This open access book provides state-of-the-art theory and application in geostatistics contains peer-reviewed articles of world-leading expert authors

Ramon Hanssen is assistant-professor in geostatistics, working on radar remote sensing for geodetic applications. Peter Teunissen is professor of Mathematical Geodesy and Positioning and authored the Lambda method. Peter Joosten graduated at the Faculty of Geodesy of Delft University of Technology. The authors are currently engaged in the development of ambiguity resolution algorithms for GPS d...

Classical Geostatistics methods have been designed to use mainly statistical knowledge about natural variables and they lack the ability to incorporate important forms of knowledge like physical laws and scientific theories into the mapping process. On the other hand, the powerful and versatile Bayesian maximum entropy (BME) method of Modern Geostatistics can accomplish such a task, rigorously ...

The methods of classical geostatistics were primarily developed under a set of constraining assumptions (linear estimator, measurements are exacts, etc.) and they lack the theoretical underpinnings and practical flexibility to incorporate the many sources of information available in modern days sciences (such as physical laws, empirical models, higher statistical moments, uncertain information)...

Geostatistics is a branch of statistics dealing with spatial phenomena modelled by random functions. In particular, it is assumed that, under some wellchosen simplifying hypotheses of stationarity, this probabilistic model, i.e. the random function describing spatial dependencies, can be completely assessed from the dataset by the experts. Kriging is a method for estimating or predicting the sp...

This paper presents a geostatistical model as a new approach to the linear prediction analysis of speech. The autocorrelation method of autoregressive modeling, which is widely applied in the linear predictive coding of speech, is used as a benchmark for comparison with the present algorithm. Before discussing the proposed model, we will briefly describe the concepts of linear prediction analys...

The application of state-of-the-art history matching methods to large heterogeneous reservoirs is hampered by two main problems: (1) reservoir models should be constrained jointly to dynamic data and a large variety of geological continuity information, (2) CPU demand should not be prohibitive for large models. This paper proposes a method contributing to alleviating these two main concerns. By...