Abstract
A combination of factorial kriging and probability field simulation is proposed to correct realizations resulting from any simulation algorithm for either too high nugget effect (noise) or poor histogram reproduction. First, a factorial kriging is done to filter out the noise from the noisy realization. Second, the uniform scores of the filtered realization are used as probability field to sample the local probability distributions conditional to the same dataset used to generate the original realization. This second step allows to restore the data variance. The result is a corrected realization which reproduces better target variogram and histogram models, yet honoring the conditioning data.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Almeida, S. A., and Journel, A. G., 1994, Joint simulation of multiple variables with a markovtype coregionalization model: Math. Geology, v. 26, no. 5, p. 565–588.
Bourgault, G., 1994, Robustness of noise filtering by factorial kriging: Math. Geology, v. 26, no. 6, p. 733–752.
Bourgault, G., and Journel, A. G., 1994, Gaussian or indicator-based simulations? Which variogram is more relevant?in Chung C. F., ed., IAMG '94 Annual Meeting, Mont-Tremblant (Québec, Canada), p. 32–37.
Daly, C., Jeulin, D., and Lajaunie, C., 1989, Application of multivariate kriging to the processing of noisy images,in Armstrong, M., ed., Geostatistics, v. 2, Quantitative geology and geostatistics: 3rd Intern. Geostatistics Congress (Avignon, France), Kluwer Academic Publ., Dordrect. The Netherlands, p. 749–760.
Deutsch, C. V., and Journel, A. G., 1992, GSLIB Geostatistical Software Library and user's guide: Oxford Press, Oxford, 340 p.
Froidevaux, R., 1992, Probability field simulation,in Soares, A., ed., Geostatistics Troia '92. Quantitative geology and geostatistics, v. I: Kluwer Academic Publ., Dordrect, The Netherlands, p. 73–83.
Journel, A. G., and Xu, W., 1995, Posterior identification of histograms conditional to local data: Math. Geology, v. 26, no. 3, p. 323–359.
Ma, Y. Z., and Royer, J. J., 1988, Local geostatistical filtering application to remote sensing: Sciences de la Terre, Série Informatique (Nancy), v. 27, p. 17–36.
Marcotte, D., 1995, Conditional simulation with data subject to measurement erior: Post-stimulation filtering with modified factorial kriging: Math. Geology, v. 27, no. 6, p. 749–762.
Matheron, G., 1982. Pour une analyse krigeante des données régionalisées: Publ. N-732. Centre de Géostatistique et de Morphologie Mathématique, École des Mines de Paris. Fontainebleau, 22 p.
Sandjivy, L., 1984, The factorial kriging analysis of regionalized data. Its application to geochemical prospecting,in Verly, G., and others, eds., Geostatistics for natural resources characterization: NATO-ASI, Serie C, v. 122, pt. 1, p. 559–572.
Srivastava, R. M., 1992. Reservoir characterization with probability field simulation: SPE Paper No. 24753, preprint.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Bourgault, G. Probability field for the post-processing of stochastic simulations. Math Geol 28, 723–734 (1996). https://doi.org/10.1007/BF02066342
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02066342