Multiple-point geostatistical modeling based on the cross-correlation functions

By Pejman Tahmasebi, Ardeshir Hezarkhani, Muhammad Sahimi. Computational Geosciences, 2012

295 citations recorded by the source corpus.

Subfields: Environmental Engineering, Mechanical Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/ef49f7e7e3a26515d5afc9df147debef30dbf298

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. Wei Chen
4. Daniel W. Apley

In Mechanical Engineering

1. Muhammad Sahimi
2. Pejman Tahmasebi
3. L. Catherine Brinson
4. Wing Kam Liu
5. Ted Belytschko

In Ocean Engineering

1. Muhammad Sahimi
2. Pejman Tahmasebi

Citations in the corpus

• Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques (2018, background): “We note that, some texture synthesis methods [254] use patches instead of pixels and hence are computationally more efficient (see [261,262] for similar works in geostatistics).”
• Enhancing multiple‐point geostatistical modeling: 1. Graph theory and pattern adjustment (2016, methodology): “In general, such methods are classified into three main groups [Tahmasebi et al., 2012].”
• 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].”