Ergebnisse einschränken






Université de Neuchâtel

Conditioning multiple-point statistics simulations to block data

Straubhaar, J ; Renard, Philippe ; Mariethoz, Gregoire

In: Spatial Statistics, 2016, vol. 16, p. 53-71

Multiple-points statistics (MPS) allows to generate random fields reproducing spatial statistics derived from a training image. MPS methods consist in borrowing patterns from the training set. Therefore, the simulation domain is assumed to be at the same resolution as the conceptual model, although geometrical deformations can be handled by such techniques. Whereas punctual conditioning data...

Université de Neuchâtel

Missing data simulation inside flow rate time-series using multiple-point statistics

Oriani, F ; Borghi, A ; Straubhaar, J ; Mariethoz, Grégoire ; Renard, Philippe

In: Environmental Modelling & Software, 2016, vol. 86, p. 264-276

The direct sampling (DS) multiple-point statistical technique is proposed as a non-parametric missing data simulator for hydrological flow rate time-series. The algorithm makes use of the patterns contained inside a training data set to reproduce the complexity of the missing data. The proposed setup is tested in the reconstruction of a flow rate time-series while considering several missing data...

Université de Neuchâtel

Integrating aerial geophysical data in multiple-point statistics simulations to assist groundwater flow models

Dickson, N.E.M ; Comte, J.-C ; Renard, Philippe ; Straubhaar, J ; McKinley, J.M ; Ofterdinger, U

In: Hydrogeology Journal, 2015, vol. 23, no. 5, p. 883-900

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by...