admin    August 18, 2021    0


Computerized data management is one of the major developments in mineral exploration. The flow of large amount of data generated by modern instrumentation, as well as speeding up and improving decision making in mineral exploration can be achieve using computerized softwares (Moon and Whateley 2006). However mineral exploration data can be handled using either the Geographical Informations Systems (GIS) for early stage exploration data, or mining-specific packages designed to enable mine planning and resource calculations.

The first step in data integration is to put the data in an appropriate digital format. If the data are in paper form, they require conversion, a process known as digitization. Even if data are derived as output from digital instruments,
such as airborne magnetometers or down hole loggers, the data may need conversion to a different format. This data must be store in a particular format because computers do not know how to classify geological objects. The format is determined by the type, relationship, attributes, geometry, and quality of data objects (Bonham-Carter 1994). In all data types, two main components can be separated: (i) a spatial component dependent on location and (ii) an attribute component not dependent on location but linked to the spatial component by a unique identifier.

This presentation seeks to explain how mineral exploration data can be store in an appropriate format and how such data can be interpreted using softwares.



Flat file method is the simplest solution for data storage in which each point has associated x, y (and z) coordinates, as well as attributes. In this format (Table 1) attributes are stored in columns and rows, which are known as tuples. The features of this type of storage entails that: (i) all the data are represented in the table; (ii) any cell in the table must have a single value, replicate samples require additional tuples; (iii) no duplicate tuples are allowed; and (iv) tuples can be rearranged without changing the nature of the relation (Bonham-Carter 1994).

Table 1: An example of a flat file method for data storage

Latitudes Longitude Lithology Lith#
4⁰47’40.1” 009⁰25’53.8” Vesicular Basalts 5
4⁰47’20.4” 009⁰25’50.0” Vesicular Basalts 5
4⁰47’06.0” 009⁰25’55.3” Schist 2
4⁰47’01.7” 009⁰25’55.7” Gneiss 2
4⁰47’08.7” 009⁰25’48.9” Columnar Basalts 1
4⁰45’35.5” 009⁰26’22.6” Vesicular Basalts 5
4⁰46’41.2” 009⁰26’14.1” Schist 2
4⁰44’30.0” 009⁰25’30.0” Massive Basalts 3
4⁰45’47.3” 009⁰25’22.7” Porphyritic Basalts 2
4⁰45’13.2” 009⁰25’20.5” Vesicular Basalts 5
4⁰45’41.0” 009⁰29’21.2” Porphyritic Basalts 2
4⁰43’31.5” 009⁰29’13.7” Massive Basalts 3
4⁰45’39.5” 009⁰29’16.6” Vesicular Basalts 5
4⁰45’58.3” 009⁰28’54.0” Massive Basalts 3
4⁰49’28.0” 009⁰28’10.0” Gneiss 2


The flat file method is however an inefficient way to store data as a minor change, for example, a change to the name of a lithology in Table 1 requires a global search and change of all examples. However, data are more efficiently stored and edited in a relational database in which the data are stored as a series of tables linked by unique keys, such as sample numbers. In order for us to easily edit flat file data, we have to convert data into a relational database by a process known as normalization. That is, an attribute in our flat file format after normalization can be corrected with a single edit.

Corporate solutions

It is important that data are safely archived and made available to those who need them as easily as possible because large amount of money are invested in collecting data.

Data integrity is paramount for any mining or exploration company, both from a technical and legal viewpoint (acQuire 2004), although this has often been lacking in the past giving rise to inconsistencies of data, lost data, and errors in many organizations.

However, relational databases provide the means by which data can be stored with correct quality control procedures and retrieved in a secure environment.

Many registered 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 registered formats.

Company engagement in the collection and evaluation of data (Walters 1999) is vital in order to filtered out errors. In terms of ranges, values, and units every geologist and mining or processing engineer knows what the database should contain. In order to do this, a validation tables to check that the data conform to the ranges, values, and units expected is established. A simple example would be ensuring that the dip of drill holes is between 0 and −90 degrees for surface drilling.

The source and method of data entry as well as their format is essential during documentation for the database. The database should be flexible in that, it should be possible to add fields and columns to the database if need be in the later stage.
It is also essential that the data in the database can be evaluated, review and manipulated

A single, maintained, flexible and secure storage source is recommended. This means that only the most recent copy of the database is being used for evaluation at the mine site with older versions archived regularly. However, Paper and a hard copy remains the ultimate long-term storage for all important data sets.

