ESTIMATING MINERAL DISTRIBUTION USING MACHINE LEARNING MODELS
Estimating mineral distribution is important in mine planning. In this research, we studied how to apply tensor completion methods to estimate mineral distribution from partial observations. This includes how to map a partial observations as boreholes data format into tensor format, which problems should be considered to estimate mineral distributions, how to deal with these problems by modifying existing tensor completion methods. Our research showed capability to estimate mineral distributions from sparse and irregularly distributed observations.