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| Titel |
Integrate metalogenic database with GIS geological project (deposite Au-Ag Far East Russia). WEB-GIS approach. |
| VerfasserIn |
Evgeniy Kucharenko, Alex Asavin |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250105370
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| Publikation (Nr.) |
 EGU/EGU2015-4891.pdf |
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| Zusammenfassung |
| Resource depletion has forced us to search for new ore deposit and reanalyze old mineral
deposits. This is the main aim of metallogenic studies. Synthesis information about
features resources work out deposit and emerging fields will play a key role in future.
Development of metallogeny databases is one of the most difficult tasks for Earth
sciences.
Database needs to enter a large number of parameters describing the object of study -
mine or ore occurrence. Majority of these parameters belong to different areas of
geological knowledge. It can be ore mineralogy, geochemistry, lithology of host rocks,
tectonic characteristics ore-controlling structures, geochemical parameters of ore
processes, geochronological data on age of geological formations and processes of ore
formation and some others. However, the cartographic materials of various scales apart
from diverse documentation and numerical information are of a great importance.
The adopted framework for the analysis of large-scale metallogeny has several
levels:
1. The ore body (usually 1: 50000, 1: 100000)
2. The ore field, the field (1: 200000)
3. The ore cluster (1: 500000)
Researchers can vary scheme and scale values, but fundamentally three levels of scale
describing the location and geological structures controlling the placement of ore are
included at least. Attention should be pay to the system of description the ore deposit. It is
necessary to create the universal scheme for development of metallogeny information
systems and set up the universal algorithm of ore deposit description. There is its own order
of importance of used features and a form of description for each type of deposits and ore
and genetic group and ore element. Lack of definition in the classification of a
particular metallogenic object makes the choice of algorithm description justified quite
weakly.
It is quite notable that available features which used for description of different deposit
(even of the same genetic group) are not of the same type or detailed enough. Waste deposit
usually takes as a reference object with the most complete description in opposite to
the recently discovered deposit not enough studied and with quite limited list of
information indicators. There are following most actual tasks for information metallogeny
system:
1. Search summarizing the characteristics of different objects
2. Select the most informative group of features
3. Show the links of groups of signs and analyze it as far as genesis of deposits.
The actual task’s list could be continued but it is enough to start. Essentially mentioned
problems put us in a situation when deposit’s metallogenic database is not available. There is
only limited number of typical databases (for certain types of minerals) characterized nothing
more than name of the fields and basic indicators of its economic importance (stocks,
component content, ore types). The additional information: the age of host rock or ores or
geochemistry features of some geological objects uses quite rarely. There is no systematic
data for all objects in the database.
Database of carbonatite deposits is the most well-developed. It should be also mentioned
some works [Woolley & Kjarsgaard 2009; Bagdasarov et al.,2001; Burmistrov et al., 2008].
Unfortunately, such important characteristics as geological maps are not included there as |
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