Coordinate systems and projections

A coordinate system can be defined as a system that uses coordinates to established position. In the past, Geologists have generally managed to avoid dealing with different coordinate systems in any detail, since they were dealing with small areas. However, the advent of GPS and computerized data management has
changed this. When real world data are plotted on a flat surface, it 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 flattened sphere. The choice of projection is governed by the scale of the data. For maps of scales larger than 1:250,000, either a national grid or a Universal Transverse Mercator (UTM) grid is generally used. Coordinate reference system is related to the real world by a datum and the most commonly used datum for GPS work is World Geodetic System (WGS 1984).


Most field data are now generated in digital form but any data only available on paper will require digitization.

  • Field data capture

Using computers that can be easily transported for data Capturing in the field
is becoming a routine. Now our days, this approach is widely used for routine tasks such as sample collection and core logging but is less well suited to geological mapping. Nonetheless, this situation is changing rapidly with the arrival of inexpensive portable digital assistants using a stylus for input and
better quality displays.

  • Digitization
    Spatial data are usually digitized either by scanning a map or by using a digitizing table. In the digitizing table method, a point or line is entered by tracing the position of a puck over it relative to fine wires within the table. The position of the point or line is then converted by software into the original map coordinates
    from the position measured on the table. Tracing lines is very strenuous and maps often have to be simplified or linework traced to avoid confusion during the digitizing process. The scanning method has become much easier with the advent of inexpensive scanners. In this method a georeferenced image is traced on a
    computer screen using a mouse or puck. When the map or scan has been digitized all line work are carefully edited. Generally, this editing is strenuous and more prone to errors than the original digitization. Below is an example of a digitized map.


Figure 1: An example of a digitized map


Attribute data

Attribute data can be captured by typing and written data or by scanning data that is already type written and relatively clean. The scanned images are then converted into characters for storage using optical character recognition software. This software is however not perfect and the resulting characters should be carefully
checked for errors.



The ability to integrate data easily has been one of the major developments in technology at the early exploration stage which is driven by the development of Geographical Information Systems (GIS). GIS is a system of hardware, software and procedures to facilitate the management, manipulation, analysis, modeling, representation and display of georeferenced data to solve complex problems regards planning and management of resources (NCGIA 1990).


GIS is a tool that has the potential to help us manage, analyze and display spartial information on a computer. Although we can store data using GIS, its main function is to allow the easy integration of data and output, usually in the form of maps (Longley et al. 1999, 2001). Its development has been designed for a wide range of applications involving spatial data, including monitoring the spread of disease, but the generic commercial systems are applicable (with limitations) to mineral exploration data.


ArcView and ArcGIS (ESRI) are the dominant commercial systems and they have wide use in geological applications. Current commercial systems allow the display of both vector and raster data with varying degrees of querying and modeling facilities. These systems are well suited to 2D data but, at the time of writing,
only partly usable for 3D drill data including drill holes and underground sampling.
In addition to the complex (and expensive) full blown GIS systems there are a number of simpler software packages, such as Geosoft, Interdex, and Micromine, specifically designed for mineral exploration.



Specialized computer package (or packages) that deals with 3D data are used in most reserve calculations performed in exploration, feasibility studies, or in routine mine grade control and scheduling. At the early stages of exploration, the key features of the package will be to input drill information and relate this to surface features.

In order for us to calculate our reserve, it is very important for the package that we are using to have the ability to model the shape of geological units and calculate volumes and tonnages. Subsequently in feasibility studies the capacity to design underground or surface workings and schedule production is essential. However, when chosen a package we take into consideration the
finance available and the nature of the operation, as there are packages specifically designed for both open cut and underground mining.

Another crucial issue is the selection of the technical software. However, our previous exposure to and familiarity with the software will play an important role in the selection of such software. Unfortunately software is rarely selected for the relevance to the operation of the functions that it provides since they have their advantages and disadvantages. The selected geological and mine modeling software that suits the budget, geological and mining complexity of most operations are Surpac and Minex from the Surpac Minex Group, Maptek’s Vulcan, Mincom, Datamine, Mintec’s MineSight, and Gemcom.