Titlebook: Geostatistics Toronto 2021; Quantitative Geology Sebastian Alejandro Avalos Sotomayor,Julian M. Ort Conference proceedings‘‘‘‘‘‘‘‘ 2023 The

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Methodology for Defining the Optimal Drilling Grid in a Laterite Nickel Deposit Based on a Conditiont and proposes a methodology to address the issue of optimising the drilling grid based on uncertainty derived from Gaussian conditional geostatistical simulations. The usefulness of the proposed workflow is demonstrated in terms of saving time and money when selecting a drill hole grid.

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LSTM-Based Deep Learning Method for Automated Detection of Geophysical Signatures in Mininghigh accuracy using gamma sequences with and without added noise. Further, no feature extraction or selection is performed in this work. Hence, LSTM can be used to detect different signatures in natural gamma logs even with noise. So, this system can be introduced in mining as an aid for geoscientists.

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Spectral Simulation of?Gaussian Vector Random Fields on?the?Sphere parsimonious in terms of computation time and memory storage requirements. This work presents two such algorithms that rely on the spectral representation of isotropic covariances on the sphere. Both algorithms are illustrated with synthetic examples.

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https://doi.org/10.1007/978-3-8349-8975-8MUC panel-specific grade-tonnage curves while preserving the spatial grade distribution at the selective mining level. However, LMUC results have two severe artifacts. This paper documents both artifacts using four grades from a large nickel–cobalt laterite deposit in Western Australia.

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