Inverse problems in geophysics require the introduction of complex a priori information and are solved using computationally expensive Monte Carlo techniques where large portions of the model space are explored . The geostatistical method allows for fast integration of complex a priori information in the form of covariance functions and training images. We combine geostatistical methods and inv...

It is now common in the mining industry to deal with several correlated attributes, which need to be jointly simulated in order to reproduce their correlations and assess the multivariate grade risk reasonably. Approaches to multivariate simulation which remove the correlation between attributes of interest prior to simulate and then re-impose the relationship afterward have been gaining popula...

To have information about the soybean productivity over crop years is essential to define strategies increase profits and reduce costs most important environmental impacts. One form of monitoring use Geostatistical methods, which allow us obtain maps with more accurate predictions. In this paper, an area 127.16 ha was studied during six between 2012/2013 2017/2018. We found that values vary yea...

ABSTRACT-Determining hydraulic conductivity of soil is difficult, expensive, and time-consuming. In this study, Algorithm Genetic and geostatistical analysis and Neural Networks method are used to estimate soil saturated hydraulic conductivity using the properties of particle size distribution. The data were gathered from 134soil profiles from soil and lander form studies of the Ardabil Agricul...