Geostatistics Oslo 2012 Foreword Preface Acknowledgements Part I Theory Sequential simulation with iterative methods Applications of randomized methods for decomposing and simulating from large covariance matrices Event based geostatistical modeling: description and applications A plurigaussian model for simulating regionalized compositions New flexible non parametric data transformation for trans Gaussian kriging Revisiting the linear model of coregionalisation Modeling nonlinear beta probability fields Approximations of high order spatial statistics through decomposition Multiple point geostatistical simulation based on genetic algorithms implemented in a shared memory supercomputer The edge effect in geostatistical simulations Extensions of the parametric inference of spatial covariances by maximum likelihood Part II Petroleum Constraining a heavy oil reservoir to temperature and time lapse seismic data using the EnKF Micro modeling for enhanced small scale porosity permeability relationships Applications of data coherency for data analysis and geological zonation Multiscale modeling of fracture network in a carbonate reservoir Uncertainty quantification and feedback control using a model selection approach applied to a polymer flooding process Efficient conditional simulation of spatial patterns using a pattern growth algorithm Multiple point statistics in a non gridded domain: application to karst fracture network modeling Sequential simulations of mixed discrete continuous properties: sequential Gaussian mixture simulation Accounting for seismic trends in stochastic well correlation Some newer algorithms in joint categorical and continuous inversion problems around seismic data Non random discrete fracture network modelling Part III Mining Kriging and simulation in presence of stationary domains: Developments in boundary modeling Assessing uncertainty in recovery functions: a practical approach Comparative study of localized block simulations and localized uniform conditioning in the multivariate case Application of stochastic simulations and quantifying uncertainties in the drilling of roll front uranium deposits Multivariate estimation using log ratios: a worked alternative Measuring the impact of the change of support and information effect at olympic dam Comparative study of two gaussian simulation algorithms Boddington gold deposit Non multi gaussian multivariate simulations with guaranteed reproduction of inter variable correlations Field parametric geostatistics—a rigorous theory to solve problems of highly skewed distributions Multiple point geostatistics for modeling lithological domains at a Brazilian iron ore deposit using the single normal equations simulation algorithm Practical implementation of non linear transforms for modeling geometallurgical variables Combined use of lithological and grade simulations for risk analysis in iron ore Brazil The use of geostatistical simulation to optimize the homogenization and blending strategies Plurigaussian simulations used to analyze the uncertainty in resources estimation from a lateritic nickel deposit Domaining by clustering multivariate geostatistical data The influence of geostatistical techniques on geological uncertainty Part IV Environmental climate and hydrology A study on how top surface morphology influences the storage capacity of CO2 in saline aquifers Modeling and analysis of daily rainfall data A stochastic model in space and time for monthly maximum significant wave height Interpolation of concentration measurements by kriging using flow coordinates A comparison of methods for solving the sensor location problem Comparing geostatistical models for river networks Author index Subject index. This book consists of 44 technical papers presented at the Ninth International Geostatistics Congress held in Oslo Norway in June 2012. The papers have been reviewed by a panel of specialists in Geostatistics. The book is divided into four main sections: Theory; Petroleum; Mining; and Environment Climate and Hydrology. The first section focuses on new ideas of general interest to many fields of applications. The next sections are more focused on the particular needs of the particular industry or activity. Geostatistics is vital to any industry dependent on natural resources. Methods from geostatistics are used for estimating reserves quantifying economical risk and planning of future industrial operations. Geostatistics is also an important tool for mapping environmental hazard and integrating climate data.