GSLIB

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 222 articles )

Showing results 1 to 20 of 222.
Sorted by year (citations)

1 2 3 ... 10 11 12 next

  1. Bourgault, Gilles: Clarifications and new insights on conditional bias (2021)
  2. Gómez-Hernández, J. Jaime; Srivastava, R. Mohan: One step at a time: the origins of sequential simulation and beyond (2021)
  3. Goovaerts, Pierre: From natural resources evaluation to spatial epidemiology: 25 years in the making (2021)
  4. Hansen, Thomas Mejer: Entropy and information content of geostatistical models (2021)
  5. Liu, Wendi; Pyrcz, Michael J.: A spatial correlation-based anomaly detection method for subsurface modeling (2021)
  6. Osman, Hossam; Graham, Gavin H.; Moncorge, Arthur; Jacquemyn, Carl; Jackson, Matthew D.: Is cell-to-cell scale variability necessary in reservoir models? (2021)
  7. Prior, Ángel; Tolosana-Delgado, Raimon; van den Boogaart, K. Gerald; Benndorf, Jörg: Resource model updating for compositional geometallurgical variables (2021)
  8. Riquelme, Álvaro I.; Ortiz, Julian M.: Uncertainty assessment over any volume without simulation: revisiting multi-Gaussian kriging (2021)
  9. Walsh, D. A.; Manzocchi, T.: Connectivity in pixel-based facies models (2021)
  10. Zhang, Chengkai; Song, Xianzhi; Azevedo, Leonardo: U-net generative adversarial network for subsurface facies modeling (2021)
  11. Calderon, Hernan; Santibañez, Felipe; Silva, Jorge F.; Ortiz, Julián M.; Egaña, Alvaro: Geological facies recovery based on weighted (\ell_1)-regularization (2020)
  12. Claudia Cappello, Sandra De Iaco, Donato Posa: covatest: An R Package for Selecting a Class of Space-Time Covariance Functions (2020) not zbMATH
  13. de Figueiredo, Leandro Passos; Grana, Dario; Le Ravalec, Mickaele: Revisited formulation and applications of FFT moving average (2020)
  14. McKenna, Sean A.; Akhriev, Albert; Echeverría Ciaurri, David; Zhuk, Sergiy: Efficient uncertainty quantification of reservoir properties for parameter estimation and production forecasting (2020)
  15. Pedretti, Daniele: Heterogeneity-controlled uncertain optimization of pump-and-treat systems explained through geological entropy (2020)
  16. Pereira, Pedro; Calçôa, Inês; Azevedo, Leonardo; Nunes, Rúben; Soares, Amílcar: Iterative geostatistical seismic inversion incorporating local anisotropies (2020)
  17. Pradhan, Anshuman; Mukerji, Tapan: Seismic Bayesian evidential learning: estimation and uncertainty quantification of sub-resolution reservoir properties (2020)
  18. Rabinovich, Avinoam; Cheng, Kan Bun: Equilibrium gravity segregation in porous media with capillary heterogeneity (2020)
  19. Luo, Xin; Tjelmeland, Håkon: Prior specification for binary Markov mesh models (2019)
  20. Luo, Xin; Tjelmeland, Håkon: A multiple-try Metropolis-Hastings algorithm with tailored proposals (2019)

1 2 3 ... 10 11 12 next