Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling

By Mehrdad Honarkhah, Jef Caers. 2010

323 citations recorded by the source corpus.

Subfields: Environmental Engineering, Mechanical Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/bef9adf46f2e8780a985586fa9454d2fb14ea772

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Muhammad Sahimi
2. Pejman Tahmasebi
3. Philippe Renard
4. Gregoire Mariethoz
5. Julien Straubhaar
6. Peter Bhlmann
7. M. J. van der Laan
8. Hamidreza Hamdi

In Mechanical Engineering

1. Muhammad Sahimi
2. Pejman Tahmasebi
3. Peter Bhlmann
4. M. J. van der Laan
5. Hamidreza Hamdi
6. Petros Drineas
7. Mario Costa Sousa
8. Tom D'haene

In Ocean Engineering

1. Muhammad Sahimi
2. Pejman Tahmasebi
3. Gregoire Mariethoz
4. Julien Straubhaar
5. Peter Bhlmann
6. M. J. van der Laan
7. Hamidreza Hamdi
8. Petros Drineas

Citations in the corpus

• Handbook of Big Data (2016, methodology): “1 k-Means Clustering-Based Model Reduction k-means clustering is a standard clustering technique [14] and is widely used in many applications [8,10].”
• Gaussian Processes for history-matching: application to an unconventional gas reservoir (2017, methodology): “In addition, GP or in general, proxy-based optimization techniques might be used for different realizations if they can be combined with the other techniques such as Principal Component Analysis (PCA) [74] or Multi-Dimensional Scaling (MDS) [75].”
• Enhancing multiple‐point geostatistical modeling: 1. Graph theory and pattern adjustment (2016, methodology): “Honarkhah and Caers [2010] utilized the FILTERSIM algorithm to carry out the computations in multidimensional space and to avoid using a limited number of finite filters.”
• Multiple-point geostatistical modeling based on the cross-correlation functions (2012, methodology): “These results should be compared with those obtained with other methods for similar TIs, given by Wu et al. [78] and Honarkhah and Caers [35].”
• A review of clustering techniques and developments (2017, background): “Clustering is useful to extract interesting features and identify the patterns, which exist in huge amounts of spatial databases [106, 127-129].”
• Simulation of rainfall time series from different climatic regions using the direct sampling technique (2014, methodology): “, 2006; Arpat and Caers , 2007; Honarkhah and Caers , 2010; Straubhaar et al. , 2011; Tahmasebi et al. , 2012), MPS is a family of geostatistical techniques widely used in spatial-data simulations and particularly suited to pattern reproduction. MPS algorithms use a training image; i.e., a data set ”