Computer Applications in Exploration and Mining Geology: Ten Years of Progress

  • G. S. KochJr.
Part of the Computer Applications in the Earth Sciences book series (CAES)


Although many applications of computers to exploration and mining geology had been developed prior to 1969, their use and acceptance in mining was limited, even by the technologically advanced countries. Today, most mining companies and governmental agencies concerned with natural resources apply computers extensively.

During the decade, Matheron’s French geostatistics has undergone extensive theoretical expansion on the one hand, and reduction to understandable form, through several textbooks, on the other hand. Classical statistics for mining geology has been refined further as the result of many detailed applications with much feedback from industrial practice.

The manipulation by computer of large data bases has made possible a closer relationship between geology and mine systems analysis, and between geology and mining.

Whereas in 1969 the contribution of statistics and computers to geological exploration for mineral deposits was in its infancy, today these methods are used widely, although the most extensive applications are in the mining of known ore deposits. Particularly influential have been (1) the development of models for drillhole exploration and (2) operations research methods to conceptualize and organize exploration effort.

A significant step has been the development of many computer programs, some relatively large and complex, for the computer analysis of data from the mineral industry. Some of these programs are proprietary, but many have been published in technical journals.

Exploration geochemistry and geophysics grew at an explosive rate. Today, many computer applications have been made for the organization, display, and interpretation of these data.


Mineral Industry Porphyry Copper Mining Engineer Mining Geology Canada Paper 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Plenum Press, New York 1981

Authors and Affiliations

  • G. S. KochJr.
    • 1
  1. 1.University of GeorgiaUSA

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