Masters Theses

Title

A microcomputer geostatistical analysis program for optimal drift location

Abstract

"The use of geostatistics is rapidly becoming common in the mining industry. Ore reserve estimation by use of geostatistical analysis is one of the major estimation techniques available. However, the geostatistical method is elaborate and not easily understood. Because of the complexity of the geostatistical analysis process, computers are employed to carry out the many matrix calculations. Primarily, the available geostatistical programs have been written for and applied on mainframe or mini-computers. This work develops a geostatistical analysis program for an Apple Ile microcomputer. The programs were developed within the limitations of an eight-bit CPU and 64K RAM. The programs can operate with a maximum of 1,000 initial data points and provide kriging results for a 12,800 point grid. Development of the results can be accomplished in approximately 30 hours. Additional to the geostatistical aspects of this work, programs are included to determine optimal drift locations and to provide graphical representations of results. Optimal drift location is based upon maximum ore grade. The elementary graphical routines provide the capability to create plan view maps of the original drill hole data, create graphical representations of the kriging results and create three-dimensional perspectives of the optimal drift locations"--Abstract, leaf ii.

Advisor(s)

Haas, Charles J.

Committee Member(s)

Summers, David A.
Carr, James R.

Department(s)

Mining and Nuclear Engineering

Degree Name

M.S. in Mining Engineering

Sponsor(s)

Rochester & Pittsburgh Coal Company

Publisher

University of Missouri--Rolla

Publication Date

1984

Pagination

ix, 214 leaves

Note about bibliography

Includes bibliographical references (leaves 122-124).

Rights

© 1984 Neal Borden Nagel, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Geology -- Statistical methods
Mines and mineral resources -- Statistical methods

Thesis Number

T 5109

Print OCLC #

11299511

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu:80/record=b2693328~S5

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