Information about reservoir properties usually comes from two sources: seismic data and well logs. The former provide an indirect, low resolution image of rock velocity and density. The latter provide direct, high resolution (but laterally sparse) sampling of these and other rock parameters. An important problem in reservoir characterization is how best to combine these data sets, allowing the ...

background: stomach cancer has the highest prevalence of gastrointestinal cancer in iran. therefore, the aim of this study was mapping stomach cancer rate in iran using area-to-area poisson kriging.   methods: data of 336 cities in iran was analyzed that was gathered by the ministry of health and medical education (in the non-infectious diseases management center) from 2003 to 2007. area-to-are...

A study was designed to compare the performance of six spatial interpolation methods to estimate soil properties at unvisited points. These methods were global mean, moving average, nearest neighbour, inverse squared distance, Laplacian smoothing splines and ordinary point kriging. These methods were also applied in combination with a choropleth map (soil map) by stratifying the area. The soil ...

     Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. In many instances, drought indices are used for monitoring purposes. Geostatistical methods allow the interpolation of spatially referenced data and the prediction of v...

This paper addresses the issue of incorporating a digital elevation model into the mapping of Ž . annual and monthly erosivity values in the Algarve region Portugal . Besides linear regression of erosivity against elevation, three geostatistical algorithms are introduced: simple kriging with Ž . Ž . varying local means SKlm , kriging with an external drift KED and colocated cokriging. Cross val...

Valuation and risk management of large portfolios of variable annuity policies are a big challenge to insurance companies because pricing a large portfolio of variable annuity policies is a time consuming task. Recently, a method based on clustering and kriging has been proposed to address the computational problem arising from this area. In this method, the value of the portfolio is estimated ...

Metamodelling offers an efficient way to imitate the behaviour of computationally expensive simulators. Kriging based metamodels are popular in approximating computation-intensive simulations of deterministic nature. Irrespective of the existence of various variants of Kriging in the literature, only a handful of Kriging implementations are publicly available and most, if not all, free librarie...

We develop a novel multi-fidelity framework that goes far beyond the classical AR(1) Co-kriging scheme of Kennedy and O’Hagan (2000). Our method can handle general discontinuous cross-correlations among systems with different levels of fidelity. A combination of multi-fidelity Gaussian Processes (AR(1) Co-kriging) and deep neural networks enables us to construct a method that is immune to disco...

Genomic data provide a valuable source of information for modeling covariance structures, allowing a more accurate prediction of total genetic values (GVs). We apply the kriging concept, originally developed in the geostatistical context for predictions in the low-dimensional space, to the high-dimensional space spanned by genomic single nucleotide polymorphism (SNP) vectors and study its prope...

When analysing data from computationally expensive simulation codes or process measurements, surrogate modelling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualisation and optimisation. Kriging is a popular surrogate modelling technique for data based on deterministic computer experiments. There exist several types of Kriging, mostly dif...