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 156 articles )

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  1. Ibrahima, Fayadhoi; Tchelepi, Hamdi A.; Meyer, Daniel W.: An efficient distribution method for nonlinear two-phase flow in highly heterogeneous multidimensional stochastic porous media (2018)
  2. Yao, Lingqing; Dimitrakopoulos, Roussos; Gamache, Michel: A new computational model of high-order stochastic simulation based on spatial Legendre moments (2018)
  3. Deng, Q.; Ginting, V.; McCaskill, B.; Torsu, P.: A locally conservative stabilized continuous Galerkin finite element method for two-phase flow in poroelastic subsurfaces (2017)
  4. Emerick, Alexandre A.: Investigation on principal component analysis parameterizations for history matching channelized facies models with ensemble-based data assimilation (2017)
  5. Fossum, Kristian; Mannseth, Trond: Coarse-scale data assimilation as a generic alternative to localization (2017)
  6. Galerne, Bruno; Leclaire, Arthur: Texture inpainting using efficient Gaussian conditional simulation (2017)
  7. Ibrahima, Fayadhoi; Tchelepi, Hamdi A.: Multipoint distribution of saturation for stochastic nonlinear two-phase transport (2017)
  8. Sandra de Iaco: The cgeostat Software for Analyzing Complex-Valued Random Fields (2017) not zbMATH
  9. Trangenstein, John A.: Scientific computing. Vol. I. Linear and nonlinear equations (2017)
  10. Trangenstein, John A.: Scientific computing. Vol. II. Eigenvalues and optimization (2017)
  11. Trangenstein, John A.: Scientific computing. Vol. III. Approximation and integration (2017)
  12. van den Boogaart, K. Gerald; Mueller, Ute; Tolosana-Delgado, Raimon: An affine equivariant multivariate normal score transform for compositional data (2017)
  13. Vigsnes, Maria; Kolbjørnsen, Odd; Hauge, Vera Louise; Dahle, Pål; Abrahamsen, Petter: Fast and accurate approximation to Kriging using common data neighborhoods (2017)
  14. Wambeke, T.; Benndorf, J.: A simulation-based geostatistical approach to real-time reconciliation of the grade control model (2017)
  15. Bakshevskaia, Veronika A.; Pozdniakov, Sergey P.: Simulation of hydraulic heterogeneity and upscaling permeability and dispersivity in Sandy-Clay formations (2016)
  16. Chatterjee, Snehamoy; Sethi, Manas Ranjan; Asad, Mohammad Waqar Ali: Production phase and ultimate pit limit design under commodity price uncertainty (2016)
  17. Goovaerts, Pierre; Albuquerque, M. T. D.; Antunes, I. M. H. R.: A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration (2016)
  18. Li, Hangyu; Durlofsky, Louis J.: Ensemble level upscaling for compositional flow simulation (2016)
  19. Peredo, Oscar; Ortiz, Julián M.; Leuangthong, Oy: Inverse modeling of moving average isotropic kernels for non-parametric three-dimensional Gaussian simulation (2016)
  20. Perozzi, Lorenzo; Gloaguen, Erwan; Giroux, Bernard; Holliger, Klaus: A stochastic inversion workflow for monitoring the distribution of $\textCO_2$ injected into deep saline aquifers (2016)

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