Abstract
Due to declining commodity prices in a constantly dynamic environment, there has always been a desire to maximize profits and achieve value from limited resources. Traditional experimental and numerical simulation techniques have failed to provide comprehensive and optimized solutions in a bit of time. With the enormous volume of data produced daily, a solution to meet the industry’s challenges was imminent. The various opinions of the expert are fraught with additional challenges to achieving timely and cost-effective solutions. Data analysis has contributed significantly to several areas. This chapter overviews the various applications of advanced data analysis and machine learning in mine exploration. After an introduction to exploring the geological features and genetic models of mineral deposits will be discussed. Later in this chapter, the role of advanced analytics in minerals prospecting and exploration will be explained. Finally, at the end of this section of advanced analytics in the mining engineering book, the details of mining geophysical and geochemical aspects when the analytics approaches are used will be described.
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Mehrali, S., Soofastaei, A. (2022). Advanced Analytics for Mine Exploration. In: Soofastaei, A. (eds) Advanced Analytics in Mining Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-91589-6_6
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DOI: https://doi.org/10.1007/978-3-030-91589-6_6
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