TECHNOLOGY OF REMOTE SENSING DATA FREQUENCY-RESONANCE PROCESSING AND INTERPRETATION: THE RESULTS OF TESTING AND PROSPECTS FOR THEIR FURTHER APPLICATION IN ORE MINERALS PROSPECTING AND EXPLORATION

Purpose. The purpose of the article is to analyze the results of experimental testing and practical application of the mobile direct prospecting technology of the remote sensing (RS) data frequency-resonance processing and interpretation (decoding) for “direct” searches of various types minerals on ore deposits and prospective areas. Exploratory studies conducted with its application within ore bearing areas in the Republic of Kazakhstan, Ukraine, Cameroon, Sudan and Canada. Design/methodology/approach. Experiments carried out with the mobile technology of frequency-resonance processing and interpretation of remote sensing data using, which is the “direct” method of minerals and oil and gas exploration and operates within the “substantial” paradigm of geophysical investigations. The technologies and methods developed on the principles of this paradigm are aimed at searching a particular (desired in each case) substance ? gold, silver, copper, lead, zinc, uranium, oil, gas, condensate, etc. Findings. The anomalous zones of the “zones of ore (gold-bearing) mineralization” type detected and mapped within the investigated areas and ore deposits. Many of the found anomalous zones of the “zone of gold mineralization” type were certified by the detailed geological and geophysical works and drilling. It is shown that for small objects (lodes) detection and mapping the remote sensing data processing should be carried out in a large scale ? 1 : 2000 and larger. At the local prospecting area within the famous Klondike Gold Fields, the materials of remote sensing data processing and interpretation compared with the results of the investigation by conventional geophysical and geochemical methods. Practical value/implications. This direct prospecting technology inclusion in the traditional complex of exploratory geological and geophysical methods will contribute both to minimizing the financial cost for particular exploration problem solving and to reducing significantly the time to implement them.