Abstract
The application of certain research methods to determine the potential of the area for certain types of minerals requires specialty software that must be compatible with common types of data and supported by major operating systems, as well as have a simple graphical interface for comfortable work of a wide range of users. In addition to research tools, the software program should have the ability to save results in common file formats. The method of base erosion surfaces is based on topographic computation using a detected erosion network. It facilitates outlining of the local zones of Neotectonic movements and computing of their amplitudes. The compiled maps of different order base erosion surfaces and their differences enable the buried intrusions of potentially ore bearing nature and placer sources to be revealed. The paper examines the ENOE 0.6a software and its application to the analysis of ore-bearing structures of the Sikhote-Alin mobile belt using as an example gold placers in the zone adjacent to the Bekchiul multiphase pluton that hosts the large Mnogovershinnoe gold-silver deposit. ENOE allowed us to combine datasets describing Neotectonic processes and development of the erosion network. Based on the obtained datasets, geological data included, a predictive machine learning model developed by the maximum entropy method was trained and tested which made it possible to delineate the known hard-rock and placer targets. Model validation and testing have shown its applicability for preliminary territory analysis.
Published Version
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