Geostatistical modeling of the geological uncertainty in an iron ore deposit

N Mery, X Emery, A Cáceres, D Ribeiro, E Cunha - Ore Geology Reviews, 2017 - Elsevier
This paper addresses the problem of quantifying the joint uncertainty in the grades of
elements of interest (iron, silica, manganese, phosphorus and alumina), loss on ignition …

[图书][B] Plurigaussian simulations in geosciences

M Armstrong, A Galli, H Beucher, G Loc'h, D Renard… - 2011 - books.google.com
Simulation is the fastest developing branch of geostatistics and simulating facies inside
reservoirs and orebodies is the most exciting part of this. Several methods have been …

[图书][B] Geostatistics for the mining industry: applications to porphyry copper deposits

X Emery, SA Séguret - 2020 - taylorfrancis.com
This book covers the main mining issues where geostatistics, a discipline founded in the
1960s to study regionalized variables measured at a limited number of points in space, is …

Cokriging prediction using as secondary variable a functional random field with application in environmental pollution

R Giraldo, L Herrera, V Leiva - Mathematics, 2020 - mdpi.com
Cokriging is a geostatistical technique that is used for spatial prediction when realizations of
a random field are available. If a secondary variable is cross-correlated with the primary …

Stochastic open-pit mine production scheduling: A case study of an iron deposit

M Maleki, E Jélvez, X Emery, N Morales - Minerals, 2020 - mdpi.com
Production planning decisions in the mining industry are affected by geological,
geometallurgical, economic and operational information. However, the traditional approach …

Sources and spatial variations of heavy metals in offshore sediments of the western Pearl River Estuary

J Zhao, K Yang, F Chu, Q Ge, D Xu, X Han, L Ye - Marine Pollution Bulletin, 2023 - Elsevier
The concentrations of six heavy metals (Cd, Cr, Cu, Pb, Zn, and As) in offshore surface
sediments of western Pearl River Estuary were analyzed to investigate their sources and …

Automatic semivariogram modeling by convolutional neural network

H Jo, MJ Pyrcz - Mathematical Geosciences, 2022 - Springer
Modeling the semivariogram to characterize spatial continuity requires expert geostatistical
knowledge and domain expertise about the spatial phenomenon of interest. Moreover …

[HTML][HTML] Comparing sequential Gaussian and turning bands algorithms for cosimulating grades in multi-element deposits

S Paravarzar, X Emery… - Comptes …, 2015 - comptes-rendus.academie-sciences …
Résumé Stochastic simulation is increasingly used to map the spatial variability in the
grades of elements of interest and to assess the uncertainty in the mineral resources and ore …

An automatic variogram modeling method with high reliability fitness and estimates

Z Li, X Zhang, KC Clarke, G Liu, R Zhu - Computers & Geosciences, 2018 - Elsevier
Modeling of the variogram is a critical step for most geostatistical methods. However, most of
the prevalent variogram-based solutions are designed without sufficient consideration of the …

New validity conditions for the multivariate Matérn coregionalization model, with an application to exploration geochemistry

X Emery, E Porcu, P White - Mathematical Geosciences, 2022 - Springer
This paper addresses the problem of finding parametric constraints that ensure the validity of
the multivariate Matérn covariance for modeling the spatial correlation structure of …