GSLIB is an acronym for Geostatistical Software LIBrary. This name was originally used for a collection of geostatistical programs developed at Stanford University over the last 15 years. The original GSLIB inspired the writing of GSLIB: Geostatistical Software Library and User’s Guide by Clayton Deutsch and André Journel, 1992, 340 pp. during 1990 - 1992. The second edition was completed in 1997. Both editions were published by Oxford University Press.

References in zbMATH (referenced in 188 articles )

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  1. Nejadi, Siavash; Leung, Juliana; Trivedi, Japan: Characterization of non-Gaussian geologic facies distribution using ensemble Kalman filter with probability weighted re-sampling (2015)
  2. Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus: Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods (2015)
  3. Skou Cordua, Knud; Mejer Hansen, Thomas; Mosegaard, Klaus: Improving the pattern reproducibility of multiple-point-based prior models using frequency matching (2015)
  4. Barnett, Ryan M.; Manchuk, John G.; Deutsch, Clayton V.: Projection pursuit multivariate transform (2014)
  5. Bourgault, Gilles: Revisiting multi-Gaussian kriging with the Nataf transformation or the Bayes’ rule for the estimation of spatial distributions (2014)
  6. Gardet, Caroline; Le Ravalec, Mickaele; Gloaguen, Erwan: Multiscale parameterization of petrophysical properties for efficient history-matching (2014)
  7. Golay, Jean; Kanevski, Mikhail; Vega Orozco, Carmen D.; Leuenberger, Michael: The multipoint Morisita index for the analysis of spatial patterns (2014)
  8. Harris, Paul; Brunsdon, Chris; Charlton, Martin; Juggins, Steve; Clarke, Annemarie: Multivariate spatial outlier detection using robust geographically weighted methods (2014)
  9. Iranshahr, Alireza; Chen, Yuguang; Voskov, Denis V.: A coarse-scale compositional model (2014)
  10. Kaveh, Marjan; Khaledi, Majid Jafari: Estimation in truncated GLG model for ordered categorical spatial data using the SAEM algorithm (2014)
  11. Khaninezhad, Mohammadreza M.; Jafarpour, Behnam: Prior model identification during subsurface flow data integration with adaptive sparse representation techniques (2014)
  12. Lien, Martha; Mannseth, Trond: Facies estimation through data assimilation and structure parameterization (2014)
  13. Silva, Daniel A.; Deutsch, Clayton V.: A multiple training image approach for spatial modeling of geologic domains (2014)
  14. Strebelle, Sebastien; Cavelius, Claude: Solving speed and memory issues in multiple-point statistics simulation program SNESIM (2014)
  15. Bivand, Roger S.; Pebesma, Edzer J.; Gómez-Rubio, Virgilio: Applied spatial data analysis with R (2013)
  16. De Iaco, Sandra; Palma, Monica; Posa, Donato: Prediction of particle pollution through spatio-temporal multivariate geostatistical analysis: spatial special issue (2013)
  17. Horta, Ana; Correia, Pedro; Pinheiro, Luís Menezes; Soares, Amílcar: Geostatistical data integration model for contamination assessment (2013)
  18. Machuca-Mory, David F.; Deutsch, Clayton V.: Non-stationary geostatistical modeling based on distance weighted statistics and distributions (2013)
  19. Sapriza Azuri, Gonzalo; Jódar, Jorge; Carrera, Jesús; Gupta, Hoshin V.: Stochastic simulation of nonstationary rainfall fields, accounting for seasonality and atmospheric circulation pattern evolution (2013)
  20. Sebacher, Bogdan; Hanea, Remus; Heemink, Arnold: A probabilistic parametrization for geological uncertainty estimation using the ensemble Kalman filter (EnKF) (2013)

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