are gross−90

and can be easily filtered out. Each geologist

and mining or processing engineer knows what

the database should contain in terms of ranges,

values, and units. It is a simple matter of setting

up the validation tables to check that the

data conform to the ranges, values, and units

expected. A simple example would be ensuring

that the dip of drillholes is between 0 and

degrees for surface drilling.

Data Capture & Storage

There are two major methods of representing

spatial data, raster and vector. In the vector

model the spatial element of the data is represented

by a series of coordinates, whereas in the

raster model space is divided into regular pixels,

usually square. Each model has advantages and

disadvantages summarized but the

key factors in deciding on a format are resolution

and amount of storage required. A simple geological map in vector and

raster format. The raster method is commonly

used for remote sensing and discussed, whereas the vector method is used

for drillholes and geological mapping. Most

modern systems allow for integration of the

two different types as well as conversion from

one model to another, although raster to vector

conversion is much more difficult than that

from vector to raster.

In a simple (two-dimensional) vector model,

points are represented by

lines as a series of connected points (known as

vertices), and polygons as a series of connected

lines or strings. This simple model for polygons

is known as a spaghetti model and is that

adopted by computer aided drawing (CAD)

packages. For more complex querying and

modeling of polygons, the relationship between

adjoining polygons must be established and

the entire space of the study area subdivided.

This is known as the topological model. In this

model, polygons are formed by the use of

software as a mesh of lines, often known as

arcs, that meet at nodes. Another variation of

this model often used for height data is that of

the triangular irregular networks (TIN) and is

used to visualize digital elevation surfaces or

construct digital terrain models (DTM). The

TIN model is similar to the polygons used in

ore resource and reserve calculationx and y coordinates,

Introduction

One of the major developments in mineral

exploration has been the increased use of computerized

data management. This has been used

to handle the flow of the large amounts of data

generated by modern instrumentation as well

as to speed up and improve decision making.

This chapter details some of the techniques

used to integrate data sets and to visualize this

integration. Two types of computer packages

have evolved to handle exploration and development

data: (i) Geographical Informations

Systems (GIS) for early stage exploration data,

usually generic software developed for other

nongeologic applications, discussed in section

DATA INTEGRATION AND GEOGRAPHICAL

INFORMATION SYSTEMS

to enable mine planning and resource calculations,

discussed in section .

INTEGRATION WITH RESOURCE

CALCULATION AND MINE PLANNING

SOFTWARE

What must be emphasized is that the quality

of data is all important. The old adage “rubbish

in and rubbish out” unfortunately still applies.

It is essential that all data should be carefully

checked before interpretation, and the best

times to do this are during entry of the data into

the database and when the data are collected.

A clear record should also be maintained of

the origin of the data and when and who edited

the data. These data about data are known as

metadata., and (ii) mining-specific packages designed