In addition to seismic and well constraints, production data must be integrated into geostatistical reservoir models for reliable reservoir performance predictions. An iterative inversion algorithm is required for such integration and is usually computationally intensive since forward flow simulation must be performed at each iteration. This paper presents an efficient approach for generating f...

The paper presents some contemporary approaches to the spatial environmental data analysis, processing and presentation. The main topics are concentrated on the decision–oriented problems of environmental and pollution spatial data mining and modelling: valorisation and representativity of data with the help of exploratory data analysis, topological, statistical and fractal measures of monitori...

The sequential-self calibration (SSC) method is a geostatistical-based inverse technique that allows fast integration of dynamic production data into geostatistical models. In this paper, we replace the gradient-based optimization in SSC by genetic algorithms (GA). GA, without requiring sensitivity, searches for global minimum. Although GA is computationally intensive, it provides significant f...

Probabilistic weather forecasting consists of finding a joint probability distribution for future weather quantities or events. It is typically done by using a numerical weather prediction model, perturbing the inputs to the model in various ways, often depending on data assimilation, and running the model for each perturbed set of inputs. The result is then viewed as an ensemble of forecasts, ...

The objective of this work is to extend kriging, a geostatistical interpolation method, to honor parameter nonnegativity. The new method uses a prior probability distribution based on reflected Brownian motion that enforces this constraint. The work presented in this paper focuses on interpolation problems where the unknown is a function of a single variable (e.g. time), and is developed both f...

Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014) using the Ordinary Kriging method based on ...

Monitoring of landscapes or sea bottoms by means of laser altimetry or multibeam results in huge amount of data covering the same area in different epochs. Often stable benchmarks are not available in the area covered. We propose a geodetic/geostatistical method to analyze possible deformations in such area out of time series of data. The method is used for a deformation analysis of six consecu...