In: Computers & Geosciences, 2011, vol. 40, p. 49-65
One of the main issues in the application of multiple-point statistics (MPS) to the simulation of three-dimensional (3D) blocks is the lack of a suitable 3D training image. In this work, we compare three methods of overcoming this issue using information coming from bidimensional (2D) training images. One approach is based on the aggregation of probabilities. The other approaches are novel. One...
|
In: Journal of Hydrology, 2011, vol. 405, no. 1, p. 10
The heterogeneity of sedimentary structures at the decimeter scale is crucial to the understanding of groundwater flow and transport. In a series of two papers, we provide a detailed analysis of a fluvio-glacial aquifer analog: the Herten site. The geological data along a series of 2D sections in a quarry, the corresponding GPR measurements, and their sedimentological interpretation are described...
|
In: Mathematical Geosciences, 2014, vol. 46, no. 5, p. 625-645
|
In: Mathematical Geosciences, 2011, vol. 43, no. 7, p. 783-797
|
In: Water Resources Research, 2010, vol. 46, no. W11536, p. 1-14
Multiple-point geostatistics is a general statistical framework to model spatial fields displaying a wide range of complex structures. In particular, it allows controlling connectivity patterns that have a critical importance for groundwater flow and transport problems. This approach involves considering data events (spatial arrangements of values) derived from a training image (TI). All data...
|
In: Computers & Geosciences, 2013, vol. 52, p. 307-324
The Direct Sampling (DS) algorithm is a recently developed multiple-point statistical simulation technique. It directly scans the training image (TI) for a given data event instead of storing the training probability values in a catalogue prior to simulation. By using distances between the given data events and the TI patterns, DS allows to simulate categorical, continuous and multivariate...
|
In: Stochastic Environmental Research and Risk Assessment, 2018, vol. 32, p. 321-340
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is...
|
In: Hydrology and Earth System Sciences, 2014, vol. 18, p. 3015-3031
The direct sampling technique, belonging to the family of multiple-point statistics, is proposed as a nonparametric alternative to the classical autoregressive and Markovchain-based models for daily rainfall time-series simulation. The algorithm makes use of the patterns contained inside the training image (the past rainfall record) to reproduce the complexity of the signal without inferring its...
|
In: Geomorphology, 2014, vol. 214, p. 148-156
A new method is proposed to generate successive topographies in a braided river system. Indeed, braided river morphologymodels are a key factor influencing river–aquifer interactions and have repercussions in ecosystems, flood risk or water management. It is essentially based on multivariate multiple-point statistics simulations and digital elevation models as training data sets. On the one...
|
In: Mathematical Geosciences, 2011, vol. 43, no. 8, p. 879-903
|
