Results 1 to 10 of about 1,087,662 (308)

Conditioning Multiple‐Point Statistics Simulation to Inequality Data

Earth and Space Science, 2021
Stochastic modeling is often employed in environmental sciences for the analysis and understanding of complex systems. For example, random fields are key components in uncertainty analysis or Bayesian inverse modeling.
Julien Straubhaar, Philippe Renard
doaj   +5 more sources

A new methodology to train fracture network simulation using multiple-point statistics [PDF]

Solid Earth, 2019
Natural fracture network characteristics can be establishes from high-resolution outcrop images acquired from drone and photogrammetry. Such images might also be good analogues of subsurface naturally fractured reservoirs and can be used to make ...
P.-O. Bruna, J. Straubhaar, R. Prabhakaran, R. Prabhakaran, G. Bertotti, K. Bisdom, G. Mariethoz, M. Meda   +7 more
doaj   +6 more sources

Functional multiple-point simulation

Computers and Geosciences
We present a new paradigm, called functional multiple-point simulation, in which multiple-point geostatistical simulation can be performed when functions or curves are observed at each location of a random field.
Oluwasegun Taiwo Ojo, Marc G Genton
exaly   +2 more sources

Efficiency of template matching methods for Multiple-Point Statistics simulations

Applied Computing and Geosciences, 2021
Almost all Multiple-Point Statistic (MPS) methods use internally a template matching method to select patterns that best match conditioning data. The purpose of this paper is to analyze the performances of ten of the most frequently used template ...
Mansoureh Sharifzadeh Lari, Julien Straubhaar, Philippe Renard   +2 more
doaj   +1 more source

Contributions to uncertainty related to hydrostratigraphic modeling using multiple-point statistics [PDF]

Hydrology and Earth System Sciences, 2018
Forecasting the flow of groundwater requires a hydrostratigraphic model, which describes the architecture of the subsurface. State-of-the-art multiple-point statistical (MPS) tools are readily available for creating models depicting subsurface geology.
A. A. S. Barfod, A. A. S. Barfod, T. N. Vilhelmsen, F. Jørgensen, A. V. Christiansen, A.-S. Høyer, J. Straubhaar, I. Møller   +7 more
doaj   +1 more source

Hydrostratigraphic modeling using multiple-point statistics and airborne transient electromagnetic methods [PDF]

Hydrology and Earth System Sciences, 2018
Creating increasingly realistic groundwater models involves the inclusion of additional geological and geophysical data in the hydrostratigraphic modeling procedure.
A. A. S. Barfod, A. A. S. Barfod, I. Møller, A. V. Christiansen, A.-S. Høyer, J. Hoffimann, J. Straubhaar, J. Caers   +7 more
doaj   +1 more source

3D multiple-point statistics simulations of the Roussillon Continental Pliocene aquifer using DeeSse [PDF]

Hydrology and Earth System Sciences, 2020
This study introduces a novel workflow to model the heterogeneity of complex aquifers using the multiple-point statistics algorithm DeeSse. We illustrate the approach by modeling the Continental Pliocene layer of the Roussillon aquifer in the region of ...
V. Dall'Alba, P. Renard, J. Straubhaar, B. Issautier, C. Duvail, Y. Caballero   +5 more
doaj   +1 more source

Machine Learning-Based Urban Renovation Design for Improving Wind Environment: A Case Study in Xi’an, China

Land, 2023
The high-density urban form and building arrangement of modern cities have contributed to numerous environmental problems. The calm wind area caused by inappropriate building arrangements results in pollutant accumulation.
Chen Zuo, Chengcheng Liang, Jing Chen, Rui Xi, Junfei Zhang   +4 more
doaj   +1 more source

A Pattern Classification Distribution Method for Geostatistical Modeling Evaluation and Uncertainty Quantification

Remote Sensing, 2023
Geological models are essential components in various applications. To generate reliable realizations, the geostatistical method focuses on reproducing spatial structures from training images (TIs).
Chen Zuo, Zhuo Li, Zhe Dai, Xuan Wang, Yue Wang   +4 more
doaj   +1 more source

A parsimonious parametrization of the Direct Sampling algorithm for multiple-point statistical simulations

Applied Computing and Geosciences, 2022
Multiple-point statistics algorithms allow modeling spatial variability from training images. Among these techniques, the Direct Sampling (DS) algorithm has advanced capabilities, such as multivariate simulations, treatment of non-stationarity, multi ...
Przemysław Juda, Philippe Renard, Julien Straubhaar   +2 more
doaj   +1 more source