In mining projects, all uncertainties associated with a project must be considered to determine the feasibility study. Grade uncertainty is one of the major components of technical uncertainty that affects the variability of the project. Geostatistical simulation, as a reliable approach, is the most widely used method to quantify risk analysis to overcome the drawbacks of the estimation methods...

In this technical note, a geostatistical model was applied to explore the spatial distribution of source rock data in terms total organic carbon weight concentration. The median polish kriging method used approximate “row and column effect” generated array data, order for ordinary methodology be by means residuals. Moreover, sequential Gaussian simulation employed quantify uncertainty estimates...

Bayesian updating provides a sound mathematical framework for probabilistic calibration as new information emerges. Updating with Structural reliability methods (BUS) reformulates the acceptance domain in rejection sampling failure analysis, offering considerable potential higher efficiency and accuracy. Kriging-based Monte Carlo Simulation has been studied to facilitate application of BUS prob...

Information about soil properties helps the farmers to adopt effective and efficient farming practices, which can increase higher yields with optimum usage of farm resources. An attempt has been made in this paper predict using geospatial kriging approaches. This study mainly focuses on predicting pH different methods. Soil dramatically affects many other processes, such as nitrification denitrifi...

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model...

Maps are useful scientific tools for presenting environmental information, but the statistical techniques necessary to prepare scientifically rigorous maps have primarily focused on terrestrial habitats. This study compares three popular techniques (triangulation, kriging, and co-kriging) to map sediment grain size in Santa Monica Bay, California. Two grain size data sets, one collected in 1994...

This paper investigates the use of Kriging in random simulation when the simulation output variances are not constant. Kriging gives a response surface or metamodel that can be used for interpolation. Because Ordinary Kriging assumes constant variances, this paper also applies Detrended Kriging to estimate a non-constant signal function, and then standardizes the residual noise through the hete...

This paper describes a combination approach of a digital finite element modeling technique and the Kriging method for structural optimization. Since the digital modeling technique includes some inaccuracies in a modeling process, applicability of the Kriging method to noisy data is investigated. An estimated surface generated by the conventional Kriging method will be wavy and not appropriate t...

“Kriging” is the name of a parametric regression method used by hydrologists and mining engineers, among others. Features of the kriging approach are that it also provides an error estimate and that it can conveniently be employed also to estimate the integral of the regression function. In the present work, the kriging method is described and some of its statistical characteristics are explore...