Page 196 - Introduction to Mineral Exploration

9

Mineral Exploration Data

Charles J. Moon and Michael K.G. Whateley

One of the major developments in mineral process known as digitization. Even if data
exploration has been the increased use of com- are derived as output from digital instruments,
puterized data management. This has been used such as airborne magnetometers or downhole
to handle the flow of the large amounts of data loggers, the data may need conversion to a
generated by modern instrumentation as well different format.
as to speed up and improve decision making. Computers do not know how to classify geo-
This chapter details some of the techniques logical objects so a format for storing data must
used to integrate data sets and to visualize this be defined. This format will be determined by
integration. Two types of computer packages the type, relationship, attributes, geometry,
have evolved to handle exploration and devel- and quality of data objects (for further details
opment data: (i) Geographical Informations see Bonham-Carter 1994). An example of
Systems (GIS) for early stage exploration data, simple geological map data based on Fig. 9.1
usually generic software developed for other is: (i) type – geological unit; (ii) relationship –
nongeologic applications, discussed in section contacts; (iii) attributes – age, lithology; (iv)
9.2, and (ii) mining-specific packages designed shape – polygon. Two main components can be
to enable mine planning and resource calcula- separated out for all data types: (i) a spatial
tions, discussed in section 9.3. component dependent on location (e.g. sample
What must be emphasized is that the quality location for a point sample with x, y ± z com-
of data is all important. The old adage “rubbish ponents); and (ii) an attribute component not
in and rubbish out” unfortunately still applies. dependent on location but linked to the spatial
It is essential that all data should be carefully component by a unique identifier (e.g. sample
checked before interpretation, and the best number or drillhole number and depth). Figure
times to do this are during entry of the data into 9.1 shows typical geological objects with differ-
the database and when the data are collected. ing dimensions: lithological units as polygons,
A clear record should also be maintained of samples as points, faults as lines, structures
the origin of the data and when and who edited as points with orientation, drillholes as points
the data. These data about data are known as (vertical) or lines (inclined).
metadata.
9.1.2 Spatial data models
9.1 DATA CAPTURE AND STORAGE There are two major methods of representing
spatial data, raster and vector. In the vector
model the spatial element of the data is repres-
9.1.1 Theory
ented by a series of coordinates, whereas in the
In order to integrate data, they must be avail- raster model space is divided into regular pixels,
able in an appropriate digital form. If the data usually square. Each model has advantages and
are in paper form they require conversion, a disadvantages summarized in Table 9.1 but the